From 695b10377e3905f8ac519668e005b8deaa8f2ed9 Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Wed, 15 Nov 2017 20:05:08 +0800 Subject: [PATCH 0001/1416] port hsigmoid layer --- paddle/operators/hierarchical_sigmoid_op.cc | 121 ++++++++++++++++++++ paddle/operators/hierarchical_sigmoid_op.h | 35 ++++++ paddle/operators/math/CMakeLists.txt | 1 + paddle/operators/math/matrix_bit_code.cc | 84 ++++++++++++++ paddle/operators/math/matrix_bit_code.h | 64 +++++++++++ 5 files changed, 305 insertions(+) create mode 100644 paddle/operators/hierarchical_sigmoid_op.cc create mode 100644 paddle/operators/hierarchical_sigmoid_op.h create mode 100644 paddle/operators/math/matrix_bit_code.cc create mode 100644 paddle/operators/math/matrix_bit_code.h diff --git a/paddle/operators/hierarchical_sigmoid_op.cc b/paddle/operators/hierarchical_sigmoid_op.cc new file mode 100644 index 00000000000..1f77ff1268a --- /dev/null +++ b/paddle/operators/hierarchical_sigmoid_op.cc @@ -0,0 +1,121 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#include "hierarchical_sigmoid_op.h" + +namespace paddle { +namespace operators { + +/** + * Organize the classes into a binary tree. At each node, a sigmoid function + * is used to calculate the probability of belonging to the right branch. + * This idea is from "F. Morin, Y. Bengio (AISTATS 05): + * Hierarchical Probabilistic Neural Network Language Model." + * + * Here we uses a simple way of making the binary tree. + * Assuming the number of classes C = 6, + * The classes are organized as a binary tree in the following way: + * + * @code{.py} + * *-*-*- 2 + * | | |- 3 + * | | + * | |-*- 4 + * | |- 5 + * | + * |-*- 0 + * |- 1 + * @endcode + * + * where * indicates an internal node, and each leaf node represents a class. + * - Node 0 ... C-2 are internal nodes. + * - Node C-1 ... 2C-2 are leaf nodes. + * - Class c is represented by leaf node \f$c+C-1\f$. + * + * We assign an id for each node: + * - the id of root be 0. + * - the left child of a node i is 2*i+1. + * - the right child of a node i is 2*i+2. + * + * It's easy to see that: + * - the parent of node i is \f$\left\lfloor(i-1)/2\right\rfloor\f$. + * - the j-th level ancestor of node i is + * \f$\left\lfloor(i+1)/2^{j+1}\right\rfloor - 1\f$. + * - A node i is a left child of its parent if \f$(i-1)\%2==0\f$. + * + */ + +class HierarchicalSigmoidOp : public framework::OperatorWithKernel { + public: + using framework::OperatorWithKernel::OperatorWithKernel; + void InferShape(framework::InferShapeContext* ctx) const override { + PADDLE_ENFORCE(ctx->HasInputs("X"), "Inputs(X) should not be null."); + PADDLE_ENFORCE(ctx->HasInput("Label"), "Input(Label) should not be null."); + PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output(Out) should not be null."); + const int64_t batch_size = ctx->GetInputsDim("X")[0][0]; + const int64_t size = ctx->GetInputsDim("X").size(); + std::vector output_shape({batch_size, size}); + ctx->SetOutputDim("Out", framework::make_ddim(output_shape)); + } +}; + +class HierarchicalSigmoidGradOp : public framework::OperatorWithKernel { + public: + using framework::OperatorWithKernel::OperatorWithKernel; + void InferShape(framework::InferShapeContext* ctx) const override {} +}; + +class HierarchicalSigmoidOpMaker : public framework::OpProtoAndCheckerMaker { + public: + HierarchicalSigmoidOpMaker(framework::OpProto* proto, + framework::OpAttrChecker* op_checker) + : OpProtoAndCheckerMaker(proto, op_checker) { + AddInput("X", + "(TensorArray, required) The input array. Each Tensor has the " + "same shape with [N * D]." + .AsDuplicable(); + AddInput("Label", + "(Tensor, required), The labels of training data. It's a" + "1-D tensor."); + AddInput("Bias", + "(Tensor, optional), The bias is a 1-D tensor, " + "which is applied to the output"); + AddOutput("Out", + "(Tensor, required) The output of hierarchical sigmoid operator."); + AddAttr("num_classes", + "(int, required)", + "The number of classes"); + AddComment(R"DOC( +The hierarchical sigmoid operator organize the classes into a binary tree. +At each node, a sigmoid function is used to caculate the probability of +belonging to the right branch. This idea is from +"F. Morin, Y. Bengio (AISTATS 05): +Hierarchical Probabilistic Neural Network Language Model." + )DOC"); + } +}; + +} // namespace operators +} // namespace paddle + +namespace ops = paddle::operators; +REGISTER_OP(hierarchical_sigmoid, ops::HierarchicalSigmoidOp, + ops::HierarchicalSigmoidOpMaker, hierarchical_sigmoid_grad, + ops::HierarchicalSigmoidGradOp); +REGISTER_OP_CPU_KERNEL( + hierarchical_sigmoid, + ops::HierarchicalSigmoidOpKernel); +REGISTER_OP_CPU_KERNEL( + hierarchical_sigmoid_grad, + ops::HierarchicalSigmoidGradOpKernel); diff --git a/paddle/operators/hierarchical_sigmoid_op.h b/paddle/operators/hierarchical_sigmoid_op.h new file mode 100644 index 00000000000..8a753605d6e --- /dev/null +++ b/paddle/operators/hierarchical_sigmoid_op.h @@ -0,0 +1,35 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#pragma once +#include "paddle/framework/op_registry.h" +#include "paddle/operators/math/matrix_bit_code.h" + +namespace paddle { +namespace operators { +template + +class HierarchicalSigmoidOpKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& ctx) const override {} +}; + +template +class HierarchicalSigmoidGradOpKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& ctx) const override {} +}; + +} // namespace operators +} // namespace paddle diff --git a/paddle/operators/math/CMakeLists.txt b/paddle/operators/math/CMakeLists.txt index ab7f23f5704..cc96b27c25e 100644 --- a/paddle/operators/math/CMakeLists.txt +++ b/paddle/operators/math/CMakeLists.txt @@ -26,6 +26,7 @@ else() cc_library(sequence2batch SRCS sequence2batch.cc DEPS device_context) cc_library(lstm_compute SRCS lstm_compute.cc DEPS device_context activation_functions) cc_library(gru_compute SRCS gru_compute.cc DEPS device_context activation_functions math_function) + cc_library(matrix_bit_code SRCS matrix_bit_code.cc) endif() cc_test(math_function_test SRCS math_function_test.cc DEPS math_function tensor) diff --git a/paddle/operators/math/matrix_bit_code.cc b/paddle/operators/math/matrix_bit_code.cc new file mode 100644 index 00000000000..3f1dbbf3994 --- /dev/null +++ b/paddle/operators/math/matrix_bit_code.cc @@ -0,0 +1,84 @@ +/* Copyright (c) 2017 PaddlePaddle Authors. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#include "matrix_bit_code.h" + +namespace paddle { +namespace operators { +namespace math { + +/** + * CodeTable class should support 3 functions: + * + * size_t size() + * return the number of codes + * + * int getMaxCodeLength() + * return the maximal code length + * + * Code operator()(size_t i) + * return the i-th code. Code class is descriebed below. + * + * Code class should support 3 functions: + * + * int getLength() + * return the length of the code + * + * bool calcIndex(int bit) + * bit ranges from 0 to getLength() - 1 + * return the index for the (1+bit) level parent + * + * bool calcBit(int bit) + * return true if the bit level parent is the right child of (1+bit) level + * parent + * + */ + +/* + for i: + for j < codeLength: + op(a(i, j), b(0, index(i, j))) +*/ +template +static void AddByBitCodeT(Op op, CodeTable code_table, + const framework::Tensor& codes, framework::Tensor& a, + framework::Tensor& b) { + size_t num_classes = code_table.size(); + size_t max_code_length = code_table.get_max_code_length(); + size_t num_sample = a.dims()[0].size(); + size_t width = a.dims()[1].size(); + + for (size_t i = 0; i < num_sample; ++i) { + auto code = code_table(codes.data()[i]) int code_length = + code.get_length(); + for (int j = 0; j < code_length; + j) { + size_t index = code.calc_index(j); + op(a.data()[i * width + j], b.data()[index]); + } + } +} + +/* For j < codeLength: + a(i, j) += b(0, index(i, j)) +*/ +template +void AddByBitCode(size_t num_classes, const framework::Tensor& codes, + framework::Tensor& a, const framework::Tensor& b) { + auto op = [](T& t, T& v) { t += v; }; + AddByBitCodeT(op, SimpleCodeTable(num_classes), codes, a, b); +} + +} // namespace math +} // namespace operators +} // namespace paddle diff --git a/paddle/operators/math/matrix_bit_code.h b/paddle/operators/math/matrix_bit_code.h new file mode 100644 index 00000000000..a0dd89ebe01 --- /dev/null +++ b/paddle/operators/math/matrix_bit_code.h @@ -0,0 +1,64 @@ +/* Copyright (c) 2017 PaddlePaddle Authors. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#pragma once +#include "paddle/framework/eigen.h" +#include "paddle/framework/tensor.h" + +namespace paddle { +namespace operators { +namespace math { + +/** + * return the 1-based index of the highest bit set + * + * for x > 0: + * \f[ + * findLastSet(x) = 1 + \floor*{\log_{2}x} + * \f] + */ +inline constexpr size_t FindLastSet(size_t x) { + return std::is_same::value + ? (x ? 8 * sizeof(x) - __builtin_clz(x) : 0) + : (std::is_same::value // NOLINT + ? (x ? 8 * sizeof(x) - __builtin_clzl(x) : 0) + : (x ? 8 * sizeof(x) - __builtin_clzll(x) : 0)); +} + +struct SimpleCode { + SimpleCode(size_t code, size_t num_classes) : c_(code + num_classes) {} + inline size_t calc_index(int bit) const { return (c_ >> (bit + 1)) - 1; } + inline bool calc_bit(int bit) const { return c_ & (1 << bit); } + inline int get_length() const { return FindLastSet(c_) - 1; } + + private: + size_t c_; +}; + +struct SimpleCodeTable { + explicit SimpleCodeTable(size_t num_classes) : num_classes_(num_classes) {} + SimpleCode operator()(size_t code) const { + return SimpleCode(code, num_classes_); + } + size_t size() const { return num_classes_; } + int get_max_code_length() const { return FindLastSet(num_classes_ - 1); } + + private: + size_t num_classes_; + int max_code_length_; +}; + +} // namespace math +} // namespace operators +} // namespace paddle -- GitLab From a25c3aeba6d1a370e4b361f26f0e112fd00e7c4e Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Fri, 17 Nov 2017 10:31:44 +0800 Subject: [PATCH 0002/1416] add forward --- paddle/operators/hierarchical_sigmoid_op.cc | 13 ++++++------- paddle/operators/hierarchical_sigmoid_op.h | 16 +++++++++++++++- paddle/operators/math/matrix_bit_code.cc | 6 +++--- paddle/operators/math/matrix_bit_code.h | 4 ++++ 4 files changed, 28 insertions(+), 11 deletions(-) diff --git a/paddle/operators/hierarchical_sigmoid_op.cc b/paddle/operators/hierarchical_sigmoid_op.cc index 1f77ff1268a..9b7af92662e 100644 --- a/paddle/operators/hierarchical_sigmoid_op.cc +++ b/paddle/operators/hierarchical_sigmoid_op.cc @@ -83,19 +83,18 @@ class HierarchicalSigmoidOpMaker : public framework::OpProtoAndCheckerMaker { : OpProtoAndCheckerMaker(proto, op_checker) { AddInput("X", "(TensorArray, required) The input array. Each Tensor has the " - "same shape with [N * D]." - .AsDuplicable(); + "same shape with [N * D].") + .AsDuplicable(); AddInput("Label", "(Tensor, required), The labels of training data. It's a" "1-D tensor."); AddInput("Bias", "(Tensor, optional), The bias is a 1-D tensor, " "which is applied to the output"); - AddOutput("Out", - "(Tensor, required) The output of hierarchical sigmoid operator."); - AddAttr("num_classes", - "(int, required)", - "The number of classes"); + AddOutput( + "Out", + "(Tensor, required) The output of hierarchical sigmoid operator."); + AddAttr("num_classes", "(int, required)", "The number of classes"); AddComment(R"DOC( The hierarchical sigmoid operator organize the classes into a binary tree. At each node, a sigmoid function is used to caculate the probability of diff --git a/paddle/operators/hierarchical_sigmoid_op.h b/paddle/operators/hierarchical_sigmoid_op.h index 8a753605d6e..11a553a4039 100644 --- a/paddle/operators/hierarchical_sigmoid_op.h +++ b/paddle/operators/hierarchical_sigmoid_op.h @@ -22,7 +22,21 @@ template class HierarchicalSigmoidOpKernel : public framework::OpKernel { public: - void Compute(const framework::ExecutionContext& ctx) const override {} + void Compute(const framework::ExecutionContext& ctx) const override { + auto ins = ctx.MultiInput("X"); + auto* label = ctx.Input("Label"); + auto* bias = ctx.Input("Bias"); + size_t num_classes = static_cast(ctx.Attr("num_classes")); + int64_t batch_size = ins[0]->dims()[0]; + int64_t size = ins.size(); + framework::Tensor pre_out; + std::vector pre_out_dims({batch_size, size}); + pre_out.mutable_data(framework::make_ddim(pre_out_dims), ctx.GetPlace()); + + if (bias != NULL) { + math::AddByBitCode(num_classes, *label, pre_out, *bias); + } + } }; template diff --git a/paddle/operators/math/matrix_bit_code.cc b/paddle/operators/math/matrix_bit_code.cc index 3f1dbbf3994..30c2ffc2cfd 100644 --- a/paddle/operators/math/matrix_bit_code.cc +++ b/paddle/operators/math/matrix_bit_code.cc @@ -50,7 +50,7 @@ namespace math { for j < codeLength: op(a(i, j), b(0, index(i, j))) */ -template +template static void AddByBitCodeT(Op op, CodeTable code_table, const framework::Tensor& codes, framework::Tensor& a, framework::Tensor& b) { @@ -72,11 +72,11 @@ static void AddByBitCodeT(Op op, CodeTable code_table, /* For j < codeLength: a(i, j) += b(0, index(i, j)) */ -template +template void AddByBitCode(size_t num_classes, const framework::Tensor& codes, framework::Tensor& a, const framework::Tensor& b) { auto op = [](T& t, T& v) { t += v; }; - AddByBitCodeT(op, SimpleCodeTable(num_classes), codes, a, b); + AddByBitCodeT(op, SimpleCodeTable(num_classes), codes, a, b); } } // namespace math diff --git a/paddle/operators/math/matrix_bit_code.h b/paddle/operators/math/matrix_bit_code.h index a0dd89ebe01..bb0599aa177 100644 --- a/paddle/operators/math/matrix_bit_code.h +++ b/paddle/operators/math/matrix_bit_code.h @@ -59,6 +59,10 @@ struct SimpleCodeTable { int max_code_length_; }; +template +void AddByBitCode(size_t num_classes, const framework::Tensor& codes, + framework::Tensor& a, const framework::Tensor& b); + } // namespace math } // namespace operators } // namespace paddle -- GitLab From 1abd3b3a29b6964323d679d47dea31830f5b5e6a Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Mon, 27 Nov 2017 19:28:57 +0800 Subject: [PATCH 0003/1416] implement forward --- paddle/operators/CMakeLists.txt | 4 +- paddle/operators/hierarchical_sigmoid_op.cc | 6 +- paddle/operators/hierarchical_sigmoid_op.h | 39 ++++++++++- paddle/operators/math/math_function.cc | 2 + paddle/operators/math/math_function.cu | 2 + paddle/operators/math/math_function.h | 6 ++ paddle/operators/math/math_function_impl.h | 14 ++++ paddle/operators/math/matrix_bit_code.cc | 77 +++++++++++++++++++-- paddle/operators/math/matrix_bit_code.h | 19 ++++- 9 files changed, 157 insertions(+), 12 deletions(-) diff --git a/paddle/operators/CMakeLists.txt b/paddle/operators/CMakeLists.txt index a719da25602..93ec763424d 100644 --- a/paddle/operators/CMakeLists.txt +++ b/paddle/operators/CMakeLists.txt @@ -185,7 +185,8 @@ set(DEPS_OPS tensor_array_read_write_op gru_op adagrad_op - sgd_op) + sgd_op + hierarchical_sigmoid_op) op_library(cond_op SRCS cond_op.cc DEPS framework_proto tensor operator net_op) @@ -203,6 +204,7 @@ op_library(lod_rank_table_op SRCS lod_rank_table_op.cc DEPS lod_rank_table) op_library(lod_tensor_to_array_op SRCS lod_tensor_to_array_op.cc DEPS lod_rank_table_op) op_library(array_to_lod_tensor_op SRCS array_to_lod_tensor_op.cc DEPS lod_rank_table_op) op_library(tensor_array_read_write_op SRCS tensor_array_read_write_op.cc) +op_library(hierarchical_sigmoid_op DEPS matrix_bit_code) if(WITH_GPU) op_library(nccl_op DEPS nccl_common) endif() diff --git a/paddle/operators/hierarchical_sigmoid_op.cc b/paddle/operators/hierarchical_sigmoid_op.cc index 9b7af92662e..f81f3d34d19 100644 --- a/paddle/operators/hierarchical_sigmoid_op.cc +++ b/paddle/operators/hierarchical_sigmoid_op.cc @@ -85,12 +85,16 @@ class HierarchicalSigmoidOpMaker : public framework::OpProtoAndCheckerMaker { "(TensorArray, required) The input array. Each Tensor has the " "same shape with [N * D].") .AsDuplicable(); + AddInput("Parameters", + "(Tensor, required), The parameters of hierarchical " + "sigmoid operator, each of them is s a 2-D tensor.") + .AsDuplicable(); AddInput("Label", "(Tensor, required), The labels of training data. It's a" "1-D tensor."); AddInput("Bias", "(Tensor, optional), The bias is a 1-D tensor, " - "which is applied to the output"); + "which is applied to the output."); AddOutput( "Out", "(Tensor, required) The output of hierarchical sigmoid operator."); diff --git a/paddle/operators/hierarchical_sigmoid_op.h b/paddle/operators/hierarchical_sigmoid_op.h index 11a553a4039..baf655f2141 100644 --- a/paddle/operators/hierarchical_sigmoid_op.h +++ b/paddle/operators/hierarchical_sigmoid_op.h @@ -14,28 +14,61 @@ limitations under the License. */ #pragma once #include "paddle/framework/op_registry.h" +#include "paddle/operators/math/math_function.h" #include "paddle/operators/math/matrix_bit_code.h" namespace paddle { namespace operators { -template +template +using EigenMatrix = framework::EigenMatrix; + +template class HierarchicalSigmoidOpKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& ctx) const override { auto ins = ctx.MultiInput("X"); + auto params = ctx.MultiInput("Parameters"); auto* label = ctx.Input("Label"); auto* bias = ctx.Input("Bias"); + auto* out = ctx.Output("Out"); size_t num_classes = static_cast(ctx.Attr("num_classes")); + + framework::Tensor sum; + framework::Tensor pre_out; + auto place = ctx.GetEigenDevice(); + auto& device_ctx = ctx.device_context(); + math::ColwiseSum col_sum; + math::RowwiseSum row_sum; + + auto pre_out_mat = EigenMatrix::From(pre_out); int64_t batch_size = ins[0]->dims()[0]; int64_t size = ins.size(); - framework::Tensor pre_out; + std::vector pre_out_dims({batch_size, size}); pre_out.mutable_data(framework::make_ddim(pre_out_dims), ctx.GetPlace()); + std::vector sum_dims({batch_size, 1UL}); + sum.mutable_data(framework::make_ddim(sum_dims), ctx.GetPlace()); + out->mutable_data(ctx.GetPlace()); - if (bias != NULL) { + if (bias) { math::AddByBitCode(num_classes, *label, pre_out, *bias); } + + for (size_t i = 0; i < ins.size(); ++i) { + math::MulByBitCode(num_classes, *label, pre_out, *params[i], *ins[i]); + } + // clip the matrix with (-40, 40) + pre_out_mat.device(place) = + pre_out_mat.abs().cwiseMax(static_cast(40.0)); + math::SumByBitCode(num_classes, *label, *out, pre_out, + static_cast(-1)); + // softrelu + pre_out_mat.device(place) = (static_cast(1) + pre_out_mat.exp()).log(); + + row_sum(device_ctx, pre_out, &sum); + col_sum(device_ctx, *out, &sum); } }; diff --git a/paddle/operators/math/math_function.cc b/paddle/operators/math/math_function.cc index 2e333a8cde7..3bc0945fe3a 100644 --- a/paddle/operators/math/math_function.cc +++ b/paddle/operators/math/math_function.cc @@ -314,6 +314,8 @@ template struct RowwiseAdd; template struct RowwiseAdd; template struct ColwiseSum; template struct ColwiseSum; +template struct RowwiseSum; +template struct RowwiseSum; } // namespace math } // namespace operators diff --git a/paddle/operators/math/math_function.cu b/paddle/operators/math/math_function.cu index 58356a4b778..1a226821f71 100644 --- a/paddle/operators/math/math_function.cu +++ b/paddle/operators/math/math_function.cu @@ -298,6 +298,8 @@ template struct RowwiseAdd; template struct RowwiseAdd; template struct ColwiseSum; template struct ColwiseSum; +template struct RowwiseSum; +template struct RowwiseSum; } // namespace math } // namespace operators diff --git a/paddle/operators/math/math_function.h b/paddle/operators/math/math_function.h index ffb99f53808..c21a20fc326 100644 --- a/paddle/operators/math/math_function.h +++ b/paddle/operators/math/math_function.h @@ -130,6 +130,12 @@ struct ColwiseSum { const framework::Tensor& input, framework::Tensor* vec); }; +template +struct RowwiseSum { + void operator()(const platform::DeviceContext& context, + const framework::Tensor& input, framework::Tensor* vec); +}; + } // namespace math } // namespace operators } // namespace paddle diff --git a/paddle/operators/math/math_function_impl.h b/paddle/operators/math/math_function_impl.h index 4dc17a4e525..8c1971fc611 100644 --- a/paddle/operators/math/math_function_impl.h +++ b/paddle/operators/math/math_function_impl.h @@ -78,6 +78,20 @@ void ColwiseSum::operator()(const platform::DeviceContext& context, in.sum(Eigen::array({{0}})).reshape(shape); } +template +void RowwiseSum::operator()(const platform::DeviceContext& context, + const framework::Tensor& input, + framework::Tensor* vector) { + auto in_dims = input.dims(); + auto size = input.numel() / in_dims[1]; + PADDLE_ENFORCE_EQ(vector->numel(), size); + + auto in = framework::EigenMatrix::From(input); + auto vec = framework::EigenMatrix::From(*vector); + Eigen::array shape({{static_cast(size), 1}}); + vec.reshape(shape).device(*context.GetEigenDevice()) = + in.sum(Eigen::array({{0}})).reshape(shape); +} } // namespace math } // namespace operators } // namespace paddle diff --git a/paddle/operators/math/matrix_bit_code.cc b/paddle/operators/math/matrix_bit_code.cc index 30c2ffc2cfd..8f68e2f79dd 100644 --- a/paddle/operators/math/matrix_bit_code.cc +++ b/paddle/operators/math/matrix_bit_code.cc @@ -53,18 +53,18 @@ namespace math { template static void AddByBitCodeT(Op op, CodeTable code_table, const framework::Tensor& codes, framework::Tensor& a, - framework::Tensor& b) { + const framework::Tensor& b) { size_t num_classes = code_table.size(); size_t max_code_length = code_table.get_max_code_length(); - size_t num_sample = a.dims()[0].size(); - size_t width = a.dims()[1].size(); + size_t num_sample = a.dims()[0]; + size_t width = a.dims()[1]; for (size_t i = 0; i < num_sample; ++i) { - auto code = code_table(codes.data()[i]) int code_length = - code.get_length(); + auto code = code_table(codes.data()[i]); + int code_length = code.get_length(); for (int j = 0; j < code_length; + j) { size_t index = code.calc_index(j); - op(a.data()[i * width + j], b.data()[index]); + op(a.data()[i * width + j], b.data()[index]); } } } @@ -79,6 +79,71 @@ void AddByBitCode(size_t num_classes, const framework::Tensor& codes, AddByBitCodeT(op, SimpleCodeTable(num_classes), codes, a, b); } +template +void SumByBitCodeT(CodeTable code_table, const framework::Tensor& codes, + framework::Tensor& tmat, framework::Tensor& sum, + const T& scale_sum) { + size_t max_code_length = code_table.get_max_code_length(); + size_t num_samples = tmat.dims()[0]; + size_t o_width = tmat.dims()[1]; + for (size_t i = 0; i < num_samples; ++i) { + T sm = 0; + auto code = code_table(codes.data()[i]); + int code_length = code.get_length(); + for (int j = 0; j < code_length; ++j) { + if (code.calc_bit(j)) { + sm += tmat.data()[i * o_width + j]; + } + } + sum.data()[i] = scale_sum * sm; + } +} +/* For j < codeLength: + sum(i, 0) = \sum_j bit(i, j) * input(i, j) +*/ +template +void SumByBitCode(size_t num_classes, const framework::Tensor& codes, + framework::Tensor& tmat, framework::Tensor& sum, + T scale_sum) { + SumByBitCodeT(SimpleCodeTable(num_classes), codes, tmat, scale_sum); +} + +template +void MulByBitCodeT(Op op, CodeTable code_table, const framework::Tensor& codes, + framework::Tensor& tmat, framework::Tensor& weight, + framework::Tensor& input) { + size_t num_classes = code_table.size(); + size_t max_code_length = code_table.get_max_code_length(); + size_t num_samples = tmat.dims()[0]; + size_t input_dim = input.dims()[1]; + size_t o_width = tmat.dims()[1]; + + for (size_t i = 0; i < num_samples; ++i) { + auto code = code_table(codes.data()[i]); + int code_length = code.get_length(); + for (int j = 0; j < code_length; ++j) { + size_t index = code.calc_index(j); + op(tmat.data()[i * o_width + j], + weight.data() + index * weight.dims()[1], + input.data() + i * input.dims()[1], input_dim); + } + } +} + +template +void MulByBitCode(size_t num_classes, const framework::Tensor& codes, + framework::Tensor& tmat, const framework::Tensor& weight, + const framework::Tensor& input) { + auto op = [](T& t, const T* weight_row, const T* input_row, + size_t input_dim) { + T sum = 0; + for (size_t k = 0; k < input_dim; ++k) { + sum += weight_row[k] * input_row[k]; + } + t += sum; + }; + MulByBitCode(op, SimpleCodeTable(num_classes), codes, tmat, weight, input); +} } // namespace math } // namespace operators } // namespace paddle diff --git a/paddle/operators/math/matrix_bit_code.h b/paddle/operators/math/matrix_bit_code.h index bb0599aa177..7bef5077b9b 100644 --- a/paddle/operators/math/matrix_bit_code.h +++ b/paddle/operators/math/matrix_bit_code.h @@ -59,10 +59,27 @@ struct SimpleCodeTable { int max_code_length_; }; +/* For j < codeLength + tmat(i, j) += vec(0, index(i, j)) +*/ template void AddByBitCode(size_t num_classes, const framework::Tensor& codes, - framework::Tensor& a, const framework::Tensor& b); + framework::Tensor& tmat, const framework::Tensor& vec); +/* For j < codeLength + sum(i, 0) = \sum_j bit(i, j) * tmat(i, j) +*/ +template +void SumByBitCode(size_t num_classes, const framework::Tensor& codes, + framework::Tensor& tmat, framework::Tensor& sum, T scale_sum); + +/* For j < codeLength + input.row(i) += tmat(i, j) * weight.row(index(i, j)) +*/ +template +void MulByBitCode(size_t num_classes, const framework::Tensor& codes, + framework::Tensor& tmat, const framework::Tensor& weight, + const framework::Tensor& input); } // namespace math } // namespace operators } // namespace paddle -- GitLab From 1f9426fd47d4cc3911e9f0a2f23274d69dd104e8 Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Wed, 29 Nov 2017 20:17:22 +0800 Subject: [PATCH 0004/1416] add backward --- paddle/operators/hierarchical_sigmoid_op.h | 52 ++++++++++++++-- paddle/operators/math/matrix_bit_code.cc | 71 +++++++++++++++++++--- paddle/operators/math/matrix_bit_code.h | 36 ++++++++++- 3 files changed, 144 insertions(+), 15 deletions(-) diff --git a/paddle/operators/hierarchical_sigmoid_op.h b/paddle/operators/hierarchical_sigmoid_op.h index baf655f2141..186c7679323 100644 --- a/paddle/operators/hierarchical_sigmoid_op.h +++ b/paddle/operators/hierarchical_sigmoid_op.h @@ -44,9 +44,9 @@ class HierarchicalSigmoidOpKernel : public framework::OpKernel { auto pre_out_mat = EigenMatrix::From(pre_out); int64_t batch_size = ins[0]->dims()[0]; - int64_t size = ins.size(); + int64_t code_length = math::FindLastSet(num_classes - 1); - std::vector pre_out_dims({batch_size, size}); + std::vector pre_out_dims({batch_size, code_length}); pre_out.mutable_data(framework::make_ddim(pre_out_dims), ctx.GetPlace()); std::vector sum_dims({batch_size, 1UL}); sum.mutable_data(framework::make_ddim(sum_dims), ctx.GetPlace()); @@ -64,8 +64,11 @@ class HierarchicalSigmoidOpKernel : public framework::OpKernel { pre_out_mat.abs().cwiseMax(static_cast(40.0)); math::SumByBitCode(num_classes, *label, *out, pre_out, static_cast(-1)); - // softrelu - pre_out_mat.device(place) = (static_cast(1) + pre_out_mat.exp()).log(); + + // softrelu with threshold is 40.0 + pre_out_mat.device(place) = + pre_out_mat.abs().cwiseMax(static_cast(40.0)); + pre_out_mat.device(place) = (static_cast(1.0) + pre_out_mat.exp()).log(); row_sum(device_ctx, pre_out, &sum); col_sum(device_ctx, *out, &sum); @@ -75,7 +78,46 @@ class HierarchicalSigmoidOpKernel : public framework::OpKernel { template class HierarchicalSigmoidGradOpKernel : public framework::OpKernel { public: - void Compute(const framework::ExecutionContext& ctx) const override {} + void Compute(const framework::ExecutionContext& ctx) const override { + auto ins = ctx.MultiInput("X"); + auto ins_grad = + ctx.MultiOutput(framework::GradVarName("X")); + auto params = ctx.MultiOutput( + framework::GradVarName("Parameters")); + auto* bias = ctx.Output(framework::GradVarName("Bias")); + auto* label = + ctx.Output(framework::GradVarName("Label")); + size_t num_classes = static_cast(ctx.Attr("num_classes")); + + framework::Tensor pre_out; + auto place = ctx.GetEigenDevice(); + auto& dev_ctx = ctx.device_context(); + int64_t batch_size = ins_grad.size(); + int64_t code_length = math::FindLastSet(num_classes - 1); + auto pre_out_mat = EigenMatrix::From(pre_out); + + // init pre_out matrix with {1.0} + std::vector pre_out_dims({batch_size, code_length}); + pre_out.mutable_data(framework::make_ddim(pre_out_dims), ctx.GetPlace()); + math::SetConstant set; + set(dev_ctx, &pre_out, static_cast(1.0)); + // softrelu derivative + pre_out_mat.device(place) = + pre_out_mat * (static_cast(1.0) - static_cast(1.0) / pre_out_mat); + + math::SubByBitCode(num_classes, *label, pre_out); + + if (bias) { + math::AddByBitCodeGrad(num_classes, *label, pre_out, *bias); + } + + for (size_t i = 0; i < ins_grad.size(); ++i) { + math::MulByBitCodeGradWeight(num_classes, *label, pre_out, *params[i], + *ins[i]); + math::MulByBitCodeGradError(num_classes, *label, pre_out, *params[i], + *ins_grad[i]); + } + } }; } // namespace operators diff --git a/paddle/operators/math/matrix_bit_code.cc b/paddle/operators/math/matrix_bit_code.cc index 8f68e2f79dd..996e0b819f6 100644 --- a/paddle/operators/math/matrix_bit_code.cc +++ b/paddle/operators/math/matrix_bit_code.cc @@ -69,19 +69,23 @@ static void AddByBitCodeT(Op op, CodeTable code_table, } } -/* For j < codeLength: - a(i, j) += b(0, index(i, j)) -*/ template void AddByBitCode(size_t num_classes, const framework::Tensor& codes, - framework::Tensor& a, const framework::Tensor& b) { + framework::Tensor& tmat, const framework::Tensor& vec) { auto op = [](T& t, T& v) { t += v; }; - AddByBitCodeT(op, SimpleCodeTable(num_classes), codes, a, b); + AddByBitCodeT(op, SimpleCodeTable(num_classes), codes, tmat, vec); +} + +template +void AddByBitCodeGrad(size_t num_classes, const framework::Tensor& codes, + const framework::Tensor& tmat, framework::Tensor& vec) { + auto op = [](T& t, T& v) { v += t; }; + AddByBitCode(op, SimpleCodeTable(num_classes), codes, tmat, vec); } template void SumByBitCodeT(CodeTable code_table, const framework::Tensor& codes, - framework::Tensor& tmat, framework::Tensor& sum, + framework::Tensor& tmat, const framework::Tensor& sum, const T& scale_sum) { size_t max_code_length = code_table.get_max_code_length(); size_t num_samples = tmat.dims()[0]; @@ -142,8 +146,61 @@ void MulByBitCode(size_t num_classes, const framework::Tensor& codes, } t += sum; }; - MulByBitCode(op, SimpleCodeTable(num_classes), codes, tmat, weight, input); + MulByBitCodeT(op, SimpleCodeTable(num_classes), codes, tmat, weight, + input); +} + +template +void MulByBitCodeGradWeight(size_t num_classes, const framework::Tensor& codes, + const framework::Tensor& tmat, + framework::Tensor& weight, + const framework::Tensor& input) { + auto op = [](const T t, T* weight_row, const T* input_row, size_t input_dim) { + for (size_t k = 0; k < input_dim; ++k) { + weight_row[k] += t * input_row[k]; + } + }; + MulByBitCodeT(op, SimpleCodeTable(num_classes), codes, tmat, weight, + input); } + +template +void MulByBitCodeGradError(size_t num_classes, const framework::Tensor& codes, + const framework::Tensor& tmat, + const framework::Tensor& weight, + framework::Tensor& input) { + auto op = [](const T t, const T* weight_row, T* input_row, size_t input_dim) { + for (size_t k = 0; k < input_dim; ++k) { + input_row[k] += t * weight_row[k]; + } + }; + MulByBitCodeT(op, SimpleCodeTable(num_classes), codes, tmat, weight, + input); +} + +template +void SubByBitCodeT(CodeTable code_table, const framework::Tensor& codes, + framework::Tensor& tmat) { + size_t max_code_length = code_table.get_max_code_length(); + size_t num_samples = tmat.dims()[0]; + size_t o_width = tmat.dims()[1]; + for (size_t i = 0; i < num_samples; ++i) { + auto code = code_table(codes.data()[i]); + int code_length = code.get_length(); + for (int j = 0; j < code_length; ++j) { + if (code.calc_bit(j)) { + tmat.data()[i * o_width + j] -= 1; + } + } + } +} + +template +void SubByBitCode(size_t num_classes, const framework::Tensor& codes, + framework::Tensor& tmat) { + SubByBitCodeT(SimpleCodeTable(num_classes), codes, tmat); +} + } // namespace math } // namespace operators } // namespace paddle diff --git a/paddle/operators/math/matrix_bit_code.h b/paddle/operators/math/matrix_bit_code.h index 7bef5077b9b..43c9d43d89d 100644 --- a/paddle/operators/math/matrix_bit_code.h +++ b/paddle/operators/math/matrix_bit_code.h @@ -59,27 +59,57 @@ struct SimpleCodeTable { int max_code_length_; }; -/* For j < codeLength +/* For j < code_length tmat(i, j) += vec(0, index(i, j)) */ template void AddByBitCode(size_t num_classes, const framework::Tensor& codes, framework::Tensor& tmat, const framework::Tensor& vec); -/* For j < codeLength +/* For j < code_length + vec(0, index(i, j)) += tmat(i, j) +*/ +template +void AddByBitCodeGrad(size_t num_classes, const framework::Tensor& codes, + const framework::Tensor& tmat, framework::Tensor& vec); +/* For j < code_length sum(i, 0) = \sum_j bit(i, j) * tmat(i, j) */ template void SumByBitCode(size_t num_classes, const framework::Tensor& codes, framework::Tensor& tmat, framework::Tensor& sum, T scale_sum); -/* For j < codeLength +/* For j < code_length input.row(i) += tmat(i, j) * weight.row(index(i, j)) */ template void MulByBitCode(size_t num_classes, const framework::Tensor& codes, framework::Tensor& tmat, const framework::Tensor& weight, const framework::Tensor& input); + +/* For index(i, j) >= 0: + weight.row(index(i, j)) += tmat(i, j) * input.row(i) +*/ +template +void MulByBitCodeGradWeight(size_t num_classes, const framework::Tensor& codes, + const framework::Tensor& tmat, + framework::Tensor& weight, + const framework::Tensor& input); +/* For j < code_length + input.row(i) += tmat(i, j) * weight.row(index(i, j)) +*/ +template +void MulByBitCodeGradError(size_t num_classes, const framework::Tensor& codes, + const framework::Tensor& tmat, + const framework::Tensor& weight, + framework::Tensor& input); + +/* For j < code_length + tmat(i, j) -= bit(i, j) +*/ +template +void SubByBitCode(size_t num_classes, const framework::Tensor& codes, + framework::Tensor& tmat); } // namespace math } // namespace operators } // namespace paddle -- GitLab From f8395631e12e19d433ce4d5b6ddcefc0b04db6e1 Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Thu, 14 Dec 2017 13:12:00 +0800 Subject: [PATCH 0005/1416] fix invalid dims --- paddle/operators/hierarchical_sigmoid_op.cc | 28 +++++++-------- paddle/operators/hierarchical_sigmoid_op.h | 26 +++++++------- paddle/operators/math/matrix_bit_code.cc | 11 +++--- .../paddle/v2/fluid/tests/test_hsigmoid_op.py | 34 +++++++++++++++++++ 4 files changed, 67 insertions(+), 32 deletions(-) create mode 100644 python/paddle/v2/fluid/tests/test_hsigmoid_op.py diff --git a/paddle/operators/hierarchical_sigmoid_op.cc b/paddle/operators/hierarchical_sigmoid_op.cc index f81f3d34d19..063f8576e66 100644 --- a/paddle/operators/hierarchical_sigmoid_op.cc +++ b/paddle/operators/hierarchical_sigmoid_op.cc @@ -60,12 +60,11 @@ class HierarchicalSigmoidOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; void InferShape(framework::InferShapeContext* ctx) const override { - PADDLE_ENFORCE(ctx->HasInputs("X"), "Inputs(X) should not be null."); + PADDLE_ENFORCE(ctx->hasInput("X"), "Input(X) should not be null."); PADDLE_ENFORCE(ctx->HasInput("Label"), "Input(Label) should not be null."); PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output(Out) should not be null."); - const int64_t batch_size = ctx->GetInputsDim("X")[0][0]; - const int64_t size = ctx->GetInputsDim("X").size(); - std::vector output_shape({batch_size, size}); + const int64_t batch_size = ctx->GetInputDim("X")[0]; + std::vector output_shape({batch_size, num_classes_ - 1}); ctx->SetOutputDim("Out", framework::make_ddim(output_shape)); } }; @@ -82,22 +81,23 @@ class HierarchicalSigmoidOpMaker : public framework::OpProtoAndCheckerMaker { framework::OpAttrChecker* op_checker) : OpProtoAndCheckerMaker(proto, op_checker) { AddInput("X", - "(TensorArray, required) The input array. Each Tensor has the " - "same shape with [N * D].") - .AsDuplicable(); + "(Tensor, required) The input Tensor, which the shape is" + "[N * D], which N is the size of mini-batch," + "D is the embded size"); AddInput("Parameters", "(Tensor, required), The parameters of hierarchical " - "sigmoid operator, each of them is s a 2-D tensor.") - .AsDuplicable(); + "sigmoid operator, each of them is s a 3-D tensor, the shape is" + "[N, num_classes - 1, D]"); AddInput("Label", "(Tensor, required), The labels of training data. It's a" - "1-D tensor."); + "1-D tensor, which the shape is [1, N]"); AddInput("Bias", "(Tensor, optional), The bias is a 1-D tensor, " - "which is applied to the output."); - AddOutput( - "Out", - "(Tensor, required) The output of hierarchical sigmoid operator."); + "which is applied to the output, the shape is" + "[1, num_classes -1]"); + AddOutput("Out", + "(Tensor, required) The output of hierarchical sigmoid operator." + "the shape is [N, 1]"); AddAttr("num_classes", "(int, required)", "The number of classes"); AddComment(R"DOC( The hierarchical sigmoid operator organize the classes into a binary tree. diff --git a/paddle/operators/hierarchical_sigmoid_op.h b/paddle/operators/hierarchical_sigmoid_op.h index 186c7679323..e3f0bcacd8b 100644 --- a/paddle/operators/hierarchical_sigmoid_op.h +++ b/paddle/operators/hierarchical_sigmoid_op.h @@ -28,8 +28,8 @@ template class HierarchicalSigmoidOpKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& ctx) const override { - auto ins = ctx.MultiInput("X"); - auto params = ctx.MultiInput("Parameters"); + auto* in = ctx.Input("X"); + auto* param = ctx.Input("Parameter"); auto* label = ctx.Input("Label"); auto* bias = ctx.Input("Bias"); auto* out = ctx.Output("Out"); @@ -56,8 +56,9 @@ class HierarchicalSigmoidOpKernel : public framework::OpKernel { math::AddByBitCode(num_classes, *label, pre_out, *bias); } - for (size_t i = 0; i < ins.size(); ++i) { - math::MulByBitCode(num_classes, *label, pre_out, *params[i], *ins[i]); + for (size_t i = 0; i < in.dims()[0]; ++i) { + math::MulByBitCode(num_classes, *label, pre_out, + *params->Slice(i, i + 1), *in->Slice(i, i + 1)); } // clip the matrix with (-40, 40) pre_out_mat.device(place) = @@ -79,11 +80,10 @@ template class HierarchicalSigmoidGradOpKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& ctx) const override { - auto ins = ctx.MultiInput("X"); - auto ins_grad = - ctx.MultiOutput(framework::GradVarName("X")); - auto params = ctx.MultiOutput( - framework::GradVarName("Parameters")); + auto* in = ctx.Input("X"); + auto* in_grad = ctx.Output(framework::GradVarName("X")); + auto* params = + ctx.Output(framework::GradVarName("Parameters")); auto* bias = ctx.Output(framework::GradVarName("Bias")); auto* label = ctx.Output(framework::GradVarName("Label")); @@ -92,7 +92,7 @@ class HierarchicalSigmoidGradOpKernel : public framework::OpKernel { framework::Tensor pre_out; auto place = ctx.GetEigenDevice(); auto& dev_ctx = ctx.device_context(); - int64_t batch_size = ins_grad.size(); + int64_t batch_size = in_grad.dims()[0]; int64_t code_length = math::FindLastSet(num_classes - 1); auto pre_out_mat = EigenMatrix::From(pre_out); @@ -111,11 +111,11 @@ class HierarchicalSigmoidGradOpKernel : public framework::OpKernel { math::AddByBitCodeGrad(num_classes, *label, pre_out, *bias); } - for (size_t i = 0; i < ins_grad.size(); ++i) { + for (size_t i = 0; i < in_grad.dims()[0]; ++i) { math::MulByBitCodeGradWeight(num_classes, *label, pre_out, *params[i], - *ins[i]); + *in[i]->Slice(i, i + 1)); math::MulByBitCodeGradError(num_classes, *label, pre_out, *params[i], - *ins_grad[i]); + *ins_grad[i]->Slice(i, i + 1)); } } }; diff --git a/paddle/operators/math/matrix_bit_code.cc b/paddle/operators/math/matrix_bit_code.cc index 996e0b819f6..df988510547 100644 --- a/paddle/operators/math/matrix_bit_code.cc +++ b/paddle/operators/math/matrix_bit_code.cc @@ -52,19 +52,20 @@ namespace math { */ template static void AddByBitCodeT(Op op, CodeTable code_table, - const framework::Tensor& codes, framework::Tensor& a, - const framework::Tensor& b) { + const framework::Tensor& codes, + framework::Tensor& tmat, + const framework::Tensor& vec) { size_t num_classes = code_table.size(); size_t max_code_length = code_table.get_max_code_length(); - size_t num_sample = a.dims()[0]; - size_t width = a.dims()[1]; + size_t num_sample = tmat.dims()[0]; + size_t width = vec.dims()[1]; for (size_t i = 0; i < num_sample; ++i) { auto code = code_table(codes.data()[i]); int code_length = code.get_length(); for (int j = 0; j < code_length; + j) { size_t index = code.calc_index(j); - op(a.data()[i * width + j], b.data()[index]); + op(tmat.data()[i * width + j], vec.data()[index]); } } } diff --git a/python/paddle/v2/fluid/tests/test_hsigmoid_op.py b/python/paddle/v2/fluid/tests/test_hsigmoid_op.py new file mode 100644 index 00000000000..25c13aabe97 --- /dev/null +++ b/python/paddle/v2/fluid/tests/test_hsigmoid_op.py @@ -0,0 +1,34 @@ +import unittest +import numpy as np +from op_test import OpTest + + +class TestHSigmoidOp(OpTest): + def setUp(self): + self.op_type = "hierarchical_sigmoid_op" + num_classes = 6 + embded_size = 10 + batch_size = 5 + x = np.random.random((batch_size, embded_size)).astype("float32") + parameter = np.random.random( + (batch_size, num_classes - 1, embded_size)).astype("float32") + label = np.random.randint(0, num_classes, batch_size).astype("int64") + bias = np.random.random((1, num_classes - 1)) + self.inputs = { + 'X': x, + 'Parameters': parameter, + 'Label': label, + 'Bias': bias + } + self.attrs = {'num_classes': num_classes} + self.outputs = {'Out': label} + + def test_check_output(self): + self.check_output() + + def test_check_grad(self): + self.check_grad(['x0'], 'Out') + + +if __name__ == '__main__': + unittest.main() -- GitLab From fb9c08f0438fe0a25d0d2517e5e770ea5a22555d Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Mon, 25 Dec 2017 08:51:04 +0800 Subject: [PATCH 0006/1416] make forward work --- paddle/operators/CMakeLists.txt | 2 +- paddle/operators/hierarchical_sigmoid_op.cc | 50 ++++- paddle/operators/hierarchical_sigmoid_op.h | 95 ++++---- paddle/operators/math/CMakeLists.txt | 2 +- paddle/operators/math/math_function.cc | 12 +- paddle/operators/math/math_function.h | 6 +- paddle/operators/math/math_function_impl.h | 16 +- paddle/operators/math/matrix_bit_code.cc | 211 ++++++++++-------- paddle/operators/math/matrix_bit_code.h | 86 ++++--- paddle/pybind/pybind.cc | 2 + python/paddle/v2/fluid/tests/op_test.py | 11 +- .../paddle/v2/fluid/tests/test_hsigmoid_op.py | 15 +- 12 files changed, 285 insertions(+), 223 deletions(-) diff --git a/paddle/operators/CMakeLists.txt b/paddle/operators/CMakeLists.txt index d79f19e670d..5fb14cc6d4a 100644 --- a/paddle/operators/CMakeLists.txt +++ b/paddle/operators/CMakeLists.txt @@ -207,7 +207,7 @@ set(DEPS_OPS gru_op adagrad_op sgd_op - hierarchical_sigmoid_op) + hierarchical_sigmoid_op save_op load_op send_op diff --git a/paddle/operators/hierarchical_sigmoid_op.cc b/paddle/operators/hierarchical_sigmoid_op.cc index 063f8576e66..fa816d9215d 100644 --- a/paddle/operators/hierarchical_sigmoid_op.cc +++ b/paddle/operators/hierarchical_sigmoid_op.cc @@ -60,19 +60,48 @@ class HierarchicalSigmoidOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; void InferShape(framework::InferShapeContext* ctx) const override { - PADDLE_ENFORCE(ctx->hasInput("X"), "Input(X) should not be null."); + PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null."); PADDLE_ENFORCE(ctx->HasInput("Label"), "Input(Label) should not be null."); + PADDLE_ENFORCE(ctx->HasInput("Parameters"), + "Input(Parameters)" + "should not be null."); PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output(Out) should not be null."); const int64_t batch_size = ctx->GetInputDim("X")[0]; - std::vector output_shape({batch_size, num_classes_ - 1}); + std::vector output_shape({batch_size, 1}); ctx->SetOutputDim("Out", framework::make_ddim(output_shape)); } + + protected: + framework::OpKernelType GetKernelType( + const framework::ExecutionContext& ctx) const override { + return framework::OpKernelType( + framework::ToDataType(ctx.Input("X")->type()), + ctx.GetPlace()); + } }; class HierarchicalSigmoidGradOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; - void InferShape(framework::InferShapeContext* ctx) const override {} + void InferShape(framework::InferShapeContext* ctx) const override { + PADDLE_ENFORCE(ctx->HasInput("Parameters"), + "Input(Parameters)" + "should not be null."); + PADDLE_ENFORCE(ctx->HasInput("Label"), + "Input(Label)" + "should not be null."); + PADDLE_ENFORCE(ctx->HasOutput(framework::GradVarName("Parameters")), + "Input(Parameters@Grad should not be null.)"); + PADDLE_ENFORCE(ctx->HasOutput(framework::GradVarName("X"))); + } + + protected: + framework::OpKernelType GetKernelType( + const framework::ExecutionContext& ctx) const override { + return framework::OpKernelType( + framework::ToDataType(ctx.Input("X")->type()), + ctx.GetPlace()); + } }; class HierarchicalSigmoidOpMaker : public framework::OpProtoAndCheckerMaker { @@ -98,7 +127,8 @@ class HierarchicalSigmoidOpMaker : public framework::OpProtoAndCheckerMaker { AddOutput("Out", "(Tensor, required) The output of hierarchical sigmoid operator." "the shape is [N, 1]"); - AddAttr("num_classes", "(int, required)", "The number of classes"); + AddAttr("num_classes", "(int, required)", "The number of classes") + .SetDefault(2); AddComment(R"DOC( The hierarchical sigmoid operator organize the classes into a binary tree. At each node, a sigmoid function is used to caculate the probability of @@ -116,9 +146,9 @@ namespace ops = paddle::operators; REGISTER_OP(hierarchical_sigmoid, ops::HierarchicalSigmoidOp, ops::HierarchicalSigmoidOpMaker, hierarchical_sigmoid_grad, ops::HierarchicalSigmoidGradOp); -REGISTER_OP_CPU_KERNEL( - hierarchical_sigmoid, - ops::HierarchicalSigmoidOpKernel); -REGISTER_OP_CPU_KERNEL( - hierarchical_sigmoid_grad, - ops::HierarchicalSigmoidGradOpKernel); +REGISTER_OP_CPU_KERNEL(hierarchical_sigmoid, + ops::HierarchicalSigmoidOpKernel< + paddle::platform::CPUDeviceContext, float>); +REGISTER_OP_CPU_KERNEL(hierarchical_sigmoid_grad, + ops::HierarchicalSigmoidGradOpKernel< + paddle::platform::CPUDeviceContext, float>); diff --git a/paddle/operators/hierarchical_sigmoid_op.h b/paddle/operators/hierarchical_sigmoid_op.h index e3f0bcacd8b..531fd9f7fc0 100644 --- a/paddle/operators/hierarchical_sigmoid_op.h +++ b/paddle/operators/hierarchical_sigmoid_op.h @@ -14,8 +14,10 @@ limitations under the License. */ #pragma once #include "paddle/framework/op_registry.h" +#include "paddle/operators/clip_op.h" #include "paddle/operators/math/math_function.h" #include "paddle/operators/math/matrix_bit_code.h" +#include "paddle/platform/transform.h" namespace paddle { namespace operators { @@ -23,60 +25,64 @@ namespace operators { template using EigenMatrix = framework::EigenMatrix; +using platform::Transform; -template +template class HierarchicalSigmoidOpKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& ctx) const override { auto* in = ctx.Input("X"); - auto* param = ctx.Input("Parameter"); + auto* params = ctx.Input("Parameters"); auto* label = ctx.Input("Label"); auto* bias = ctx.Input("Bias"); auto* out = ctx.Output("Out"); size_t num_classes = static_cast(ctx.Attr("num_classes")); - framework::Tensor sum; + int64_t code_length = math::FindLastSet(num_classes - 1); + int64_t batch_size = in->dims()[0]; + auto* ids = label->data(); framework::Tensor pre_out; - auto place = ctx.GetEigenDevice(); - auto& device_ctx = ctx.device_context(); - math::ColwiseSum col_sum; - math::RowwiseSum row_sum; - + framework::Tensor sum; + auto pre_out_data = pre_out.mutable_data( + framework::make_ddim({batch_size, code_length}), ctx.GetPlace()); auto pre_out_mat = EigenMatrix::From(pre_out); - int64_t batch_size = ins[0]->dims()[0]; - int64_t code_length = math::FindLastSet(num_classes - 1); - std::vector pre_out_dims({batch_size, code_length}); - pre_out.mutable_data(framework::make_ddim(pre_out_dims), ctx.GetPlace()); + auto& place = *ctx.template device_context().eigen_device(); + auto& device_ctx = ctx.template device_context(); + math::RowwiseSum row_sum; + math::MatrixBitCodeFunctor bit_code; + std::vector sum_dims({batch_size, 1UL}); sum.mutable_data(framework::make_ddim(sum_dims), ctx.GetPlace()); + auto sum_mat = EigenMatrix::From(sum); out->mutable_data(ctx.GetPlace()); + auto out_mat = framework::EigenVector::Flatten(*out); if (bias) { - math::AddByBitCode(num_classes, *label, pre_out, *bias); + bit_code.Add(num_classes, ids, pre_out, *bias); } - - for (size_t i = 0; i < in.dims()[0]; ++i) { - math::MulByBitCode(num_classes, *label, pre_out, - *params->Slice(i, i + 1), *in->Slice(i, i + 1)); + for (int i = 0; i < in->dims()[0]; ++i) { + bit_code.Mul(num_classes, ids, pre_out, params->Slice(i, i + 1), + in->Slice(i, i + 1)); } // clip the matrix with (-40, 40) - pre_out_mat.device(place) = - pre_out_mat.abs().cwiseMax(static_cast(40.0)); - math::SumByBitCode(num_classes, *label, *out, pre_out, - static_cast(-1)); - + Transform trans; + trans(ctx.template device_context(), pre_out_data, + pre_out_data + pre_out.numel(), pre_out_data, + ClipFunctor(static_cast(-40.0), static_cast(40.0))); + bit_code.Sum(num_classes, ids, pre_out, *out, static_cast(-1)); // softrelu with threshold is 40.0 - pre_out_mat.device(place) = - pre_out_mat.abs().cwiseMax(static_cast(40.0)); + trans(ctx.template device_context(), pre_out_data, + pre_out_data + pre_out.numel(), pre_out_data, + ClipFunctor(static_cast(-40.0), static_cast(40.0))); pre_out_mat.device(place) = (static_cast(1.0) + pre_out_mat.exp()).log(); row_sum(device_ctx, pre_out, &sum); - col_sum(device_ctx, *out, &sum); + out_mat.device(place) = sum_mat + out_mat; } }; -template +template class HierarchicalSigmoidGradOpKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& ctx) const override { @@ -85,37 +91,40 @@ class HierarchicalSigmoidGradOpKernel : public framework::OpKernel { auto* params = ctx.Output(framework::GradVarName("Parameters")); auto* bias = ctx.Output(framework::GradVarName("Bias")); - auto* label = - ctx.Output(framework::GradVarName("Label")); + auto* label = ctx.Input("Label"); size_t num_classes = static_cast(ctx.Attr("num_classes")); + int64_t code_length = math::FindLastSet(num_classes - 1); + int64_t batch_size = in->dims()[0]; framework::Tensor pre_out; - auto place = ctx.GetEigenDevice(); - auto& dev_ctx = ctx.device_context(); - int64_t batch_size = in_grad.dims()[0]; - int64_t code_length = math::FindLastSet(num_classes - 1); + pre_out.mutable_data(framework::make_ddim({batch_size, code_length}), + ctx.GetPlace()); + auto& place = *ctx.template device_context().eigen_device(); + auto& device_ctx = ctx.template device_context(); auto pre_out_mat = EigenMatrix::From(pre_out); + auto* ids = label->data(); // init pre_out matrix with {1.0} - std::vector pre_out_dims({batch_size, code_length}); - pre_out.mutable_data(framework::make_ddim(pre_out_dims), ctx.GetPlace()); - math::SetConstant set; - set(dev_ctx, &pre_out, static_cast(1.0)); + math::SetConstant one; + math::MatrixBitCodeFunctor bit_code; + one(device_ctx, &pre_out, static_cast(1.0)); // softrelu derivative pre_out_mat.device(place) = pre_out_mat * (static_cast(1.0) - static_cast(1.0) / pre_out_mat); - math::SubByBitCode(num_classes, *label, pre_out); + bit_code.Sub(num_classes, ids, pre_out); if (bias) { - math::AddByBitCodeGrad(num_classes, *label, pre_out, *bias); + bit_code.AddGrad(num_classes, ids, pre_out, *bias); } - for (size_t i = 0; i < in_grad.dims()[0]; ++i) { - math::MulByBitCodeGradWeight(num_classes, *label, pre_out, *params[i], - *in[i]->Slice(i, i + 1)); - math::MulByBitCodeGradError(num_classes, *label, pre_out, *params[i], - *ins_grad[i]->Slice(i, i + 1)); + for (int i = 0; i < in_grad->dims()[0]; ++i) { + auto p_sliced = params->Slice(i, i + 1); + auto in_sliced = in->Slice(i, i + 1); + auto in_grad_sliced = in_grad->Slice(i, i + 1); + bit_code.MulGradWeight(num_classes, ids, pre_out, p_sliced, in_sliced); + bit_code.MulGradError(num_classes, ids, pre_out, p_sliced, + in_grad_sliced); } } }; diff --git a/paddle/operators/math/CMakeLists.txt b/paddle/operators/math/CMakeLists.txt index 6467d8ddb33..82ba24f35b9 100644 --- a/paddle/operators/math/CMakeLists.txt +++ b/paddle/operators/math/CMakeLists.txt @@ -27,7 +27,7 @@ else() cc_library(context_project SRCS context_project.cc DEPS device_context math_function) cc_library(sequence2batch SRCS sequence2batch.cc DEPS device_context) cc_library(lstm_compute SRCS lstm_compute.cc DEPS device_context activation_functions) - cc_library(matrix_bit_code SRCS matrix_bit_code.cc) + cc_library(matrix_bit_code SRCS matrix_bit_code.cc DEPS device_context) cc_library(maxouting SRCS maxouting.cc DEPS device_context) cc_library(unpooling SRCS unpooling.cc DEPS device_context) cc_library(gru_compute SRCS gru_compute.cc DEPS device_context activation_functions math_function) diff --git a/paddle/operators/math/math_function.cc b/paddle/operators/math/math_function.cc index ead0fe19713..474fd0b0a94 100644 --- a/paddle/operators/math/math_function.cc +++ b/paddle/operators/math/math_function.cc @@ -302,12 +302,12 @@ void set_constant(const platform::DeviceContext& context, #endif } -template struct RowwiseAdd; -template struct RowwiseAdd; -template struct ColwiseSum; -template struct ColwiseSum; -template struct RowwiseSum; -template struct RowwiseSum; +template struct RowwiseAdd; +template struct RowwiseAdd; +template struct ColwiseSum; +template struct ColwiseSum; +template struct RowwiseSum; +template struct RowwiseSum; } // namespace math } // namespace operators diff --git a/paddle/operators/math/math_function.h b/paddle/operators/math/math_function.h index 51e0fd9ad77..b49294e6216 100644 --- a/paddle/operators/math/math_function.h +++ b/paddle/operators/math/math_function.h @@ -128,10 +128,10 @@ struct ColwiseSum { framework::Tensor* vec); }; -template +template struct RowwiseSum { - void operator()(const platform::DeviceContext& context, - const framework::Tensor& input, framework::Tensor* vec); + void operator()(const DeviceContext& context, const framework::Tensor& input, + framework::Tensor* vec); }; } // namespace math diff --git a/paddle/operators/math/math_function_impl.h b/paddle/operators/math/math_function_impl.h index 4d5e8481018..2b3b6c335b3 100644 --- a/paddle/operators/math/math_function_impl.h +++ b/paddle/operators/math/math_function_impl.h @@ -79,19 +79,19 @@ void ColwiseSum::operator()(const DeviceContext& context, in.sum(Eigen::array({{0}})).reshape(shape); } -template -void RowwiseSum::operator()(const platform::DeviceContext& context, - const framework::Tensor& input, - framework::Tensor* vector) { +template +void RowwiseSum::operator()(const DeviceContext& context, + const framework::Tensor& input, + framework::Tensor* vector) { auto in_dims = input.dims(); auto size = input.numel() / in_dims[1]; PADDLE_ENFORCE_EQ(vector->numel(), size); - auto in = framework::EigenMatrix::From(input); - auto vec = framework::EigenMatrix::From(*vector); + auto in = framework::EigenMatrix::From(input); + auto vec = framework::EigenMatrix::From(*vector); Eigen::array shape({{static_cast(size), 1}}); - vec.reshape(shape).device(*context.GetEigenDevice()) = - in.sum(Eigen::array({{0}})).reshape(shape); + vec.reshape(shape).device(*context.eigen_device()) = + in.sum(Eigen::array({{1}})).reshape(shape); } } // namespace math } // namespace operators diff --git a/paddle/operators/math/matrix_bit_code.cc b/paddle/operators/math/matrix_bit_code.cc index df988510547..9e3836b06dc 100644 --- a/paddle/operators/math/matrix_bit_code.cc +++ b/paddle/operators/math/matrix_bit_code.cc @@ -50,50 +50,52 @@ namespace math { for j < codeLength: op(a(i, j), b(0, index(i, j))) */ -template -static void AddByBitCodeT(Op op, CodeTable code_table, - const framework::Tensor& codes, - framework::Tensor& tmat, +template +static void AddByBitCodeT(Op op, CodeTable code_table, const int64_t* codes, + const framework::Tensor& tmat, const framework::Tensor& vec) { - size_t num_classes = code_table.size(); - size_t max_code_length = code_table.get_max_code_length(); size_t num_sample = tmat.dims()[0]; size_t width = vec.dims()[1]; for (size_t i = 0; i < num_sample; ++i) { - auto code = code_table(codes.data()[i]); + auto code = code_table(static_cast(codes[i])); int code_length = code.get_length(); - for (int j = 0; j < code_length; + j) { + for (int j = 0; j < code_length; ++j) { size_t index = code.calc_index(j); - op(tmat.data()[i * width + j], vec.data()[index]); + auto t = tmat.data()[i * width + j]; + auto v = vec.data()[index]; + op(t, v); } } } -template -void AddByBitCode(size_t num_classes, const framework::Tensor& codes, - framework::Tensor& tmat, const framework::Tensor& vec) { - auto op = [](T& t, T& v) { t += v; }; - AddByBitCodeT(op, SimpleCodeTable(num_classes), codes, tmat, vec); -} - -template -void AddByBitCodeGrad(size_t num_classes, const framework::Tensor& codes, - const framework::Tensor& tmat, framework::Tensor& vec) { - auto op = [](T& t, T& v) { v += t; }; - AddByBitCode(op, SimpleCodeTable(num_classes), codes, tmat, vec); +template +void SubByBitCodeT(CodeTable code_table, const int64_t* codes, + framework::Tensor& tmat) { + // size_t max_code_length = code_table.get_max_code_length(); + size_t num_samples = tmat.dims()[0]; + size_t o_width = tmat.dims()[1]; + for (size_t i = 0; i < num_samples; ++i) { + auto code = code_table(static_cast(codes[i])); + int code_length = code.get_length(); + for (int j = 0; j < code_length; ++j) { + if (code.calc_bit(j)) { + tmat.data()[i * o_width + j] -= 1; + } + } + } } -template -void SumByBitCodeT(CodeTable code_table, const framework::Tensor& codes, - framework::Tensor& tmat, const framework::Tensor& sum, +template +void SumByBitCodeT(CodeTable code_table, const int64_t* codes, + framework::Tensor& tmat, framework::Tensor& sum, const T& scale_sum) { - size_t max_code_length = code_table.get_max_code_length(); + // size_t max_code_length = code_table.get_max_code_length(); size_t num_samples = tmat.dims()[0]; size_t o_width = tmat.dims()[1]; for (size_t i = 0; i < num_samples; ++i) { - T sm = 0; - auto code = code_table(codes.data()[i]); + T sm = static_cast(0.0); + auto code = code_table(static_cast(codes[i])); int code_length = code.get_length(); for (int j = 0; j < code_length; ++j) { if (code.calc_bit(j)) { @@ -103,105 +105,124 @@ void SumByBitCodeT(CodeTable code_table, const framework::Tensor& codes, sum.data()[i] = scale_sum * sm; } } -/* For j < codeLength: - sum(i, 0) = \sum_j bit(i, j) * input(i, j) -*/ + template -void SumByBitCode(size_t num_classes, const framework::Tensor& codes, - framework::Tensor& tmat, framework::Tensor& sum, - T scale_sum) { - SumByBitCodeT(SimpleCodeTable(num_classes), codes, tmat, scale_sum); +void MatrixBitCodeFunctor::Add(size_t num_classes, const int64_t* codes, + framework::Tensor& tmat, + const framework::Tensor& vec) { + auto op = [](T& t, const T& v) { t += v; }; + AddByBitCodeT(op, SimpleCodeTable(num_classes), codes, tmat, vec); } -template -void MulByBitCodeT(Op op, CodeTable code_table, const framework::Tensor& codes, - framework::Tensor& tmat, framework::Tensor& weight, - framework::Tensor& input) { - size_t num_classes = code_table.size(); - size_t max_code_length = code_table.get_max_code_length(); - size_t num_samples = tmat.dims()[0]; - size_t input_dim = input.dims()[1]; - size_t o_width = tmat.dims()[1]; +template +void MatrixBitCodeFunctor::AddGrad(size_t num_classes, const int64_t* codes, + framework::Tensor& tmat, + framework::Tensor& vec) { + auto op = [](T& t, T& v) { v += t; }; + AddByBitCodeT(op, SimpleCodeTable(num_classes), codes, tmat, vec); +} +template +void MatrixBitCodeFunctor::Sum(size_t num_classes, const int64_t* codes, + framework::Tensor& tmat, + framework::Tensor& sum, T scale_sum) { + SumByBitCodeT(SimpleCodeTable(num_classes), codes, tmat, sum, scale_sum); +} + +template +void MatrixBitCodeFunctor::Mul(size_t num_classes, const int64_t* codes, + framework::Tensor& tmat, + const framework::Tensor& weight, + const framework::Tensor& input) { + size_t num_samples = tmat.dims()[0]; + size_t tmat_width = tmat.dims()[1]; + size_t input_width = input.dims()[1]; + size_t weight_width = weight.dims()[1]; + auto tmat_p = tmat.data(); + auto weight_p = weight.data(); + auto input_p = input.data(); + auto code_table = SimpleCodeTable(num_classes); for (size_t i = 0; i < num_samples; ++i) { - auto code = code_table(codes.data()[i]); + auto code = code_table(static_cast(codes[i])); int code_length = code.get_length(); for (int j = 0; j < code_length; ++j) { size_t index = code.calc_index(j); - op(tmat.data()[i * o_width + j], - weight.data() + index * weight.dims()[1], - input.data() + i * input.dims()[1], input_dim); + + T sum = static_cast(0.0); + for (size_t k = 0; k < input_width; ++k) { + sum += + weight_p[weight_width * index + k] * input_p[input_width * i + k]; + } + std::cout << sum << std::endl; + tmat_p[i * tmat_width + j] += sum; } } } template -void MulByBitCode(size_t num_classes, const framework::Tensor& codes, - framework::Tensor& tmat, const framework::Tensor& weight, - const framework::Tensor& input) { - auto op = [](T& t, const T* weight_row, const T* input_row, - size_t input_dim) { - T sum = 0; - for (size_t k = 0; k < input_dim; ++k) { - sum += weight_row[k] * input_row[k]; - } - t += sum; - }; - MulByBitCodeT(op, SimpleCodeTable(num_classes), codes, tmat, weight, - input); -} +void MatrixBitCodeFunctor::MulGradWeight(size_t num_classes, + const int64_t* codes, + const framework::Tensor& tmat, + framework::Tensor& weight, + const framework::Tensor& input) { + size_t num_samples = tmat.dims()[0]; + size_t input_width = input.dims()[1]; + size_t weight_width = weight.dims()[1]; + auto tmat_p = tmat.data(); + auto weight_p = weight.data(); + auto input_p = input.data(); + auto code_table = SimpleCodeTable(num_classes); + for (size_t i = 0; i < num_samples; ++i) { + auto code = code_table(static_cast(codes[i])); + int code_length = code.get_length(); + for (int j = 0; j < code_length; ++j) { + size_t index = code.calc_index(j); -template -void MulByBitCodeGradWeight(size_t num_classes, const framework::Tensor& codes, - const framework::Tensor& tmat, - framework::Tensor& weight, - const framework::Tensor& input) { - auto op = [](const T t, T* weight_row, const T* input_row, size_t input_dim) { - for (size_t k = 0; k < input_dim; ++k) { - weight_row[k] += t * input_row[k]; + for (size_t k = 0; k < input_width; ++k) { + weight_p[weight_width * index * k] += + tmat_p[i * weight_width * j] * input_p[input_width * i + k]; + } } - }; - MulByBitCodeT(op, SimpleCodeTable(num_classes), codes, tmat, weight, - input); + } } template -void MulByBitCodeGradError(size_t num_classes, const framework::Tensor& codes, - const framework::Tensor& tmat, - const framework::Tensor& weight, - framework::Tensor& input) { - auto op = [](const T t, const T* weight_row, T* input_row, size_t input_dim) { - for (size_t k = 0; k < input_dim; ++k) { - input_row[k] += t * weight_row[k]; - } - }; - MulByBitCodeT(op, SimpleCodeTable(num_classes), codes, tmat, weight, - input); -} - -template -void SubByBitCodeT(CodeTable code_table, const framework::Tensor& codes, - framework::Tensor& tmat) { - size_t max_code_length = code_table.get_max_code_length(); +void MatrixBitCodeFunctor::MulGradError(size_t num_classes, + const int64_t* codes, + const framework::Tensor& tmat, + const framework::Tensor& weight, + framework::Tensor& input) { size_t num_samples = tmat.dims()[0]; - size_t o_width = tmat.dims()[1]; + size_t input_width = input.dims()[1]; + size_t weight_width = weight.dims()[1]; + auto tmat_p = tmat.data(); + auto weight_p = weight.data(); + auto input_p = input.data(); + auto code_table = SimpleCodeTable(num_classes); + for (size_t i = 0; i < num_samples; ++i) { - auto code = code_table(codes.data()[i]); + auto code = code_table(static_cast(codes[i])); int code_length = code.get_length(); for (int j = 0; j < code_length; ++j) { - if (code.calc_bit(j)) { - tmat.data()[i * o_width + j] -= 1; + size_t index = code.calc_index(j); + + for (size_t k = 0; k < input_width; ++k) { + input_p[weight_width * index * k] += + tmat_p[i * weight_width * j] * weight_p[weight_width * i + k]; } } } } template -void SubByBitCode(size_t num_classes, const framework::Tensor& codes, - framework::Tensor& tmat) { +void MatrixBitCodeFunctor::Sub(size_t num_classes, const int64_t* codes, + framework::Tensor& tmat) { SubByBitCodeT(SimpleCodeTable(num_classes), codes, tmat); } +template class MatrixBitCodeFunctor; +template class MatrixBitCodeFunctor; + } // namespace math } // namespace operators } // namespace paddle diff --git a/paddle/operators/math/matrix_bit_code.h b/paddle/operators/math/matrix_bit_code.h index 43c9d43d89d..d2ebf182c86 100644 --- a/paddle/operators/math/matrix_bit_code.h +++ b/paddle/operators/math/matrix_bit_code.h @@ -15,6 +15,7 @@ limitations under the License. */ #pragma once #include "paddle/framework/eigen.h" #include "paddle/framework/tensor.h" +#include "paddle/platform/device_context.h" namespace paddle { namespace operators { @@ -59,57 +60,50 @@ struct SimpleCodeTable { int max_code_length_; }; -/* For j < code_length - tmat(i, j) += vec(0, index(i, j)) -*/ template -void AddByBitCode(size_t num_classes, const framework::Tensor& codes, - framework::Tensor& tmat, const framework::Tensor& vec); +class MatrixBitCodeFunctor { + public: + /* For j < code_length + tmat(i, j) += vec(0, index(i, j)) + */ + void Add(size_t num_classes, const int64_t* codes, framework::Tensor& tmat, + const framework::Tensor& vec); -/* For j < code_length - vec(0, index(i, j)) += tmat(i, j) -*/ -template -void AddByBitCodeGrad(size_t num_classes, const framework::Tensor& codes, - const framework::Tensor& tmat, framework::Tensor& vec); -/* For j < code_length + /* For j < code_length + vec(0, index(i, j)) += tmat(i, j) + */ + void AddGrad(size_t num_classes, const int64_t* codes, + framework::Tensor& tmat, framework::Tensor& vec); + + /* For j < code_length sum(i, 0) = \sum_j bit(i, j) * tmat(i, j) -*/ -template -void SumByBitCode(size_t num_classes, const framework::Tensor& codes, - framework::Tensor& tmat, framework::Tensor& sum, T scale_sum); + */ + void Sum(size_t num_classes, const int64_t* codes, framework::Tensor& tmat, + framework::Tensor& sum, T scale_sum); -/* For j < code_length - input.row(i) += tmat(i, j) * weight.row(index(i, j)) -*/ -template -void MulByBitCode(size_t num_classes, const framework::Tensor& codes, - framework::Tensor& tmat, const framework::Tensor& weight, - const framework::Tensor& input); + /* For j < code_length + tmat(i, j) -= bit(i, j) + */ + void Sub(size_t num_classes, const int64_t* codes, framework::Tensor& tmat); + /* For j < code_length + input.row(i) += tmat(i, j) * weight.row(index(i, j)) + */ + void Mul(size_t num_classes, const int64_t* codes, framework::Tensor& tmat, + const framework::Tensor& weight, const framework::Tensor& input); -/* For index(i, j) >= 0: - weight.row(index(i, j)) += tmat(i, j) * input.row(i) -*/ -template -void MulByBitCodeGradWeight(size_t num_classes, const framework::Tensor& codes, - const framework::Tensor& tmat, - framework::Tensor& weight, - const framework::Tensor& input); -/* For j < code_length - input.row(i) += tmat(i, j) * weight.row(index(i, j)) -*/ -template -void MulByBitCodeGradError(size_t num_classes, const framework::Tensor& codes, - const framework::Tensor& tmat, - const framework::Tensor& weight, - framework::Tensor& input); - -/* For j < code_length - tmat(i, j) -= bit(i, j) -*/ -template -void SubByBitCode(size_t num_classes, const framework::Tensor& codes, - framework::Tensor& tmat); + /* For index(i, j) >= 0: + weight.row(index(i, j)) += tmat(i, j) * input.row(i) + */ + void MulGradWeight(size_t num_classes, const int64_t* codes, + const framework::Tensor& tmat, framework::Tensor& weight, + const framework::Tensor& input); + /* For j < code_length + input.row(i) += tmat(i, j) * weight.row(index(i, j)) + */ + void MulGradError(size_t num_classes, const int64_t* codes, + const framework::Tensor& tmat, + const framework::Tensor& weight, framework::Tensor& input); +}; } // namespace math } // namespace operators } // namespace paddle diff --git a/paddle/pybind/pybind.cc b/paddle/pybind/pybind.cc index c16d3e0cbe0..a05fcd0451c 100644 --- a/paddle/pybind/pybind.cc +++ b/paddle/pybind/pybind.cc @@ -126,6 +126,8 @@ PYBIND11_PLUGIN(core) { .def("shape", [](Tensor &self) { return vectorize(self.dims()); }) .def("set_float_element", TensorSetElement) .def("get_float_element", TensorGetElement) + .def("set_int64_element", TensorSetElement) + .def("get_int64_element", TensorGetElement) .def("set_double_element", TensorSetElement) .def("get_double_element", TensorGetElement) .def("dtype", [](Tensor &self) { return ToDataType(self.type()); }); diff --git a/python/paddle/v2/fluid/tests/op_test.py b/python/paddle/v2/fluid/tests/op_test.py index e83c4a06220..edf68075bec 100644 --- a/python/paddle/v2/fluid/tests/op_test.py +++ b/python/paddle/v2/fluid/tests/op_test.py @@ -49,7 +49,6 @@ def create_op(scope, op_type, inputs, outputs, attrs): for attr_name in Operator.get_op_attr_names(op_type): if attr_name in attrs: kwargs[attr_name] = attrs[attr_name] - return Operator(op_type, **kwargs) @@ -107,6 +106,8 @@ def get_numeric_gradient(scope, tensor_to_check_dtype = np.float32 elif tensor_to_check_dtype == core.DataType.FP64: tensor_to_check_dtype = np.float64 + elif tensor_to_check_dtype == core.DataType.INT64: + tensor_to_check_dtype = np.int64 else: raise ValueError("Not supported data type " + str( tensor_to_check_dtype)) @@ -116,12 +117,16 @@ def get_numeric_gradient(scope, def __get_elem__(tensor, i): if tensor_to_check_dtype == np.float32: return tensor.get_float_element(i) + elif tensor_to_check_dtype == np.int64: + return tensor.get_int64_element(i) else: return tensor.get_double_element(i) def __set_elem__(tensor, i, e): if tensor_to_check_dtype == np.float32: tensor.set_float_element(i, e) + elif tensor_to_check_dtype == np.int64: + tensor.set_int64_element(i, e) else: tensor.set_double_element(i, e) @@ -355,13 +360,11 @@ class OpTest(unittest.TestCase): op_attrs = self.attrs if hasattr(self, "attrs") else dict() self.op = create_op(self.scope, self.op_type, op_inputs, op_outputs, op_attrs) - if no_grad_set is None: no_grad_set = set() if not type(output_names) is list: output_names = [output_names] - numeric_grads = user_defined_grads or [ get_numeric_gradient( self.scope, @@ -457,9 +460,7 @@ class OpTest(unittest.TestCase): # infer variable type and infer shape in compile-time op.desc.infer_var_type(block.desc) op.desc.infer_shape(block.desc) - mean_inputs = map(block.var, output_names) - if len(mean_inputs) == 1: loss = block.create_var(dtype=mean_inputs[0].dtype, shape=[1]) op = block.append_op( diff --git a/python/paddle/v2/fluid/tests/test_hsigmoid_op.py b/python/paddle/v2/fluid/tests/test_hsigmoid_op.py index 25c13aabe97..194d5e315fc 100644 --- a/python/paddle/v2/fluid/tests/test_hsigmoid_op.py +++ b/python/paddle/v2/fluid/tests/test_hsigmoid_op.py @@ -5,15 +5,15 @@ from op_test import OpTest class TestHSigmoidOp(OpTest): def setUp(self): - self.op_type = "hierarchical_sigmoid_op" + self.op_type = "hierarchical_sigmoid" num_classes = 6 embded_size = 10 batch_size = 5 x = np.random.random((batch_size, embded_size)).astype("float32") parameter = np.random.random( (batch_size, num_classes - 1, embded_size)).astype("float32") - label = np.random.randint(0, num_classes, batch_size).astype("int64") - bias = np.random.random((1, num_classes - 1)) + label = np.random.randint(0, num_classes, batch_size) + bias = np.random.random((1, num_classes - 1)).astype("float32") self.inputs = { 'X': x, 'Parameters': parameter, @@ -21,13 +21,18 @@ class TestHSigmoidOp(OpTest): 'Bias': bias } self.attrs = {'num_classes': num_classes} - self.outputs = {'Out': label} + self.outputs = { + 'Out': np.random.random((batch_size, 1)).astype("float32") + } def test_check_output(self): self.check_output() def test_check_grad(self): - self.check_grad(['x0'], 'Out') + self.check_grad( + ['X', 'Parameters', 'Label', 'Bias'], + 'Out', + no_grad_set=set(['Label'])) if __name__ == '__main__': -- GitLab From f07164912bca60a36a72dc6ce22f8e00caa99301 Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Wed, 3 Jan 2018 20:00:07 +0800 Subject: [PATCH 0007/1416] fix backward --- paddle/operators/hierarchical_sigmoid_op.cc | 28 +++++++------- paddle/operators/hierarchical_sigmoid_op.h | 38 +++++++++---------- paddle/operators/math/matrix_bit_code.cc | 1 - paddle/pybind/pybind.cc | 2 - python/paddle/v2/fluid/executor.py | 1 - python/paddle/v2/fluid/tests/op_test.py | 2 - .../paddle/v2/fluid/tests/test_hsigmoid_op.py | 16 ++------ 7 files changed, 37 insertions(+), 51 deletions(-) diff --git a/paddle/operators/hierarchical_sigmoid_op.cc b/paddle/operators/hierarchical_sigmoid_op.cc index 4b3487f8b96..bc6ceb98747 100644 --- a/paddle/operators/hierarchical_sigmoid_op.cc +++ b/paddle/operators/hierarchical_sigmoid_op.cc @@ -61,10 +61,8 @@ class HierarchicalSigmoidOp : public framework::OperatorWithKernel { using framework::OperatorWithKernel::OperatorWithKernel; void InferShape(framework::InferShapeContext* ctx) const override { PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null."); - PADDLE_ENFORCE(ctx->HasInput("Label"), "Input(Label) should not be null."); - PADDLE_ENFORCE(ctx->HasInput("Parameters"), - "Input(Parameters)" - "should not be null."); + PADDLE_ENFORCE(ctx->HasInput("Ids"), "Input(Ids) should not be null."); + PADDLE_ENFORCE(ctx->HasInput("W"), "Input(W) should not be null."); PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output(Out) should not be null."); const int64_t batch_size = ctx->GetInputDim("X")[0]; std::vector output_shape({batch_size, 1}); @@ -84,15 +82,17 @@ class HierarchicalSigmoidGradOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; void InferShape(framework::InferShapeContext* ctx) const override { - PADDLE_ENFORCE(ctx->HasInput("Parameters"), - "Input(Parameters)" - "should not be null."); - PADDLE_ENFORCE(ctx->HasInput("Label"), - "Input(Label)" - "should not be null."); - PADDLE_ENFORCE(ctx->HasOutput(framework::GradVarName("Parameters")), - "Input(Parameters@Grad should not be null.)"); + PADDLE_ENFORCE(ctx->HasInput("W"), "Input(W) should not be null."); + PADDLE_ENFORCE(ctx->HasInput("Ids"), "Input(Ids) should not be null."); + PADDLE_ENFORCE(ctx->HasOutput(framework::GradVarName("W")), + "Input(W@Grad should not be null.)"); PADDLE_ENFORCE(ctx->HasOutput(framework::GradVarName("X"))); + if (ctx->HasOutput(framework::GradVarName("Bias"))) { + ctx->SetOutputDim(framework::GradVarName("Bias"), + ctx->GetInputDim("Bias")); + } + ctx->SetOutputDim(framework::GradVarName("W"), ctx->GetInputDim("W")); + ctx->SetOutputDim(framework::GradVarName("X"), ctx->GetInputDim("X")); } protected: @@ -112,11 +112,11 @@ class HierarchicalSigmoidOpMaker : public framework::OpProtoAndCheckerMaker { "(Tensor, required) The input Tensor, which the shape is" "[N * D], which N is the size of mini-batch," "D is the embded size"); - AddInput("Parameters", + AddInput("W", "(Tensor, required), The parameters of hierarchical " "sigmoid operator, each of them is s a 3-D tensor, the shape is" "[N, num_classes - 1, D]"); - AddInput("Label", + AddInput("Ids", "(Tensor, required), The labels of training data. It's a" "1-D tensor, which the shape is [1, N]"); AddInput("Bias", diff --git a/paddle/operators/hierarchical_sigmoid_op.h b/paddle/operators/hierarchical_sigmoid_op.h index 531fd9f7fc0..1b8d21c095e 100644 --- a/paddle/operators/hierarchical_sigmoid_op.h +++ b/paddle/operators/hierarchical_sigmoid_op.h @@ -32,15 +32,14 @@ class HierarchicalSigmoidOpKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& ctx) const override { auto* in = ctx.Input("X"); - auto* params = ctx.Input("Parameters"); - auto* label = ctx.Input("Label"); + auto* w = ctx.Input("W"); + auto* ids = ctx.Input("Ids"); auto* bias = ctx.Input("Bias"); auto* out = ctx.Output("Out"); size_t num_classes = static_cast(ctx.Attr("num_classes")); int64_t code_length = math::FindLastSet(num_classes - 1); int64_t batch_size = in->dims()[0]; - auto* ids = label->data(); framework::Tensor pre_out; framework::Tensor sum; auto pre_out_data = pre_out.mutable_data( @@ -59,18 +58,19 @@ class HierarchicalSigmoidOpKernel : public framework::OpKernel { auto out_mat = framework::EigenVector::Flatten(*out); if (bias) { - bit_code.Add(num_classes, ids, pre_out, *bias); + bit_code.Add(num_classes, ids->data(), pre_out, *bias); } for (int i = 0; i < in->dims()[0]; ++i) { - bit_code.Mul(num_classes, ids, pre_out, params->Slice(i, i + 1), - in->Slice(i, i + 1)); + bit_code.Mul(num_classes, ids->data(), pre_out, + w->Slice(i, i + 1), in->Slice(i, i + 1)); } // clip the matrix with (-40, 40) Transform trans; trans(ctx.template device_context(), pre_out_data, pre_out_data + pre_out.numel(), pre_out_data, ClipFunctor(static_cast(-40.0), static_cast(40.0))); - bit_code.Sum(num_classes, ids, pre_out, *out, static_cast(-1)); + bit_code.Sum(num_classes, ids->data(), pre_out, *out, + static_cast(-1)); // softrelu with threshold is 40.0 trans(ctx.template device_context(), pre_out_data, pre_out_data + pre_out.numel(), pre_out_data, @@ -88,10 +88,9 @@ class HierarchicalSigmoidGradOpKernel : public framework::OpKernel { void Compute(const framework::ExecutionContext& ctx) const override { auto* in = ctx.Input("X"); auto* in_grad = ctx.Output(framework::GradVarName("X")); - auto* params = - ctx.Output(framework::GradVarName("Parameters")); + auto* w = ctx.Output(framework::GradVarName("W")); auto* bias = ctx.Output(framework::GradVarName("Bias")); - auto* label = ctx.Input("Label"); + auto* ids = ctx.Input("Ids"); size_t num_classes = static_cast(ctx.Attr("num_classes")); int64_t code_length = math::FindLastSet(num_classes - 1); int64_t batch_size = in->dims()[0]; @@ -102,8 +101,6 @@ class HierarchicalSigmoidGradOpKernel : public framework::OpKernel { auto& place = *ctx.template device_context().eigen_device(); auto& device_ctx = ctx.template device_context(); auto pre_out_mat = EigenMatrix::From(pre_out); - auto* ids = label->data(); - // init pre_out matrix with {1.0} math::SetConstant one; math::MatrixBitCodeFunctor bit_code; @@ -112,19 +109,22 @@ class HierarchicalSigmoidGradOpKernel : public framework::OpKernel { pre_out_mat.device(place) = pre_out_mat * (static_cast(1.0) - static_cast(1.0) / pre_out_mat); - bit_code.Sub(num_classes, ids, pre_out); + bit_code.Sub(num_classes, ids->data(), pre_out); if (bias) { - bit_code.AddGrad(num_classes, ids, pre_out, *bias); + bias->mutable_data(ctx.GetPlace()); + bit_code.AddGrad(num_classes, ids->data(), pre_out, *bias); } - + in_grad->mutable_data(ctx.GetPlace()); + w->mutable_data(ctx.GetPlace()); for (int i = 0; i < in_grad->dims()[0]; ++i) { - auto p_sliced = params->Slice(i, i + 1); + auto p_sliced = w->Slice(i, i + 1); auto in_sliced = in->Slice(i, i + 1); auto in_grad_sliced = in_grad->Slice(i, i + 1); - bit_code.MulGradWeight(num_classes, ids, pre_out, p_sliced, in_sliced); - bit_code.MulGradError(num_classes, ids, pre_out, p_sliced, - in_grad_sliced); + bit_code.MulGradWeight(num_classes, ids->data(), pre_out, + p_sliced, in_sliced); + bit_code.MulGradError(num_classes, ids->data(), pre_out, + p_sliced, in_grad_sliced); } } }; diff --git a/paddle/operators/math/matrix_bit_code.cc b/paddle/operators/math/matrix_bit_code.cc index 4ad0a000083..b192183b101 100644 --- a/paddle/operators/math/matrix_bit_code.cc +++ b/paddle/operators/math/matrix_bit_code.cc @@ -56,7 +56,6 @@ static void AddByBitCodeT(Op op, CodeTable code_table, const int64_t* codes, const framework::Tensor& vec) { size_t num_sample = tmat.dims()[0]; size_t width = vec.dims()[1]; - for (size_t i = 0; i < num_sample; ++i) { auto code = code_table(static_cast(codes[i])); int code_length = code.get_length(); diff --git a/paddle/pybind/pybind.cc b/paddle/pybind/pybind.cc index 921b316a695..de6b24f70d8 100644 --- a/paddle/pybind/pybind.cc +++ b/paddle/pybind/pybind.cc @@ -109,8 +109,6 @@ PYBIND11_PLUGIN(core) { .def("shape", [](Tensor &self) { return vectorize(self.dims()); }) .def("set_float_element", TensorSetElement) .def("get_float_element", TensorGetElement) - .def("set_int64_element", TensorSetElement) - .def("get_int64_element", TensorGetElement) .def("set_double_element", TensorSetElement) .def("get_double_element", TensorGetElement) .def("dtype", [](Tensor &self) { return ToDataType(self.type()); }); diff --git a/python/paddle/v2/fluid/executor.py b/python/paddle/v2/fluid/executor.py index cdd576294f4..a054d5eafb2 100644 --- a/python/paddle/v2/fluid/executor.py +++ b/python/paddle/v2/fluid/executor.py @@ -148,7 +148,6 @@ class Executor(object): inputs={'X': [var]}, outputs={'Out': [fetch_var]}, attrs={'col': i}) - self.executor.run(program.desc, scope, 0, True, True) outs = [ core.get_fetch_variable(scope, fetch_var_name, i) diff --git a/python/paddle/v2/fluid/tests/op_test.py b/python/paddle/v2/fluid/tests/op_test.py index 287dc298048..0493a0c2061 100644 --- a/python/paddle/v2/fluid/tests/op_test.py +++ b/python/paddle/v2/fluid/tests/op_test.py @@ -123,8 +123,6 @@ def get_numeric_gradient(scope, def __set_elem__(tensor, i, e): if tensor_to_check_dtype == np.float32: tensor.set_float_element(i, e) - elif tensor_to_check_dtype == np.int64: - tensor.set_int64_element(i, e) else: tensor.set_double_element(i, e) diff --git a/python/paddle/v2/fluid/tests/test_hsigmoid_op.py b/python/paddle/v2/fluid/tests/test_hsigmoid_op.py index 194d5e315fc..b6d961b6318 100644 --- a/python/paddle/v2/fluid/tests/test_hsigmoid_op.py +++ b/python/paddle/v2/fluid/tests/test_hsigmoid_op.py @@ -10,16 +10,11 @@ class TestHSigmoidOp(OpTest): embded_size = 10 batch_size = 5 x = np.random.random((batch_size, embded_size)).astype("float32") - parameter = np.random.random( + w = np.random.random( (batch_size, num_classes - 1, embded_size)).astype("float32") - label = np.random.randint(0, num_classes, batch_size) + ids = np.random.randint(0, num_classes, batch_size) bias = np.random.random((1, num_classes - 1)).astype("float32") - self.inputs = { - 'X': x, - 'Parameters': parameter, - 'Label': label, - 'Bias': bias - } + self.inputs = {'X': x, 'W': w, 'Ids': ids, 'Bias': bias} self.attrs = {'num_classes': num_classes} self.outputs = { 'Out': np.random.random((batch_size, 1)).astype("float32") @@ -29,10 +24,7 @@ class TestHSigmoidOp(OpTest): self.check_output() def test_check_grad(self): - self.check_grad( - ['X', 'Parameters', 'Label', 'Bias'], - 'Out', - no_grad_set=set(['Label'])) + self.check_grad(['X', 'W', 'Bias'], 'Out', no_grad_set=set('Ids')) if __name__ == '__main__': -- GitLab From 80ce7edbb79244f6946cf38e233d3914ef40ddf5 Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Tue, 9 Jan 2018 20:26:37 +0800 Subject: [PATCH 0008/1416] make farward correct --- paddle/operators/hierarchical_sigmoid_op.cc | 4 +- paddle/operators/hierarchical_sigmoid_op.h | 35 ++-- paddle/operators/math/math_function_impl.h | 8 +- paddle/operators/math/matrix_bit_code.cc | 156 ++++++++---------- paddle/operators/math/matrix_bit_code.h | 25 ++- python/paddle/v2/fluid/tests/op_test.py | 9 +- .../paddle/v2/fluid/tests/test_hsigmoid_op.py | 70 +++++++- 7 files changed, 170 insertions(+), 137 deletions(-) diff --git a/paddle/operators/hierarchical_sigmoid_op.cc b/paddle/operators/hierarchical_sigmoid_op.cc index bc6ceb98747..e2ba65d6f9c 100644 --- a/paddle/operators/hierarchical_sigmoid_op.cc +++ b/paddle/operators/hierarchical_sigmoid_op.cc @@ -70,7 +70,7 @@ class HierarchicalSigmoidOp : public framework::OperatorWithKernel { } protected: - framework::OpKernelType GetKernelType( + framework::OpKernelType GetActualKernelType( const framework::ExecutionContext& ctx) const override { return framework::OpKernelType( framework::ToDataType(ctx.Input("X")->type()), @@ -96,7 +96,7 @@ class HierarchicalSigmoidGradOp : public framework::OperatorWithKernel { } protected: - framework::OpKernelType GetKernelType( + framework::OpKernelType GetActualKernelType( const framework::ExecutionContext& ctx) const override { return framework::OpKernelType( framework::ToDataType(ctx.Input("X")->type()), diff --git a/paddle/operators/hierarchical_sigmoid_op.h b/paddle/operators/hierarchical_sigmoid_op.h index 1b8d21c095e..f5b1b97169c 100644 --- a/paddle/operators/hierarchical_sigmoid_op.h +++ b/paddle/operators/hierarchical_sigmoid_op.h @@ -49,34 +49,31 @@ class HierarchicalSigmoidOpKernel : public framework::OpKernel { auto& place = *ctx.template device_context().eigen_device(); auto& device_ctx = ctx.template device_context(); math::RowwiseSum row_sum; - math::MatrixBitCodeFunctor bit_code; + math::MatrixBitCodeFunctor bit_code(num_classes, ids->data()); std::vector sum_dims({batch_size, 1UL}); sum.mutable_data(framework::make_ddim(sum_dims), ctx.GetPlace()); auto sum_mat = EigenMatrix::From(sum); out->mutable_data(ctx.GetPlace()); auto out_mat = framework::EigenVector::Flatten(*out); - if (bias) { - bit_code.Add(num_classes, ids->data(), pre_out, *bias); + bit_code.Add(pre_out, *bias); } - for (int i = 0; i < in->dims()[0]; ++i) { - bit_code.Mul(num_classes, ids->data(), pre_out, - w->Slice(i, i + 1), in->Slice(i, i + 1)); + for (int64_t i = 0; i < batch_size; ++i) { + auto w_i = w->Slice(i, i + 1); + bit_code.Mul(pre_out, w_i, *in); } // clip the matrix with (-40, 40) Transform trans; trans(ctx.template device_context(), pre_out_data, pre_out_data + pre_out.numel(), pre_out_data, ClipFunctor(static_cast(-40.0), static_cast(40.0))); - bit_code.Sum(num_classes, ids->data(), pre_out, *out, - static_cast(-1)); + bit_code.Sum(pre_out, *out, static_cast(-1)); // softrelu with threshold is 40.0 trans(ctx.template device_context(), pre_out_data, pre_out_data + pre_out.numel(), pre_out_data, ClipFunctor(static_cast(-40.0), static_cast(40.0))); pre_out_mat.device(place) = (static_cast(1.0) + pre_out_mat.exp()).log(); - row_sum(device_ctx, pre_out, &sum); out_mat.device(place) = sum_mat + out_mat; } @@ -103,28 +100,26 @@ class HierarchicalSigmoidGradOpKernel : public framework::OpKernel { auto pre_out_mat = EigenMatrix::From(pre_out); // init pre_out matrix with {1.0} math::SetConstant one; - math::MatrixBitCodeFunctor bit_code; + math::MatrixBitCodeFunctor bit_code(num_classes, ids->data()); one(device_ctx, &pre_out, static_cast(1.0)); // softrelu derivative pre_out_mat.device(place) = pre_out_mat * (static_cast(1.0) - static_cast(1.0) / pre_out_mat); - bit_code.Sub(num_classes, ids->data(), pre_out); + bit_code.Sub(pre_out); if (bias) { bias->mutable_data(ctx.GetPlace()); - bit_code.AddGrad(num_classes, ids->data(), pre_out, *bias); + bit_code.AddGrad(pre_out, *bias); } in_grad->mutable_data(ctx.GetPlace()); w->mutable_data(ctx.GetPlace()); - for (int i = 0; i < in_grad->dims()[0]; ++i) { - auto p_sliced = w->Slice(i, i + 1); - auto in_sliced = in->Slice(i, i + 1); - auto in_grad_sliced = in_grad->Slice(i, i + 1); - bit_code.MulGradWeight(num_classes, ids->data(), pre_out, - p_sliced, in_sliced); - bit_code.MulGradError(num_classes, ids->data(), pre_out, - p_sliced, in_grad_sliced); + for (int i = 0; i < batch_size; ++i) { + auto w_i = w->Slice(i, i + 1); + // auto in_i = in->Slice(i, i + 1); + // auto in_grad_i = in_grad->Slice(i, i + 1); + bit_code.MulGradWeight(pre_out, w_i, *in); + bit_code.MulGradError(pre_out, w_i, *in_grad); } } }; diff --git a/paddle/operators/math/math_function_impl.h b/paddle/operators/math/math_function_impl.h index 98722ff5d29..63fb7182dfd 100644 --- a/paddle/operators/math/math_function_impl.h +++ b/paddle/operators/math/math_function_impl.h @@ -62,13 +62,13 @@ void ColwiseSum::operator()(const DeviceContext& context, template void RowwiseSum::operator()(const DeviceContext& context, const framework::Tensor& input, - framework::Tensor* vector) { + framework::Tensor* out) { auto in_dims = input.dims(); auto size = input.numel() / in_dims[1]; - PADDLE_ENFORCE_EQ(vector->numel(), size); + PADDLE_ENFORCE_EQ(out->numel(), size); - auto in = framework::EigenMatrix::From(input); - auto vec = framework::EigenMatrix::From(*vector); + auto in = framework::EigenMatrix::From(input); + auto vec = framework::EigenVector::Flatten(*out); vec.device(*context.eigen_device()) = in.sum(Eigen::array({{1}})); } diff --git a/paddle/operators/math/matrix_bit_code.cc b/paddle/operators/math/matrix_bit_code.cc index b192183b101..34f5f6ef61b 100644 --- a/paddle/operators/math/matrix_bit_code.cc +++ b/paddle/operators/math/matrix_bit_code.cc @@ -22,7 +22,7 @@ namespace math { * CodeTable class should support 3 functions: * * size_t size() - * return the number of codes + * return the number of ids * * int getMaxCodeLength() * return the maximal code length @@ -45,56 +45,47 @@ namespace math { * */ -/* - for i: - for j < codeLength: - op(a(i, j), b(0, index(i, j))) -*/ -template -static void AddByBitCodeT(Op op, CodeTable code_table, const int64_t* codes, - const framework::Tensor& tmat, - const framework::Tensor& vec) { - size_t num_sample = tmat.dims()[0]; - size_t width = vec.dims()[1]; - for (size_t i = 0; i < num_sample; ++i) { - auto code = code_table(static_cast(codes[i])); +template +void MatrixBitCodeFunctor::Add(framework::Tensor& tmat, + const framework::Tensor& vec) { + SimpleCodeTable code_table(num_classes_); + size_t batch_size = tmat.dims()[0]; + size_t width = tmat.dims()[1]; + for (size_t i = 0; i < batch_size; ++i) { + auto code = code_table(static_cast(ids_[i])); int code_length = code.get_length(); for (int j = 0; j < code_length; ++j) { size_t index = code.calc_index(j); - auto t = tmat.data()[i * width + j]; - auto v = vec.data()[index]; - op(t, v); + tmat.data()[i * width + j] += vec.data()[index]; } } } -template -void SubByBitCodeT(CodeTable code_table, const int64_t* codes, - framework::Tensor& tmat) { - // size_t max_code_length = code_table.get_max_code_length(); - size_t num_samples = tmat.dims()[0]; - size_t o_width = tmat.dims()[1]; - for (size_t i = 0; i < num_samples; ++i) { - auto code = code_table(static_cast(codes[i])); +template +void MatrixBitCodeFunctor::AddGrad(framework::Tensor& tmat, + framework::Tensor& vec) { + SimpleCodeTable code_table(num_classes_); + size_t batch_size = tmat.dims()[0]; + size_t width = tmat.dims()[1]; + for (size_t i = 0; i < batch_size; ++i) { + auto code = code_table(static_cast(ids_[i])); int code_length = code.get_length(); for (int j = 0; j < code_length; ++j) { - if (code.calc_bit(j)) { - tmat.data()[i * o_width + j] -= 1; - } + size_t index = code.calc_index(j); + vec.data()[index] += tmat.data()[i * width + j]; } } } -template -void SumByBitCodeT(CodeTable code_table, const int64_t* codes, - framework::Tensor& tmat, framework::Tensor& sum, - const T& scale_sum) { - // size_t max_code_length = code_table.get_max_code_length(); +template +void MatrixBitCodeFunctor::Sum(framework::Tensor& tmat, + framework::Tensor& sum, T scale_sum) { + SimpleCodeTable code_table(num_classes_); size_t num_samples = tmat.dims()[0]; size_t o_width = tmat.dims()[1]; for (size_t i = 0; i < num_samples; ++i) { T sm = static_cast(0.0); - auto code = code_table(static_cast(codes[i])); + auto code = code_table(static_cast(ids_[i])); int code_length = code.get_length(); for (int j = 0; j < code_length; ++j) { if (code.calc_bit(j)) { @@ -106,116 +97,99 @@ void SumByBitCodeT(CodeTable code_table, const int64_t* codes, } template -void MatrixBitCodeFunctor::Add(size_t num_classes, const int64_t* codes, - framework::Tensor& tmat, - const framework::Tensor& vec) { - auto op = [](T& t, const T& v) { t += v; }; - AddByBitCodeT(op, SimpleCodeTable(num_classes), codes, tmat, vec); -} - -template -void MatrixBitCodeFunctor::AddGrad(size_t num_classes, const int64_t* codes, - framework::Tensor& tmat, - framework::Tensor& vec) { - auto op = [](T& t, T& v) { v += t; }; - AddByBitCodeT(op, SimpleCodeTable(num_classes), codes, tmat, vec); -} - -template -void MatrixBitCodeFunctor::Sum(size_t num_classes, const int64_t* codes, - framework::Tensor& tmat, - framework::Tensor& sum, T scale_sum) { - SumByBitCodeT(SimpleCodeTable(num_classes), codes, tmat, sum, scale_sum); -} - -template -void MatrixBitCodeFunctor::Mul(size_t num_classes, const int64_t* codes, - framework::Tensor& tmat, +void MatrixBitCodeFunctor::Mul(framework::Tensor& tmat, const framework::Tensor& weight, const framework::Tensor& input) { + SimpleCodeTable code_table(num_classes_); size_t num_samples = tmat.dims()[0]; size_t tmat_width = tmat.dims()[1]; size_t input_width = input.dims()[1]; - size_t weight_width = weight.dims()[1]; - auto tmat_p = tmat.data(); - auto weight_p = weight.data(); - auto input_p = input.data(); - auto code_table = SimpleCodeTable(num_classes); + size_t weight_width = weight.dims()[2]; + auto tmat_value = tmat.data(); + auto weight_value = weight.data(); + auto input_value = input.data(); for (size_t i = 0; i < num_samples; ++i) { - auto code = code_table(static_cast(codes[i])); + auto code = code_table(static_cast(ids_[i])); int code_length = code.get_length(); for (int j = 0; j < code_length; ++j) { size_t index = code.calc_index(j); T sum = static_cast(0.0); for (size_t k = 0; k < input_width; ++k) { - sum += - weight_p[weight_width * index + k] * input_p[input_width * i + k]; + sum += weight_value[weight_width * index + k] * + input_value[input_width * i + k]; } - tmat_p[i * tmat_width + j] += sum; + tmat_value[i * tmat_width + j] += sum; } } } template -void MatrixBitCodeFunctor::MulGradWeight(size_t num_classes, - const int64_t* codes, - const framework::Tensor& tmat, +void MatrixBitCodeFunctor::MulGradWeight(const framework::Tensor& tmat, framework::Tensor& weight, const framework::Tensor& input) { + SimpleCodeTable code_table(num_classes_); size_t num_samples = tmat.dims()[0]; size_t input_width = input.dims()[1]; size_t weight_width = weight.dims()[1]; - auto tmat_p = tmat.data(); - auto weight_p = weight.data(); - auto input_p = input.data(); - auto code_table = SimpleCodeTable(num_classes); + auto tmat_value = tmat.data(); + auto weight_value = weight.data(); + auto input_value = input.data(); for (size_t i = 0; i < num_samples; ++i) { - auto code = code_table(static_cast(codes[i])); + auto code = code_table(static_cast(ids_[i])); int code_length = code.get_length(); for (int j = 0; j < code_length; ++j) { size_t index = code.calc_index(j); for (size_t k = 0; k < input_width; ++k) { - weight_p[weight_width * index * k] += - tmat_p[i * weight_width * j] * input_p[input_width * i + k]; + weight_value[weight_width * index * k] += + tmat_value[i * weight_width * j] * input_value[input_width * i + k]; } } } } template -void MatrixBitCodeFunctor::MulGradError(size_t num_classes, - const int64_t* codes, - const framework::Tensor& tmat, +void MatrixBitCodeFunctor::MulGradError(const framework::Tensor& tmat, const framework::Tensor& weight, framework::Tensor& input) { + SimpleCodeTable code_table(num_classes_); size_t num_samples = tmat.dims()[0]; size_t input_width = input.dims()[1]; size_t weight_width = weight.dims()[1]; - auto tmat_p = tmat.data(); - auto weight_p = weight.data(); - auto input_p = input.data(); - auto code_table = SimpleCodeTable(num_classes); + auto tmat_value = tmat.data(); + auto weight_value = weight.data(); + auto input_value = input.data(); for (size_t i = 0; i < num_samples; ++i) { - auto code = code_table(static_cast(codes[i])); + auto code = code_table(static_cast(ids_[i])); int code_length = code.get_length(); for (int j = 0; j < code_length; ++j) { size_t index = code.calc_index(j); for (size_t k = 0; k < input_width; ++k) { - input_p[weight_width * index * k] += - tmat_p[i * weight_width * j] * weight_p[weight_width * i + k]; + input_value[weight_width * index * k] += + tmat_value[i * weight_width * j] * + weight_value[weight_width * i + k]; } } } } template -void MatrixBitCodeFunctor::Sub(size_t num_classes, const int64_t* codes, - framework::Tensor& tmat) { - SubByBitCodeT(SimpleCodeTable(num_classes), codes, tmat); +void MatrixBitCodeFunctor::Sub(framework::Tensor& tmat) { + SimpleCodeTable code_table(num_classes_); + size_t num_samples = tmat.dims()[0]; + size_t o_width = tmat.dims()[1]; + for (size_t i = 0; i < num_samples; ++i) { + auto code = code_table(static_cast(ids_[i])); + int code_length = code.get_length(); + for (int j = 0; j < code_length; ++j) { + if (code.calc_bit(j)) { + tmat.data()[i * o_width + j] -= 1; + } + } + } } template class MatrixBitCodeFunctor; diff --git a/paddle/operators/math/matrix_bit_code.h b/paddle/operators/math/matrix_bit_code.h index d2ebf182c86..43c676f5cc5 100644 --- a/paddle/operators/math/matrix_bit_code.h +++ b/paddle/operators/math/matrix_bit_code.h @@ -63,46 +63,45 @@ struct SimpleCodeTable { template class MatrixBitCodeFunctor { public: + explicit MatrixBitCodeFunctor(size_t num_classes, const int64_t* ids) + : num_classes_(num_classes), ids_(ids) {} /* For j < code_length tmat(i, j) += vec(0, index(i, j)) */ - void Add(size_t num_classes, const int64_t* codes, framework::Tensor& tmat, - const framework::Tensor& vec); + void Add(framework::Tensor& tmat, const framework::Tensor& vec); /* For j < code_length vec(0, index(i, j)) += tmat(i, j) */ - void AddGrad(size_t num_classes, const int64_t* codes, - framework::Tensor& tmat, framework::Tensor& vec); + void AddGrad(framework::Tensor& tmat, framework::Tensor& vec); /* For j < code_length sum(i, 0) = \sum_j bit(i, j) * tmat(i, j) */ - void Sum(size_t num_classes, const int64_t* codes, framework::Tensor& tmat, - framework::Tensor& sum, T scale_sum); + void Sum(framework::Tensor& tmat, framework::Tensor& sum, T scale_sum); /* For j < code_length tmat(i, j) -= bit(i, j) */ - void Sub(size_t num_classes, const int64_t* codes, framework::Tensor& tmat); + void Sub(framework::Tensor& tmat); /* For j < code_length input.row(i) += tmat(i, j) * weight.row(index(i, j)) */ - void Mul(size_t num_classes, const int64_t* codes, framework::Tensor& tmat, - const framework::Tensor& weight, const framework::Tensor& input); + void Mul(framework::Tensor& tmat, const framework::Tensor& weight, + const framework::Tensor& input); /* For index(i, j) >= 0: weight.row(index(i, j)) += tmat(i, j) * input.row(i) */ - void MulGradWeight(size_t num_classes, const int64_t* codes, - const framework::Tensor& tmat, framework::Tensor& weight, + void MulGradWeight(const framework::Tensor& tmat, framework::Tensor& weight, const framework::Tensor& input); /* For j < code_length input.row(i) += tmat(i, j) * weight.row(index(i, j)) */ - void MulGradError(size_t num_classes, const int64_t* codes, - const framework::Tensor& tmat, + void MulGradError(const framework::Tensor& tmat, const framework::Tensor& weight, framework::Tensor& input); + size_t num_classes_; + const int64_t* ids_; }; } // namespace math } // namespace operators diff --git a/python/paddle/v2/fluid/tests/op_test.py b/python/paddle/v2/fluid/tests/op_test.py index acc42fd3b3d..b77d2b1268f 100644 --- a/python/paddle/v2/fluid/tests/op_test.py +++ b/python/paddle/v2/fluid/tests/op_test.py @@ -49,6 +49,7 @@ def create_op(scope, op_type, inputs, outputs, attrs): for attr_name in Operator.get_op_attr_names(op_type): if attr_name in attrs: kwargs[attr_name] = attrs[attr_name] + return Operator(op_type, **kwargs) @@ -104,8 +105,6 @@ def get_numeric_gradient(scope, tensor_to_check_dtype = np.float32 elif tensor_to_check_dtype == core.DataType.FP64: tensor_to_check_dtype = np.float64 - elif tensor_to_check_dtype == core.DataType.INT64: - tensor_to_check_dtype = np.int64 else: raise ValueError("Not supported data type " + str( tensor_to_check_dtype)) @@ -115,8 +114,6 @@ def get_numeric_gradient(scope, def __get_elem__(tensor, i): if tensor_to_check_dtype == np.float32: return tensor.get_float_element(i) - elif tensor_to_check_dtype == np.int64: - return tensor.get_int64_element(i) else: return tensor.get_double_element(i) @@ -356,11 +353,13 @@ class OpTest(unittest.TestCase): op_attrs = self.attrs if hasattr(self, "attrs") else dict() self.op = create_op(self.scope, self.op_type, op_inputs, op_outputs, op_attrs) + if no_grad_set is None: no_grad_set = set() if not type(output_names) is list: output_names = [output_names] + numeric_grads = user_defined_grads or [ get_numeric_gradient( self.scope, @@ -456,7 +455,9 @@ class OpTest(unittest.TestCase): # infer variable type and infer shape in compile-time op.desc.infer_var_type(block.desc) op.desc.infer_shape(block.desc) + mean_inputs = map(block.var, output_names) + if len(mean_inputs) == 1: loss = block.create_var(dtype=mean_inputs[0].dtype, shape=[1]) op = block.append_op( diff --git a/python/paddle/v2/fluid/tests/test_hsigmoid_op.py b/python/paddle/v2/fluid/tests/test_hsigmoid_op.py index b6d961b6318..41e95e43639 100644 --- a/python/paddle/v2/fluid/tests/test_hsigmoid_op.py +++ b/python/paddle/v2/fluid/tests/test_hsigmoid_op.py @@ -1,6 +1,71 @@ import unittest import numpy as np from op_test import OpTest +import math + + +def find_latest_set(num): + return 1 + int(math.floor(math.log(num, 2))) + + +class CodeTable(object): + def __init__(self, num_classes, code): + self.c = num_classes + code + + def cal_index(self, bit): + return (self.c >> (bit + 1)) - 1 + + def get_length(self): + return find_latest_set(self.c) - 1 + + def cal_bit(self, bit): + return self.c & (1 << bit) + + +def hsigmoid(x, w, ids, bias, num_classes): + # code length = + # initialize pre out with dims={batch_size, code_length} + batch_size = x.shape[0] + code_length = find_latest_set(num_classes - 1) + code_table = [0 for _ in range(code_length)] + pre_output = np.zeros((batch_size, code_length)) + pre_sum = np.zeros((batch_size, 1)) + out = np.zeros((batch_size, 1)).astype("float32") + # pre_out += code(bias) + for i in xrange(batch_size): + code_table = CodeTable(num_classes, ids[i]) + length = code_table.get_length() + for j in xrange(length): + idx = code_table.cal_index(j) + pre_output[i][j] += bias[0][idx] + # pre_out += code(w) * x + for i in xrange(batch_size): + for j in xrange(batch_size): + code_table = CodeTable(num_classes, ids[j]) + length = code_table.get_length() + for k in xrange(length): + idx = code_table.cal_index(k) + sum = 0.0 + for l in xrange(x.shape[1]): + sum += w[i][idx][l] * x[j][l] + pre_output[j][k] += sum + # clip[-40.0, 40.0] + np.clip(pre_output, -40.0, 40.0) + # out(i, 0) = \sum_j bit(i, j) * preout(i, j) + for i in xrange(batch_size): + code_table = CodeTable(num_classes, ids[i]) + length = code_table.get_length() + sum = 0.0 + for j in xrange(length): + if code_table.cal_bit(j): + sum += pre_output[i][j] + out[i] = -1.0 * sum + # soft relu + np.clip(pre_output, -40.0, 40.0) + pre_output = np.log(1 + np.exp(pre_output)) + pre_sum = pre_output.sum(1).reshape((batch_size, 1)) + out += pre_sum + return out class TestHSigmoidOp(OpTest): @@ -16,9 +81,8 @@ class TestHSigmoidOp(OpTest): bias = np.random.random((1, num_classes - 1)).astype("float32") self.inputs = {'X': x, 'W': w, 'Ids': ids, 'Bias': bias} self.attrs = {'num_classes': num_classes} - self.outputs = { - 'Out': np.random.random((batch_size, 1)).astype("float32") - } + out = hsigmoid(x, w, ids, bias, num_classes) + self.outputs = {'Out': out} def test_check_output(self): self.check_output() -- GitLab From cb7891a45868c450cbdd4c85d7325c1702107f9a Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Wed, 14 Mar 2018 17:27:24 +0800 Subject: [PATCH 0009/1416] Add large model design doc --- doc/fluid/design/dist_train/large_model.md | 40 ++++++++++++++++++ .../src/prefetch_parameters.graffle | Bin 0 -> 10073 bytes .../dist_train/src/prefetch_parameters.png | Bin 0 -> 180176 bytes .../dist_train/src/split_parameter.graffle | Bin 0 -> 7812 bytes .../design/dist_train/src/split_parameter.png | Bin 0 -> 69134 bytes 5 files changed, 40 insertions(+) create mode 100644 doc/fluid/design/dist_train/large_model.md create mode 100644 doc/fluid/design/dist_train/src/prefetch_parameters.graffle create mode 100644 doc/fluid/design/dist_train/src/prefetch_parameters.png create mode 100644 doc/fluid/design/dist_train/src/split_parameter.graffle create mode 100644 doc/fluid/design/dist_train/src/split_parameter.png diff --git a/doc/fluid/design/dist_train/large_model.md b/doc/fluid/design/dist_train/large_model.md new file mode 100644 index 00000000000..f82fa6f81e5 --- /dev/null +++ b/doc/fluid/design/dist_train/large_model.md @@ -0,0 +1,40 @@ +# Design Doc: Large Model + +## Abstract + +We propose an approach to support the large parameter. +For embedding layer, the parameter may very large and could +not be stored in one trainer's memory. In this approach, a Trainer would +prefetch a sliced parameter from different Parameter Server instances +according to the input `Ids`, and then run forward, backward and send +the gradient to Parameter Server to execute the optimize program. + +## Design + +Fluid large model distributed training use +[Distributed Transpiler](./parameter_server.md#distributed-transpiler) to split +a large parameter into multiple parameters which stored on Parameter Server, and +the Trainer would prefetch them by `RPC` interface. + +### Split Large Parameter + + + +**Distributed Transpiler** would split the large parameter +(weight) into some sliced parameters (weight_0, weight_1, weight_2) as the +figure above. + +### Prefetch Parameters from Parameter Servers + + + +- `PrefetchRpc` operator would send the rows index the multiple Parameter Servers, + and then receive the SelctedRows. +- The different with normal Fluid distributed training, we only prefetch the rows + +## TODO + +- Async Update + + To 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zo2Ico^LzbUeMes$-VPq+e)(|uq%at$=Jp&g?=HT(IWIAGx_c9zZ~&UydeXQ3uTE7T z`2`5^hMT<04J9DVMKyk{9S3gnd1H}2N*{;+NHdzb%nQ`TU-;9wE=XlaGbF2l@dd4r1G3Ys>B?|J^ucYoYi Y@u9GY^6=g-i}2r`T^cH>J50R(7s7Yq&;S4c -- GitLab From b382747396e11bae1b38f7624550e98e7d58d39a Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Wed, 14 Mar 2018 17:42:46 +0800 Subject: [PATCH 0011/1416] add note message --- doc/fluid/design/dist_train/large_model.md | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/doc/fluid/design/dist_train/large_model.md b/doc/fluid/design/dist_train/large_model.md index f82fa6f81e5..96895821307 100644 --- a/doc/fluid/design/dist_train/large_model.md +++ b/doc/fluid/design/dist_train/large_model.md @@ -11,6 +11,10 @@ the gradient to Parameter Server to execute the optimize program. ## Design +**NOTE**: this approach is a feature of Fluid distributed trianing, maybe you want +to know [Distributed Architecture](./distributed_architecture.md) and +[Parameter Server](./parameter_server.md) before reading the following content. + Fluid large model distributed training use [Distributed Transpiler](./parameter_server.md#distributed-transpiler) to split a large parameter into multiple parameters which stored on Parameter Server, and -- GitLab From f839e91b04105565789fc5fb28b5934c2c79de89 Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Wed, 14 Mar 2018 23:54:38 +0800 Subject: [PATCH 0012/1416] update by comment --- doc/fluid/design/dist_train/large_model.md | 52 ++++++++++-------- .../src/prefetch_parameters.graffle | Bin 10058 -> 7340 bytes .../dist_train/src/split_parameter.graffle | Bin 7812 -> 7054 bytes .../design/dist_train/src/split_parameter.png | Bin 69134 -> 78741 bytes 4 files changed, 28 insertions(+), 24 deletions(-) diff --git a/doc/fluid/design/dist_train/large_model.md b/doc/fluid/design/dist_train/large_model.md index 96895821307..92daa2b52ea 100644 --- a/doc/fluid/design/dist_train/large_model.md +++ b/doc/fluid/design/dist_train/large_model.md @@ -1,44 +1,48 @@ -# Design Doc: Large Model +# Design Doc: Prefecting Parameter From Parameter Server ## Abstract -We propose an approach to support the large parameter. -For embedding layer, the parameter may very large and could -not be stored in one trainer's memory. In this approach, a Trainer would -prefetch a sliced parameter from different Parameter Server instances -according to the input `Ids`, and then run forward, backward and send -the gradient to Parameter Server to execute the optimize program. +We propose an approach to prefetch parameter from Parameter +Server while distributed training so that Fluid would training +a model including the large parameter which could not be stored in one +trainer's memory. + +## Background + +For an embedding layer, the trainable parameter may be very large and could +not be stored in one trainer's memory. In Fluid distributed training, +[Distributed Transpiler](./parameter_server.md#distributed-transpiler) would split every parameter into a number of small +parameters and stored in Parameter Server, so we could prefetch the parameter +from the specified Parameter Server according to the input `Ids`. ## Design -**NOTE**: this approach is a feature of Fluid distributed trianing, maybe you want +This is a feature of Fluid distributed training, maybe you want to know [Distributed Architecture](./distributed_architecture.md) and [Parameter Server](./parameter_server.md) before reading the following content. -Fluid large model distributed training use -[Distributed Transpiler](./parameter_server.md#distributed-transpiler) to split -a large parameter into multiple parameters which stored on Parameter Server, and -the Trainer would prefetch them by `RPC` interface. - -### Split Large Parameter +### Partationed Parameter -**Distributed Transpiler** would split the large parameter -(weight) into some sliced parameters (weight_0, weight_1, weight_2) as the +- **Distributed Transpiler** would split the large parameter +(weight) into some partitioned parameters (weight_0, weight_1, weight_2) as the figure above. +- We could use `round-robin` to distribute the partitioned parameter. -### Prefetch Parameters from Parameter Servers +### Prefetching Parameter -- `PrefetchRpc` operator would send the rows index the multiple Parameter Servers, - and then receive the SelctedRows. -- The different with normal Fluid distributed training, we only prefetch the rows +- `prefetch_rpc` operator would prefetch the parameter from different Parameter + Server according with the input `Ids`, we use [SelectedRows](../../../design/selected_rows.md) + as the received variable type. +- `merge_selected_rows` operator would merge the received parameters into one + `SelectedRows` variable. ## TODO -- Async Update - - To avoid slow-node, Async update is important for distributed training, - we need an design doc and implement it in future. +- `prefetch_rpc` operator to send rows index and receive SelectedRows variables. +- `lookup_table` need to support `SelectedRows` variable type as input `Weight`. +- Async Update, To avoid slow-node, Async update is important for distributed training, + we need a design doc and implement it in future. diff --git a/doc/fluid/design/dist_train/src/prefetch_parameters.graffle b/doc/fluid/design/dist_train/src/prefetch_parameters.graffle index c1a59b901745d81add42328b9995408d32d8127b..abbb7089829709cb5fdc337b7f9521a34f7d131a 100644 GIT binary patch literal 7340 zcmV;d98=>TiwFP!000030PTHgm!e3w?&q#wk+;9xdu~>zfZ*_+>OLo!6bBR;99FLN zE+zp*P(V?8^?$#?V5S3_R&~{TyWgW#D@A#B#Eyu)ckGBD^ZD{$+lBkIF@w$FqL@S(eyeYCr$iZ=b&WFSdRz@qn>{LrBnjTrE8W- zv_wDkJDeyz!7@rEhX48LXFH0P|0tE>IDSzR)Qj#f5@1;B2maCwqFo0T_6rnvF(Tt< zSWQ;?i8}CG!_lMPKK=A%Zti|ds&jNTg7=jS_NA134{xhMpe7eTeF>ug>i-+8?!{kt zjurUp4 z`$PV^$fM9wG=;uJGYG4gm3WuL87cUgDs$uQBzPF0d8s69#K((jx&lR04K 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zK08@->s#za3+coCjq1JLJWAkku6+?5)lMQm;;HqzxZwN%riVu97391GsE>LVLB7;gKh!@UrB1Ql}sEV&^~&!%3rPvt>x zJ6%F&PLU;kxZ3v+6zF-WYovl7Ec$;0%vUyOYC)$IqjKknfIPK{p&tpKDtLZx!)qj_ zibNLv#Jw#_M97a_?0#7uk|Q4cfBhwLo!%c} z2sz0(b7W=y`WabC@UXil+YJ!=_}_2&{e?+vaN$4QWHN!$ZH(;iA0R*-VfULf3V;4C z_HTE90ftk;LFHV!q4T#pz({yV;KE~Pkv1g3^Vb1jogpMluTLoXxADrsg%hbMR%ieI z0YZ{g1z2C!6&%CgACLe|CQndb!N#g~@t=>##tPOx?=YA1&+*=*h6_jLE#r{$_iqz6 zPYpGNr Date: Wed, 14 Mar 2018 23:57:31 +0800 Subject: [PATCH 0013/1416] update by comment --- .../design/dist_train/{large_model.md => prefetch_parameter.md} | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) rename doc/fluid/design/dist_train/{large_model.md => prefetch_parameter.md} (97%) diff --git a/doc/fluid/design/dist_train/large_model.md b/doc/fluid/design/dist_train/prefetch_parameter.md similarity index 97% rename from doc/fluid/design/dist_train/large_model.md rename to doc/fluid/design/dist_train/prefetch_parameter.md index 92daa2b52ea..ac56502c280 100644 --- a/doc/fluid/design/dist_train/large_model.md +++ b/doc/fluid/design/dist_train/prefetch_parameter.md @@ -1,4 +1,4 @@ -# Design Doc: Prefecting Parameter From Parameter Server +# Design Doc: Prefetching Parameter From Parameter Server ## Abstract -- GitLab From 5948fd27170d91e2728e9366e9852f32dc17fd2f Mon Sep 17 00:00:00 2001 From: Abhinav Arora Date: Wed, 14 Mar 2018 11:21:56 -0700 Subject: [PATCH 0014/1416] Refine the prefetch parameter document --- .../design/dist_train/prefetch_parameter.md | 27 +++++++------------ 1 file changed, 10 insertions(+), 17 deletions(-) diff --git a/doc/fluid/design/dist_train/prefetch_parameter.md b/doc/fluid/design/dist_train/prefetch_parameter.md index ac56502c280..e8ea7fe67b9 100644 --- a/doc/fluid/design/dist_train/prefetch_parameter.md +++ b/doc/fluid/design/dist_train/prefetch_parameter.md @@ -2,40 +2,33 @@ ## Abstract -We propose an approach to prefetch parameter from Parameter -Server while distributed training so that Fluid would training -a model including the large parameter which could not be stored in one -trainer's memory. +We propose an approach to pre-fetch the parameters from a Parameter Server while distributed training so that Fluid is able to train a model with a large number of parameters that cannot be stored in one trainer's memory. ## Background -For an embedding layer, the trainable parameter may be very large and could -not be stored in one trainer's memory. In Fluid distributed training, -[Distributed Transpiler](./parameter_server.md#distributed-transpiler) would split every parameter into a number of small -parameters and stored in Parameter Server, so we could prefetch the parameter -from the specified Parameter Server according to the input `Ids`. +For an embedding layer, the number of trainable parameters may be very large and it is likely that they may not be able to be stored in one trainer's memory. In Fluid distributed training, +the [Distributed Transpiler](./parameter_server.md#distributed-transpiler) would split every parameter into a number of small parameters that are stored on the Parameter Server. Hence, we can pre-fetch the parameters from the specified Parameter Server using the input `Ids`. ## Design -This is a feature of Fluid distributed training, maybe you want -to know [Distributed Architecture](./distributed_architecture.md) and -[Parameter Server](./parameter_server.md) before reading the following content. +Prior to reading this design, it would be useful for the reader to make themselves familiar with Fluid [Distributed Training Architecture](./distributed_architecture.md) and +[Parameter Server](./parameter_server.md). ### Partationed Parameter -- **Distributed Transpiler** would split the large parameter -(weight) into some partitioned parameters (weight_0, weight_1, weight_2) as the +- **Distributed Transpiler** would split the large parameters +(`weight`) into some partitioned parameters (`weight_0`, `weight_1`, `weight_2`) as shown in the figure above. -- We could use `round-robin` to distribute the partitioned parameter. +- We can use `round-robin` to distribute the partitioned parameter. -### Prefetching Parameter +### Pre-fetching Parameters - `prefetch_rpc` operator would prefetch the parameter from different Parameter - Server according with the input `Ids`, we use [SelectedRows](../../../design/selected_rows.md) + Servers using the input `Ids`. We use [SelectedRows](../../../design/selected_rows.md) as the received variable type. - `merge_selected_rows` operator would merge the received parameters into one `SelectedRows` variable. -- GitLab From 1b4db80b10056be045702fd4a6078bbcc5a36db2 Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Thu, 15 Mar 2018 18:48:23 +0800 Subject: [PATCH 0015/1416] update by lookup remote table --- .../design/dist_train/prefetch_parameter.md | 37 +++++++++++------- .../dist_train/src/lookup_local_table.graffle | Bin 0 -> 11311 bytes .../dist_train/src/lookup_local_table.png | Bin 0 -> 303842 bytes .../src/lookup_remote_table.graffle | Bin 0 -> 10636 bytes .../dist_train/src/lookup_remote_table.png | Bin 0 -> 290825 bytes .../src/prefetch_parameters.graffle | Bin 7340 -> 0 bytes .../dist_train/src/prefetch_parameters.png | Bin 167376 -> 0 bytes 7 files changed, 23 insertions(+), 14 deletions(-) create mode 100644 doc/fluid/design/dist_train/src/lookup_local_table.graffle create mode 100644 doc/fluid/design/dist_train/src/lookup_local_table.png create mode 100644 doc/fluid/design/dist_train/src/lookup_remote_table.graffle create mode 100644 doc/fluid/design/dist_train/src/lookup_remote_table.png delete mode 100644 doc/fluid/design/dist_train/src/prefetch_parameters.graffle delete mode 100644 doc/fluid/design/dist_train/src/prefetch_parameters.png diff --git a/doc/fluid/design/dist_train/prefetch_parameter.md b/doc/fluid/design/dist_train/prefetch_parameter.md index e8ea7fe67b9..952d2bada92 100644 --- a/doc/fluid/design/dist_train/prefetch_parameter.md +++ b/doc/fluid/design/dist_train/prefetch_parameter.md @@ -1,36 +1,45 @@ -# Design Doc: Prefetching Parameter From Parameter Server +# Design Doc: Lookup Remote Table while Distributed training ## Abstract -We propose an approach to pre-fetch the parameters from a Parameter Server while distributed training so that Fluid is able to train a model with a large number of parameters that cannot be stored in one trainer's memory. +We propose an approach to pre-fetch the parameters from a Parameter Server while distributed training so that Fluid can train a model with the very large parameter that cannot be stored in one trainer's memory. ## Background -For an embedding layer, the number of trainable parameters may be very large and it is likely that they may not be able to be stored in one trainer's memory. In Fluid distributed training, -the [Distributed Transpiler](./parameter_server.md#distributed-transpiler) would split every parameter into a number of small parameters that are stored on the Parameter Server. Hence, we can pre-fetch the parameters from the specified Parameter Server using the input `Ids`. +For an embedding layer, the trainable parameter may be very large, and it is likely that it may not be able to be stored in one trainer's memory. In Fluid distributed training, +the [Distributed Transpiler](./parameter_server.md#distributed-transpiler) would split every parameter into some small parameters that stored on the Parameter Server. Hence, we can pre-fetch the parameter from the specified Parameter Server using the input `Ids`. ## Design Prior to reading this design, it would be useful for the reader to make themselves familiar with Fluid [Distributed Training Architecture](./distributed_architecture.md) and [Parameter Server](./parameter_server.md). -### Partationed Parameter +The execution of `lookup local table` is as follows: - + -- **Distributed Transpiler** would split the large parameters -(`weight`) into some partitioned parameters (`weight_0`, `weight_1`, `weight_2`) as shown in the -figure above. -- We can use `round-robin` to distribute the partitioned parameter. +For some cases, the parameter(`weight`) may be very large, such as 10 billion features, the entire +data could not be stored in one trainer's memory, so we need to partition this parameter and +pre-fetch it at the beginning of each mini-batch, and we call it `lookup remote table`: -### Pre-fetching Parameters + - +The processing flow of `lookup remote table` is as follows: -- `prefetch_rpc` operator would prefetch the parameter from different Parameter +1. partitioned parameter + + + + - **Distributed Transpiler** would split the large parameters + (`weight`) into some partitioned parameters (`weight_0`, `weight_1`, `weight_2`) as shown in the figure above. + - We can use `round-robin` to distribute the partitioned parameter. + +1. pre-fetching parameter at the beginning of each mini-batch + + - `prefetch_rpc` operator would prefetch the parameter from different Parameter Servers using the input `Ids`. We use [SelectedRows](../../../design/selected_rows.md) as the received variable type. -- `merge_selected_rows` operator would merge the received parameters into one + - `merge_selected_rows` operator would merge the received parameters into one `SelectedRows` variable. ## TODO diff --git a/doc/fluid/design/dist_train/src/lookup_local_table.graffle b/doc/fluid/design/dist_train/src/lookup_local_table.graffle new file mode 100644 index 0000000000000000000000000000000000000000..180004cec944783468158ebcacd430e14a4fb2bb GIT binary patch literal 11311 zcmb8!Q*b6gv>@OZlT2*ewr$&X^2atOp4iDm^T)PrPi!X>^N+oA@7{-7TX(l=yG}ox zr|yTY?$hTZj)epJj{ymG*=?HwltH6<_j%P`EWSitqg3CV|s#1fP11A7zo?V_zH*tB1>~mhH<wXaDyeq}g{yNbsl%_cx$K;u8&e(px>XIvRhG()-L72`7WQAKUO zhfm?#ez_KVP7QRCR}c+Mz9NFLXs#~I#K3YOFf-&zT*wfNgIk{HovA`XfFVbL;h4}3 z_I9|JKigv&GLd;heqv~v|41rgKmiwcn`R^gYZ0n`PGqMm<50Mz4~+Yz9E1Q_I-}%K zvb2)HS!?(cEe|)%K*Q*k_xX2~Ef;5;-O%vEdZnfI<(Tn#8b=^wa);E1$FTMe!UX*v 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zdU>hBu=F?B^C=fhVp`KSZvEHvlI7`BJ21I=(Nu?KuT${9AC$&)wIa02@{KM_OyyDx h^E{{WRP9UTAw -- GitLab From 282aa96731d2a23f93f8f0f26a5215fbe809a1a5 Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Thu, 15 Mar 2018 18:53:39 +0800 Subject: [PATCH 0016/1416] modify the picture size --- doc/fluid/design/dist_train/prefetch_parameter.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/doc/fluid/design/dist_train/prefetch_parameter.md b/doc/fluid/design/dist_train/prefetch_parameter.md index 952d2bada92..b3e2210fdff 100644 --- a/doc/fluid/design/dist_train/prefetch_parameter.md +++ b/doc/fluid/design/dist_train/prefetch_parameter.md @@ -16,13 +16,13 @@ Prior to reading this design, it would be useful for the reader to make themselv The execution of `lookup local table` is as follows: - + For some cases, the parameter(`weight`) may be very large, such as 10 billion features, the entire data could not be stored in one trainer's memory, so we need to partition this parameter and pre-fetch it at the beginning of each mini-batch, and we call it `lookup remote table`: - + The processing flow of `lookup remote table` is as follows: -- GitLab From cc1e94931e1b4ca18219df2af7e5743882d41f07 Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Fri, 16 Mar 2018 18:56:02 +0800 Subject: [PATCH 0017/1416] update figure --- .../design/dist_train/prefetch_parameter.md | 2 +- .../dist_train/src/split_parameter.graffle | Bin 7054 -> 7065 bytes 2 files changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/fluid/design/dist_train/prefetch_parameter.md b/doc/fluid/design/dist_train/prefetch_parameter.md index b3e2210fdff..7cea942279d 100644 --- a/doc/fluid/design/dist_train/prefetch_parameter.md +++ b/doc/fluid/design/dist_train/prefetch_parameter.md @@ -32,7 +32,7 @@ The processing flow of `lookup remote table` is as follows: - **Distributed Transpiler** would split the large parameters (`weight`) into some partitioned parameters (`weight_0`, `weight_1`, `weight_2`) as shown in the figure above. - - We can use `round-robin` to distribute the partitioned parameter. + - We can use some algorithms to distribute the partitioned parameters, such as `round-robin` or `hash-name`. 1. pre-fetching parameter at the beginning of each mini-batch diff --git a/doc/fluid/design/dist_train/src/split_parameter.graffle b/doc/fluid/design/dist_train/src/split_parameter.graffle index f020c0291e99f758f532d2611e72003478656750..db1f8dc2c7888d0f71337142bcccd0faeb09efe8 100644 GIT binary patch literal 7065 zcmV;K8)oDmiwFP!000030PUS=m!jB~_g`0jig@ZpukMb_l+mGXR&^gH#Q{YI#g%K_ z#U!8z2B4_5>bpOO!3Z?eFtTs;t>->rt`(yE_Zc{QZw?3i<+uOZt^9|r9mQT4{Q5Kc z75VwW4$RQ<0_WGC6`A|e{Q19r`}FPqFhg3_M(o4d_u}MXq)>gHe)#!Itp?U>->%gd znRyuXc}aeNWz=e{@bkmZZj!8jsnyan{i8Ec?d;eQjooDI^+^-h0Z?)`uxLc1RJ=^%{Tbx9&{lCHLzJ{y7 zbE0sw{yKzP?MR=`eY^3kR!S;rw26KtU{kPG18+1dif^@J$$1Ot&<`Wnfw||~@rBCE z*8WteEj`hXqHHJpm~R091`@kl8>=SG!VkuTL`=Wi5j{$qsG&nO2>=|>1waD>5&oSB zhs@4oQF-jcFW^g3REF;e(iq{vtJlbw0Kn#(nH{o6d4+~0zT;K4^ZYf|aB6R5TWbFK 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zy*8vPSB=}N*RaAf`1RM9W$)Kz;e6@XxVX%GX_48vTN&MNqQnUG=;4Yn~L)?zO%7O8m_&&ZO&c)5~S`nS}AvzVPI!5b0Yx8VfsDzB`Cj}y_6H% zWG}fyUMhG|XO5m*DS`LAv8%U_Z#GE%o}5sUEY;A1^QQfI4=Q)_uAyC}l^!Me@yghn z1>dwF&fS4G&5g5o&;!%{PFp3m*&y+vli_?F%;M*+USNgkb*3i0i6YqQd{|zYewTm! zSUfNgozNd&9&JEAKQxfyk%nfzefG1~a`aEzQb|TH`^Ovq6?*zc01uF%zqfnhS(PAu zjR@pIe@c_T%erw_|4Vln+s+9a^7Ro9jA-W1c#v2lI~0FfW@{1 zTk6{*hPy7bck2)a5tLUo7l)yu7dN`^CHtyL(Qo86ZC2#jV=E_(eLW&YwyMN>d3^sL zzPtV(hGqXz7#BwH40vCo-DKtGM=blf@qH# Date: Mon, 21 May 2018 02:38:37 +0000 Subject: [PATCH 0018/1416] Add an interface to set the number of threads for math function, and set the default value to 1 for inference. --- cmake/external/openblas.cmake | 2 ++ paddle/fluid/inference/io.cc | 4 ++++ paddle/fluid/operators/math/blas.h | 15 +++++++++++++++ paddle/fluid/operators/math/math_function.h | 2 ++ paddle/math/MathFunctions.h | 9 ++++----- 5 files changed, 27 insertions(+), 5 deletions(-) diff --git a/cmake/external/openblas.cmake b/cmake/external/openblas.cmake index 8af2765f587..4a49a92f2b1 100644 --- a/cmake/external/openblas.cmake +++ b/cmake/external/openblas.cmake @@ -29,6 +29,8 @@ IF(NOT ${CBLAS_FOUND}) "${CBLAS_INSTALL_DIR}/lib/${CMAKE_STATIC_LIBRARY_PREFIX}openblas${CMAKE_STATIC_LIBRARY_SUFFIX}" CACHE FILEPATH "openblas library." FORCE) + ADD_DEFINITIONS(-DPADDLE_USE_OPENBLAS) + SET(OPENBLAS_CC "${CMAKE_C_COMPILER} -Wno-unused-but-set-variable -Wno-unused-variable") SET(OPENBLAS_COMMIT "v0.2.20") diff --git a/paddle/fluid/inference/io.cc b/paddle/fluid/inference/io.cc index 65db7c7b500..6b03ac7119b 100644 --- a/paddle/fluid/inference/io.cc +++ b/paddle/fluid/inference/io.cc @@ -20,16 +20,20 @@ limitations under the License. */ #include "paddle/fluid/framework/block_desc.h" #include "paddle/fluid/framework/feed_fetch_type.h" #include "paddle/fluid/framework/op_registry.h" +#include "paddle/fluid/operators/math/blas.h" #include "paddle/fluid/pybind/pybind.h" DEFINE_string(devices, "", "The devices to be used which is joined by comma."); DEFINE_bool(init_p2p, false, "Whether to init p2p."); +DEFINE_int32(math_num_threads, 1, + "Number of threads used to run math functions."); namespace paddle { namespace inference { void Init(const std::vector argv) { framework::InitGflags(argv); + operators::math::SetNumThreads(FLAGS_math_num_threads); // init devices std::vector devices; std::string token; diff --git a/paddle/fluid/operators/math/blas.h b/paddle/fluid/operators/math/blas.h index dabde43850d..b393139acd0 100644 --- a/paddle/fluid/operators/math/blas.h +++ b/paddle/fluid/operators/math/blas.h @@ -20,13 +20,16 @@ #ifdef PADDLE_WITH_MKLML #include #include +#include #include #endif #ifdef PADDLE_USE_OPENBLAS #include +#ifdef LAPACK_FOUND #include #endif +#endif #ifndef LAPACK_FOUND extern "C" { @@ -46,6 +49,18 @@ namespace paddle { namespace operators { namespace math { +static void SetNumThreads(int num_threads) { +#ifdef PADDLE_USE_OPENBLAS + int real_num_threads = num_threads > 1 ? num_threads : 1; + openblas_set_num_threads(real_num_threads); +#elif defined(PADDLE_WITH_MKLML) + int real_num_threads = num_threads > 1 ? num_threads : 1; + mkl_set_num_threads(real_num_threads); +#else + PADDLE_ENFORCE(false, "To be implemented."); +#endif +} + /** * Matrix Descriptor of a memory buffer. * diff --git a/paddle/fluid/operators/math/math_function.h b/paddle/fluid/operators/math/math_function.h index d4b0e17ed44..8b296b6a07c 100644 --- a/paddle/fluid/operators/math/math_function.h +++ b/paddle/fluid/operators/math/math_function.h @@ -21,8 +21,10 @@ limitations under the License. */ #ifdef PADDLE_USE_OPENBLAS #include +#ifdef LAPACK_FOUND #include #endif +#endif #ifndef LAPACK_FOUND extern "C" { diff --git a/paddle/math/MathFunctions.h b/paddle/math/MathFunctions.h index f3d8b1a39e8..854e4baa398 100644 --- a/paddle/math/MathFunctions.h +++ b/paddle/math/MathFunctions.h @@ -12,8 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ -#ifndef MATHFUNCTIONS_H_ -#define MATHFUNCTIONS_H_ +#pragma once #ifdef PADDLE_WITH_MKLML #include @@ -21,7 +20,7 @@ limitations under the License. */ #include #endif -#if defined(PADDLE_USE_VECLIB) +#ifdef PADDLE_USE_VECLIB extern "C" { #include #include @@ -30,8 +29,10 @@ extern "C" { #ifdef PADDLE_USE_OPENBLAS #include +#ifdef LAPACK_FOUND #include #endif +#endif #ifndef LAPACK_FOUND extern "C" { @@ -126,5 +127,3 @@ template void vTanh(const int n, const T* a, T* r); } // namespace paddle - -#endif // MATHFUNCTIONS_H_ -- GitLab From b044724db710dabf5bea23195b599eab3ba46bb3 Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Tue, 22 May 2018 14:35:02 +0800 Subject: [PATCH 0019/1416] update fluid Train API param_path to checkpoint_config --- python/paddle/fluid/trainer.py | 50 +++++++++++++++++++++++++++------- 1 file changed, 40 insertions(+), 10 deletions(-) diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py index 7da123dd92e..01c40bb90e4 100644 --- a/python/paddle/fluid/trainer.py +++ b/python/paddle/fluid/trainer.py @@ -27,11 +27,8 @@ import parallel_executor from transpiler import distribute_transpiler __all__ = [ - 'Trainer', - 'BeginEpochEvent', - 'EndEpochEvent', - 'BeginStepEvent', - 'EndStepEvent', + 'Trainer', 'BeginEpochEvent', 'EndEpochEvent', 'BeginStepEvent', + 'EndStepEvent', 'CheckpointConfig' ] @@ -59,6 +56,17 @@ class EndStepEvent(object): self.metrics = metrics +class CheckpointConfig(object): + def __init__(self, + checkpoint_dir=None, + max_num_checkpoints=3, + save_interval_secs=600): + if checkpoint_dir is None: + self.checkpoint_dir = os.getcwd() + self.max_num_checkpoints = max_num_checkpoints + self.save_interval_secs = save_interval_secs + + def check_and_get_place(place): """ Check the type of place or get the default place @@ -97,9 +105,9 @@ class Trainer(object): def __init__(self, train_func, optimizer, - param_path=None, place=None, - parallel=False): + parallel=False, + checkpoint_config=None): self.__stop = False self.parallel = parallel # 1. we need to generate a framework.Program by calling @@ -108,6 +116,16 @@ class Trainer(object): if not isinstance(optimizer, opt_module.Optimizer): raise TypeError("The optimizer should be an instance of Optimizer") + # config for checkpoint + # only chief worker will save variables + self.chief = True + self.checkpoint = checkpoint_config + if self.checkpoint and not isinstance(self.checkpoint, + CheckpointConfig): + raise TypeError( + "The checkpoint_config shoule be an instance of CheckpointConfig" + ) + self.scope = core.Scope() self.startup_program = framework.Program() @@ -136,9 +154,10 @@ class Trainer(object): exe = executor.Executor(place) exe.run(self.startup_program) - if param_path: - # load params from param_path into scope - io.load_persistables(exe, dirname=param_path) + if self.checkpoint: + exe = executor.Executor(place) + io.load_checkpoint(exe, self.checkpoint.checkpoint_dir, + self.startup_program) def _transpile_nccl2_dist(self): # PADDLE_TRAINER_IPS @@ -146,6 +165,7 @@ class Trainer(object): self.nccl_id_var = None else: self.trainer_id = int(os.getenv("PADDLE_TRAINER_ID")) + self.chief = self.trainer_id == 0 port = os.getenv("PADDLE_PSERVER_PORT") worker_ips = os.getenv("PADDLE_TRAINER_IPS") worker_endpoints = [] @@ -194,6 +214,7 @@ class Trainer(object): # the unique trainer id, starting from 0, needed by trainer # only trainer_id = int(os.getenv("PADDLE_TRAINER_ID", "0")) + self.chief = self.trainer_id == 0 # the role, should be either PSERVER or TRAINER training_role = os.getenv("PADDLE_TRAINING_ROLE") with self._prog_and_scope_guard(): @@ -263,6 +284,14 @@ class Trainer(object): exe = executor.Executor(self.place) io.save_persistables(exe, dirname=param_path) + def _save_checkpoint(self): + if self.checkpoint and self.chief: + exe = executor.Executor(self.place) + io.save_checkpoint(exe, self.checkpoint.checkpoint_dir, + self.checkpoint.max_num_checkpoints, + self.checkpoint.save_interval_secs, + self.train_program) + @contextlib.contextmanager def _prog_and_scope_guard(self): with framework.program_guard( @@ -309,6 +338,7 @@ class Trainer(object): else: metrics = exe.run(feed=data, fetch_list=[]) event_handler(EndStepEvent(epoch_id, step_id, metrics)) + self._save_checkpoint() event_handler(EndEpochEvent(epoch_id)) def _test_by_executor(self, reader, feed_order, fetch_list): -- GitLab From dca0b6d9ccc5b770e78a0903839f2ed89d79be58 Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Wed, 23 May 2018 19:50:25 +0800 Subject: [PATCH 0020/1416] restore param_path --- python/paddle/fluid/trainer.py | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py index 01c40bb90e4..24254b4980c 100644 --- a/python/paddle/fluid/trainer.py +++ b/python/paddle/fluid/trainer.py @@ -105,6 +105,7 @@ class Trainer(object): def __init__(self, train_func, optimizer, + param_path=None, place=None, parallel=False, checkpoint_config=None): @@ -120,8 +121,8 @@ class Trainer(object): # only chief worker will save variables self.chief = True self.checkpoint = checkpoint_config - if self.checkpoint and not isinstance(self.checkpoint, - CheckpointConfig): + if self.checkpoint and \ + not isinstance(self.checkpoint, CheckpointConfig): raise TypeError( "The checkpoint_config shoule be an instance of CheckpointConfig" ) @@ -159,6 +160,10 @@ class Trainer(object): io.load_checkpoint(exe, self.checkpoint.checkpoint_dir, self.startup_program) + if param_path: + # load params from param_path into scope + io.load_persistables(exe, dirname=param_path) + def _transpile_nccl2_dist(self): # PADDLE_TRAINER_IPS if "PADDLE_TRAINER_IPS" not in os.environ: -- GitLab From 98fb8e58fd4fb91423d414d67f2a2684b6841020 Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Fri, 25 May 2018 11:57:44 +0800 Subject: [PATCH 0021/1416] test infer nlp --- paddle/fluid/inference/io.cc | 2 +- .../fluid/inference/tests/book/CMakeLists.txt | 1 + .../tests/book/test_inference_nlp.cc | 85 +++++++++++++++++++ paddle/fluid/inference/tests/test_helper.h | 3 + 4 files changed, 90 insertions(+), 1 deletion(-) create mode 100644 paddle/fluid/inference/tests/book/test_inference_nlp.cc diff --git a/paddle/fluid/inference/io.cc b/paddle/fluid/inference/io.cc index 65db7c7b500..98780b6881c 100644 --- a/paddle/fluid/inference/io.cc +++ b/paddle/fluid/inference/io.cc @@ -117,7 +117,7 @@ std::unique_ptr Load(framework::Executor* executor, std::string program_desc_str; VLOG(3) << "loading model from " << model_filename; ReadBinaryFile(model_filename, &program_desc_str); - + // LOG(INFO) << program_desc_str; std::unique_ptr main_program( new framework::ProgramDesc(program_desc_str)); diff --git a/paddle/fluid/inference/tests/book/CMakeLists.txt b/paddle/fluid/inference/tests/book/CMakeLists.txt index dbb81462b82..90357f99d1d 100644 --- a/paddle/fluid/inference/tests/book/CMakeLists.txt +++ b/paddle/fluid/inference/tests/book/CMakeLists.txt @@ -35,6 +35,7 @@ inference_test(image_classification ARGS vgg resnet) inference_test(label_semantic_roles) inference_test(recognize_digits ARGS mlp conv) inference_test(recommender_system) +inference_test(nlp) #inference_test(rnn_encoder_decoder) #inference_test(understand_sentiment ARGS conv) inference_test(word2vec) diff --git a/paddle/fluid/inference/tests/book/test_inference_nlp.cc b/paddle/fluid/inference/tests/book/test_inference_nlp.cc new file mode 100644 index 00000000000..0d6d0adfb23 --- /dev/null +++ b/paddle/fluid/inference/tests/book/test_inference_nlp.cc @@ -0,0 +1,85 @@ +/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#include "gflags/gflags.h" +#include "gtest/gtest.h" +#include "paddle/fluid/inference/tests/test_helper.h" + +DEFINE_string(dirname, "", "Directory of the inference model."); + +TEST(inference, understand_sentiment) { + if (FLAGS_dirname.empty()) { + LOG(FATAL) << "Usage: ./example --dirname=path/to/your/model"; + } + + LOG(INFO) << "FLAGS_dirname: " << FLAGS_dirname << std::endl; + std::string dirname = FLAGS_dirname; + + // 0. Call `paddle::framework::InitDevices()` initialize all the devices + // In unittests, this is done in paddle/testing/paddle_gtest_main.cc + paddle::framework::LoDTensor words; + + paddle::framework::LoD lod{{0, 83}}; + int64_t word_dict_len = 198392; + SetupLoDTensor(&words, lod, static_cast(0), + static_cast(word_dict_len - 1)); + /* + std::vector srcdata{ + 784, 784, 1550, 6463, 56, 75693, 6189, 784, 784, 1550, + 198391, 6463, 42468, 4376, 10251, 10760, 6189, 297, 396, 6463, + 6463, 1550, 198391, 6463, 22564, 1612, 291, 68, 164, 784, + 784, 1550, 198391, 6463, 13659, 3362, 42468, 6189, 2209, + 198391, + 6463, 2209, 2209, 198391, 6463, 2209, 1062, 3029, 1831, 3029, + 1065, 2281, 100, 11216, 1110, 56, 10869, 9811, 100, + 198391, + 6463, 100, 9280, 100, 288, 40031, 1680, 1335, 100, 1550, + 9280, 7265, 244, 1550, 198391, 6463, 1550, 198391, 6463, + 42468, + 4376, 10251, 10760}; + paddle::framework::LoD lod{{0, srcdata.size()}}; + words.set_lod(lod); + int64_t* pdata = + words.mutable_data({static_cast(srcdata.size()), 1}, + paddle::platform::CPUPlace()); + memcpy(pdata, srcdata.data(), words.numel() * sizeof(int64_t)); + */ + LOG(INFO) << "number of input size:" << words.numel(); + std::vector cpu_feeds; + cpu_feeds.push_back(&words); + + paddle::framework::LoDTensor output1; + std::vector cpu_fetchs1; + cpu_fetchs1.push_back(&output1); + + int repeat = 100; + // Run inference on CPU + TestInference(dirname, cpu_feeds, + cpu_fetchs1, repeat); + LOG(INFO) << output1.lod(); + LOG(INFO) << output1.dims(); + +#ifdef PADDLE_WITH_CUDA + paddle::framework::LoDTensor output2; + std::vector cpu_fetchs2; + cpu_fetchs2.push_back(&output2); + + // Run inference on CUDA GPU + TestInference(dirname, cpu_feeds, cpu_fetchs2); + LOG(INFO) << output2.lod(); + LOG(INFO) << output2.dims(); + + CheckError(output1, output2); +#endif +} diff --git a/paddle/fluid/inference/tests/test_helper.h b/paddle/fluid/inference/tests/test_helper.h index 01b8dc0be66..1f5551567c6 100644 --- a/paddle/fluid/inference/tests/test_helper.h +++ b/paddle/fluid/inference/tests/test_helper.h @@ -182,6 +182,9 @@ void TestInference(const std::string& dirname, "init_program", paddle::platform::DeviceContextPool::Instance().Get(place)); inference_program = InitProgram(&executor, scope, dirname, is_combined); + // std::string binary_str; + // inference_program->Proto()->SerializeToString(&binary_str); + // LOG(INFO) << binary_str; if (use_mkldnn) { EnableMKLDNN(inference_program); } -- GitLab From 602e28bf1c30cd72e7378d6dc1071423086bdc73 Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Fri, 25 May 2018 14:38:01 +0800 Subject: [PATCH 0022/1416] use the actual data --- .../tests/book/test_inference_nlp.cc | 48 +++++++++---------- 1 file changed, 23 insertions(+), 25 deletions(-) diff --git a/paddle/fluid/inference/tests/book/test_inference_nlp.cc b/paddle/fluid/inference/tests/book/test_inference_nlp.cc index 0d6d0adfb23..27bdd5528ef 100644 --- a/paddle/fluid/inference/tests/book/test_inference_nlp.cc +++ b/paddle/fluid/inference/tests/book/test_inference_nlp.cc @@ -12,6 +12,8 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ +#include +#include #include "gflags/gflags.h" #include "gtest/gtest.h" #include "paddle/fluid/inference/tests/test_helper.h" @@ -29,32 +31,28 @@ TEST(inference, understand_sentiment) { // 0. Call `paddle::framework::InitDevices()` initialize all the devices // In unittests, this is done in paddle/testing/paddle_gtest_main.cc paddle::framework::LoDTensor words; - - paddle::framework::LoD lod{{0, 83}}; - int64_t word_dict_len = 198392; - SetupLoDTensor(&words, lod, static_cast(0), - static_cast(word_dict_len - 1)); /* - std::vector srcdata{ - 784, 784, 1550, 6463, 56, 75693, 6189, 784, 784, 1550, - 198391, 6463, 42468, 4376, 10251, 10760, 6189, 297, 396, 6463, - 6463, 1550, 198391, 6463, 22564, 1612, 291, 68, 164, 784, - 784, 1550, 198391, 6463, 13659, 3362, 42468, 6189, 2209, - 198391, - 6463, 2209, 2209, 198391, 6463, 2209, 1062, 3029, 1831, 3029, - 1065, 2281, 100, 11216, 1110, 56, 10869, 9811, 100, - 198391, - 6463, 100, 9280, 100, 288, 40031, 1680, 1335, 100, 1550, - 9280, 7265, 244, 1550, 198391, 6463, 1550, 198391, 6463, - 42468, - 4376, 10251, 10760}; - paddle::framework::LoD lod{{0, srcdata.size()}}; - words.set_lod(lod); - int64_t* pdata = - words.mutable_data({static_cast(srcdata.size()), 1}, - paddle::platform::CPUPlace()); - memcpy(pdata, srcdata.data(), words.numel() * sizeof(int64_t)); - */ + paddle::framework::LoD lod{{0, 83}}; + int64_t word_dict_len = 198392; + SetupLoDTensor(&words, lod, static_cast(0), + static_cast(word_dict_len - 1)); + */ + std::vector srcdata{ + 784, 784, 1550, 6463, 56, 75693, 6189, 784, 784, 1550, + 198391, 6463, 42468, 4376, 10251, 10760, 6189, 297, 396, 6463, + 6463, 1550, 198391, 6463, 22564, 1612, 291, 68, 164, 784, + 784, 1550, 198391, 6463, 13659, 3362, 42468, 6189, 2209, 198391, + 6463, 2209, 2209, 198391, 6463, 2209, 1062, 3029, 1831, 3029, + 1065, 2281, 100, 11216, 1110, 56, 10869, 9811, 100, 198391, + 6463, 100, 9280, 100, 288, 40031, 1680, 1335, 100, 1550, + 9280, 7265, 244, 1550, 198391, 6463, 1550, 198391, 6463, 42468, + 4376, 10251, 10760}; + paddle::framework::LoD lod{{0, srcdata.size()}}; + words.set_lod(lod); + int64_t* pdata = words.mutable_data( + {static_cast(srcdata.size()), 1}, paddle::platform::CPUPlace()); + memcpy(pdata, srcdata.data(), words.numel() * sizeof(int64_t)); + LOG(INFO) << "number of input size:" << words.numel(); std::vector cpu_feeds; cpu_feeds.push_back(&words); -- GitLab From ce20dfa236a0bf874d8580a7861b7a85dffdf74c Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Fri, 25 May 2018 15:17:06 +0800 Subject: [PATCH 0023/1416] enable more choices --- .../tests/book/test_inference_nlp.cc | 29 +++++++++++++++++-- 1 file changed, 26 insertions(+), 3 deletions(-) diff --git a/paddle/fluid/inference/tests/book/test_inference_nlp.cc b/paddle/fluid/inference/tests/book/test_inference_nlp.cc index 27bdd5528ef..c942b43f174 100644 --- a/paddle/fluid/inference/tests/book/test_inference_nlp.cc +++ b/paddle/fluid/inference/tests/book/test_inference_nlp.cc @@ -19,6 +19,10 @@ limitations under the License. */ #include "paddle/fluid/inference/tests/test_helper.h" DEFINE_string(dirname, "", "Directory of the inference model."); +DEFINE_int32(repeat, 100, "Running the inference program repeat times"); +DEFINE_bool(use_mkldnn, false, "Use MKLDNN to run inference"); +DEFINE_bool(prepare_vars, true, "Prepare variables before executor"); +DEFINE_bool(prepare_context, true, "Prepare Context before executor"); TEST(inference, understand_sentiment) { if (FLAGS_dirname.empty()) { @@ -61,10 +65,29 @@ TEST(inference, understand_sentiment) { std::vector cpu_fetchs1; cpu_fetchs1.push_back(&output1); - int repeat = 100; // Run inference on CPU - TestInference(dirname, cpu_feeds, - cpu_fetchs1, repeat); + const bool model_combined = false; + if (FLAGS_prepare_vars) { + if (FLAGS_prepare_context) { + TestInference( + dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, + FLAGS_use_mkldnn); + } else { + TestInference( + dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, + FLAGS_use_mkldnn); + } + } else { + if (FLAGS_prepare_context) { + TestInference( + dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, + FLAGS_use_mkldnn); + } else { + TestInference( + dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, + FLAGS_use_mkldnn); + } + } LOG(INFO) << output1.lod(); LOG(INFO) << output1.dims(); -- GitLab From 400f5e7c3ce21ba63bee62a599a82c4a0bbc299d Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Fri, 25 May 2018 21:08:49 +0800 Subject: [PATCH 0024/1416] add threads test --- .../tests/book/test_inference_nlp.cc | 135 +++++++++--------- 1 file changed, 67 insertions(+), 68 deletions(-) diff --git a/paddle/fluid/inference/tests/book/test_inference_nlp.cc b/paddle/fluid/inference/tests/book/test_inference_nlp.cc index c942b43f174..ca02e38ede7 100644 --- a/paddle/fluid/inference/tests/book/test_inference_nlp.cc +++ b/paddle/fluid/inference/tests/book/test_inference_nlp.cc @@ -14,6 +14,7 @@ limitations under the License. */ #include #include +#include // NOLINT #include "gflags/gflags.h" #include "gtest/gtest.h" #include "paddle/fluid/inference/tests/test_helper.h" @@ -31,76 +32,74 @@ TEST(inference, understand_sentiment) { LOG(INFO) << "FLAGS_dirname: " << FLAGS_dirname << std::endl; std::string dirname = FLAGS_dirname; - - // 0. Call `paddle::framework::InitDevices()` initialize all the devices - // In unittests, this is done in paddle/testing/paddle_gtest_main.cc - paddle::framework::LoDTensor words; - /* - paddle::framework::LoD lod{{0, 83}}; - int64_t word_dict_len = 198392; - SetupLoDTensor(&words, lod, static_cast(0), - static_cast(word_dict_len - 1)); - */ - std::vector srcdata{ - 784, 784, 1550, 6463, 56, 75693, 6189, 784, 784, 1550, - 198391, 6463, 42468, 4376, 10251, 10760, 6189, 297, 396, 6463, - 6463, 1550, 198391, 6463, 22564, 1612, 291, 68, 164, 784, - 784, 1550, 198391, 6463, 13659, 3362, 42468, 6189, 2209, 198391, - 6463, 2209, 2209, 198391, 6463, 2209, 1062, 3029, 1831, 3029, - 1065, 2281, 100, 11216, 1110, 56, 10869, 9811, 100, 198391, - 6463, 100, 9280, 100, 288, 40031, 1680, 1335, 100, 1550, - 9280, 7265, 244, 1550, 198391, 6463, 1550, 198391, 6463, 42468, - 4376, 10251, 10760}; - paddle::framework::LoD lod{{0, srcdata.size()}}; - words.set_lod(lod); - int64_t* pdata = words.mutable_data( - {static_cast(srcdata.size()), 1}, paddle::platform::CPUPlace()); - memcpy(pdata, srcdata.data(), words.numel() * sizeof(int64_t)); - - LOG(INFO) << "number of input size:" << words.numel(); - std::vector cpu_feeds; - cpu_feeds.push_back(&words); - - paddle::framework::LoDTensor output1; - std::vector cpu_fetchs1; - cpu_fetchs1.push_back(&output1); - - // Run inference on CPU const bool model_combined = false; - if (FLAGS_prepare_vars) { - if (FLAGS_prepare_context) { - TestInference( - dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, - FLAGS_use_mkldnn); - } else { - TestInference( - dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, - FLAGS_use_mkldnn); - } - } else { - if (FLAGS_prepare_context) { - TestInference( - dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, - FLAGS_use_mkldnn); - } else { - TestInference( - dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, - FLAGS_use_mkldnn); - } - } - LOG(INFO) << output1.lod(); - LOG(INFO) << output1.dims(); + int total_work = 100; + int num_threads = 10; + int work_per_thread = total_work / num_threads; + std::vector> infer_threads; + for (int i = 0; i < num_threads; ++i) { + infer_threads.emplace_back(new std::thread([&, i]() { + for (int j = 0; j < work_per_thread; ++j) { + // 0. Call `paddle::framework::InitDevices()` initialize all the devices + // In unittests, this is done in paddle/testing/paddle_gtest_main.cc + paddle::framework::LoDTensor words; + /* + paddle::framework::LoD lod{{0, 83}}; + int64_t word_dict_len = 198392; + SetupLoDTensor(&words, lod, static_cast(0), + static_cast(word_dict_len - 1)); + */ + std::vector srcdata{ + 784, 784, 1550, 6463, 56, 75693, 6189, 784, 784, + 1550, 198391, 6463, 42468, 4376, 10251, 10760, 6189, 297, + 396, 6463, 6463, 1550, 198391, 6463, 22564, 1612, 291, + 68, 164, 784, 784, 1550, 198391, 6463, 13659, 3362, + 42468, 6189, 2209, 198391, 6463, 2209, 2209, 198391, 6463, + 2209, 1062, 3029, 1831, 3029, 1065, 2281, 100, 11216, + 1110, 56, 10869, 9811, 100, 198391, 6463, 100, 9280, + 100, 288, 40031, 1680, 1335, 100, 1550, 9280, 7265, + 244, 1550, 198391, 6463, 1550, 198391, 6463, 42468, 4376, + 10251, 10760}; + paddle::framework::LoD lod{{0, srcdata.size()}}; + words.set_lod(lod); + int64_t* pdata = words.mutable_data( + {static_cast(srcdata.size()), 1}, + paddle::platform::CPUPlace()); + memcpy(pdata, srcdata.data(), words.numel() * sizeof(int64_t)); -#ifdef PADDLE_WITH_CUDA - paddle::framework::LoDTensor output2; - std::vector cpu_fetchs2; - cpu_fetchs2.push_back(&output2); + LOG(INFO) << "number of input size:" << words.numel(); + std::vector cpu_feeds; + cpu_feeds.push_back(&words); - // Run inference on CUDA GPU - TestInference(dirname, cpu_feeds, cpu_fetchs2); - LOG(INFO) << output2.lod(); - LOG(INFO) << output2.dims(); + paddle::framework::LoDTensor output1; + std::vector cpu_fetchs1; + cpu_fetchs1.push_back(&output1); - CheckError(output1, output2); -#endif + // Run inference on CPU + if (FLAGS_prepare_vars) { + if (FLAGS_prepare_context) { + TestInference( + dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, + FLAGS_use_mkldnn); + } else { + TestInference( + dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, + FLAGS_use_mkldnn); + } + } else { + if (FLAGS_prepare_context) { + TestInference( + dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, + FLAGS_use_mkldnn); + } else { + TestInference( + dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, + FLAGS_use_mkldnn); + } + } + LOG(INFO) << output1.lod(); + LOG(INFO) << output1.dims(); + } + })); + } } -- GitLab From 514b2427edbd30013ca1783769af18fb96ffb626 Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Mon, 28 May 2018 20:08:23 +0800 Subject: [PATCH 0025/1416] add save/load persist_vars_without_grad --- python/paddle/fluid/io.py | 46 +++++++++++++++++++++++----------- python/paddle/fluid/trainer.py | 3 ++- 2 files changed, 33 insertions(+), 16 deletions(-) diff --git a/python/paddle/fluid/io.py b/python/paddle/fluid/io.py index 8e58e5eb794..f626039363a 100644 --- a/python/paddle/fluid/io.py +++ b/python/paddle/fluid/io.py @@ -24,7 +24,8 @@ __all__ = [ 'save_vars', 'save_params', 'save_persistables', 'load_vars', 'load_params', 'load_persistables', 'save_inference_model', 'load_inference_model', 'get_inference_program', 'save_checkpoint', 'load_checkpoint', - 'clean_checkpoint' + 'clean_checkpoint', 'load_persist_vars_without_grad', + 'save_persist_vars_without_grad' ] @@ -455,6 +456,33 @@ def get_parameter_value_by_name(name, executor, program=None): return get_parameter_value(var, executor) +def load_persist_vars_without_grad(executor, dirname, program): + """ + load_persist_vars_without_grad will load variables from a directory by an executor, + the variable named end with "@GRAD" will not be loaded. + """ + load_vars( + executor, + dirname=dirname, + main_program=program, + predicate=_is_checkpoint_var, + filename=None) + + +def save_persist_vars_without_grad(executor, dirname, program): + """ + save_persist_vars_without_grad will save variables to a directory by an executor, + the variable named end with "@GRAD" will not be saved. + """ + save_vars( + executor, + dirname=dirname, + main_program=program, + vars=None, + predicate=_is_checkpoint_var, + filename=None) + + SUCCESS_MARK_FILENAME = "_SUCCESS" CHECKPOINT_PREFIX = "checkpoint" CHECKPOINT_SEPARATOR = "_" @@ -491,13 +519,7 @@ def save_checkpoint(executor, serial += 1 cur_dir = _get_serial_dir(serial, checkpoint_dir) - save_vars( - executor, - dirname=cur_dir, - main_program=main_program, - vars=None, - predicate=_is_checkpoint_var, - filename=None) + load_persist_vars_without_grad(executor, cur_dir, main_program) _write_success(cur_dir) _lru_delete(checkpoint_dir, max_num_checkpoints) @@ -521,13 +543,7 @@ def load_checkpoint(executor, checkpoint_dir=None, main_program=None): return cur_dir = _get_serial_dir(serial, checkpoint_dir) - - load_vars( - executor, - dirname=cur_dir, - main_program=main_program, - predicate=_is_checkpoint_var, - filename=None) + load_persist_vars_without_grad(executor, cur_dir, main_program) def clean_checkpoint(checkpoint_dir, delete_dir=False): diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py index 24254b4980c..b4b7b75b96e 100644 --- a/python/paddle/fluid/trainer.py +++ b/python/paddle/fluid/trainer.py @@ -162,7 +162,8 @@ class Trainer(object): if param_path: # load params from param_path into scope - io.load_persistables(exe, dirname=param_path) + io.load_persist_vars_without_grad( + exe, dirname=param_path, program=self.startup_program) def _transpile_nccl2_dist(self): # PADDLE_TRAINER_IPS -- GitLab From 5eea5db95fb6eaca2db9a0af63e871a9fc29c6bf Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Tue, 29 May 2018 14:37:59 +0800 Subject: [PATCH 0026/1416] optimized checkpoint and save_model --- python/paddle/fluid/__init__.py | 1 + python/paddle/fluid/io.py | 61 +++++++++++++++------------------ python/paddle/fluid/trainer.py | 40 +++++++++++++++------ 3 files changed, 58 insertions(+), 44 deletions(-) diff --git a/python/paddle/fluid/__init__.py b/python/paddle/fluid/__init__.py index 859605d0053..aece8fc1490 100644 --- a/python/paddle/fluid/__init__.py +++ b/python/paddle/fluid/__init__.py @@ -26,6 +26,7 @@ from trainer import BeginEpochEvent from trainer import EndEpochEvent from trainer import BeginStepEvent from trainer import EndStepEvent +from trainer import CheckpointConfig import inferencer from inferencer import Inferencer diff --git a/python/paddle/fluid/io.py b/python/paddle/fluid/io.py index f626039363a..aa039bdfaa4 100644 --- a/python/paddle/fluid/io.py +++ b/python/paddle/fluid/io.py @@ -491,7 +491,6 @@ CHECKPOINT_SEPARATOR = "_" def save_checkpoint(executor, checkpoint_dir=None, max_num_checkpoints=3, - save_interval_secs=600, main_program=None): """ Save Checkpoint will save persistable LodTensor variables from main_program in checkpoint directory, @@ -511,15 +510,10 @@ def save_checkpoint(executor, if not os.path.isdir(checkpoint_dir): os.makedirs(checkpoint_dir) - serial = _get_lastest_checkpoint_dir(checkpoint_dir) - if serial >= 0 and not _interval_secs_exceed( - _get_serial_dir(serial, checkpoint_dir), save_interval_secs): - return - - serial += 1 - cur_dir = _get_serial_dir(serial, checkpoint_dir) + serial = _get_lastest_checkpoint_dir(checkpoint_dir) + 1 + cur_dir = _get_serial_dir(checkpoint_dir, serial) - load_persist_vars_without_grad(executor, cur_dir, main_program) + save_persist_vars_without_grad(executor, cur_dir, main_program) _write_success(cur_dir) _lru_delete(checkpoint_dir, max_num_checkpoints) @@ -542,7 +536,7 @@ def load_checkpoint(executor, checkpoint_dir=None, main_program=None): if serial < 0: return - cur_dir = _get_serial_dir(serial, checkpoint_dir) + cur_dir = _get_serial_dir(checkpoint_dir, serial) load_persist_vars_without_grad(executor, cur_dir, main_program) @@ -559,11 +553,6 @@ def clean_checkpoint(checkpoint_dir, delete_dir=False): os.rmdir(checkpoint_dir) -def _get_serial_dir(serial, checkpoint_dir): - serial_folder = CHECKPOINT_PREFIX + CHECKPOINT_SEPARATOR + str(serial) - return os.path.join(checkpoint_dir, serial_folder) - - def _is_checkpoint_var(var): """ the checkpoint will not save or load all the variables. @@ -582,29 +571,37 @@ def _is_checkpoint_var(var): return var.persistable -def _interval_secs_exceed(dirname, save_interval_secs): - dir_time = os.path.getmtime(dirname) - if save_interval_secs > (time.time() - dir_time): - return False - return True +def _get_dir_serial(dirname): + _, serial = dirname.split(CHECKPOINT_SEPARATOR) + + serial_num = -1 + try: + serial_num = int(serial) + except ValueError: + serial_num = -1 + return serial_num + + +def _get_serial_dir(dirname, serial): + serial_folder = CHECKPOINT_PREFIX + CHECKPOINT_SEPARATOR + str(serial) + return os.path.join(dirname, serial_folder) def _lru_delete(dirname, max_num_checkpoints=3): dirs = os.listdir(dirname) - serials = [] + serial_map = {} for serial in dirs: - try: - serials.append(int(serial)) - except ValueError: - continue + serial_num = _get_dir_serial(serial) + serial_map[serial_num] = serial - if len(serials) <= max_num_checkpoints: + if len(serial_map.keys()) <= max_num_checkpoints: return + serials = serial_map.keys() serials.sort(reverse=True) serials = serials[max_num_checkpoints:] for serial in serials: - cur_dir = os.path.join(dirname, str(serial)) + cur_dir = _get_serial_dir(dirname, serial) shutil.rmtree(cur_dir) @@ -633,20 +630,18 @@ def _get_lastest_checkpoint_dir(checkpoint_dir): """ is _SUCCESS in this dir """ - _, serial = cur_dir.split(CHECKPOINT_SEPARATOR) - try: - int(serial) - except ValueError: + serial = _get_dir_serial(cur_dir) + if serial == -1: return -1 if not os.path.isdir(os.path.join(checkpoint_dir, cur_dir)): return -1 success_path = os.path.join( - _get_serial_dir(serial, checkpoint_dir), SUCCESS_MARK_FILENAME) + _get_serial_dir(checkpoint_dir, serial), SUCCESS_MARK_FILENAME) if os.path.isfile(success_path): - return int(serial) + return serial if not os.path.isdir(checkpoint_dir): return -1 diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py index b4b7b75b96e..3cf96ac2511 100644 --- a/python/paddle/fluid/trainer.py +++ b/python/paddle/fluid/trainer.py @@ -60,11 +60,24 @@ class CheckpointConfig(object): def __init__(self, checkpoint_dir=None, max_num_checkpoints=3, - save_interval_secs=600): + epoch_interval=1, + step_interval=10): if checkpoint_dir is None: self.checkpoint_dir = os.getcwd() + else: + self.checkpoint_dir = checkpoint_dir + self.max_num_checkpoints = max_num_checkpoints - self.save_interval_secs = save_interval_secs + + if epoch_interval < 1: + self.epoch_interval = 1 + else: + self.epoch_interval = epoch_interval + + if step_interval < 1: + self.step_interval = 10 + else: + self.step_interval = step_interval def check_and_get_place(place): @@ -290,14 +303,6 @@ class Trainer(object): exe = executor.Executor(self.place) io.save_persistables(exe, dirname=param_path) - def _save_checkpoint(self): - if self.checkpoint and self.chief: - exe = executor.Executor(self.place) - io.save_checkpoint(exe, self.checkpoint.checkpoint_dir, - self.checkpoint.max_num_checkpoints, - self.checkpoint.save_interval_secs, - self.train_program) - @contextlib.contextmanager def _prog_and_scope_guard(self): with framework.program_guard( @@ -343,8 +348,9 @@ class Trainer(object): ]) else: metrics = exe.run(feed=data, fetch_list=[]) + event_handler(EndStepEvent(epoch_id, step_id, metrics)) - self._save_checkpoint() + self._save_checkpoint(epoch_id, step_id) event_handler(EndEpochEvent(epoch_id)) def _test_by_executor(self, reader, feed_order, fetch_list): @@ -384,6 +390,18 @@ class Trainer(object): loss_name=self.train_func_outputs[0].name) return self._get_parallel_executor() + def _save_checkpoint(self, epoch_id, step_id): + if not self.checkpoint or not self.chief: + return + + if epoch_id % self.checkpoint.epoch_interval == 0 and step_id % self.checkpoint.step_interval == 0: + exe = executor.Executor(self.place) + io.save_checkpoint( + executor=exe, + checkpoint_dir=self.checkpoint.checkpoint_dir, + max_num_checkpoints=self.checkpoint.max_num_checkpoints, + main_program=self.train_program) + def build_feed_var_list(program, feed_order): if not isinstance(program, framework.Program): -- GitLab From 5f5d6a9dc7eaf2e1c5b069454497d11a28701ddb Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Tue, 29 May 2018 16:01:26 +0800 Subject: [PATCH 0027/1416] optimized checkpoint and save_model --- python/paddle/fluid/io.py | 17 ++++++++--------- 1 file changed, 8 insertions(+), 9 deletions(-) diff --git a/python/paddle/fluid/io.py b/python/paddle/fluid/io.py index aa039bdfaa4..bd3c2e3d9a3 100644 --- a/python/paddle/fluid/io.py +++ b/python/paddle/fluid/io.py @@ -489,9 +489,9 @@ CHECKPOINT_SEPARATOR = "_" def save_checkpoint(executor, - checkpoint_dir=None, - max_num_checkpoints=3, - main_program=None): + checkpoint_dir, + main_program=None, + max_num_checkpoints=3): """ Save Checkpoint will save persistable LodTensor variables from main_program in checkpoint directory, the directory named by serial number from 0 to (n -1), save_checkpoint use LRU strategy @@ -500,12 +500,11 @@ def save_checkpoint(executor, :param executor :param checkpoint_dir - :param max_num_checkpoints - :param save_interval_secs :param main_program + :param max_num_checkpoints """ if checkpoint_dir is None: - checkpoint_dir = os.getcwd() + raise ValueError("The values of 'checkpoint_dir' should not be None") if not os.path.isdir(checkpoint_dir): os.makedirs(checkpoint_dir) @@ -518,7 +517,7 @@ def save_checkpoint(executor, _lru_delete(checkpoint_dir, max_num_checkpoints) -def load_checkpoint(executor, checkpoint_dir=None, main_program=None): +def load_checkpoint(executor, checkpoint_dir, main_program=None): """ Load checkpoint from a directory by executor, it will find the most recent saved checkpoint file and load it auto. @@ -529,7 +528,7 @@ def load_checkpoint(executor, checkpoint_dir=None, main_program=None): """ if checkpoint_dir is None: - checkpoint_dir = os.getcwd() + raise ValueError("The values of 'checkpoint_dir' should not be None") serial = _get_lastest_checkpoint_dir(checkpoint_dir) @@ -546,7 +545,7 @@ def clean_checkpoint(checkpoint_dir, delete_dir=False): delete_dir only works when the directory is empty, otherwise, OSError is raised. """ if checkpoint_dir is None: - checkpoint_dir = os.getcwd() + raise ValueError("The values of 'checkpoint_dir' should not be None") _lru_delete(checkpoint_dir, max_num_checkpoints=0) if delete_dir and not os.listdir(checkpoint_dir): -- GitLab From c00843f4e8860d7abff0077168942fa99ef37154 Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Tue, 29 May 2018 17:43:01 +0800 Subject: [PATCH 0028/1416] enable multi-threads --- .../tests/book/test_inference_nlp.cc | 12 ++++++++ paddle/fluid/inference/tests/test_helper.h | 29 ------------------- 2 files changed, 12 insertions(+), 29 deletions(-) diff --git a/paddle/fluid/inference/tests/book/test_inference_nlp.cc b/paddle/fluid/inference/tests/book/test_inference_nlp.cc index ca02e38ede7..6ff8a18cdb1 100644 --- a/paddle/fluid/inference/tests/book/test_inference_nlp.cc +++ b/paddle/fluid/inference/tests/book/test_inference_nlp.cc @@ -25,6 +25,12 @@ DEFINE_bool(use_mkldnn, false, "Use MKLDNN to run inference"); DEFINE_bool(prepare_vars, true, "Prepare variables before executor"); DEFINE_bool(prepare_context, true, "Prepare Context before executor"); +inline double get_current_ms() { + struct timeval time; + gettimeofday(&time, NULL); + return 1e+3 * time.tv_sec + 1e-3 * time.tv_usec; +} + TEST(inference, understand_sentiment) { if (FLAGS_dirname.empty()) { LOG(FATAL) << "Usage: ./example --dirname=path/to/your/model"; @@ -102,4 +108,10 @@ TEST(inference, understand_sentiment) { } })); } + auto start_ms = get_current_ms(); + for (int i = 0; i < num_threads; ++i) { + infer_threads[i]->join(); + } + auto stop_ms = get_current_ms(); + LOG(INFO) << "total: " << stop_ms - start_ms << " ms"; } diff --git a/paddle/fluid/inference/tests/test_helper.h b/paddle/fluid/inference/tests/test_helper.h index 1f5551567c6..dd3a7a584ad 100644 --- a/paddle/fluid/inference/tests/test_helper.h +++ b/paddle/fluid/inference/tests/test_helper.h @@ -156,27 +156,10 @@ void TestInference(const std::string& dirname, auto executor = paddle::framework::Executor(place); auto* scope = new paddle::framework::Scope(); - // Profile the performance - paddle::platform::ProfilerState state; - if (paddle::platform::is_cpu_place(place)) { - state = paddle::platform::ProfilerState::kCPU; - } else { -#ifdef PADDLE_WITH_CUDA - state = paddle::platform::ProfilerState::kAll; - // The default device_id of paddle::platform::CUDAPlace is 0. - // Users can get the device_id using: - // int device_id = place.GetDeviceId(); - paddle::platform::SetDeviceId(0); -#else - PADDLE_THROW("'CUDAPlace' is not supported in CPU only device."); -#endif - } - // 2. Initialize the inference_program and load parameters std::unique_ptr inference_program; // Enable the profiler - paddle::platform::EnableProfiler(state); { paddle::platform::RecordEvent record_event( "init_program", @@ -189,10 +172,6 @@ void TestInference(const std::string& dirname, EnableMKLDNN(inference_program); } } - // Disable the profiler and print the timing information - paddle::platform::DisableProfiler(paddle::platform::EventSortingKey::kDefault, - "load_program_profiler"); - paddle::platform::ResetProfiler(); // 3. Get the feed_target_names and fetch_target_names const std::vector& feed_target_names = @@ -233,9 +212,6 @@ void TestInference(const std::string& dirname, true, CreateVars); } - // Enable the profiler - paddle::platform::EnableProfiler(state); - // Run repeat times to profile the performance for (int i = 0; i < repeat; ++i) { paddle::platform::RecordEvent record_event( @@ -252,11 +228,6 @@ void TestInference(const std::string& dirname, CreateVars); } } - - // Disable the profiler and print the timing information - paddle::platform::DisableProfiler( - paddle::platform::EventSortingKey::kDefault, "run_inference_profiler"); - paddle::platform::ResetProfiler(); } delete scope; -- GitLab From ad9dfeb0180b40905d245354e733e750009cc173 Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Tue, 29 May 2018 20:28:40 +0800 Subject: [PATCH 0029/1416] bug fix and optimize --- python/paddle/fluid/io.py | 153 +++++++++++++++++++++++++-------- python/paddle/fluid/trainer.py | 52 +++++++++-- 2 files changed, 162 insertions(+), 43 deletions(-) diff --git a/python/paddle/fluid/io.py b/python/paddle/fluid/io.py index bd3c2e3d9a3..ed560304e25 100644 --- a/python/paddle/fluid/io.py +++ b/python/paddle/fluid/io.py @@ -456,40 +456,18 @@ def get_parameter_value_by_name(name, executor, program=None): return get_parameter_value(var, executor) -def load_persist_vars_without_grad(executor, dirname, program): - """ - load_persist_vars_without_grad will load variables from a directory by an executor, - the variable named end with "@GRAD" will not be loaded. - """ - load_vars( - executor, - dirname=dirname, - main_program=program, - predicate=_is_checkpoint_var, - filename=None) - - -def save_persist_vars_without_grad(executor, dirname, program): - """ - save_persist_vars_without_grad will save variables to a directory by an executor, - the variable named end with "@GRAD" will not be saved. - """ - save_vars( - executor, - dirname=dirname, - main_program=program, - vars=None, - predicate=_is_checkpoint_var, - filename=None) - - SUCCESS_MARK_FILENAME = "_SUCCESS" CHECKPOINT_PREFIX = "checkpoint" +MODEL_DIR = "__model__" +TRAINER_PREFIX = "trainer" CHECKPOINT_SEPARATOR = "_" def save_checkpoint(executor, checkpoint_dir, + trainer_id, + is_chief=False, + trainer_args=None, main_program=None, max_num_checkpoints=3): """ @@ -502,22 +480,35 @@ def save_checkpoint(executor, :param checkpoint_dir :param main_program :param max_num_checkpoints + :param is_chief """ if checkpoint_dir is None: raise ValueError("The values of 'checkpoint_dir' should not be None") + if trainer_args and not isinstance(trainer_args, dict): + raise TypeError("The type of 'trainer_args' should be dict") + if not os.path.isdir(checkpoint_dir): os.makedirs(checkpoint_dir) serial = _get_lastest_checkpoint_dir(checkpoint_dir) + 1 cur_dir = _get_serial_dir(checkpoint_dir, serial) - save_persist_vars_without_grad(executor, cur_dir, main_program) - _write_success(cur_dir) + if is_chief: + save_persist_vars_without_grad(executor, cur_dir, main_program) + + save_trainer_args(cur_dir, trainer_id, trainer_args) _lru_delete(checkpoint_dir, max_num_checkpoints) -def load_checkpoint(executor, checkpoint_dir, main_program=None): +def need_load_checkpoint(checkpoint_dir): + serial = _get_lastest_checkpoint_dir(checkpoint_dir) + if serial < 0: + return None + return serial + + +def load_checkpoint(executor, checkpoint_dir, serial, main_program): """ Load checkpoint from a directory by executor, it will find the most recent saved checkpoint file and load it auto. @@ -528,14 +519,17 @@ def load_checkpoint(executor, checkpoint_dir, main_program=None): """ if checkpoint_dir is None: - raise ValueError("The values of 'checkpoint_dir' should not be None") + raise ValueError( + "The values of 'checkpoint_dir' or 'serial' should not be None") - serial = _get_lastest_checkpoint_dir(checkpoint_dir) + if serial is None or serial < 0: + raise ValueError("The values of 'serial' should not be None or <0 ") - if serial < 0: - return + if main_program is None: + raise ValueError("The values of 'main_program'should not be None") cur_dir = _get_serial_dir(checkpoint_dir, serial) + cur_dir = _get_model_dir(cur_dir) load_persist_vars_without_grad(executor, cur_dir, main_program) @@ -552,6 +546,68 @@ def clean_checkpoint(checkpoint_dir, delete_dir=False): os.rmdir(checkpoint_dir) +def load_persist_vars_without_grad(executor, dirname, program, nest=True): + """ + load_persist_vars_without_grad will load variables from a directory by an executor, + the variable named end with "@GRAD" will not be loaded. + """ + + if nest: + dirname = _get_model_dir(dirname) + + load_vars( + executor, + dirname=dirname, + main_program=program, + predicate=_is_checkpoint_var, + filename=None) + + +def save_persist_vars_without_grad(executor, dirname, program): + """ + save_persist_vars_without_grad will save variables to a directory by an executor, + the variable named end with "@GRAD" will not be saved. + """ + cur_dir = _get_model_dir(dirname) + save_vars( + executor, + dirname=cur_dir, + main_program=program, + vars=None, + predicate=_is_checkpoint_var, + filename=None) + _write_success(cur_dir) + + +def save_trainer_args(dirname, trainer_id, trainer_args): + if not isinstance(trainer_args, dict): + raise TypeError("The type of 'trainer_args' should be dict") + cur_dir = _get_trainer_dir(dirname, trainer_id) + + for name, value in trainer_args.iteritems(): + args_file = os.path.join(cur_dir, name) + with open(args_file, 'w') as f: + f.write(str(value)) + _write_success(cur_dir) + + +def load_trainer_args(checkpoint_dir, serial, trainer_id, trainer_args): + cur_dir = _get_serial_dir(checkpoint_dir, serial) + cur_dir = _get_trainer_dir(cur_dir, trainer_id) + + if not isinstance(trainer_args, list): + raise TypeError("The type of 'trainer_args' should be list") + + ret_values = [] + + for arg in trainer_args: + cur_file = os.path.join(cur_dir, arg) + with open(cur_file, 'r') as f: + contents = f.read() + ret_values.append(contents.strip()) + return ret_values + + def _is_checkpoint_var(var): """ the checkpoint will not save or load all the variables. @@ -583,7 +639,31 @@ def _get_dir_serial(dirname): def _get_serial_dir(dirname, serial): serial_folder = CHECKPOINT_PREFIX + CHECKPOINT_SEPARATOR + str(serial) - return os.path.join(dirname, serial_folder) + serial_dir = os.path.join(dirname, serial_folder) + + if not os.path.isdir(serial_dir): + os.makedirs(serial_dir) + + return serial_dir + + +def _get_model_dir(dirname): + model_dir = os.path.join(dirname, MODEL_DIR) + + if not os.path.isdir(model_dir): + os.makedirs(model_dir) + + return model_dir + + +def _get_trainer_dir(dirname, trainer_id): + trainer_folder = TRAINER_PREFIX + CHECKPOINT_SEPARATOR + str(trainer_id) + trainer_dir = os.path.join(dirname, trainer_folder) + + if not os.path.isdir(trainer_dir): + os.makedirs(trainer_dir) + + return trainer_dir def _lru_delete(dirname, max_num_checkpoints=3): @@ -638,7 +718,8 @@ def _get_lastest_checkpoint_dir(checkpoint_dir): return -1 success_path = os.path.join( - _get_serial_dir(checkpoint_dir, serial), SUCCESS_MARK_FILENAME) + _get_serial_dir(checkpoint_dir, serial), MODEL_DIR, + SUCCESS_MARK_FILENAME) if os.path.isfile(success_path): return serial diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py index 3cf96ac2511..206d582cdca 100644 --- a/python/paddle/fluid/trainer.py +++ b/python/paddle/fluid/trainer.py @@ -79,6 +79,9 @@ class CheckpointConfig(object): else: self.step_interval = step_interval + self.epoch_id = 0 + self.step_id = 0 + def check_and_get_place(place): """ @@ -132,6 +135,7 @@ class Trainer(object): # config for checkpoint # only chief worker will save variables + self.trainer_id = 0 self.chief = True self.checkpoint = checkpoint_config if self.checkpoint and \ @@ -139,6 +143,8 @@ class Trainer(object): raise TypeError( "The checkpoint_config shoule be an instance of CheckpointConfig" ) + self.load_checkpoint_serial = io.need_load_checkpoint( + self.checkpoint.checkpoint_dir) self.scope = core.Scope() @@ -168,15 +174,25 @@ class Trainer(object): exe = executor.Executor(place) exe.run(self.startup_program) - if self.checkpoint: + if self.load_checkpoint_serial: exe = executor.Executor(place) io.load_checkpoint(exe, self.checkpoint.checkpoint_dir, + self.load_checkpoint_serial, self.startup_program) - if param_path: + epoch_id, step_id = io.load_trainer_args( + self.checkpoint.checkpoint_dir, self.load_checkpoint_serial, + self.trainer_id, ["epoch_id", "step_id"]) + self.checkpoint.epoch_id = int(epoch_id) + self.checkpoint.step_id = int(step_id) + + if param_path and os.path.isdir(param_path): # load params from param_path into scope io.load_persist_vars_without_grad( - exe, dirname=param_path, program=self.startup_program) + exe, + dirname=param_path, + program=self.startup_program, + nest=False) def _transpile_nccl2_dist(self): # PADDLE_TRAINER_IPS @@ -333,11 +349,20 @@ class Trainer(object): self._train_by_any_executor(event_handler, exe, num_epochs, reader) def _train_by_any_executor(self, event_handler, exe, num_epochs, reader): - for epoch_id in range(num_epochs): + epochs = [ + epoch_id for epoch_id in range(num_epochs) + if epoch_id >= self.checkpoint.epoch_id + ] + for epoch_id in epochs: event_handler(BeginEpochEvent(epoch_id)) for step_id, data in enumerate(reader()): if self.__stop: + self._clean_checkpoint() return + + if self.checkpoint and self.checkpoint.step_id >= step_id and self.checkpoint.epoch_id == epoch_id: + continue + begin_event = BeginStepEvent(epoch_id, step_id) event_handler(begin_event) if begin_event.fetch_metrics: @@ -352,6 +377,7 @@ class Trainer(object): event_handler(EndStepEvent(epoch_id, step_id, metrics)) self._save_checkpoint(epoch_id, step_id) event_handler(EndEpochEvent(epoch_id)) + self._clean_checkpoint() def _test_by_executor(self, reader, feed_order, fetch_list): with executor.scope_guard(self.scope): @@ -390,17 +416,29 @@ class Trainer(object): loss_name=self.train_func_outputs[0].name) return self._get_parallel_executor() + def _clean_checkpoint(self): + if not self.checkpoint: + return + io.clean_checkpoint(checkpoint_dir=self.checkpoint.checkpoint_dir) + def _save_checkpoint(self, epoch_id, step_id): - if not self.checkpoint or not self.chief: + if not self.checkpoint: return if epoch_id % self.checkpoint.epoch_interval == 0 and step_id % self.checkpoint.step_interval == 0: + trainer_args = {} + trainer_args["epoch_id"] = epoch_id + trainer_args["step_id"] = step_id + exe = executor.Executor(self.place) io.save_checkpoint( executor=exe, checkpoint_dir=self.checkpoint.checkpoint_dir, - max_num_checkpoints=self.checkpoint.max_num_checkpoints, - main_program=self.train_program) + trainer_id=self.trainer_id, + is_chief=self.chief, + trainer_args=trainer_args, + main_program=self.train_program, + max_num_checkpoints=self.checkpoint.max_num_checkpoints) def build_feed_var_list(program, feed_order): -- GitLab From 486e1e337d05679a22b389840136b9f07714646b Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Tue, 29 May 2018 20:36:45 +0800 Subject: [PATCH 0030/1416] bug fix and optimize --- python/paddle/fluid/trainer.py | 18 ++++++++++-------- 1 file changed, 10 insertions(+), 8 deletions(-) diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py index 206d582cdca..35bb8ded5d9 100644 --- a/python/paddle/fluid/trainer.py +++ b/python/paddle/fluid/trainer.py @@ -79,8 +79,9 @@ class CheckpointConfig(object): else: self.step_interval = step_interval - self.epoch_id = 0 - self.step_id = 0 + self._epoch_id = 0 + self._step_id = 0 + self._load_serial = None def check_and_get_place(place): @@ -174,17 +175,17 @@ class Trainer(object): exe = executor.Executor(place) exe.run(self.startup_program) - if self.load_checkpoint_serial: + if self.checkpoint._load_serial: exe = executor.Executor(place) io.load_checkpoint(exe, self.checkpoint.checkpoint_dir, - self.load_checkpoint_serial, + self.checkpoint._load_serial, self.startup_program) epoch_id, step_id = io.load_trainer_args( self.checkpoint.checkpoint_dir, self.load_checkpoint_serial, self.trainer_id, ["epoch_id", "step_id"]) - self.checkpoint.epoch_id = int(epoch_id) - self.checkpoint.step_id = int(step_id) + self.checkpoint._epoch_id = int(epoch_id) + self.checkpoint._step_id = int(step_id) if param_path and os.path.isdir(param_path): # load params from param_path into scope @@ -351,7 +352,7 @@ class Trainer(object): def _train_by_any_executor(self, event_handler, exe, num_epochs, reader): epochs = [ epoch_id for epoch_id in range(num_epochs) - if epoch_id >= self.checkpoint.epoch_id + if epoch_id >= self.checkpoint._epoch_id ] for epoch_id in epochs: event_handler(BeginEpochEvent(epoch_id)) @@ -360,7 +361,8 @@ class Trainer(object): self._clean_checkpoint() return - if self.checkpoint and self.checkpoint.step_id >= step_id and self.checkpoint.epoch_id == epoch_id: + if self.checkpoint and self.checkpoint._load_serial \ + and self.checkpoint._step_id >= step_id and self.checkpoint._epoch_id == epoch_id: continue begin_event = BeginStepEvent(epoch_id, step_id) -- GitLab From 9086043090f80ee7695d043e84fbe8068b2f76e7 Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Tue, 29 May 2018 20:52:01 +0800 Subject: [PATCH 0031/1416] bug fix and optimize --- python/paddle/fluid/io.py | 1 - python/paddle/fluid/trainer.py | 4 ++-- 2 files changed, 2 insertions(+), 3 deletions(-) diff --git a/python/paddle/fluid/io.py b/python/paddle/fluid/io.py index ed560304e25..2925e8eb289 100644 --- a/python/paddle/fluid/io.py +++ b/python/paddle/fluid/io.py @@ -529,7 +529,6 @@ def load_checkpoint(executor, checkpoint_dir, serial, main_program): raise ValueError("The values of 'main_program'should not be None") cur_dir = _get_serial_dir(checkpoint_dir, serial) - cur_dir = _get_model_dir(cur_dir) load_persist_vars_without_grad(executor, cur_dir, main_program) diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py index 35bb8ded5d9..5ca93821e22 100644 --- a/python/paddle/fluid/trainer.py +++ b/python/paddle/fluid/trainer.py @@ -144,7 +144,7 @@ class Trainer(object): raise TypeError( "The checkpoint_config shoule be an instance of CheckpointConfig" ) - self.load_checkpoint_serial = io.need_load_checkpoint( + self.checkpoint._load_serial = io.need_load_checkpoint( self.checkpoint.checkpoint_dir) self.scope = core.Scope() @@ -182,7 +182,7 @@ class Trainer(object): self.startup_program) epoch_id, step_id = io.load_trainer_args( - self.checkpoint.checkpoint_dir, self.load_checkpoint_serial, + self.checkpoint.checkpoint_dir, self.checkpoint._load_serial, self.trainer_id, ["epoch_id", "step_id"]) self.checkpoint._epoch_id = int(epoch_id) self.checkpoint._step_id = int(step_id) -- GitLab From 0211c5df0a12de2647b339dc0a8c36d35209a1a3 Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Wed, 30 May 2018 11:45:25 +0800 Subject: [PATCH 0032/1416] bug fix --- python/paddle/fluid/trainer.py | 17 +++++++++-------- tools/codestyle/docstring_checker.pyc | Bin 0 -> 12561 bytes 2 files changed, 9 insertions(+), 8 deletions(-) create mode 100644 tools/codestyle/docstring_checker.pyc diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py index 5ca93821e22..34db9b39b77 100644 --- a/python/paddle/fluid/trainer.py +++ b/python/paddle/fluid/trainer.py @@ -139,13 +139,14 @@ class Trainer(object): self.trainer_id = 0 self.chief = True self.checkpoint = checkpoint_config - if self.checkpoint and \ - not isinstance(self.checkpoint, CheckpointConfig): - raise TypeError( - "The checkpoint_config shoule be an instance of CheckpointConfig" - ) - self.checkpoint._load_serial = io.need_load_checkpoint( - self.checkpoint.checkpoint_dir) + if self.checkpoint: + if not isinstance(self.checkpoint, CheckpointConfig): + raise TypeError( + "The checkpoint_config shoule be an instance of CheckpointConfig" + ) + else: + self.checkpoint._load_serial = io.need_load_checkpoint( + self.checkpoint.checkpoint_dir) self.scope = core.Scope() @@ -175,7 +176,7 @@ class Trainer(object): exe = executor.Executor(place) exe.run(self.startup_program) - if self.checkpoint._load_serial: + if self.checkpoint and self.checkpoint._load_serial: exe = executor.Executor(place) io.load_checkpoint(exe, self.checkpoint.checkpoint_dir, self.checkpoint._load_serial, diff --git a/tools/codestyle/docstring_checker.pyc b/tools/codestyle/docstring_checker.pyc new file mode 100644 index 0000000000000000000000000000000000000000..1f0255b763c8d154b7cc17d2d525148dfea3b42d GIT binary patch literal 12561 zcmdT~Npl;=7488*kbt;or54N9SSu6>B(+$!8Cn)4%CZuRQVr#(M2iK3m?1gT00T}B zEYg-Lm69vVF}LI&q$*W8rE*K<5Z`=Een4`}DTh=}i7WZO*Mk8_(T-GhiZsb-cE9fF z<@MX&WdAWx{QTCy2Q`)aWbywB9{o!cu2QooE#+oZV5wPDOg*D!Gg8m0Agk&*HJelQ z9yQyeERM*jAg}7ZYPQ$3dsNV;>IF4hFm23MRI^3p=GCWIVux~jmDjHp@M<3+PnEhq zJD}Wx@^S(#rqDs|Wu~-)Tbw{K71ned`HjVEOJ41v7umkHTiSE&IJ9d7+0C_hDQwto 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May 2018 12:15:10 +0800 Subject: [PATCH 0033/1416] enable read dataset --- .../tests/book/test_inference_nlp.cc | 32 +++++++++++++++++-- 1 file changed, 29 insertions(+), 3 deletions(-) diff --git a/paddle/fluid/inference/tests/book/test_inference_nlp.cc b/paddle/fluid/inference/tests/book/test_inference_nlp.cc index 6ff8a18cdb1..95cdeb4ad1f 100644 --- a/paddle/fluid/inference/tests/book/test_inference_nlp.cc +++ b/paddle/fluid/inference/tests/book/test_inference_nlp.cc @@ -14,7 +14,12 @@ limitations under the License. */ #include #include +#include +#include +#include +#include #include // NOLINT +#include #include "gflags/gflags.h" #include "gtest/gtest.h" #include "paddle/fluid/inference/tests/test_helper.h" @@ -31,16 +36,37 @@ inline double get_current_ms() { return 1e+3 * time.tv_sec + 1e-3 * time.tv_usec; } +void read_data( + std::vector>* out, + const std::string& filename = "/home/tangjian/paddle-tj/out.ids.txt") { + using namespace std; // NOLINT + fstream fin(filename); + string line; + out->clear(); + while (getline(fin, line)) { + istringstream iss(line); + vector ids; + string field; + while (getline(iss, field, ' ')) { + ids.push_back(stoi(field)); + } + out->push_back(ids); + } +} + TEST(inference, understand_sentiment) { if (FLAGS_dirname.empty()) { LOG(FATAL) << "Usage: ./example --dirname=path/to/your/model"; } - + std::vector> inputdatas; + read_data(&inputdatas); + LOG(INFO) << "---------- dataset size: " << inputdatas.size(); LOG(INFO) << "FLAGS_dirname: " << FLAGS_dirname << std::endl; std::string dirname = FLAGS_dirname; + const bool model_combined = false; - int total_work = 100; - int num_threads = 10; + int total_work = 10; + int num_threads = 2; int work_per_thread = total_work / num_threads; std::vector> infer_threads; for (int i = 0; i < num_threads; ++i) { -- GitLab From 0deb6f90baa5dab02b5ff1cbc98dcaf7fae9b80b Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Wed, 30 May 2018 14:20:51 +0800 Subject: [PATCH 0034/1416] annotation optimized and code style optimized --- python/paddle/fluid/io.py | 22 +++++++++++++++++++++- python/paddle/fluid/trainer.py | 12 ++++++------ 2 files changed, 27 insertions(+), 7 deletions(-) diff --git a/python/paddle/fluid/io.py b/python/paddle/fluid/io.py index 2925e8eb289..d52c9a88236 100644 --- a/python/paddle/fluid/io.py +++ b/python/paddle/fluid/io.py @@ -478,9 +478,10 @@ def save_checkpoint(executor, :param executor :param checkpoint_dir + :param trainer_id + :param is_chief :param main_program :param max_num_checkpoints - :param is_chief """ if checkpoint_dir is None: raise ValueError("The values of 'checkpoint_dir' should not be None") @@ -502,6 +503,11 @@ def save_checkpoint(executor, def need_load_checkpoint(checkpoint_dir): + """ + If the directory have checkpoint files, it will return lastest checkpoint directory serial number + + :param checkpoint_dir + """ serial = _get_lastest_checkpoint_dir(checkpoint_dir) if serial < 0: return None @@ -515,6 +521,7 @@ def load_checkpoint(executor, checkpoint_dir, serial, main_program): :param executor :param checkpoint_dir + :param serial :param main_program """ @@ -536,7 +543,11 @@ def clean_checkpoint(checkpoint_dir, delete_dir=False): """ clean the checkpoint dir, when the train exits normally, the trainer will call clean_checkpoint to delete checkpoint directory saved before. delete_dir only works when the directory is empty, otherwise, OSError is raised. + + :param checkpoint_dir + :param delete_dir """ + if checkpoint_dir is None: raise ValueError("The values of 'checkpoint_dir' should not be None") _lru_delete(checkpoint_dir, max_num_checkpoints=0) @@ -549,6 +560,11 @@ def load_persist_vars_without_grad(executor, dirname, program, nest=True): """ load_persist_vars_without_grad will load variables from a directory by an executor, the variable named end with "@GRAD" will not be loaded. + + :param executor + :param dirname + :param program + :param nest """ if nest: @@ -566,6 +582,10 @@ def save_persist_vars_without_grad(executor, dirname, program): """ save_persist_vars_without_grad will save variables to a directory by an executor, the variable named end with "@GRAD" will not be saved. + + :param executor + :param dirname + :param program """ cur_dir = _get_model_dir(dirname) save_vars( diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py index 34db9b39b77..6d8d4a3e43b 100644 --- a/python/paddle/fluid/trainer.py +++ b/python/paddle/fluid/trainer.py @@ -79,8 +79,8 @@ class CheckpointConfig(object): else: self.step_interval = step_interval - self._epoch_id = 0 - self._step_id = 0 + self.epoch_id = 0 + self.step_id = 0 self._load_serial = None @@ -185,8 +185,8 @@ class Trainer(object): epoch_id, step_id = io.load_trainer_args( self.checkpoint.checkpoint_dir, self.checkpoint._load_serial, self.trainer_id, ["epoch_id", "step_id"]) - self.checkpoint._epoch_id = int(epoch_id) - self.checkpoint._step_id = int(step_id) + self.checkpoint.epoch_id = int(epoch_id) + self.checkpoint.step_id = int(step_id) if param_path and os.path.isdir(param_path): # load params from param_path into scope @@ -353,7 +353,7 @@ class Trainer(object): def _train_by_any_executor(self, event_handler, exe, num_epochs, reader): epochs = [ epoch_id for epoch_id in range(num_epochs) - if epoch_id >= self.checkpoint._epoch_id + if epoch_id >= self.checkpoint.epoch_id ] for epoch_id in epochs: event_handler(BeginEpochEvent(epoch_id)) @@ -363,7 +363,7 @@ class Trainer(object): return if self.checkpoint and self.checkpoint._load_serial \ - and self.checkpoint._step_id >= step_id and self.checkpoint._epoch_id == epoch_id: + and self.checkpoint.step_id >= step_id and self.checkpoint.epoch_id == epoch_id: continue begin_event = BeginStepEvent(epoch_id, step_id) -- GitLab From d712af25dcee298a1bd1fda1bba6a1f0ed001ab0 Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Wed, 30 May 2018 16:29:05 +0800 Subject: [PATCH 0035/1416] add distribute config --- python/paddle/fluid/trainer.py | 25 +++++++++++++++---------- 1 file changed, 15 insertions(+), 10 deletions(-) diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py index 6d8d4a3e43b..e98672f3187 100644 --- a/python/paddle/fluid/trainer.py +++ b/python/paddle/fluid/trainer.py @@ -81,7 +81,8 @@ class CheckpointConfig(object): self.epoch_id = 0 self.step_id = 0 - self._load_serial = None + self.load_serial = None + self.is_pserver = False def check_and_get_place(place): @@ -145,7 +146,7 @@ class Trainer(object): "The checkpoint_config shoule be an instance of CheckpointConfig" ) else: - self.checkpoint._load_serial = io.need_load_checkpoint( + self.checkpoint.load_serial = io.need_load_checkpoint( self.checkpoint.checkpoint_dir) self.scope = core.Scope() @@ -176,17 +177,18 @@ class Trainer(object): exe = executor.Executor(place) exe.run(self.startup_program) - if self.checkpoint and self.checkpoint._load_serial: + if self.checkpoint and self.checkpoint.load_serial: exe = executor.Executor(place) io.load_checkpoint(exe, self.checkpoint.checkpoint_dir, - self.checkpoint._load_serial, + self.checkpoint.load_serial, self.startup_program) - epoch_id, step_id = io.load_trainer_args( - self.checkpoint.checkpoint_dir, self.checkpoint._load_serial, - self.trainer_id, ["epoch_id", "step_id"]) - self.checkpoint.epoch_id = int(epoch_id) - self.checkpoint.step_id = int(step_id) + if not self.checkpoint.is_pserver: + epoch_id, step_id = io.load_trainer_args( + self.checkpoint.checkpoint_dir, self.checkpoint.load_serial, + self.trainer_id, ["epoch_id", "step_id"]) + self.checkpoint.epoch_id = int(epoch_id) + self.checkpoint.step_id = int(step_id) if param_path and os.path.isdir(param_path): # load params from param_path into scope @@ -259,6 +261,9 @@ class Trainer(object): t.transpile( trainer_id, pservers=pserver_endpoints, trainers=trainers) if training_role == "PSERVER": + if self.checkpoint: + self.is_pserver = True + self.train_program = t.get_pserver_program(current_endpoint) self.startup_program = t.get_startup_program(current_endpoint, self.train_program) @@ -362,7 +367,7 @@ class Trainer(object): self._clean_checkpoint() return - if self.checkpoint and self.checkpoint._load_serial \ + if self.checkpoint and self.checkpoint.load_serial \ and self.checkpoint.step_id >= step_id and self.checkpoint.epoch_id == epoch_id: continue -- GitLab From b44ede803387c0e292322ba140468599a9136352 Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Wed, 30 May 2018 19:26:12 +0800 Subject: [PATCH 0036/1416] bug fix --- python/paddle/fluid/trainer.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py index e98672f3187..b4f719855f4 100644 --- a/python/paddle/fluid/trainer.py +++ b/python/paddle/fluid/trainer.py @@ -252,14 +252,14 @@ class Trainer(object): current_endpoint = os.getenv("PADDLE_CURRENT_IP", "") + ":" + port # the unique trainer id, starting from 0, needed by trainer # only - trainer_id = int(os.getenv("PADDLE_TRAINER_ID", "0")) + self.trainer_id = int(os.getenv("PADDLE_TRAINER_ID", "0")) self.chief = self.trainer_id == 0 # the role, should be either PSERVER or TRAINER training_role = os.getenv("PADDLE_TRAINING_ROLE") with self._prog_and_scope_guard(): t = distribute_transpiler.DistributeTranspiler() t.transpile( - trainer_id, pservers=pserver_endpoints, trainers=trainers) + self.trainer_id, pservers=pserver_endpoints, trainers=trainers) if training_role == "PSERVER": if self.checkpoint: self.is_pserver = True -- GitLab From 94eaf94cf57ec2cc951d046e847b69c348b8f9c9 Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Wed, 30 May 2018 21:51:16 +0800 Subject: [PATCH 0037/1416] bug fix about lru and save --- python/paddle/fluid/io.py | 14 ++++++++++---- 1 file changed, 10 insertions(+), 4 deletions(-) diff --git a/python/paddle/fluid/io.py b/python/paddle/fluid/io.py index d52c9a88236..8e10b01a4ab 100644 --- a/python/paddle/fluid/io.py +++ b/python/paddle/fluid/io.py @@ -495,11 +495,11 @@ def save_checkpoint(executor, serial = _get_lastest_checkpoint_dir(checkpoint_dir) + 1 cur_dir = _get_serial_dir(checkpoint_dir, serial) + save_trainer_args(cur_dir, trainer_id, trainer_args) + if is_chief: save_persist_vars_without_grad(executor, cur_dir, main_program) - - save_trainer_args(cur_dir, trainer_id, trainer_args) - _lru_delete(checkpoint_dir, max_num_checkpoints) + _lru_delete(checkpoint_dir, max_num_checkpoints) def need_load_checkpoint(checkpoint_dir): @@ -639,7 +639,13 @@ def _is_checkpoint_var(var): var.desc.type() == core.VarDesc.VarType.RAW: return False - if var.name.endswith("@GRAD"): + if "@GRAD" in var.name: + return False + + if ".trainer_" in var.name: + return False + + if ".block" in var.name: return False return var.persistable -- GitLab From e44c278e60603c37640a0a352f4bbb7f8363bebc Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Wed, 30 May 2018 21:55:12 +0800 Subject: [PATCH 0038/1416] bug fix about clean --- python/paddle/fluid/trainer.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py index b4f719855f4..69577a98fbd 100644 --- a/python/paddle/fluid/trainer.py +++ b/python/paddle/fluid/trainer.py @@ -425,7 +425,7 @@ class Trainer(object): return self._get_parallel_executor() def _clean_checkpoint(self): - if not self.checkpoint: + if not self.checkpoint and not self.chief: return io.clean_checkpoint(checkpoint_dir=self.checkpoint.checkpoint_dir) -- GitLab From bca4da422582990b4308932d2c20274cdb6c5a60 Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Wed, 30 May 2018 21:56:54 +0800 Subject: [PATCH 0039/1416] cancle only chief delete files --- python/paddle/fluid/io.py | 3 ++- python/paddle/fluid/trainer.py | 2 +- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/python/paddle/fluid/io.py b/python/paddle/fluid/io.py index 8e10b01a4ab..62e3046db64 100644 --- a/python/paddle/fluid/io.py +++ b/python/paddle/fluid/io.py @@ -499,7 +499,8 @@ def save_checkpoint(executor, if is_chief: save_persist_vars_without_grad(executor, cur_dir, main_program) - _lru_delete(checkpoint_dir, max_num_checkpoints) + + _lru_delete(checkpoint_dir, max_num_checkpoints) def need_load_checkpoint(checkpoint_dir): diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py index 69577a98fbd..b4f719855f4 100644 --- a/python/paddle/fluid/trainer.py +++ b/python/paddle/fluid/trainer.py @@ -425,7 +425,7 @@ class Trainer(object): return self._get_parallel_executor() def _clean_checkpoint(self): - if not self.checkpoint and not self.chief: + if not self.checkpoint: return io.clean_checkpoint(checkpoint_dir=self.checkpoint.checkpoint_dir) -- GitLab From a2c017da9b77ac76359dcb3dc24fccde6d71f32b Mon Sep 17 00:00:00 2001 From: minqiyang Date: Thu, 31 May 2018 01:58:00 +0800 Subject: [PATCH 0040/1416] 1. merge simple_dist_transpiler to distribute_transpiler 2. add align_var_to_block argument to func transpile 3. remove concat and spilt if align_var_to_block is False 4. unittests for simple_dist_transpiler --- .../unittests/test_simple_dist_transpiler.py | 120 +++++++++ .../fluid/transpiler/distribute_transpiler.py | 45 +++- .../distribute_transpiler_simple.py | 254 ------------------ 3 files changed, 156 insertions(+), 263 deletions(-) create mode 100644 python/paddle/fluid/tests/unittests/test_simple_dist_transpiler.py delete mode 100644 python/paddle/fluid/transpiler/distribute_transpiler_simple.py diff --git a/python/paddle/fluid/tests/unittests/test_simple_dist_transpiler.py b/python/paddle/fluid/tests/unittests/test_simple_dist_transpiler.py new file mode 100644 index 00000000000..d51e356a536 --- /dev/null +++ b/python/paddle/fluid/tests/unittests/test_simple_dist_transpiler.py @@ -0,0 +1,120 @@ +# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import unittest + +import paddle.fluid as fluid +import paddle.fluid.core as core +import paddle.fluid.layers as layers +from paddle.fluid.transpiler.distribute_transpiler import delete_ops +import numpy as np + + +class TestSimpleDistTranspiler(unittest.TestCase): + def setUp(self): + self.trainer_id = 0 + self.trainers = 2 + self.pservers = 2 + self.pserver_eps = "127.0.0.1:6174,127.0.0.1:6175" + self.current_pserver_ep = "127.0.0.1:6175" + + def net_conf(self): + x = fluid.layers.data(name='x', shape=[1000], dtype='float32') + + y_predict = fluid.layers.fc(input=x, + size=1000, + act=None, + param_attr=fluid.ParamAttr(name='fc_w')) + + y = fluid.layers.data(name='y', shape=[1], dtype='float32') + + cost = fluid.layers.square_error_cost(input=y_predict, label=y) + avg_cost = fluid.layers.mean(cost) + sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.1) + + optimize_ops, params_grads = sgd_optimizer.minimize(avg_cost) + return optimize_ops, params_grads + + def test_simple_transpiler(self): + np.random.seed(1) + + trainer = self.get_trainer() + pserver, startup = self.get_pserver(self.current_pserver_ep) + self.assertEqual([op.type for op in trainer.global_block().ops], + self.get_expect_trainer_ops()) + + self.assertEqual(len(pserver.blocks), 2) + # block0: listen_and_serv + self.assertEqual([op.type for op in pserver.blocks[0].ops], + ["listen_and_serv"]) + # block1: optimize pass + self.assertEqual([op.type for op in pserver.blocks[1].ops], + ["sum", "scale", "sgd"]) + + print("xxx", [op.output_arg_names for op in startup.global_block().ops]) + # confirm startup program + self.assertEqual([op.type for op in startup.global_block().ops], + ["fill_constant", "uniform_random", "uniform_random"]) + + # the variable #fc_w will NOT be splited + fc_w_var = startup.global_block().var("fc_w@GRAD") + self.assertEqual(fc_w_var.shape, (1000, 1000)) + + fc_w_var = startup.global_block().var("fc_w@GRAD.trainer_0") + self.assertEqual(fc_w_var.shape, (1000, 1000)) + + def get_main_program(self): + main = fluid.Program() + + with fluid.program_guard(main): + self.net_conf() + + return main + + def get_expect_trainer_ops(self): + trainer = fluid.Program() + + with fluid.program_guard(trainer): + optimize_ops, params_grads = self.net_conf() + + delete_ops(trainer.global_block(), optimize_ops) + ops = [op.type for op in trainer.global_block().ops] + [ + "send_vars", "send_barrier", "recv", "recv", "fetch_barrier" + ] + ops.insert(ops.index("elementwise_add_grad") + 1, "send_vars") + return ops + + def get_trainer(self): + return self._transpiler_instance().get_trainer_program() + + def get_pserver(self, ep): + t = self._transpiler_instance() + pserver = t.get_pserver_program(ep) + startup = t.get_startup_program(ep, pserver) + return pserver, startup + + def _transpiler_instance(self): + main = self.get_main_program() + t = fluid.DistributeTranspiler() + t.transpile( + self.trainer_id, + program=main, + pservers=self.pserver_eps, + trainers=self.trainers, + align_var_to_block=False) + return t + + +if __name__ == "__main__": + unittest.main() diff --git a/python/paddle/fluid/transpiler/distribute_transpiler.py b/python/paddle/fluid/transpiler/distribute_transpiler.py index e9b7d9e9d2d..eb7daeffb9e 100644 --- a/python/paddle/fluid/transpiler/distribute_transpiler.py +++ b/python/paddle/fluid/transpiler/distribute_transpiler.py @@ -15,6 +15,7 @@ from __future__ import print_function import math +import numpy as np from ps_dispatcher import RoundRobin, HashName, PSDispatcher from .. import core, framework @@ -103,7 +104,7 @@ def split_dense_variable(var_list, service_count, min_block_size=8192): We need to have a minimal block size so that the calculations in the parameter server side can gain better performance. By default - minimum block size 8K elements (maybe 16bit or 32bit or 64bit). + minimum block size 8K elements (maybe 16bit or 32bit or 64bit). Args: var_list (list): List of variables. @@ -111,7 +112,7 @@ def split_dense_variable(var_list, service_count, min_block_size=8192): or more listening ports. min_block_size (int): Minimum splitted block size. Returns: - blocks (list[(varname, block_id, current_block_size)]): A list + blocks (list[(varname, block_id, current_block_size)]): A list of VarBlocks. Each VarBlock specifies a shard of the var. """ blocks = [] @@ -171,6 +172,7 @@ class DistributeTranspiler: program=None, pservers="127.0.0.1:6174", trainers=1, + align_var_to_block=True, split_method=RoundRobin, sync_mode=True): """ @@ -183,7 +185,8 @@ class DistributeTranspiler: parameter servers. Steps to transpile trainer: - 1. split variable to multiple blocks, aligned by product(dim[1:]) (width). + 1. split variable to multiple blocks, aligned by product(dim[1:]) (width) + if align_var_to_block is True 2. rename splited grad variables to add trainer_id suffix ".trainer_%d". 3. modify trainer program add split_op to each grad variable. 4. append send_op to send splited variables to server and fetch @@ -293,9 +296,18 @@ class DistributeTranspiler: for index in range(len(self.pserver_endpoints)) ] - grad_blocks = split_dense_variable(grad_list, len(pserver_endpoints)) - param_blocks = split_dense_variable(param_list, len(pserver_endpoints)) + if align_var_to_block: + grad_blocks = split_dense_variable(grad_list, + len(pserver_endpoints)) + param_blocks = split_dense_variable(param_list, + len(pserver_endpoints)) + else: + # when we do NOT align var to block, we will always split params + # grads into one block. + grad_blocks = split_dense_variable(grad_list, 1) + param_blocks = split_dense_variable(param_list, 1) assert (len(grad_blocks) == len(param_blocks)) + # step2: Create new vars for the parameters and gradients blocks and # add ops to do the split. param_var_mapping = self._create_vars_from_blocklist(program, @@ -325,8 +337,22 @@ class DistributeTranspiler: # step 3.1: insert send op to send gradient vars to parameter servers ps_dispatcher.reset() send_vars = [] - for orig_varname, splited_vars in grad_var_mapping.items(): + + # in general cases, the number of pservers is times of 2, and this + # will lead to uneven distribution among weights and bias: + # fc_w@GRAD_trainer_0, fc_w@GRAD_trainer_1 --> pserver1 + # fc_b@GRAD_trainer_0, fc_b@GRAD_trainer_1 --> pserver2 + # shuffle the map will avoid the uneven distribution above + grad_var_mapping_items = grad_var_mapping.items() + if not align_var_to_block: + np.random.shuffle(grad_var_mapping_items) + + for orig_varname, splited_vars in grad_var_mapping_items: eplist = ps_dispatcher.dispatch(splited_vars) + + if not align_var_to_block: + assert (len(splited_vars) == 1) + if len(splited_vars) == 1: orig_varname = splited_vars[0].name index = find_op_by_output_arg(program.global_block(), @@ -374,7 +400,7 @@ class DistributeTranspiler: for i, ep in enumerate(eplist): self.param_grad_ep_mapping[ep]["params"].append(recv_vars[i]) self.param_grad_ep_mapping[ep]["grads"].append(send_vars[i]) - # step4: Concat the parameters splits together after recv. + for varname, splited_var in param_var_mapping.iteritems(): eps = [] for var in splited_var: @@ -399,6 +425,7 @@ class DistributeTranspiler: RPC_OP_ROLE_ATTR_NAME: RPC_OP_ROLE_ATTR_VALUE }) + # step4: Concat the parameters splits together after recv. for varname, splited_var in param_var_mapping.iteritems(): if len(splited_var) <= 1: continue @@ -849,8 +876,8 @@ class DistributeTranspiler: program (ProgramDesc): ProgramDesc which gradients blong. block_list (list[(varname, block_id, block_size)]): List of gradient blocks. add_trainer_suffix (Bool): Add trainer suffix to new variable's name if set True. - Returns: - var_mapping (dict(varname->[new_varname_variable])):A dict mapping + Returns: + var_mapping (dict(varname->[new_varname_variable])):A dict mapping from original var name to each var split. """ diff --git a/python/paddle/fluid/transpiler/distribute_transpiler_simple.py b/python/paddle/fluid/transpiler/distribute_transpiler_simple.py deleted file mode 100644 index ea8c27cdca8..00000000000 --- a/python/paddle/fluid/transpiler/distribute_transpiler_simple.py +++ /dev/null @@ -1,254 +0,0 @@ -# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from ..framework import Program, default_main_program, Parameter, Variable -from ..layer_helper import LayerHelper - - -def hash_name_to_server(params_grads, pserver_endpoints): - """ - :param param_grads: - :return: a map of pserver endpoint -> - params -> [param list] - grads -> [grad list] - """ - - def _hash_param(param_name, total): - return hash(param_name) % total - - param_grad_map = dict() - for param, grad in params_grads: - if param.trainable is True and grad is not None: - server_id = _hash_param(param.name, len(pserver_endpoints)) - server_for_param = pserver_endpoints[server_id] - if not param_grad_map.has_key(server_for_param): - param_grad_map[server_for_param] = {"params": [], "grads": []} - param_grad_map[server_for_param]["params"].append(param) - param_grad_map[server_for_param]["grads"].append(grad) - - return param_grad_map - - -def round_robin(params_grads, pserver_endpoints): - assert (len(params_grads) > len(pserver_endpoints)) - - param_grad_map = dict() - pserver_idx = 0 - for param, grad in params_grads: - if param.trainable is True: - server_for_param = pserver_endpoints[pserver_idx] - if not param_grad_map.has_key(server_for_param): - param_grad_map[server_for_param] = {"params": [], "grads": []} - - param_grad_map[server_for_param]["params"].append(param) - param_grad_map[server_for_param]["grads"].append(grad) - - pserver_idx += 1 - if pserver_idx >= len(pserver_endpoints): - pserver_idx = 0 - return param_grad_map - - -class SimpleDistributeTranspiler: - def transpile(self, - optimize_ops, - params_grads, - program=None, - pservers="127.0.0.1:6174", - trainers=1, - split_method=round_robin): - """ - Transpile the program to a distributed data-parallelism programs. - - The main_program will be transform to use a remote parameter server - to do parameter optimization. And the optimization graph will be put - in to a parameter server program. - - Use different methods to split trainable varialbles to different - parameter servers. - - Example to run: - - exe = fluid.Executor(place) - t = fluid.DistributeTranspiler() - t.transpile(optimize_ops, params_grads, pservers="127.0.0.1:6174", trainers=1) - - pserver_endpoint = os.getenv("PSERVER") - if pserver_endpoint: - pserver_prog = t.get_pserver_program(pserver_endpoint, optimize_ops) - exe.run(fluid.default_startup_program()) - exe.run(pserver_prog) - else: - feeder = fluid.DataFeeder(feed_list=[images, label], place=place) - exe.run(fluid.default_startup_program()) - - for pass_id in range(PASS_NUM): - ... - - :param optimize_ops: op list of optimization, should be the - return value of Optimizer.minimize - :type optimize_ops: list - :param program: program to optimize, default default_main_program - :param pservers: parameter server endpoints like "m1:6174,m2:6174" - :type pservers: string - - :return: return a list of programs - """ - if program is None: - program = default_main_program() - self.program = program - self.trainers = trainers - self.optimize_ops = optimize_ops - self._optimize_distributed( - optimize_ops, - program, - params_grads, - pservers=pservers, - trainers=trainers, - split_method=split_method) - - def _clone_param(self, block, v): - assert isinstance(v, Parameter) - new_p = Parameter( - block=block, - shape=v.shape, - dtype=v.dtype, - type=v.type, - lod_level=v.lod_level, - stop_gradient=v.stop_gradient, - trainable=v.trainable, - optimize_attr=v.optimize_attr, - regularizer=v.regularizer, - name=v.name) - block.vars[new_p.name] = new_p - - def _clone_var(self, block, var): - assert isinstance(var, Variable) - return block.create_var( - name=var.name, - shape=var.shape, - dtype=var.dtype, - type=var.type, - lod_level=var.lod_level, - persistable=var.persistable) - - def _optimize_distributed(self, optimize_ops, program, params_and_grads, - **kwargs): - if kwargs.has_key("split_method"): - split_method = kwargs["split_method"] - else: - split_method = round_robin - - assert (callable(split_method)) - pserver_endpoints = kwargs["pservers"].split(",") - self.param_grad_map = split_method(params_and_grads, pserver_endpoints) - - send_op_ordered_inputs = [] - send_op_ordered_outputs = [] - epmap = [] - for ep, v in self.param_grad_map.iteritems(): - send_op_ordered_inputs.extend(v["grads"]) - send_op_ordered_outputs.extend(v["params"]) - for i in v["grads"]: - epmap.append(ep) - send_op = program.global_block().append_op( - type="send", - inputs={"X": send_op_ordered_inputs - }, # inputs is a list of tensors to be send - outputs={"Out": send_op_ordered_outputs}, - attrs={"endpoints": pserver_endpoints, - "epmap": epmap}) - - def get_trainer_program(self): - # remove optimize ops and add a send op to main_program - self.program.global_block().delete_ops(self.optimize_ops) - return self.program - - def _create_var_for_trainers(self, block, var, trainers): - var_list = [] - for i in xrange(trainers): - var_each = block.create_var( - name="%s.trainer_%d" % (var.name, i), - psersistable=var.persistable, - dtype=var.dtype, - shape=var.shape) - var_list.append(var_each) - return var_list - - def get_pserver_program(self, endpoint, optimize_ops): - pserver_program = Program() - for v in self.param_grad_map[endpoint]["params"]: - self._clone_param(pserver_program.global_block(), v) - - optimize_sub_program = Program() - grad_var_names = [ - var.name for var in self.param_grad_map[endpoint]["grads"] - ] - for opt_op in optimize_ops: - for _, var in opt_op.inputs.iteritems(): - # NOTE: append operators to merge gradients from multiple - # trainers. If trainers == 1, this is not needed. - if self.trainers > 1 and var.name in grad_var_names: - vars2merge = self._create_var_for_trainers( - optimize_sub_program.global_block(), var, self.trainers) - merged_var = optimize_sub_program.global_block().create_var( - name=var.name, - persistable=var.persistable, - dtype=var.dtype, - shape=var.shape) - optimize_sub_program.global_block().append_op( - type="sum", - inputs={"X": vars2merge}, - outputs={"Out": merged_var}) - optimize_sub_program.global_block().append_op( - type="scale", - inputs={"X": merged_var}, - outputs={"Out": merged_var}, - attrs={"scale": 1.0 / float(self.trainers)}) - else: - optimize_sub_program.global_block().create_var( - name=var.name, - persistable=var.persistable, - dtype=var.dtype, - shape=var.shape) - - if opt_op.inputs.has_key("Grad"): - if opt_op.inputs["Grad"].name in grad_var_names: - optimize_sub_program.global_block().append_op( - type=opt_op.type, - inputs=opt_op.inputs, - outputs=opt_op.outputs, - attrs=opt_op.attrs) - else: - optimize_sub_program.global_block().append_op( - type=opt_op.type, - inputs=opt_op.inputs, - outputs=opt_op.outputs, - attrs=opt_op.attrs) - pserver_program.global_block().append_op( - type="recv", - inputs={"RX": - self.param_grad_map[endpoint]["grads"]}, # grads to recv - outputs={}, - attrs={ - "OptimizeBlock": optimize_sub_program.global_block(), - "endpoint": endpoint, - "ParamList": - [p.name for p in self.param_grad_map[endpoint]["params"]], - "GradList": - [p.name for p in self.param_grad_map[endpoint]["grads"]], - "Trainers": self.trainers - }) - pserver_program.sync_with_cpp() - return pserver_program -- GitLab From 46f2688f3051b0bbeb070d05159922e8b689720e Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Thu, 31 May 2018 09:53:41 +0800 Subject: [PATCH 0041/1416] bug fix --- python/paddle/fluid/trainer.py | 12 ++++++++---- 1 file changed, 8 insertions(+), 4 deletions(-) diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py index b4f719855f4..3354d77acec 100644 --- a/python/paddle/fluid/trainer.py +++ b/python/paddle/fluid/trainer.py @@ -356,10 +356,14 @@ class Trainer(object): self._train_by_any_executor(event_handler, exe, num_epochs, reader) def _train_by_any_executor(self, event_handler, exe, num_epochs, reader): - epochs = [ - epoch_id for epoch_id in range(num_epochs) - if epoch_id >= self.checkpoint.epoch_id - ] + if self.checkpoint: + epochs = [ + epoch_id for epoch_id in range(num_epochs) + if epoch_id >= self.checkpoint.epoch_id + ] + else: + epochs = [epoch_id for epoch_id in range(num_epochs)] + for epoch_id in epochs: event_handler(BeginEpochEvent(epoch_id)) for step_id, data in enumerate(reader()): -- GitLab From 8248333ad2adcb3b3cdcb353cff4025092f8dcdb Mon Sep 17 00:00:00 2001 From: minqiyang Date: Thu, 31 May 2018 10:53:45 +0800 Subject: [PATCH 0042/1416] remove simple distranspiler in transpiler/ repo --- python/paddle/fluid/transpiler/__init__.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/python/paddle/fluid/transpiler/__init__.py b/python/paddle/fluid/transpiler/__init__.py index 045ca537b2e..cf18090f71f 100644 --- a/python/paddle/fluid/transpiler/__init__.py +++ b/python/paddle/fluid/transpiler/__init__.py @@ -15,10 +15,9 @@ from distribute_transpiler import DistributeTranspiler from inference_transpiler import InferenceTranspiler from memory_optimization_transpiler import memory_optimize, release_memory -from distribute_transpiler_simple import SimpleDistributeTranspiler from ps_dispatcher import HashName, RoundRobin __all__ = [ - "DistributeTranspiler", "InferenceTranspiler", "SimpleDistributeTranspiler", - "memory_optimize", "release_memory", "HashName", "RoundRobin" + "DistributeTranspiler", "InferenceTranspiler", "memory_optimize", + "release_memory", "HashName", "RoundRobin" ] -- GitLab From 164692da9a75744db770836111ae4c63ac6ed7c3 Mon Sep 17 00:00:00 2001 From: chengduoZH Date: Thu, 31 May 2018 11:00:40 +0800 Subject: [PATCH 0043/1416] drop the last batch, if the size of last batch is not equal to batch_size --- python/paddle/batch.py | 6 ++++-- python/paddle/v2/minibatch.py | 6 ++++-- 2 files changed, 8 insertions(+), 4 deletions(-) diff --git a/python/paddle/batch.py b/python/paddle/batch.py index 317cf037c69..d48c54fcbb6 100644 --- a/python/paddle/batch.py +++ b/python/paddle/batch.py @@ -15,7 +15,7 @@ __all__ = ['batch'] -def batch(reader, batch_size): +def batch(reader, batch_size, drop_last=False): """ Create a batched reader. @@ -23,6 +23,8 @@ def batch(reader, batch_size): :type reader: callable :param batch_size: size of each mini-batch :type batch_size: int + :param drop_last: drop the last batch, if the size of last batch is not equal to batch_size. + :type drop_last: bool :return: the batched reader. :rtype: callable """ @@ -35,7 +37,7 @@ def batch(reader, batch_size): if len(b) == batch_size: yield b b = [] - if b: + if drop_last == False and len(b) != 0: yield b return batch_reader diff --git a/python/paddle/v2/minibatch.py b/python/paddle/v2/minibatch.py index 317cf037c69..d48c54fcbb6 100644 --- a/python/paddle/v2/minibatch.py +++ b/python/paddle/v2/minibatch.py @@ -15,7 +15,7 @@ __all__ = ['batch'] -def batch(reader, batch_size): +def batch(reader, batch_size, drop_last=False): """ Create a batched reader. @@ -23,6 +23,8 @@ def batch(reader, batch_size): :type reader: callable :param batch_size: size of each mini-batch :type batch_size: int + :param drop_last: drop the last batch, if the size of last batch is not equal to batch_size. + :type drop_last: bool :return: the batched reader. :rtype: callable """ @@ -35,7 +37,7 @@ def batch(reader, batch_size): if len(b) == batch_size: yield b b = [] - if b: + if drop_last == False and len(b) != 0: yield b return batch_reader -- GitLab From b3f9e5e0079f22cdab7fa60025ab04bbee1e7827 Mon Sep 17 00:00:00 2001 From: weixing02 Date: Thu, 31 May 2018 11:21:15 +0800 Subject: [PATCH 0044/1416] make test_hsigmoid_op.py right --- .../fluid/tests/unittests/test_hsigmoid_op.py | 51 +++++++++---------- 1 file changed, 23 insertions(+), 28 deletions(-) diff --git a/python/paddle/fluid/tests/unittests/test_hsigmoid_op.py b/python/paddle/fluid/tests/unittests/test_hsigmoid_op.py index 178f56aeb81..226ce8b9042 100644 --- a/python/paddle/fluid/tests/unittests/test_hsigmoid_op.py +++ b/python/paddle/fluid/tests/unittests/test_hsigmoid_op.py @@ -1,4 +1,4 @@ -# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. +# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -14,8 +14,8 @@ import unittest import numpy as np -from op_test import OpTest import math +from op_test import OpTest def find_latest_set(num): @@ -37,40 +37,36 @@ class CodeTable(object): def hsigmoid(x, w, ids, bias, num_classes): - # code length = - # initialize pre out with dims={batch_size, code_length} + global pre_output batch_size = x.shape[0] code_length = find_latest_set(num_classes - 1) code_table = [0 for _ in range(code_length)] pre_output = np.zeros((batch_size, code_length)) pre_sum = np.zeros((batch_size, 1)) out = np.zeros((batch_size, 1)).astype("float32") - # pre_out += code(bias) - for i in xrange(batch_size): + for i in range(batch_size): code_table = CodeTable(num_classes, ids[i]) length = code_table.get_length() - for j in xrange(length): + for j in range(length): idx = code_table.cal_index(j) pre_output[i][j] += bias[0][idx] - # pre_out += code(w) * x - for i in xrange(batch_size): - for j in xrange(batch_size): - code_table = CodeTable(num_classes, ids[j]) - length = code_table.get_length() - for k in xrange(length): - idx = code_table.cal_index(k) - sum = 0.0 - for l in xrange(x.shape[1]): - sum += w[i][idx][l] * x[j][l] - pre_output[j][k] += sum + for j in range(batch_size): + code_table = CodeTable(num_classes, ids[j]) + length = code_table.get_length() + for k in range(length): + idx = code_table.cal_index(k) + sum = 0.0 + for l in range(x.shape[1]): + sum += w[idx][l] * x[j][l] + pre_output[j][k] += sum # clip[-40.0, 40.0] np.clip(pre_output, -40.0, 40.0) # out(i, 0) = \sum_j bit(i, j) * preout(i, j) - for i in xrange(batch_size): + for i in range(batch_size): code_table = CodeTable(num_classes, ids[i]) length = code_table.get_length() sum = 0.0 - for j in xrange(length): + for j in range(length): if code_table.cal_bit(j): sum += pre_output[i][j] out[i] = -1.0 * sum @@ -85,24 +81,23 @@ def hsigmoid(x, w, ids, bias, num_classes): class TestHSigmoidOp(OpTest): def setUp(self): self.op_type = "hierarchical_sigmoid" - num_classes = 6 - embded_size = 10 - batch_size = 5 + num_classes = 4 + embded_size = 1 + batch_size = 1 x = np.random.random((batch_size, embded_size)).astype("float32") - w = np.random.random( - (batch_size, num_classes - 1, embded_size)).astype("float32") + w = np.random.random((num_classes - 1, embded_size)).astype("float32") ids = np.random.randint(0, num_classes, batch_size) bias = np.random.random((1, num_classes - 1)).astype("float32") - self.inputs = {'X': x, 'W': w, 'Ids': ids, 'Bias': bias} self.attrs = {'num_classes': num_classes} + self.inputs = {'X': x, 'W': w, 'Ids': ids, 'Bias': bias} out = hsigmoid(x, w, ids, bias, num_classes) - self.outputs = {'Out': out} + self.outputs = {'PreOut': pre_output, 'Out': out} def test_check_output(self): self.check_output() def test_check_grad(self): - self.check_grad(['X', 'W', 'Bias'], 'Out', no_grad_set=set('Ids')) + self.check_grad(['Bias', 'X', 'W'], 'Out', no_grad_set=set('Ids')) if __name__ == '__main__': -- GitLab From a4d88fb6420cba41c701378b1ed56fe4f9ec45f1 Mon Sep 17 00:00:00 2001 From: minqiyang Date: Thu, 31 May 2018 11:41:08 +0800 Subject: [PATCH 0045/1416] 1. remove simple distranspiler from transpiler/ repo 2. remvoe comment line --- python/paddle/fluid/__init__.py | 4 ++-- .../fluid/tests/unittests/test_simple_dist_transpiler.py | 1 - 2 files changed, 2 insertions(+), 3 deletions(-) diff --git a/python/paddle/fluid/__init__.py b/python/paddle/fluid/__init__.py index 859605d0053..d53a96a7a79 100644 --- a/python/paddle/fluid/__init__.py +++ b/python/paddle/fluid/__init__.py @@ -44,8 +44,8 @@ import transpiler from param_attr import ParamAttr, WeightNormParamAttr from data_feeder import DataFeeder from core import LoDTensor, CPUPlace, CUDAPlace, CUDAPinnedPlace -from transpiler import DistributeTranspiler, SimpleDistributeTranspiler, \ - InferenceTranspiler, memory_optimize, release_memory +from transpiler import DistributeTranspiler, InferenceTranspiler, \ + memory_optimize, release_memory from concurrency import (Go, make_channel, channel_send, channel_recv, channel_close, Select) from lod_tensor import create_lod_tensor, create_random_int_lodtensor diff --git a/python/paddle/fluid/tests/unittests/test_simple_dist_transpiler.py b/python/paddle/fluid/tests/unittests/test_simple_dist_transpiler.py index d51e356a536..60f99f412cd 100644 --- a/python/paddle/fluid/tests/unittests/test_simple_dist_transpiler.py +++ b/python/paddle/fluid/tests/unittests/test_simple_dist_transpiler.py @@ -62,7 +62,6 @@ class TestSimpleDistTranspiler(unittest.TestCase): self.assertEqual([op.type for op in pserver.blocks[1].ops], ["sum", "scale", "sgd"]) - print("xxx", [op.output_arg_names for op in startup.global_block().ops]) # confirm startup program self.assertEqual([op.type for op in startup.global_block().ops], ["fill_constant", "uniform_random", "uniform_random"]) -- GitLab From e05abab60923c819c16980bdd53bdd684518f75b Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Thu, 31 May 2018 11:56:59 +0800 Subject: [PATCH 0046/1416] use recordio in dist train --- doc/v2/howto/recordio/README.md | 122 ++++++++++++++++++ .../details/threaded_ssa_graph_executor.cc | 6 +- .../reader/create_recordio_file_reader_op.cc | 12 +- python/paddle/fluid/layers/io.py | 20 +-- python/paddle/fluid/recordio_writer.py | 35 ++++- tools/codestyle/docstring_checker.pyc | Bin 11769 -> 11769 bytes 6 files changed, 178 insertions(+), 17 deletions(-) create mode 100644 doc/v2/howto/recordio/README.md diff --git a/doc/v2/howto/recordio/README.md b/doc/v2/howto/recordio/README.md new file mode 100644 index 00000000000..3f81d54b8e1 --- /dev/null +++ b/doc/v2/howto/recordio/README.md @@ -0,0 +1,122 @@ +# How to use RecordIO in Fluid + +If you want to use RecordIO as your training data format, you need to convert to your training data +to RecordIO files and reading them in the process of training, PaddlePaddle Fluid provides some +interface to deal with the RecordIO files. + +## Generate RecordIO File + +Before start training with RecordIO files, you need to convert your training data +to RecordIO format by `fluid.recordio_writer.convert_reader_to_recordio_file`, the sample codes +as follows: + +```python + reader = paddle.batch(mnist.train(), batch_size=1) + feeder = fluid.DataFeeder( + feed_list=[ # order is image and label + fluid.layers.data( + name='image', shape=[784]), + fluid.layers.data( + name='label', shape=[1], dtype='int64'), + ], + place=fluid.CPUPlace()) + fluid.recordio_writer.convert_reader_to_recordio_file('./mnist.recordio', reader, feeder) +``` + +The above codes would generate a RecordIO `./mnist.recordio` on your host. + +## Use the RecordIO file in a Local Training Job + +PaddlePaddle Fluid provides an interface `fluid.layers.io.open_recordio_file` to load your RecordIO file +and then you can use them as a Layer in your network configuration, the sample codes as follows: + +```python + data_file = fluid.layers.io.open_recordio_file( + filename="./mnist.recordio", + shapes=[(-1, 784),(-1, 1)], + lod_levels=[0, 0], + dtypes=["float32", "int32"]) + data_file = fluid.layers.io.batch(data_file, batch_size=4) + + img, label = fluid.layers.io.read_file(data_file) + hidden = fluid.layers.fc(input=img, size=100, act='tanh') + prediction = fluid.layers.fc(input=hidden, size=10, act='softmax') + loss = fluid.layers.cross_entropy(input=prediction, label=label) + avg_loss = fluid.layers.mean(loss) + + fluid.optimizer.Adam(learning_rate=1e-3).minimize(avg_loss) + + place = fluid.CPUPlace() + + exe = fluid.Executor(place) + exe.run(fluid.default_startup_program()) + avg_loss_np = [] + + # train a pass + batch_id = 0 + while True: + tmp, = exe.run(fetch_list=[avg_loss]) + + avg_loss_np.append(tmp) + print(batch_id) + batch_id += 1 +``` + +## Use the RecordIO files in Distributed Training + +1. generate multiple RecordIO files + +For a distributed training job, you may have multiple trainer nodes, +and one or more RecordIO files for one trainer node, you can use the interface +`fluid.recordio_writer.convert_reader_to_recordio_files` to convert your training data +into multiple RecordIO files, the sample codes as follows: + +```python + reader = paddle.batch(mnist.train(), batch_size=1) + feeder = fluid.DataFeeder( + feed_list=[ # order is image and label + fluid.layers.data( + name='image', shape=[784]), + fluid.layers.data( + name='label', shape=[1], dtype='int64'), + ], + place=fluid.CPUPlace()) + fluid.recordio_writer.convert_reader_to_recordio_files( + filename_suffix='./mnist.recordio', batch_per_file=100, reader, feeder) +``` + +The above codes would generate multiple RecordIO files on your host like: + +```bash +. + \_mnist.recordio-00000 + |-mnist.recordio-00001 + |-mnist.recordio-00002 + |-mnist.recordio-00003 + |-mnist.recordio-00004 +``` + +1. read these RecordIO files with `fluid.layers.io.open_recordio_file` + +For a distributed training job, the distributed operator system will schedule trainer process on multiple nodes, +each trainer process reads parts of the whole training data, we usually take the following approach to make the training +data allocated by each trainer process as uniform as possiable: + +```python +def gen_train_list(file_pattern, trainers, trainer_id): + file_list = glob.glob(file_pattern) + ret_list = [] + for idx, f in enumerate(file_list): + if (idx + trainers) % trainers == trainer_id: + ret_list.append(f) + return ret_list + +trainers = int(os.getenv("TRAINERS")) +trainer_id = int(os.getenv("PADDLE_INIT_TRAINER_ID")) +data_file = fluid.layers.io.open_recordio_file( + filename=gen_train_list("./mnist.recordio*", trainers, trainer_id), + shapes=[(-1, 784),(-1, 1)], + lod_levels=[0, 0], + dtypes=["float32", "int32"]) +data_file = fluid.layers.io.batch(data_file, batch_size=4) +``` diff --git a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc index 815f739371e..335c067dd73 100644 --- a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc +++ b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc @@ -189,9 +189,11 @@ void ThreadedSSAGraphExecutor::RunOp( BlockingQueue *ready_var_q, details::OpHandleBase *op) { auto op_run = [ready_var_q, op, this] { try { - VLOG(10) << op << " " << op->Name() << " : " << op->DebugString(); + VLOG(10) << "PE start " + << " " << op->Name() << " : " << op->DebugString(); op->Run(strategy_.use_event_); - VLOG(10) << op << " " << op->Name() << " Done "; + VLOG(10) << "PE end " + << " " << op->Name() << " Done "; running_ops_--; ready_var_q->Extend(op->Outputs()); VLOG(10) << op << " " << op->Name() << "Signal posted"; diff --git a/paddle/fluid/operators/reader/create_recordio_file_reader_op.cc b/paddle/fluid/operators/reader/create_recordio_file_reader_op.cc index 282ec3f36b9..6b6d4470268 100644 --- a/paddle/fluid/operators/reader/create_recordio_file_reader_op.cc +++ b/paddle/fluid/operators/reader/create_recordio_file_reader_op.cc @@ -65,20 +65,22 @@ class CreateRecordIOReaderOp : public framework::OperatorBase { static_cast(shape_concat.size()), "The accumulate of all ranks should be equal to the " "shape concat's length."); - std::string filename = Attr("filename"); + auto filenames = Attr>("filenames"); auto* out = scope.FindVar(Output("Out")) ->template GetMutable(); - - out->Reset(new RecordIOFileReader( - filename, RestoreShapes(shape_concat, ranks))); + for (auto& fn : filenames) { + out->Reset( + new RecordIOFileReader(fn, RestoreShapes(shape_concat, ranks))); + } } }; class CreateRecordIOReaderOpMaker : public FileReaderMakerBase { protected: void Apply() override { - AddAttr("filename", "The filename of record io reader"); + AddAttr>("filenames", + "The filenames of record io reader"); AddComment(R"DOC( CreateRecordIOReader Operator diff --git a/python/paddle/fluid/layers/io.py b/python/paddle/fluid/layers/io.py index 8758ac9f94a..b9d55827304 100644 --- a/python/paddle/fluid/layers/io.py +++ b/python/paddle/fluid/layers/io.py @@ -21,7 +21,7 @@ from ..layer_helper import LayerHelper from ..executor import global_scope __all__ = [ - 'data', 'BlockGuardServ', 'ListenAndServ', 'Send', 'open_recordio_file', + 'data', 'BlockGuardServ', 'ListenAndServ', 'Send', 'open_recordio_files', 'open_files', 'read_file', 'shuffle', 'batch', 'double_buffer', 'random_data_generator', 'Preprocessor' ] @@ -291,12 +291,12 @@ def _copy_reader_create_op_(block, op): return new_op -def open_recordio_file(filename, - shapes, - lod_levels, - dtypes, - pass_num=1, - for_parallel=True): +def open_recordio_files(filenames, + shapes, + lod_levels, + dtypes, + pass_num=1, + for_parallel=True): """ Open a RecordIO file @@ -304,7 +304,7 @@ def open_recordio_file(filename, Via the Reader Variable, we can get data from the given RecordIO file. Args: - filename(str): The RecordIO file's name. + filename(str) or list(str): The RecordIO file's name. shapes(list): List of tuples which declaring data shapes. lod_levels(list): List of ints which declaring data lod_level. dtypes(list): List of strs which declaring data type. @@ -336,6 +336,8 @@ def open_recordio_file(filename, ranks.append(len(shape)) var_name = unique_name('open_recordio_file') + if isinstance(filenames, str): + filenames = [filenames] startup_blk = default_startup_program().current_block() startup_var = startup_blk.create_var(name=var_name) @@ -345,7 +347,7 @@ def open_recordio_file(filename, attrs={ 'shape_concat': shape_concat, 'lod_levels': lod_levels, - 'filename': filename, + 'filenames': filenames, 'ranks': ranks }) diff --git a/python/paddle/fluid/recordio_writer.py b/python/paddle/fluid/recordio_writer.py index 5accaacd536..7c966cba74a 100644 --- a/python/paddle/fluid/recordio_writer.py +++ b/python/paddle/fluid/recordio_writer.py @@ -14,7 +14,7 @@ import core import contextlib - +from ..batch import batch __all__ = ['convert_reader_to_recordio_file'] @@ -46,3 +46,36 @@ def convert_reader_to_recordio_file( writer.complete_append_tensor() counter += 1 return counter + + +import paddle + + +def convert_reader_to_recordio_files( + filename_suffix, + batch_per_file, + reader_creator, + feeder, + compressor=core.RecordIOWriter.Compressor.Snappy, + max_num_records=1000, + feed_order=None): + if feed_order is None: + feed_order = feeder.feed_names + lines = [] + f_idx = 0 + counter = 0 + for idx, batch in enumerate(reader_creator()): + lines.append(batch) + if idx >= batch_per_file and idx % batch_per_file == 0: + filename = "%s-%05d" % (filename_suffix, f_idx) + with create_recordio_writer(filename, compressor, + max_num_records) as writer: + for l in lines: + res = feeder.feed(l) + for each in feed_order: + writer.append_tensor(res[each]) + writer.complete_append_tensor() + counter += 1 + lines = [] + f_idx += 1 + return counter diff --git a/tools/codestyle/docstring_checker.pyc b/tools/codestyle/docstring_checker.pyc index 1ce612ca2318ccb9b9f28d51cb93ce8e5e1d0680..07e875aec6c9bae8002bde4223348c6a29647b03 100644 GIT binary patch delta 939 zcmewv{WF@K`72B7N6d=Nrn_Hwj znTRk=T=oZH({v_B$ZsaXuuz4!1Pt38uT)5kv!qmAh*7pe-Ij1_)ZMJFElI##!0e@OH)lM*viO7&gxlS^|`^Gb^K(=$ur%kzt}iwhEyQzyqO z>1?)OiX=kW Date: Thu, 31 May 2018 12:21:13 +0800 Subject: [PATCH 0047/1416] clean up code --- python/paddle/fluid/recordio_writer.py | 4 ---- 1 file changed, 4 deletions(-) diff --git a/python/paddle/fluid/recordio_writer.py b/python/paddle/fluid/recordio_writer.py index 7c966cba74a..9557f91bb36 100644 --- a/python/paddle/fluid/recordio_writer.py +++ b/python/paddle/fluid/recordio_writer.py @@ -14,7 +14,6 @@ import core import contextlib -from ..batch import batch __all__ = ['convert_reader_to_recordio_file'] @@ -48,9 +47,6 @@ def convert_reader_to_recordio_file( return counter -import paddle - - def convert_reader_to_recordio_files( filename_suffix, batch_per_file, -- GitLab From a6a7b6f180ec7fe08a3bd41902e88f3fd5caa17a Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Thu, 31 May 2018 12:23:57 +0800 Subject: [PATCH 0048/1416] code cleanup --- .../details/threaded_ssa_graph_executor.cc | 6 ++---- tools/codestyle/docstring_checker.pyc | Bin 11769 -> 0 bytes 2 files changed, 2 insertions(+), 4 deletions(-) delete mode 100644 tools/codestyle/docstring_checker.pyc diff --git a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc index 335c067dd73..815f739371e 100644 --- a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc +++ b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc @@ -189,11 +189,9 @@ void ThreadedSSAGraphExecutor::RunOp( BlockingQueue *ready_var_q, details::OpHandleBase *op) { auto op_run = [ready_var_q, op, this] { try { - VLOG(10) << "PE start " - << " " << op->Name() << " : " << op->DebugString(); + VLOG(10) << op << " " << op->Name() << " : " << op->DebugString(); op->Run(strategy_.use_event_); - VLOG(10) << "PE end " - << " " << op->Name() << " Done "; + VLOG(10) << op << " " << op->Name() << " Done "; running_ops_--; ready_var_q->Extend(op->Outputs()); VLOG(10) << op << " " << op->Name() << "Signal posted"; diff --git a/tools/codestyle/docstring_checker.pyc b/tools/codestyle/docstring_checker.pyc deleted file mode 100644 index 07e875aec6c9bae8002bde4223348c6a29647b03..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 11769 zcmdT~%X1XR8SmL$t+b1Tc#4Oy8S`8MD~X3+M8*~fV-j0Xvp5to)Ogt$Nh8hftfpse z$%aa$aOH8#E%^^pm8zUlxutT5Z$2h}Kyu6}hg439EBXDto}FEU>_FK9N7A&qzkYxH zy}R@O7%8{*jJ)4a=}#X2-^8bXiNsTC4ymQQoC+;9hm6VR)Lc&Tc@^eWv!Lb*syU$M z29(7X1r-)mb5P9aQHDS=gNEPIiB>FmX6Ypt^I?AVCV)AExb6bRfzlxi+FjUwP(V;15<<$#sa49H;yjXU1$HB> zYi%z^p{MO+(YM?6nACwirPN^iq2Kgdi5@T8_{k2COO^wC9+^Z=59fvhbaQf^c~Yt6 zDI6oud$v+Q>g3s&xey4&frB`Nlp3L5kIfmeR{P=n(>Nj54O&6sx`#O@Csx*|m2HuW zy~LVnBnw?K1!Ye43c3D5zQ0gVQ-Snx&LT1<^o9aj663o6c8+@k^I)xLd8m`E0HnMHeBxuCCTbCY#g2yg^6*DBOB z`Y%XCQrW;d)Ro^zf~ckK`8aA)c8RDWk=8nmMZ2zTa@;99y6H4(`fiw&v(Lb ztv7&>b%eQMEs9uJLX+WSiOyCcf@-EalS93yMUu$&&O6%)pvLL$^Snd!8NMPxI{R3p znm3}RS0vMm2uMU}w8J2Q;)JB)0*H*Zvy)BsA~8*pdYtHwf@IMMEK0F@yY08Uge!F+ zyj<40$y(bNaYkfRWVvJ(P&K4S)G#dEH&s3HMNx#3Hk>iE+iZU3CgpHmK}M6I)lfM% z41OK~NAIwTxlt&JhkkS0ti6C2tpmAoPlaT%kjW7^Ehi5ZDbEI&2bF4i37 zRcutwZA@+ql*e8s%!ZT-pQsdM)$w=3f(Z=dKE&j+MsBRV*M;c~)2L}Ydi z3$C#!?7I+0owh^6U9`DT*i`1mqAu$m_t!cf|~IT}UC*^@IV^) zqyiL+%13cf?SaEN56UX3m%XyUwg3iK6tEG%whC+%ux$d{4%iNX?F4L>z;**RCa^t# z?G@NQ!1fF5IlvAG?0LXm5ZFP$Y=OO~UZx*BE>7?v@nnXTcUUrTfR9K9KJQV)B8C)K)XpE}S|rAagZSLt?FqgJ&Y>44@+J*>`0akHLOp&L8mV;x@C zblG2nE9yPcj;w{rs%Exo*DEHu_rRjpwGG&{mTyygbAesA4le%%`?P?y*a%pfUlkpH z8eQNId-g|*e#@@gdNGQV{=Ps1x;Np|2k>6Z7{d5BUz?mft;rxWy_vko*RYck8@7N= z6Tm(+e#mb7aS(ZCW>i#Jq1Vscx86rbsi$LPGoR6~Vdm*Dw1H4)1G+aX~!^XEg%eX;q}v#*(5KCfdYi5ZHy~q z`*9q_rx@(9&)E{put9EEEgdCI=~gxQs)HmF`9L5u`=ixHEu&iF9d|ZzH49SN9M2b7#X^9_% zc$<+=+I}kqWqwLZBPPI?xjEC1I6dOmR8lWzoF(`^z@IHsk(vqXc`GRqZ0zpz92{F5 z8n7k^?X7yK`$h;Ty=EmwB@sLkYNCtHnniIZ5hWD(kd5i>nW97G=-5oCDn(gKOcLBm z&qE{5!=VydVd90PR4JCQ0SF=V*(+3|+@lQJ)AF05;1inDj~wF90o1#YsG*VEm{rJ? zUW1A&3N%M=J&?Lurh$g*W@Quco^C}YK=MfFg1s3sbW*C$cnSB`>>sKguJ&o?- zzttO{PB0sgNGVwB*I%^-qWGaRU;#{<3JDa9?M{h-0wN!#rthdocL^1Iss+}w02G%? zsuvbmtZUb3QXy?4&|Tr~r+d;uT)!b|$bj8&VMe5M5QIqU$Y9S)CbcqIxnCu?w_pt{ zOQn{Fl)j)KEe!+`k}?&(#vMT~%vQKTf;|tu4tf!dIjaTK4R$>o5h%_%OemzDhMik} zg)4MuDmaXV_hg5(m<4_%v>~Da3eIgJHdBY|Mk8Bf)>FppMa=tKd}$z-g5ZdC& z4XOafQ1}Uge};@fFsyl?G2WSB7K#Tb%M-;9kVj~Cj)BFQJC1}Efk=tW0SzWPh(7b+)csGP375g4T+&kQ0PzLr<8>{_X%~vP68<9azu?M478wr0xb{T3y#}+k% zCTvxdi-h+KWkZf4&JCw^h!ZeY4SB%8cFv+O5IUqD(tkwKm7ZN1G{M-^Dyra$!Je|u zO`f2q2Nwse#k=X*IZt3Ii3!y;mwF>S5piv3DDiX~)aXPok$V=OX3zsV<<2e!ihxZc zVu7t6SSun^yBBfnDWYy3#3Hf`C{k*CQvS6<6CJYw;zVjw3?A|OrWX8`zuJy3{FT!f zYSCO>S<(>!l}Cav5TADF8us&&5Y?lNjc~WwxW{8VQIzH5lz+mPa!&~%}>{{eiDs!b@iu2cu@XHp%TGCTzj<3T?Io#_+$;11M* zBfv%=2fZZX8~g&Q5ar3MA+QW@d%!ZdWD%C3M$vyj(z7x8n5N4a5*FzC@AmQW<93hI zACp($q8s-FJhvI_BJ|E=+@U+)Pek-0j3j-SSR9ec&!JYl4(!j|Y`o3(J-NIQ?V!cx zu#7W|KVNNo+QGhsh}w2sgpVpk?^fY4!&TD}o6_iQNi zWguZA3UwS-)R^2rBKJFnDf+1K7^}Y})HsE;j6uf#Z)&7k<0mq52f8d68Hw9A=s@U6 zSeOW3-?^}Xq#Q<&lrJ%0Zo(6S7@ScnWAgL@vJ`Sss-R*mKyQMZAw^MwjAS&hMO{*( zEX9O)#nE34llL=$hy#{(_>3C*3S6-(Z!=bar(C$X5mgQQmy6{C3@Gd^s+QM6`!2r8gno`&E?{*f>r%yGoZGGN$&H~=!8?oaM)5Oh2g*Oc+V9q3PF6|24 z4!H-F=nSua8;e2c#eS=gxoCt;VD||*lZ*eGR^b}u# zI^#@uP2fy2p><{6j<^9|$;rh6E@|ohUcXkmdgJP~+39!OcQ4m!(^oFLS7#(@_WjGZ zZeDX{`oPXD4n(_1uQl&Rp_p`S+&;xYvL@(mYP`pzP>9;{j>vffdFM?g(@YrEb1pKW z<16;NSYr;AphMZ?aOXXhE4j^a9%$o5`1JRX6!S%^1bs`r%ilcSnw9bXq>S94q}!3> zXG(+C2rrNK$hC2?R2m*Djg@wm_Lug{yDGuEag>5pBl$-$i@EX~@7^*}Hz)_EtR!rm z*2=5ec|4ib=HU3?r4fZ;`ZP;kemW=ElZck%FlLvD*mGM?1AlV(QzjUFVJjw0uhfUF QVT9NjS|84r2F9-c7hLv=%K!iX -- GitLab From 2f49432538fd0d2d95e897ab37e7609acb145fe1 Mon Sep 17 00:00:00 2001 From: weixing02 Date: Thu, 31 May 2018 14:07:26 +0800 Subject: [PATCH 0049/1416] adjust --- python/paddle/fluid/layers/nn.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index f41a1f11955..bc3a7708363 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -3028,9 +3028,9 @@ def hsigmoid(input, label, num_classes=2, param_attr=None, bias_attr=None): pre_out = helper.create_tmp_variable(dtype) dim = input.shape[1] if num_classes < 2: - raise valueError("num_classes must be lager or equal than 2.") - if x.shape[0] != y.shape[1]: - raise valueError( + raise ValueError("num_classes must be lager or equal than 2.") + if input.shape[0] != label.shape[1]: + raise ValueError( "input's 1-st dimension and label's 2-nd dimension must be equal they both equal to batch size." ) weights = helper.create_parameter( -- GitLab From 4bd08e3408aa50cc1d762a01eded1f6464291327 Mon Sep 17 00:00:00 2001 From: weixing02 Date: Thu, 31 May 2018 15:00:36 +0800 Subject: [PATCH 0050/1416] make test_layers right --- python/paddle/fluid/layers/nn.py | 2 +- python/paddle/fluid/tests/unittests/test_layers.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index bc3a7708363..072679696b1 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -3031,7 +3031,7 @@ def hsigmoid(input, label, num_classes=2, param_attr=None, bias_attr=None): raise ValueError("num_classes must be lager or equal than 2.") if input.shape[0] != label.shape[1]: raise ValueError( - "input's 1-st dimension and label's 2-nd dimension must be equal they both equal to batch size." + "input's 1-st dimension and label's 2-nd dimension must be equal, they both equal to batch size." ) weights = helper.create_parameter( attr=helper.param_attr, diff --git a/python/paddle/fluid/tests/unittests/test_layers.py b/python/paddle/fluid/tests/unittests/test_layers.py index 5ac51847880..63ae51c4f42 100644 --- a/python/paddle/fluid/tests/unittests/test_layers.py +++ b/python/paddle/fluid/tests/unittests/test_layers.py @@ -177,7 +177,7 @@ class TestBook(unittest.TestCase): program = Program() with program_guard(program): x = layers.data(name='x', shape=[2, 2], dtype='float32') - y = layers.data(name='y', shape=[1, 3], dtype='int64') + y = layers.data(name='y', shape=[1, 2], dtype='int64') self.assertIsNotNone( layers.hsigmoid( input=x, label=y, num_classes=2)) -- GitLab From 2a1fc03e8ef65cceb8ad7e47d2609896a1911a8b Mon Sep 17 00:00:00 2001 From: weixing02 Date: Thu, 31 May 2018 15:53:14 +0800 Subject: [PATCH 0051/1416] Add hsigmoid --- python/paddle/fluid/layers/nn.py | 4 ---- 1 file changed, 4 deletions(-) diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index 072679696b1..004dcf7382a 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -3029,10 +3029,6 @@ def hsigmoid(input, label, num_classes=2, param_attr=None, bias_attr=None): dim = input.shape[1] if num_classes < 2: raise ValueError("num_classes must be lager or equal than 2.") - if input.shape[0] != label.shape[1]: - raise ValueError( - "input's 1-st dimension and label's 2-nd dimension must be equal, they both equal to batch size." - ) weights = helper.create_parameter( attr=helper.param_attr, shape=[num_classes - 1, dim], -- GitLab From 75ea577fd31a7ead1cbec6aa6b21338040ea585d Mon Sep 17 00:00:00 2001 From: Xin Pan Date: Thu, 31 May 2018 16:01:16 +0800 Subject: [PATCH 0052/1416] allow profiler and timeline to work when dev_ctx is nullptr. Sometimes dev_ctx is not available when RecordEvent. --- paddle/fluid/platform/profiler.cc | 1 + 1 file changed, 1 insertion(+) diff --git a/paddle/fluid/platform/profiler.cc b/paddle/fluid/platform/profiler.cc index 3d8d64e4c27..01de9d7041b 100644 --- a/paddle/fluid/platform/profiler.cc +++ b/paddle/fluid/platform/profiler.cc @@ -127,6 +127,7 @@ double Event::CpuElapsedMs(const Event& e) const { double Event::CudaElapsedMs(const Event& e) const { #ifdef PADDLE_WITH_CUDA + if (!has_cuda_) return 0.0; PADDLE_ENFORCE(e.has_cuda() && has_cuda()); PADDLE_ENFORCE(e.device() == device()); PADDLE_ENFORCE(cudaEventSynchronize(event_)); -- GitLab From 4d11c8e9c64f65b6701edb1ba44cefdff0423acb Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Thu, 31 May 2018 15:11:46 +0800 Subject: [PATCH 0053/1416] retest single thread --- .../tests/book/test_inference_nlp.cc | 224 +++++++++++------- 1 file changed, 143 insertions(+), 81 deletions(-) diff --git a/paddle/fluid/inference/tests/book/test_inference_nlp.cc b/paddle/fluid/inference/tests/book/test_inference_nlp.cc index 95cdeb4ad1f..e216e9dbe6f 100644 --- a/paddle/fluid/inference/tests/book/test_inference_nlp.cc +++ b/paddle/fluid/inference/tests/book/test_inference_nlp.cc @@ -30,16 +30,19 @@ DEFINE_bool(use_mkldnn, false, "Use MKLDNN to run inference"); DEFINE_bool(prepare_vars, true, "Prepare variables before executor"); DEFINE_bool(prepare_context, true, "Prepare Context before executor"); +DEFINE_int32(num_threads, 1, "Number of threads should be used"); + inline double get_current_ms() { struct timeval time; gettimeofday(&time, NULL); return 1e+3 * time.tv_sec + 1e-3 * time.tv_usec; } -void read_data( - std::vector>* out, - const std::string& filename = "/home/tangjian/paddle-tj/out.ids.txt") { +// return size of total words +size_t read_datasets(std::vector* out, + const std::string& filename) { using namespace std; // NOLINT + size_t sz = 0; fstream fin(filename); string line; out->clear(); @@ -50,94 +53,153 @@ void read_data( while (getline(iss, field, ' ')) { ids.push_back(stoi(field)); } - out->push_back(ids); + if (ids.size() >= 1024 || out->size() >= 100) { + continue; + } + + paddle::framework::LoDTensor words; + paddle::framework::LoD lod{{0, ids.size()}}; + words.set_lod(lod); + int64_t* pdata = words.mutable_data( + {static_cast(ids.size()), 1}, paddle::platform::CPUPlace()); + memcpy(pdata, ids.data(), words.numel() * sizeof(int64_t)); + out->emplace_back(words); + sz += ids.size(); } + return sz; +} + +void test_multi_threads() { + /* + size_t jobs_per_thread = std::min(inputdatas.size() / FLAGS_num_threads, + inputdatas.size()); + std::vector workers(FLAGS_num_threads, jobs_per_thread); + workers[FLAGS_num_threads - 1] += inputdatas.size() % FLAGS_num_threads; + + std::vector> infer_threads; + + for (size_t i = 0; i < workers.size(); ++i) { + infer_threads.emplace_back(new std::thread([&, i]() { + size_t start = i * jobs_per_thread; + for (size_t j = start; j < start + workers[i]; ++j ) { + // 0. Call `paddle::framework::InitDevices()` initialize all the + devices + // In unittests, this is done in paddle/testing/paddle_gtest_main.cc + paddle::framework::LoDTensor words; + auto& srcdata = inputdatas[j]; + paddle::framework::LoD lod{{0, srcdata.size()}}; + words.set_lod(lod); + int64_t* pdata = words.mutable_data( + {static_cast(srcdata.size()), 1}, + paddle::platform::CPUPlace()); + memcpy(pdata, srcdata.data(), words.numel() * sizeof(int64_t)); + + LOG(INFO) << "thread id: " << i << ", words size:" << words.numel(); + std::vector cpu_feeds; + cpu_feeds.push_back(&words); + + paddle::framework::LoDTensor output1; + std::vector cpu_fetchs1; + cpu_fetchs1.push_back(&output1); + + // Run inference on CPU + if (FLAGS_prepare_vars) { + if (FLAGS_prepare_context) { + TestInference( + dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, + FLAGS_use_mkldnn); + } else { + TestInference( + dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, + FLAGS_use_mkldnn); + } + } else { + if (FLAGS_prepare_context) { + TestInference( + dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, + FLAGS_use_mkldnn); + } else { + TestInference( + dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, + FLAGS_use_mkldnn); + } + } + //LOG(INFO) << output1.lod(); + //LOG(INFO) << output1.dims(); + } + })); + } + auto start_ms = get_current_ms(); + for (int i = 0; i < FLAGS_num_threads; ++i) { + infer_threads[i]->join(); + } + auto stop_ms = get_current_ms(); + LOG(INFO) << "total: " << stop_ms - start_ms << " ms";*/ } -TEST(inference, understand_sentiment) { +TEST(inference, nlp) { if (FLAGS_dirname.empty()) { LOG(FATAL) << "Usage: ./example --dirname=path/to/your/model"; } - std::vector> inputdatas; - read_data(&inputdatas); - LOG(INFO) << "---------- dataset size: " << inputdatas.size(); LOG(INFO) << "FLAGS_dirname: " << FLAGS_dirname << std::endl; std::string dirname = FLAGS_dirname; + std::vector datasets; + size_t num_total_words = + read_datasets(&datasets, "/home/tangjian/paddle-tj/out.ids.txt"); + LOG(INFO) << "Number of dataset samples(seq len<1024): " << datasets.size(); + LOG(INFO) << "Total number of words: " << num_total_words; + const bool model_combined = false; - int total_work = 10; - int num_threads = 2; - int work_per_thread = total_work / num_threads; - std::vector> infer_threads; - for (int i = 0; i < num_threads; ++i) { - infer_threads.emplace_back(new std::thread([&, i]() { - for (int j = 0; j < work_per_thread; ++j) { - // 0. Call `paddle::framework::InitDevices()` initialize all the devices - // In unittests, this is done in paddle/testing/paddle_gtest_main.cc - paddle::framework::LoDTensor words; - /* - paddle::framework::LoD lod{{0, 83}}; - int64_t word_dict_len = 198392; - SetupLoDTensor(&words, lod, static_cast(0), - static_cast(word_dict_len - 1)); - */ - std::vector srcdata{ - 784, 784, 1550, 6463, 56, 75693, 6189, 784, 784, - 1550, 198391, 6463, 42468, 4376, 10251, 10760, 6189, 297, - 396, 6463, 6463, 1550, 198391, 6463, 22564, 1612, 291, - 68, 164, 784, 784, 1550, 198391, 6463, 13659, 3362, - 42468, 6189, 2209, 198391, 6463, 2209, 2209, 198391, 6463, - 2209, 1062, 3029, 1831, 3029, 1065, 2281, 100, 11216, - 1110, 56, 10869, 9811, 100, 198391, 6463, 100, 9280, - 100, 288, 40031, 1680, 1335, 100, 1550, 9280, 7265, - 244, 1550, 198391, 6463, 1550, 198391, 6463, 42468, 4376, - 10251, 10760}; - paddle::framework::LoD lod{{0, srcdata.size()}}; - words.set_lod(lod); - int64_t* pdata = words.mutable_data( - {static_cast(srcdata.size()), 1}, - paddle::platform::CPUPlace()); - memcpy(pdata, srcdata.data(), words.numel() * sizeof(int64_t)); - - LOG(INFO) << "number of input size:" << words.numel(); - std::vector cpu_feeds; - cpu_feeds.push_back(&words); - - paddle::framework::LoDTensor output1; - std::vector cpu_fetchs1; - cpu_fetchs1.push_back(&output1); - - // Run inference on CPU - if (FLAGS_prepare_vars) { - if (FLAGS_prepare_context) { - TestInference( - dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, - FLAGS_use_mkldnn); - } else { - TestInference( - dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, - FLAGS_use_mkldnn); - } - } else { - if (FLAGS_prepare_context) { - TestInference( - dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, - FLAGS_use_mkldnn); - } else { - TestInference( - dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, - FLAGS_use_mkldnn); - } - } - LOG(INFO) << output1.lod(); - LOG(INFO) << output1.dims(); - } - })); + + // 0. Call `paddle::framework::InitDevices()` initialize all the devices + // 1. Define place, executor, scope + auto place = paddle::platform::CPUPlace(); + auto executor = paddle::framework::Executor(place); + auto* scope = new paddle::framework::Scope(); + + // 2. Initialize the inference_program and load parameters + std::unique_ptr inference_program; + inference_program = InitProgram(&executor, scope, dirname, model_combined); + if (FLAGS_use_mkldnn) { + EnableMKLDNN(inference_program); } - auto start_ms = get_current_ms(); - for (int i = 0; i < num_threads; ++i) { - infer_threads[i]->join(); + + if (FLAGS_num_threads > 1) { + test_multi_threads(); + } else { + if (FLAGS_prepare_vars) { + executor.CreateVariables(*inference_program, scope, 0); + } + // always prepare context and burning first time + std::unique_ptr ctx; + ctx = executor.Prepare(*inference_program, 0); + + // preapre fetch + const std::vector& fetch_target_names = + inference_program->GetFetchTargetNames(); + PADDLE_ENFORCE_EQ(fetch_target_names.size(), 1UL); + std::map fetch_targets; + paddle::framework::LoDTensor outtensor; + fetch_targets[fetch_target_names[0]] = &outtensor; + + // prepare feed + const std::vector& feed_target_names = + inference_program->GetFeedTargetNames(); + PADDLE_ENFORCE_EQ(feed_target_names.size(), 1UL); + std::map feed_targets; + + // for data and run + auto start_ms = get_current_ms(); + for (size_t i = 0; i < datasets.size(); ++i) { + feed_targets[feed_target_names[0]] = &(datasets[i]); + executor.RunPreparedContext(ctx.get(), scope, &feed_targets, + &fetch_targets, !FLAGS_prepare_vars); + } + auto stop_ms = get_current_ms(); + LOG(INFO) << "Total infer time: " << (stop_ms - start_ms) / 1000.0 / 60 + << " min, avg time per seq: " + << (stop_ms - start_ms) / datasets.size() << " ms"; } - auto stop_ms = get_current_ms(); - LOG(INFO) << "total: " << stop_ms - start_ms << " ms"; + delete scope; } -- GitLab From d13dd3b6a7ee81d4c106035ec0bad2c581ea795c Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Thu, 31 May 2018 16:04:47 +0800 Subject: [PATCH 0054/1416] revert profiling --- paddle/fluid/inference/tests/test_helper.h | 29 ++++++++++++++++++++++ 1 file changed, 29 insertions(+) diff --git a/paddle/fluid/inference/tests/test_helper.h b/paddle/fluid/inference/tests/test_helper.h index dd3a7a584ad..1f5551567c6 100644 --- a/paddle/fluid/inference/tests/test_helper.h +++ b/paddle/fluid/inference/tests/test_helper.h @@ -156,10 +156,27 @@ void TestInference(const std::string& dirname, auto executor = paddle::framework::Executor(place); auto* scope = new paddle::framework::Scope(); + // Profile the performance + paddle::platform::ProfilerState state; + if (paddle::platform::is_cpu_place(place)) { + state = paddle::platform::ProfilerState::kCPU; + } else { +#ifdef PADDLE_WITH_CUDA + state = paddle::platform::ProfilerState::kAll; + // The default device_id of paddle::platform::CUDAPlace is 0. + // Users can get the device_id using: + // int device_id = place.GetDeviceId(); + paddle::platform::SetDeviceId(0); +#else + PADDLE_THROW("'CUDAPlace' is not supported in CPU only device."); +#endif + } + // 2. Initialize the inference_program and load parameters std::unique_ptr inference_program; // Enable the profiler + paddle::platform::EnableProfiler(state); { paddle::platform::RecordEvent record_event( "init_program", @@ -172,6 +189,10 @@ void TestInference(const std::string& dirname, EnableMKLDNN(inference_program); } } + // Disable the profiler and print the timing information + paddle::platform::DisableProfiler(paddle::platform::EventSortingKey::kDefault, + "load_program_profiler"); + paddle::platform::ResetProfiler(); // 3. Get the feed_target_names and fetch_target_names const std::vector& feed_target_names = @@ -212,6 +233,9 @@ void TestInference(const std::string& dirname, true, CreateVars); } + // Enable the profiler + paddle::platform::EnableProfiler(state); + // Run repeat times to profile the performance for (int i = 0; i < repeat; ++i) { paddle::platform::RecordEvent record_event( @@ -228,6 +252,11 @@ void TestInference(const std::string& dirname, CreateVars); } } + + // Disable the profiler and print the timing information + paddle::platform::DisableProfiler( + paddle::platform::EventSortingKey::kDefault, "run_inference_profiler"); + paddle::platform::ResetProfiler(); } delete scope; -- GitLab From 708bec2e56c6a856f628ad8b650b0bf04a3df975 Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Thu, 31 May 2018 16:33:54 +0800 Subject: [PATCH 0055/1416] add test --- paddle/fluid/inference/tests/book/test_inference_nlp.cc | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/paddle/fluid/inference/tests/book/test_inference_nlp.cc b/paddle/fluid/inference/tests/book/test_inference_nlp.cc index e216e9dbe6f..990d45964e3 100644 --- a/paddle/fluid/inference/tests/book/test_inference_nlp.cc +++ b/paddle/fluid/inference/tests/book/test_inference_nlp.cc @@ -200,6 +200,14 @@ TEST(inference, nlp) { LOG(INFO) << "Total infer time: " << (stop_ms - start_ms) / 1000.0 / 60 << " min, avg time per seq: " << (stop_ms - start_ms) / datasets.size() << " ms"; + { // just for test + auto* scope = new paddle::framework::Scope(); + paddle::framework::LoDTensor outtensor; + TestInference( + dirname, {&(datasets[0])}, {&outtensor}, FLAGS_repeat, model_combined, + false); + delete scope; + } } delete scope; } -- GitLab From f9d93bfde1bd69d84a10cb676f0aba52b1596edd Mon Sep 17 00:00:00 2001 From: yuyang18 Date: Thu, 31 May 2018 16:42:00 +0800 Subject: [PATCH 0056/1416] Add document to random crop operator --- paddle/fluid/operators/random_crop_op.cc | 6 +-- .../fluid/layers/layer_function_generator.py | 53 ++++++++++++++++--- python/paddle/fluid/layers/nn.py | 29 +++++++++- 3 files changed, 75 insertions(+), 13 deletions(-) diff --git a/paddle/fluid/operators/random_crop_op.cc b/paddle/fluid/operators/random_crop_op.cc index b14b559e31d..371cdb5b858 100644 --- a/paddle/fluid/operators/random_crop_op.cc +++ b/paddle/fluid/operators/random_crop_op.cc @@ -36,11 +36,11 @@ class RandomCropOpMaker : public framework::OpProtoAndCheckerMaker { AddInput("Seed", "The random seed."); AddOutput("Out", "The cropped instance batch."); AddOutput("SeedOut", "The random seed after random cropping.") - .AsDispensable(); + .AsIntermediate(); AddAttr>("shape", "The shape of a cropped instance."); AddComment(R"DOC( - This operator takes a batch of instance, and do random cropping on each instance. - It means that cropping positions differs on each instance, which is determined + This operator takes a batch of instance, and do random cropping on each instance. + It means that cropping positions differs on each instance, which is determined by an uniform random generator. All cropped instances have the same shape, which is determined by the operator's attribute 'shape'. )DOC"); diff --git a/python/paddle/fluid/layers/layer_function_generator.py b/python/paddle/fluid/layers/layer_function_generator.py index 295d1b7190e..6026237d0b6 100644 --- a/python/paddle/fluid/layers/layer_function_generator.py +++ b/python/paddle/fluid/layers/layer_function_generator.py @@ -15,16 +15,13 @@ import re import cStringIO import functools import warnings +import string from ..proto import framework_pb2 from ..framework import OpProtoHolder, Variable from ..layer_helper import LayerHelper -__all__ = [ - 'deprecated', - 'generate_layer_fn', - 'autodoc', -] +__all__ = ['deprecated', 'generate_layer_fn', 'autodoc', 'templatedoc'] def _convert_(name): @@ -43,6 +40,10 @@ def _convert_(name): return re.sub('([a-z0-9])([A-Z])', r'\1_\2', s1).lower() +def _type_to_str_(tp): + return framework_pb2.AttrType.Name(tp) + + def _generate_doc_string_(op_proto): """ Generate docstring by OpProto @@ -54,9 +55,6 @@ def _generate_doc_string_(op_proto): str: the document string """ - def _type_to_str_(tp): - return framework_pb2.AttrType.Name(tp) - if not isinstance(op_proto, framework_pb2.OpProto): raise TypeError("OpProto should be `framework_pb2.OpProto`") @@ -220,3 +218,42 @@ def autodoc(comment=""): return func return __impl__ + + +def templatedoc(): + """ + Decorator of layer function. It will use the docstring from the layer + function as the template. The template arguments are: + + * ${comment}: The operator comment written in CPP. + * ${{name}_comment}: The comment of ${name} written with AddAttr, AddOutput, + and AddInput. The ${name} is Python snake style. i.e., xxx_xxx. + * ${{name}_type}: The type of ${name}. + + + Returns: + Decorated funciton. + """ + + def __impl__(func): + op_proto = OpProtoHolder.instance().get_op_proto(func.__name__) + tmpl = string.Template(func.__doc__) + args = {"comment": " ".join(op_proto.comment.split())} + for each_input in op_proto.inputs: + input_name = _convert_(each_input.name) + args["{0}_comment".format(input_name)] = each_input.comment + args["{0}_type".format(input_name)] = "Variable" + for each_attr in op_proto.attrs: + input_name = _convert_(each_attr.name) + args["{0}_comment".format(input_name)] = each_attr.comment + args["{0}_type".format(input_name)] = _type_to_str_(each_attr.type) + + for each_opt in op_proto.outputs: + output_name = _convert_(each_opt.name) + args["{0}_comment".format(output_name)] = each_opt.comment + args["{0}_type".format(output_name)] = "Variable" + + func.__doc__ = tmpl.substitute(args) + return func + + return __impl__ diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index 63ec8315147..acebeaebbb6 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -19,9 +19,10 @@ from ..layer_helper import LayerHelper from ..initializer import Normal, Constant from ..framework import Variable from ..param_attr import ParamAttr -from layer_function_generator import autodoc +from layer_function_generator import autodoc, templatedoc from tensor import concat import utils +import random __all__ = [ 'fc', @@ -3992,10 +3993,34 @@ def upsampling_bilinear2d(input, out_shape=None, scale=None, name=None): return out -def random_crop(input, shape, seed=1): +@templatedoc() +def random_crop(x, shape, seed=None): + """ + **Random crop operator** + + ${comment} + + Examples: + >>> img = fluid.layers.data("img", [3, 256, 256]) + >>> cropped_img = fluid.layers.random_crop(img, shape=[3, 224, 224]) + + Args: + x(${x_type}): ${x_comment} + shape(${shape_type}): ${shape_comment} + seed(int|${seed_type}|None): ${seed_comment} By default, the seed will + get from `random.randint(-65536, 65535)`. + + Returns: + ${out_comment} + + """ + helper = LayerHelper("random_crop", **locals()) dtype = helper.input_dtype() out = helper.create_tmp_variable(dtype) + if seed is None: + seed = random.randint(-65536, 65535) + if isinstance(seed, int): seed_value = seed seed = helper.create_tmp_variable(dtype="int64") -- GitLab From e330cd032e9a92e2a5851506c35c2ef31e02e01a Mon Sep 17 00:00:00 2001 From: chengduoZH Date: Thu, 31 May 2018 16:34:08 +0800 Subject: [PATCH 0057/1416] balance parameter update --- .../details/multi_devices_graph_builder.cc | 41 +++++++++++++------ .../details/multi_devices_graph_builder.h | 2 +- 2 files changed, 30 insertions(+), 13 deletions(-) diff --git a/paddle/fluid/framework/details/multi_devices_graph_builder.cc b/paddle/fluid/framework/details/multi_devices_graph_builder.cc index d8e711994c5..17baacd13ee 100644 --- a/paddle/fluid/framework/details/multi_devices_graph_builder.cc +++ b/paddle/fluid/framework/details/multi_devices_graph_builder.cc @@ -11,11 +11,15 @@ // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. -#include "paddle/fluid/framework/details/multi_devices_graph_builder.h" +#include #include +#include #include +#include + #include "paddle/fluid/framework/details/broadcast_op_handle.h" #include "paddle/fluid/framework/details/computation_op_handle.h" +#include "paddle/fluid/framework/details/multi_devices_graph_builder.h" #include "paddle/fluid/framework/details/reduce_op_handle.h" #include "paddle/fluid/framework/details/rpc_op_handle.h" #include "paddle/fluid/framework/details/scale_loss_grad_op_handle.h" @@ -26,9 +30,6 @@ #include "paddle/fluid/framework/details/nccl_all_reduce_op_handle.h" #endif -#include -#include - DEFINE_string(ssa_graph_path, "/tmp/ssa_graph.dot", "the ssa graph path only print with GLOG_v=10," "default /tmp/graph.dot"); @@ -148,9 +149,9 @@ bool MultiDevSSAGraphBuilder::IsDistTrainOp( std::unique_ptr MultiDevSSAGraphBuilder::Build( const ProgramDesc &program) const { - std::unordered_map var_types; + std::unordered_map all_vars; for (auto *var : program.Block(0).AllVars()) { - var_types[var->Name()] = var->GetType(); + all_vars[var->Name()] = var; } auto graph = new SSAGraph(); @@ -167,12 +168,28 @@ std::unique_ptr MultiDevSSAGraphBuilder::Build( auto send_vars = FindDistTrainSendVars(program); auto recv_vars = FindDistTrainRecvVars(program); - size_t cur_device_id = 0; std::vector> var_name_on_devices; std::vector> bcast_var_name_set; var_name_on_devices.resize(places_.size()); bcast_var_name_set.resize(places_.size()); + size_t cur_device_id = 0; + std::vector balance_grads(places_.size(), 0); + + auto get_appropriate_dev = [&](std::string &g_name) -> size_t { + auto var_desc = all_vars.at(g_name); + PADDLE_ENFORCE_NOT_NULL(var_desc); + auto dim = framework::make_ddim(var_desc->GetShape()); + int64_t numel = framework::product(dim); + PADDLE_ENFORCE_GE(numel, 0); + auto smallest = + std::min_element(std::begin(balance_grads), std::end(balance_grads)); + size_t dev_id = + static_cast(std::distance(std::begin(balance_grads), smallest)); + balance_grads[dev_id] += numel; + return dev_id; + }; + bool is_forwarding = true; for (auto *op : program.Block(0).AllOps()) { if (boost::get( @@ -220,13 +237,13 @@ std::unique_ptr MultiDevSSAGraphBuilder::Build( switch (strategy_.reduce_) { case BuildStrategy::ReduceStrategy::kReduce: + cur_device_id = get_appropriate_dev(g_name); CreateReduceOp(&result, g_name, cur_device_id); var_name_on_devices[cur_device_id].emplace(g_name); bcast_var_name_set[cur_device_id].emplace(p_name); - cur_device_id = (cur_device_id + 1) % places_.size(); break; case BuildStrategy::ReduceStrategy::kAllReduce: - if (IsSparseGradient(var_types, g_name)) { + if (IsSparseGradient(all_vars, g_name)) { CreateReduceOp(&result, g_name, 0); CreateBroadcastOp(&result, g_name, 0); } else { @@ -269,10 +286,10 @@ std::unique_ptr MultiDevSSAGraphBuilder::Build( } bool MultiDevSSAGraphBuilder::IsSparseGradient( - const std::unordered_map &var_types, + const std::unordered_map &all_vars, const std::string &og) const { - PADDLE_ENFORCE(var_types.count(og) != 0); - if (var_types.at(og) == proto::VarType::SELECTED_ROWS) { + PADDLE_ENFORCE(all_vars.count(og) != 0); + if (all_vars.at(og)->GetType() == proto::VarType::SELECTED_ROWS) { return true; } return false; diff --git a/paddle/fluid/framework/details/multi_devices_graph_builder.h b/paddle/fluid/framework/details/multi_devices_graph_builder.h index e07597dbd80..544cbe585c7 100644 --- a/paddle/fluid/framework/details/multi_devices_graph_builder.h +++ b/paddle/fluid/framework/details/multi_devices_graph_builder.h @@ -106,7 +106,7 @@ class MultiDevSSAGraphBuilder : public SSAGraphBuilder { size_t src_dev_id) const; bool IsSparseGradient( - const std::unordered_map &var_types, + const std::unordered_map &all_vars, const std::string &og) const; private: -- GitLab From 2a3c58d3fecab43a753bd8c47e327ceae9f0f467 Mon Sep 17 00:00:00 2001 From: fengjiayi Date: Thu, 31 May 2018 16:56:43 +0800 Subject: [PATCH 0058/1416] refine programdesc copy --- paddle/fluid/framework/block_desc.cc | 2 +- paddle/fluid/framework/block_desc.h | 2 +- paddle/fluid/framework/program_desc.cc | 15 +++++++++------ 3 files changed, 11 insertions(+), 8 deletions(-) diff --git a/paddle/fluid/framework/block_desc.cc b/paddle/fluid/framework/block_desc.cc index fd409ed4c0f..b15aba91069 100644 --- a/paddle/fluid/framework/block_desc.cc +++ b/paddle/fluid/framework/block_desc.cc @@ -209,7 +209,7 @@ BlockDesc::BlockDesc(const BlockDesc &other, proto::BlockDesc *desc, : prog_(prog), desc_(desc) { need_update_ = true; for (auto &op : other.ops_) { - ops_.emplace_back(new OpDesc(*op->Proto(), prog, this)); + ops_.emplace_back(new OpDesc(*op, this)); } for (auto &it : other.vars_) { auto *var = new VarDesc(*it.second); diff --git a/paddle/fluid/framework/block_desc.h b/paddle/fluid/framework/block_desc.h index 600601669c5..189dd6c52f8 100644 --- a/paddle/fluid/framework/block_desc.h +++ b/paddle/fluid/framework/block_desc.h @@ -105,7 +105,7 @@ class BlockDesc { size_t OpSize() const { return ops_.size(); } - OpDesc *Op(int idx) { return ops_.at(idx).get(); } + OpDesc *Op(int idx) const { return ops_.at(idx).get(); } void Flush(); diff --git a/paddle/fluid/framework/program_desc.cc b/paddle/fluid/framework/program_desc.cc index 64fb028f83a..aa01f9928cf 100644 --- a/paddle/fluid/framework/program_desc.cc +++ b/paddle/fluid/framework/program_desc.cc @@ -51,12 +51,15 @@ ProgramDesc::ProgramDesc(const ProgramDesc &o) { auto *block = desc_.mutable_blocks(i); blocks_.emplace_back(new BlockDesc(*o.blocks_[i], block, this)); } - for (auto &block : blocks_) { - for (auto *op : block->AllOps()) { - for (const auto &attr : op->Proto()->attrs()) { - if (attr.type() == proto::AttrType::BLOCK) { - size_t blk_idx = attr.block_idx(); - op->SetBlockAttr(attr.name(), this->MutableBlock(blk_idx)); + for (size_t block_id = 0; block_id < blocks_.size(); ++block_id) { + auto all_ops = blocks_[block_id]->AllOps(); + for (size_t op_id = 0; op_id < all_ops.size(); ++op_id) { + auto &op = all_ops[op_id]; + for (const std::string &attr_name : op->AttrNames()) { + if (op->GetAttrType(attr_name) == proto::AttrType::BLOCK) { + int sub_block_id = + o.Block(block_id).Op(op_id)->GetBlockAttr(attr_name); + op->SetBlockAttr(attr_name, MutableBlock(sub_block_id)); } } } -- GitLab From 7c00e164e5886bb430ff945f2de091a2d45ff811 Mon Sep 17 00:00:00 2001 From: yuyang18 Date: Thu, 31 May 2018 17:07:42 +0800 Subject: [PATCH 0059/1416] Add More comments --- .../fluid/layers/layer_function_generator.py | 13 ++++++--- python/paddle/fluid/layers/nn.py | 27 +++++++++++++++++++ 2 files changed, 37 insertions(+), 3 deletions(-) diff --git a/python/paddle/fluid/layers/layer_function_generator.py b/python/paddle/fluid/layers/layer_function_generator.py index 6026237d0b6..fb5e454e94f 100644 --- a/python/paddle/fluid/layers/layer_function_generator.py +++ b/python/paddle/fluid/layers/layer_function_generator.py @@ -230,15 +230,22 @@ def templatedoc(): and AddInput. The ${name} is Python snake style. i.e., xxx_xxx. * ${{name}_type}: The type of ${name}. - Returns: - Decorated funciton. + Decorated function. """ def __impl__(func): op_proto = OpProtoHolder.instance().get_op_proto(func.__name__) tmpl = string.Template(func.__doc__) - args = {"comment": " ".join(op_proto.comment.split())} + + comment_lines = op_proto.comment.split("\n") + comment = "" + for line in comment_lines: + line = line.lstrip() + comment += line + comment += "\n" + + args = {"comment": comment} for each_input in op_proto.inputs: input_name = _convert_(each_input.name) args["{0}_comment".format(input_name)] = each_input.comment diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index acebeaebbb6..970a186fac5 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -799,7 +799,22 @@ def gru_unit(input, return updated_hidden, reset_hidden_pre, gate +@templatedoc() def linear_chain_crf(input, label, param_attr=None): + """ + Linear Chain CRF. + + ${comment} + + Args: + input(${emission_type}): ${emission_comment} + label(${label_type}): ${label_comment} + param_attr(ParamAttr): The attribute of the learnable parameter. + + Returns: + ${log_likelihood_comment} + + """ helper = LayerHelper('linear_chain_crf', **locals()) size = input.shape[1] transition = helper.create_parameter( @@ -825,7 +840,19 @@ def linear_chain_crf(input, label, param_attr=None): return log_likelihood +@templatedoc() def crf_decoding(input, param_attr, label=None): + """ + ${comment} + + Args: + input(${emission_type}): ${emission_comment} + param_attr(ParamAttr): The parameter attribute for training. + label(${label_type}): ${label_comment} + + Returns: + ${viterbi_path_comment} + """ helper = LayerHelper('crf_decoding', **locals()) transition = helper.get_parameter(param_attr.name) viterbi_path = helper.create_tmp_variable(dtype=helper.input_dtype()) -- GitLab From 018d411075d40070b1efbae0f86185a819d35586 Mon Sep 17 00:00:00 2001 From: yuyang18 Date: Thu, 31 May 2018 17:09:26 +0800 Subject: [PATCH 0060/1416] Remove unnecessary func name --- python/paddle/fluid/layers/nn.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index 970a186fac5..5e139a26538 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -4023,8 +4023,6 @@ def upsampling_bilinear2d(input, out_shape=None, scale=None, name=None): @templatedoc() def random_crop(x, shape, seed=None): """ - **Random crop operator** - ${comment} Examples: -- GitLab From e90bfd562b4738ead125a126124bbd8d526cb7a6 Mon Sep 17 00:00:00 2001 From: minqiyang Date: Thu, 31 May 2018 18:07:06 +0800 Subject: [PATCH 0061/1416] 1. Make a base unittest class for dist transpiler unittest 2. Merge the develop repo --- .../tests/unittests/test_dist_transpiler.py | 58 +-------------- .../unittests/test_simple_dist_transpiler.py | 47 +----------- .../fluid/tests/unittests/transpiler_test.py | 73 +++++++++++++++++++ .../fluid/transpiler/distribute_transpiler.py | 15 ++-- 4 files changed, 87 insertions(+), 106 deletions(-) create mode 100644 python/paddle/fluid/tests/unittests/transpiler_test.py diff --git a/python/paddle/fluid/tests/unittests/test_dist_transpiler.py b/python/paddle/fluid/tests/unittests/test_dist_transpiler.py index fa49bd41a58..a24f2aeecda 100644 --- a/python/paddle/fluid/tests/unittests/test_dist_transpiler.py +++ b/python/paddle/fluid/tests/unittests/test_dist_transpiler.py @@ -12,40 +12,15 @@ # See the License for the specific language governing permissions and # limitations under the License. -import unittest - -import paddle.fluid as fluid -import paddle.fluid.core as core -import paddle.fluid.layers as layers from paddle.fluid.transpiler.distribute_transpiler import delete_ops -import numpy + +from transpiler_test import TranspilerTest -class TestDistTranspiler(unittest.TestCase): +class TestDistTranspiler(TranspilerTest): def setUp(self): - self.trainer_id = 0 - self.trainers = 2 - self.pservers = 2 - self.pserver_eps = "127.0.0.1:6174,127.0.0.1:6175" self.current_pserver_ep = "127.0.0.1:6174" - def net_conf(self): - x = fluid.layers.data(name='x', shape=[1000], dtype='float32') - - y_predict = fluid.layers.fc(input=x, - size=1000, - act=None, - param_attr=fluid.ParamAttr(name='fc_w')) - - y = fluid.layers.data(name='y', shape=[1], dtype='float32') - - cost = fluid.layers.square_error_cost(input=y_predict, label=y) - avg_cost = fluid.layers.mean(cost) - sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.1) - - optimize_ops, params_grads = sgd_optimizer.minimize(avg_cost) - return optimize_ops, params_grads - def test_transpiler(self): trainer = self.get_trainer() pserver, startup = self.get_pserver(self.current_pserver_ep) @@ -70,14 +45,6 @@ class TestDistTranspiler(unittest.TestCase): fc_w_var = startup.global_block().var("fc_w.block1") self.assertEqual(fc_w_var.shape, (500, 1000)) - def get_main_program(self): - main = fluid.Program() - - with fluid.program_guard(main): - self.net_conf() - - return main - def get_expect_trainer_ops(self): trainer = fluid.Program() @@ -92,25 +59,6 @@ class TestDistTranspiler(unittest.TestCase): ops.insert(ops.index("elementwise_add_grad") + 1, "send_vars") return ops - def get_trainer(self): - return self._transpiler_instance().get_trainer_program() - - def get_pserver(self, ep): - t = self._transpiler_instance() - pserver = t.get_pserver_program(ep) - startup = t.get_startup_program(ep, pserver) - return pserver, startup - - def _transpiler_instance(self): - main = self.get_main_program() - t = fluid.DistributeTranspiler() - t.transpile( - self.trainer_id, - program=main, - pservers=self.pserver_eps, - trainers=self.trainers) - return t - if __name__ == "__main__": unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_simple_dist_transpiler.py b/python/paddle/fluid/tests/unittests/test_simple_dist_transpiler.py index 60f99f412cd..25d79b51f99 100644 --- a/python/paddle/fluid/tests/unittests/test_simple_dist_transpiler.py +++ b/python/paddle/fluid/tests/unittests/test_simple_dist_transpiler.py @@ -12,40 +12,18 @@ # See the License for the specific language governing permissions and # limitations under the License. -import unittest +import numpy as np import paddle.fluid as fluid -import paddle.fluid.core as core -import paddle.fluid.layers as layers from paddle.fluid.transpiler.distribute_transpiler import delete_ops -import numpy as np +from transpiler_test import TranspilerTest -class TestSimpleDistTranspiler(unittest.TestCase): + +class TestSimpleDistTranspiler(TranspilerTest): def setUp(self): - self.trainer_id = 0 - self.trainers = 2 - self.pservers = 2 - self.pserver_eps = "127.0.0.1:6174,127.0.0.1:6175" self.current_pserver_ep = "127.0.0.1:6175" - def net_conf(self): - x = fluid.layers.data(name='x', shape=[1000], dtype='float32') - - y_predict = fluid.layers.fc(input=x, - size=1000, - act=None, - param_attr=fluid.ParamAttr(name='fc_w')) - - y = fluid.layers.data(name='y', shape=[1], dtype='float32') - - cost = fluid.layers.square_error_cost(input=y_predict, label=y) - avg_cost = fluid.layers.mean(cost) - sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.1) - - optimize_ops, params_grads = sgd_optimizer.minimize(avg_cost) - return optimize_ops, params_grads - def test_simple_transpiler(self): np.random.seed(1) @@ -73,14 +51,6 @@ class TestSimpleDistTranspiler(unittest.TestCase): fc_w_var = startup.global_block().var("fc_w@GRAD.trainer_0") self.assertEqual(fc_w_var.shape, (1000, 1000)) - def get_main_program(self): - main = fluid.Program() - - with fluid.program_guard(main): - self.net_conf() - - return main - def get_expect_trainer_ops(self): trainer = fluid.Program() @@ -94,15 +64,6 @@ class TestSimpleDistTranspiler(unittest.TestCase): ops.insert(ops.index("elementwise_add_grad") + 1, "send_vars") return ops - def get_trainer(self): - return self._transpiler_instance().get_trainer_program() - - def get_pserver(self, ep): - t = self._transpiler_instance() - pserver = t.get_pserver_program(ep) - startup = t.get_startup_program(ep, pserver) - return pserver, startup - def _transpiler_instance(self): main = self.get_main_program() t = fluid.DistributeTranspiler() diff --git a/python/paddle/fluid/tests/unittests/transpiler_test.py b/python/paddle/fluid/tests/unittests/transpiler_test.py new file mode 100644 index 00000000000..d84c5d9c41c --- /dev/null +++ b/python/paddle/fluid/tests/unittests/transpiler_test.py @@ -0,0 +1,73 @@ +# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import unittest +import numpy as np + +import paddle.fluid as fluid +import paddle.fluid.core as core +import paddle.fluid.layers as layers + + +class TranspilerTest(unittest.TestCase): + @classmethod + def setUpClass(self): + self.trainer_id = 0 + self.trainers = 2 + self.pservers = 2 + self.pserver_eps = "127.0.0.1:6174,127.0.0.1:6175" + + def net_conf(self): + x = fluid.layers.data(name='x', shape=[1000], dtype='float32') + + y_predict = fluid.layers.fc(input=x, + size=1000, + act=None, + param_attr=fluid.ParamAttr(name='fc_w')) + + y = fluid.layers.data(name='y', shape=[1], dtype='float32') + + cost = fluid.layers.square_error_cost(input=y_predict, label=y) + avg_cost = fluid.layers.mean(cost) + sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.1) + + optimize_ops, params_grads = sgd_optimizer.minimize(avg_cost) + return optimize_ops, params_grads + + def get_main_program(self): + main = fluid.Program() + + with fluid.program_guard(main): + self.net_conf() + + return main + + def get_trainer(self): + return self._transpiler_instance().get_trainer_program() + + def get_pserver(self, ep): + t = self._transpiler_instance() + pserver = t.get_pserver_program(ep) + startup = t.get_startup_program(ep, pserver) + return pserver, startup + + def _transpiler_instance(self): + main = self.get_main_program() + t = fluid.DistributeTranspiler() + t.transpile( + self.trainer_id, + program=main, + pservers=self.pserver_eps, + trainers=self.trainers) + return t diff --git a/python/paddle/fluid/transpiler/distribute_transpiler.py b/python/paddle/fluid/transpiler/distribute_transpiler.py index 04d47fb82e9..a116671c1b1 100644 --- a/python/paddle/fluid/transpiler/distribute_transpiler.py +++ b/python/paddle/fluid/transpiler/distribute_transpiler.py @@ -178,7 +178,7 @@ class DistributeTranspiler: for index in range(len(self.pserver_endpoints)) ] - def _init_splited_vars(self, split_method): + def _init_splited_vars(self, split_method, align_var_to_block=True): # update these mappings for further transpile: # 1. param_var_mapping: param var name -> [splited params vars] # 2. grad_var_mapping: grad var name -> [splited grads vars] @@ -198,15 +198,14 @@ class DistributeTranspiler: self.params_grads) if align_var_to_block: - grad_blocks = split_dense_variable(grad_list, - len(pserver_endpoints)) - param_blocks = split_dense_variable(param_list, - len(pserver_endpoints)) + grad_blocks = split_variable(grad_list, len(self.pserver_endpoints)) + param_blocks = split_variable(param_list, + len(self.pserver_endpoints)) else: # when we do NOT align var to block, we will always split params # grads into one block. - grad_blocks = split_dense_variable(grad_list, 1) - param_blocks = split_dense_variable(param_list, 1) + grad_blocks = split_variable(grad_list, 1) + param_blocks = split_variable(param_list, 1) assert (len(grad_blocks) == len(param_blocks)) # origin_varname -> [splited_var] self.param_var_mapping = self._create_vars_from_blocklist( @@ -272,7 +271,7 @@ class DistributeTranspiler: self.has_distributed_lookup_table = self._has_distributed_lookup_table() # split and create vars, then put splited vars in dicts for later use. - self._init_splited_vars(split_method) + self._init_splited_vars(split_method, align_var_to_block) # step 3.1: insert send op to send gradient vars to parameter servers ps_dispatcher.reset() -- GitLab From 733718c3e724fdd84355010e76ddd17e5b60ef2c Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Thu, 31 May 2018 19:12:23 +0800 Subject: [PATCH 0062/1416] remove the ugly test --- .../inference/tests/book/test_inference_nlp.cc | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/paddle/fluid/inference/tests/book/test_inference_nlp.cc b/paddle/fluid/inference/tests/book/test_inference_nlp.cc index 990d45964e3..5241661fb31 100644 --- a/paddle/fluid/inference/tests/book/test_inference_nlp.cc +++ b/paddle/fluid/inference/tests/book/test_inference_nlp.cc @@ -53,7 +53,7 @@ size_t read_datasets(std::vector* out, while (getline(iss, field, ' ')) { ids.push_back(stoi(field)); } - if (ids.size() >= 1024 || out->size() >= 100) { + if (ids.size() >= 1024 ) { continue; } @@ -200,14 +200,14 @@ TEST(inference, nlp) { LOG(INFO) << "Total infer time: " << (stop_ms - start_ms) / 1000.0 / 60 << " min, avg time per seq: " << (stop_ms - start_ms) / datasets.size() << " ms"; - { // just for test - auto* scope = new paddle::framework::Scope(); - paddle::framework::LoDTensor outtensor; - TestInference( - dirname, {&(datasets[0])}, {&outtensor}, FLAGS_repeat, model_combined, - false); - delete scope; - } +// { // just for test +// auto* scope = new paddle::framework::Scope(); +// paddle::framework::LoDTensor outtensor; +// TestInference( +// dirname, {&(datasets[0])}, {&outtensor}, FLAGS_repeat, model_combined, +// false); +// delete scope; +// } } delete scope; } -- GitLab From 2007f630b47d52738b3896ec7d6af90c50b129d2 Mon Sep 17 00:00:00 2001 From: Luo Tao Date: Thu, 31 May 2018 19:23:24 +0800 Subject: [PATCH 0063/1416] add build and install document of fluid inference library --- doc/fluid/howto/index_cn.rst | 2 +- doc/fluid/howto/index_en.rst | 1 - .../inference/build_and_install_lib_cn.rst | 96 +++++++++++++++++++ doc/fluid/howto/inference/index_cn.rst | 8 ++ ...id.md => inference_support_in_fluid_cn.md} | 59 +----------- 5 files changed, 106 insertions(+), 60 deletions(-) create mode 100644 doc/fluid/howto/inference/build_and_install_lib_cn.rst create mode 100644 doc/fluid/howto/inference/index_cn.rst rename doc/fluid/howto/inference/{inference_support_in_fluid.md => inference_support_in_fluid_cn.md} (90%) diff --git a/doc/fluid/howto/index_cn.rst b/doc/fluid/howto/index_cn.rst index b7c62017972..b57af64f44d 100644 --- a/doc/fluid/howto/index_cn.rst +++ b/doc/fluid/howto/index_cn.rst @@ -4,5 +4,5 @@ .. toctree:: :maxdepth: 1 + inference/index_cn.rst optimization/index_cn.rst - inference/inference_support_in_fluid.md diff --git a/doc/fluid/howto/index_en.rst b/doc/fluid/howto/index_en.rst index f3ca41cdbf1..fd21e167ce3 100644 --- a/doc/fluid/howto/index_en.rst +++ b/doc/fluid/howto/index_en.rst @@ -5,4 +5,3 @@ HOW TO :maxdepth: 1 optimization/index_en.rst - inference/inference_support_in_fluid.md diff --git a/doc/fluid/howto/inference/build_and_install_lib_cn.rst b/doc/fluid/howto/inference/build_and_install_lib_cn.rst new file mode 100644 index 00000000000..c8d9992fcc9 --- /dev/null +++ b/doc/fluid/howto/inference/build_and_install_lib_cn.rst @@ -0,0 +1,96 @@ +安装与编译C++预测库 +=========================== + +直接下载安装 +------------- + +====================== ======================================== +版本说明 C++预测库 +====================== ======================================== +cpu_avx_mkl `fluid.tgz `_ +cpu_avx_openblas `fluid.tgz `_ +cpu_noavx_openblas `fluid.tgz `_ +cuda7.5_cudnn5_avx_mkl `fluid.tgz `_ +cuda8.0_cudnn5_avx_mkl `fluid.tgz `_ +cuda8.0_cudnn7_avx_mkl `fluid.tgz `_ +====================== ======================================== + +从源码编译 +---------- +用户也可以从 PaddlePaddle 核心代码编译C++预测库，只需在编译时配制下面这些编译选项： + +================= ========= +选项 值 +================= ========= +CMAKE_BUILD_TYPE Release +FLUID_INSTALL_DIR 安装路径 +WITH_FLUID_ONLY ON（推荐） +WITH_SWIG_PY OFF（推荐 +WITH_PYTHON OFF（推荐） +WITH_GPU ON/OFF +WITH_MKL ON/OFF +================= ========= + +建议按照推荐值设置，以避免链接不必要的库。其它可选编译选项按需进行设定。 + +下面的代码片段从github拉取最新代码，配制编译选项（需要将PADDLE_ROOT替换为PaddlePaddle预测库的安装路径）： + + .. code-block:: bash + + pip install paddlepaddle-gpu + PADDLE_ROOT=/path/of/capi + git clone https://github.com/PaddlePaddle/Paddle.git + cd Paddle + mkdir build + cd build + cmake -DFLUID_INSTALL_DIR=$PADDLE_ROOT \ + -DCMAKE_BUILD_TYPE=Release \ + -DWITH_FLUID_ONLY=ON \ + -DWITH_SWIG_PY=OFF \ + -DWITH_PYTHON=OFF \ + -DWITH_MKL=OFF \ + -DWITH_GPU=OFF \ + .. + make + make inference_lib_dist + +成功编译后，使用C++预测库所需的依赖（包括：（1）编译出的PaddlePaddle预测库和头文件；（2）第三方链接库和头文件；（3）版本信息与编译选项信息） +均会存放于PADDLE_ROOT目录中。目录结构如下： + + .. code-block:: text + + PaddleRoot/ + ├── CMakeCache.txt + ├── paddle + │   └── fluid + │   ├── framework + │   ├── inference + │   ├── memory + │   ├── platform + │   ├── pybind + │   └── string + ├── third_party + │   ├── boost + │   │   └── boost + │   ├── eigen3 + │   │   ├── Eigen + │   │   └── unsupported + │   └── install + │   ├── gflags + │   ├── glog + │   ├── mklml + │   ├── protobuf + │   ├── snappy + │   ├── snappystream + │   └── zlib + └── version.txt + +version.txt 中记录了该预测库的版本信息，包括Git Commit ID、使用OpenBlas或MKL数学库、CUDA/CUDNN版本号，如： + + .. code-block:: text + + GIT COMMIT ID: c95cd4742f02bb009e651a00b07b21c979637dc8 + WITH_MKL: ON + WITH_GPU: ON + CUDA version: 8.0 + CUDNN version: v5 diff --git a/doc/fluid/howto/inference/index_cn.rst b/doc/fluid/howto/inference/index_cn.rst new file mode 100644 index 00000000000..a903423548d --- /dev/null +++ b/doc/fluid/howto/inference/index_cn.rst @@ -0,0 +1,8 @@ +预测库 +------------ + +.. toctree:: + :maxdepth: 1 + + build_and_install_lib_cn.rst + inference_support_in_fluid_cn.md diff --git a/doc/fluid/howto/inference/inference_support_in_fluid.md b/doc/fluid/howto/inference/inference_support_in_fluid_cn.md similarity index 90% rename from doc/fluid/howto/inference/inference_support_in_fluid.md rename to doc/fluid/howto/inference/inference_support_in_fluid_cn.md index d272cd3e3bd..309b17fccd5 100644 --- a/doc/fluid/howto/inference/inference_support_in_fluid.md +++ b/doc/fluid/howto/inference/inference_support_in_fluid_cn.md @@ -1,9 +1,8 @@ -# Fluid Inference使用指南 +# 使用指南 ## 目录： - Python Inference API -- 编译Fluid Inference库 - Inference C++ API - Inference实例 - Inference计算优化 @@ -55,62 +54,6 @@ return [program, feed_target_names, fetch_targets] ``` - -## 编译Fluid Inference库 - - - **不需要额外的CMake选项** - - 1、 配置CMake命令，更多配置请参考[源码编译PaddlePaddle](http://www.paddlepaddle.org/docs/develop/documentation/zh/build_and_install/build_from_source_cn.html) - ```bash - $ git clone https://github.com/PaddlePaddle/Paddle.git - $ cd Paddle - $ mkdir build - $ cd build - $ cmake -DCMAKE_INSTALL_PREFIX=your/path/to/paddle_inference_lib \ - -DCMAKE_BUILD_TYPE=Release \ - -DWITH_PYTHON=ON \ - -DWITH_MKL=OFF \ - -DWITH_GPU=OFF \ - .. - ``` - - - 2、 编译PaddlePaddle - ```bash - $ make - ``` - - - 3、 部署。执行如下命令将PaddlePaddle Fluid Inference库部署到`your/path/to/paddle_inference_lib`目录。 - ```bash - $ make inference_lib_dist - ``` - -- 目录结构 - - ```bash - $ cd your/path/to/paddle_inference_lib - $ tree - . - |-- paddle - | `-- fluid - | |-- framework - | |-- inference - | | |-- io.h - | | `-- libpaddle_fluid.so - | |-- memory - | |-- platform - | `-- string - |-- third_party - | |-- eigen3 - | `-- install - | |-- gflags - | |-- glog - | `-- protobuf - `-- ... - ``` - - 假设`PADDLE_ROOT=your/path/to/paddle_inference_lib`。 - - - ## 链接Fluid Inference库 - 示例项目([链接](https://github.com/luotao1/fluid_inference_example.git)) -- GitLab From 9d92dcea0a41093ad782561a0ade4095afbefcfa Mon Sep 17 00:00:00 2001 From: minqiyang Date: Thu, 31 May 2018 20:34:23 +0800 Subject: [PATCH 0064/1416] 1. import fluid to dist transpiler test --- python/paddle/fluid/tests/unittests/test_dist_transpiler.py | 1 + 1 file changed, 1 insertion(+) diff --git a/python/paddle/fluid/tests/unittests/test_dist_transpiler.py b/python/paddle/fluid/tests/unittests/test_dist_transpiler.py index a24f2aeecda..32647f9aa81 100644 --- a/python/paddle/fluid/tests/unittests/test_dist_transpiler.py +++ b/python/paddle/fluid/tests/unittests/test_dist_transpiler.py @@ -12,6 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. +import paddle.fluid as fluid from paddle.fluid.transpiler.distribute_transpiler import delete_ops from transpiler_test import TranspilerTest -- GitLab From a3aca2a3cfeb6ab246ff95987374809be1a3c863 Mon Sep 17 00:00:00 2001 From: fengjiayi Date: Thu, 31 May 2018 20:58:26 +0800 Subject: [PATCH 0065/1416] fix bugs --- paddle/fluid/framework/block_desc.cc | 2 +- paddle/fluid/framework/op_desc.cc | 2 +- paddle/fluid/framework/op_desc.h | 3 ++- paddle/fluid/framework/program_desc.cc | 10 ++++++++++ 4 files changed, 14 insertions(+), 3 deletions(-) diff --git a/paddle/fluid/framework/block_desc.cc b/paddle/fluid/framework/block_desc.cc index b15aba91069..e7842e9b813 100644 --- a/paddle/fluid/framework/block_desc.cc +++ b/paddle/fluid/framework/block_desc.cc @@ -200,7 +200,7 @@ BlockDesc::BlockDesc(ProgramDesc *prog, proto::BlockDesc *desc) vars_[var_desc.name()].reset(new VarDesc(var_desc)); } for (const proto::OpDesc &op_desc : desc_->ops()) { - ops_.emplace_back(new OpDesc(op_desc, prog, this)); + ops_.emplace_back(new OpDesc(op_desc, this)); } } diff --git a/paddle/fluid/framework/op_desc.cc b/paddle/fluid/framework/op_desc.cc index 09b67e5a174..f92769192c2 100644 --- a/paddle/fluid/framework/op_desc.cc +++ b/paddle/fluid/framework/op_desc.cc @@ -103,7 +103,7 @@ void OpDesc::CopyFrom(const OpDesc &op_desc) { need_update_ = true; } -OpDesc::OpDesc(const proto::OpDesc &desc, ProgramDesc *prog, BlockDesc *block) +OpDesc::OpDesc(const proto::OpDesc &desc, BlockDesc *block) : desc_(desc), need_update_(false) { // restore inputs_ int input_size = desc_.inputs_size(); diff --git a/paddle/fluid/framework/op_desc.h b/paddle/fluid/framework/op_desc.h index 1a330db7cc5..a02d3e26912 100644 --- a/paddle/fluid/framework/op_desc.h +++ b/paddle/fluid/framework/op_desc.h @@ -33,13 +33,14 @@ class OpDesc { OpDesc(const std::string &type, const VariableNameMap &inputs, const VariableNameMap &outputs, const AttributeMap &attrs); - OpDesc(const proto::OpDesc &desc, ProgramDesc *prog, BlockDesc *block); + OpDesc(const proto::OpDesc &desc, BlockDesc *block); explicit OpDesc(BlockDesc *block) : block_(block) {} OpDesc(const OpDesc &other, BlockDesc *block) { *this = other; block_ = block; + need_update_ = true; } void CopyFrom(const OpDesc &op_desc); diff --git a/paddle/fluid/framework/program_desc.cc b/paddle/fluid/framework/program_desc.cc index aa01f9928cf..1e01a6e9004 100644 --- a/paddle/fluid/framework/program_desc.cc +++ b/paddle/fluid/framework/program_desc.cc @@ -89,6 +89,16 @@ ProgramDesc::ProgramDesc(const std::string &binary_str) { for (auto &block_desc : *desc_.mutable_blocks()) { blocks_.emplace_back(new BlockDesc(this, &block_desc)); } + for (auto &block : blocks_) { + for (auto *op : block->AllOps()) { + for (const auto &attr : op->Proto()->attrs()) { + if (attr.type() == proto::AttrType::BLOCK) { + size_t blk_idx = attr.block_idx(); + op->SetBlockAttr(attr.name(), this->MutableBlock(blk_idx)); + } + } + } + } } const std::vector ProgramDesc::GetFeedTargetNames() { -- GitLab From 04ccbed5b8539bd3fb97df5169ff9103edac3d60 Mon Sep 17 00:00:00 2001 From: fengjiayi Date: Fri, 1 Jun 2018 10:04:59 +0800 Subject: [PATCH 0066/1416] fix a compile error --- paddle/fluid/inference/tensorrt/convert/ut_helper.h | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/paddle/fluid/inference/tensorrt/convert/ut_helper.h b/paddle/fluid/inference/tensorrt/convert/ut_helper.h index 37fcb5c5030..dd481fa234e 100644 --- a/paddle/fluid/inference/tensorrt/convert/ut_helper.h +++ b/paddle/fluid/inference/tensorrt/convert/ut_helper.h @@ -101,7 +101,7 @@ class TRTConvertValidation { engine_->FreezeNetwork(); // Declare outputs. - op_desc_.reset(new framework::OpDesc(desc, nullptr, nullptr)); + op_desc_.reset(new framework::OpDesc(desc, nullptr)); // Set Inputs. for (const auto& input : op_desc_->InputArgumentNames()) { -- GitLab From 7973d9b4b5b3ef032c13410401b8c368220cd21d Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Fri, 1 Jun 2018 10:09:31 +0800 Subject: [PATCH 0067/1416] bug fix --- python/paddle/fluid/trainer.py | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py index 3354d77acec..72168886fdb 100644 --- a/python/paddle/fluid/trainer.py +++ b/python/paddle/fluid/trainer.py @@ -178,10 +178,11 @@ class Trainer(object): exe.run(self.startup_program) if self.checkpoint and self.checkpoint.load_serial: - exe = executor.Executor(place) - io.load_checkpoint(exe, self.checkpoint.checkpoint_dir, - self.checkpoint.load_serial, - self.startup_program) + with self._prog_and_scope_guard(): + exe = executor.Executor(place) + io.load_checkpoint(exe, self.checkpoint.checkpoint_dir, + self.checkpoint.load_serial, + self.startup_program) if not self.checkpoint.is_pserver: epoch_id, step_id = io.load_trainer_args( -- GitLab From 31f0533c5ddce9d3db8dbabb8a581f3694f0a7e1 Mon Sep 17 00:00:00 2001 From: fengjiayi Date: Fri, 1 Jun 2018 10:54:19 +0800 Subject: [PATCH 0068/1416] fix compile errors --- paddle/fluid/inference/tensorrt/convert/activation_op.cc | 2 +- paddle/fluid/inference/tensorrt/convert/mul_op.cc | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/paddle/fluid/inference/tensorrt/convert/activation_op.cc b/paddle/fluid/inference/tensorrt/convert/activation_op.cc index 6297051e5a3..79d01b640a2 100644 --- a/paddle/fluid/inference/tensorrt/convert/activation_op.cc +++ b/paddle/fluid/inference/tensorrt/convert/activation_op.cc @@ -24,7 +24,7 @@ class ReluOpConverter : public OpConverter { void operator()(const framework::proto::OpDesc& op) override { // Here the two nullptr looks strange, that's because the // framework::OpDesc's constructor is strange. - framework::OpDesc op_desc(op, nullptr, nullptr); + framework::OpDesc op_desc(op, nullptr); LOG(INFO) << "convert a fluid relu op to tensorrt activation layer whose " "type is Relu"; const nvinfer1::ITensor* input_tensor = diff --git a/paddle/fluid/inference/tensorrt/convert/mul_op.cc b/paddle/fluid/inference/tensorrt/convert/mul_op.cc index ed09f54bde0..aa8e66490f7 100644 --- a/paddle/fluid/inference/tensorrt/convert/mul_op.cc +++ b/paddle/fluid/inference/tensorrt/convert/mul_op.cc @@ -27,7 +27,7 @@ class MulOpConverter : public OpConverter { void operator()(const framework::proto::OpDesc& op) override { VLOG(4) << "convert a fluid mul op to tensorrt fc layer without bias"; - framework::OpDesc op_desc(op, nullptr, nullptr); + framework::OpDesc op_desc(op, nullptr); // Declare inputs auto* input1 = engine_->GetITensor(op_desc.Input("X")[0]); auto* input2 = engine_->GetITensor(op_desc.Input("Y")[0]); -- GitLab From f9556dca51484c270284c181337fc041964f2db0 Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Fri, 1 Jun 2018 10:59:42 +0800 Subject: [PATCH 0069/1416] use open_files reader to read multiple files --- .../howto/cluster/fluid_recordio.md} | 26 ++++++++++-------- .../reader/create_recordio_file_reader_op.cc | 12 ++++---- python/paddle/fluid/layers/io.py | 20 ++++++-------- python/paddle/fluid/recordio_writer.py | 12 ++++++-- tools/codestyle/docstring_checker.pyc | Bin 0 -> 11769 bytes 5 files changed, 37 insertions(+), 33 deletions(-) rename doc/{v2/howto/recordio/README.md => fluid/howto/cluster/fluid_recordio.md} (88%) create mode 100644 tools/codestyle/docstring_checker.pyc diff --git a/doc/v2/howto/recordio/README.md b/doc/fluid/howto/cluster/fluid_recordio.md similarity index 88% rename from doc/v2/howto/recordio/README.md rename to doc/fluid/howto/cluster/fluid_recordio.md index 3f81d54b8e1..0e8b98542d1 100644 --- a/doc/v2/howto/recordio/README.md +++ b/doc/fluid/howto/cluster/fluid_recordio.md @@ -89,14 +89,14 @@ The above codes would generate multiple RecordIO files on your host like: ```bash . - \_mnist.recordio-00000 - |-mnist.recordio-00001 - |-mnist.recordio-00002 - |-mnist.recordio-00003 - |-mnist.recordio-00004 + \_mnist-00000.recordio + |-mnist-00001.recordio + |-mnist-00002.recordio + |-mnist-00003.recordio + |-mnist-00004.recordio ``` -1. read these RecordIO files with `fluid.layers.io.open_recordio_file` +1. open multiple RecordIO files by `fluid.layers.io.open_files` For a distributed training job, the distributed operator system will schedule trainer process on multiple nodes, each trainer process reads parts of the whole training data, we usually take the following approach to make the training @@ -113,10 +113,12 @@ def gen_train_list(file_pattern, trainers, trainer_id): trainers = int(os.getenv("TRAINERS")) trainer_id = int(os.getenv("PADDLE_INIT_TRAINER_ID")) -data_file = fluid.layers.io.open_recordio_file( - filename=gen_train_list("./mnist.recordio*", trainers, trainer_id), - shapes=[(-1, 784),(-1, 1)], - lod_levels=[0, 0], - dtypes=["float32", "int32"]) -data_file = fluid.layers.io.batch(data_file, batch_size=4) +data_file = fluid.layers.io.open_files( + filenames=gen_train_list("./mnist-[0-9]*.recordio", 2, 0), + thread_num=1, + shapes=[(-1, 784),(-1, 1)], + lod_levels=[0, 0], + dtypes=["float32", "int32"]) +img, label = fluid.layers.io.read_file(data_files) +... ``` diff --git a/paddle/fluid/operators/reader/create_recordio_file_reader_op.cc b/paddle/fluid/operators/reader/create_recordio_file_reader_op.cc index 6b6d4470268..282ec3f36b9 100644 --- a/paddle/fluid/operators/reader/create_recordio_file_reader_op.cc +++ b/paddle/fluid/operators/reader/create_recordio_file_reader_op.cc @@ -65,22 +65,20 @@ class CreateRecordIOReaderOp : public framework::OperatorBase { static_cast(shape_concat.size()), "The accumulate of all ranks should be equal to the " "shape concat's length."); - auto filenames = Attr>("filenames"); + std::string filename = Attr("filename"); auto* out = scope.FindVar(Output("Out")) ->template GetMutable(); - for (auto& fn : filenames) { - out->Reset( - new RecordIOFileReader(fn, RestoreShapes(shape_concat, ranks))); - } + + out->Reset(new RecordIOFileReader( + filename, RestoreShapes(shape_concat, ranks))); } }; class CreateRecordIOReaderOpMaker : public FileReaderMakerBase { protected: void Apply() override { - AddAttr>("filenames", - "The filenames of record io reader"); + AddAttr("filename", "The filename of record io reader"); AddComment(R"DOC( CreateRecordIOReader Operator diff --git a/python/paddle/fluid/layers/io.py b/python/paddle/fluid/layers/io.py index b9d55827304..8758ac9f94a 100644 --- a/python/paddle/fluid/layers/io.py +++ b/python/paddle/fluid/layers/io.py @@ -21,7 +21,7 @@ from ..layer_helper import LayerHelper from ..executor import global_scope __all__ = [ - 'data', 'BlockGuardServ', 'ListenAndServ', 'Send', 'open_recordio_files', + 'data', 'BlockGuardServ', 'ListenAndServ', 'Send', 'open_recordio_file', 'open_files', 'read_file', 'shuffle', 'batch', 'double_buffer', 'random_data_generator', 'Preprocessor' ] @@ -291,12 +291,12 @@ def _copy_reader_create_op_(block, op): return new_op -def open_recordio_files(filenames, - shapes, - lod_levels, - dtypes, - pass_num=1, - for_parallel=True): +def open_recordio_file(filename, + shapes, + lod_levels, + dtypes, + pass_num=1, + for_parallel=True): """ Open a RecordIO file @@ -304,7 +304,7 @@ def open_recordio_files(filenames, Via the Reader Variable, we can get data from the given RecordIO file. Args: - filename(str) or list(str): The RecordIO file's name. + filename(str): The RecordIO file's name. shapes(list): List of tuples which declaring data shapes. lod_levels(list): List of ints which declaring data lod_level. dtypes(list): List of strs which declaring data type. @@ -336,8 +336,6 @@ def open_recordio_files(filenames, ranks.append(len(shape)) var_name = unique_name('open_recordio_file') - if isinstance(filenames, str): - filenames = [filenames] startup_blk = default_startup_program().current_block() startup_var = startup_blk.create_var(name=var_name) @@ -347,7 +345,7 @@ def open_recordio_files(filenames, attrs={ 'shape_concat': shape_concat, 'lod_levels': lod_levels, - 'filenames': filenames, + 'filename': filename, 'ranks': ranks }) diff --git a/python/paddle/fluid/recordio_writer.py b/python/paddle/fluid/recordio_writer.py index 9557f91bb36..8d48e9abef0 100644 --- a/python/paddle/fluid/recordio_writer.py +++ b/python/paddle/fluid/recordio_writer.py @@ -12,9 +12,12 @@ # See the License for the specific language governing permissions and # limitations under the License. +import os import core import contextlib -__all__ = ['convert_reader_to_recordio_file'] +__all__ = [ + 'convert_reader_to_recordio_file', 'convert_reader_to_recordio_files' +] @contextlib.contextmanager @@ -48,7 +51,7 @@ def convert_reader_to_recordio_file( def convert_reader_to_recordio_files( - filename_suffix, + filename, batch_per_file, reader_creator, feeder, @@ -57,13 +60,16 @@ def convert_reader_to_recordio_files( feed_order=None): if feed_order is None: feed_order = feeder.feed_names + f_name, f_ext = os.path.splitext(filename) + assert (f_ext == ".recordio") + lines = [] f_idx = 0 counter = 0 for idx, batch in enumerate(reader_creator()): lines.append(batch) if idx >= batch_per_file and idx % batch_per_file == 0: - filename = "%s-%05d" % (filename_suffix, f_idx) + filename = "%s-%05d%s" % (f_name, f_idx, f_ext) with create_recordio_writer(filename, compressor, max_num_records) as writer: for l in lines: diff --git a/tools/codestyle/docstring_checker.pyc b/tools/codestyle/docstring_checker.pyc new file mode 100644 index 0000000000000000000000000000000000000000..07e875aec6c9bae8002bde4223348c6a29647b03 GIT binary patch literal 11769 zcmdT~%X1XR8SmL$t+b1Tc#4Oy8S`8MD~X3+M8*~fV-j0Xvp5to)Ogt$Nh8hftfpse z$%aa$aOH8#E%^^pm8zUlxutT5Z$2h}Kyu6}hg439EBXDto}FEU>_FK9N7A&qzkYxH zy}R@O7%8{*jJ)4a=}#X2-^8bXiNsTC4ymQQoC+;9hm6VR)Lc&Tc@^eWv!Lb*syU$M z29(7X1r-)mb5P9aQHDS=gNEPIiB>FmX6Ypt^I?AVCV)AExb6bRfzlxi+FjUwP(V;15<<$#sa49H;yjXU1$HB> zYi%z^p{MO+(YM?6nACwirPN^iq2Kgdi5@T8_{k2COO^wC9+^Z=59fvhbaQf^c~Yt6 zDI6oud$v+Q>g3s&xey4&frB`Nlp3L5kIfmeR{P=n(>Nj54O&6sx`#O@Csx*|m2HuW zy~LVnBnw?K1!Ye43c3D5zQ0gVQ-Snx&LT1<^o9aj663o6c8+@k^I)xLd8m`E0HnMHeBxuCCTbCY#g2yg^6*DBOB z`Y%XCQrW;d)Ro^zf~ckK`8aA)c8RDWk=8nmMZ2zTa@;99y6H4(`fiw&v(Lb ztv7&>b%eQMEs9uJLX+WSiOyCcf@-EalS93yMUu$&&O6%)pvLL$^Snd!8NMPxI{R3p znm3}RS0vMm2uMU}w8J2Q;)JB)0*H*Zvy)BsA~8*pdYtHwf@IMMEK0F@yY08Uge!F+ zyj<40$y(bNaYkfRWVvJ(P&K4S)G#dEH&s3HMNx#3Hk>iE+iZU3CgpHmK}M6I)lfM% z41OK~NAIwTxlt&JhkkS0ti6C2tpmAoPlaT%kjW7^Ehi5ZDbEI&2bF4i37 zRcutwZA@+ql*e8s%!ZT-pQsdM)$w=3f(Z=dKE&j+MsBRV*M;c~)2L}Ydi z3$C#!?7I+0owh^6U9`DT*i`1mqAu$m_t!cf|~IT}UC*^@IV^) zqyiL+%13cf?SaEN56UX3m%XyUwg3iK6tEG%whC+%ux$d{4%iNX?F4L>z;**RCa^t# z?G@NQ!1fF5IlvAG?0LXm5ZFP$Y=OO~UZx*BE>7?v@nnXTcUUrTfR9K9KJQV)B8C)K)XpE}S|rAagZSLt?FqgJ&Y>44@+J*>`0akHLOp&L8mV;x@C zblG2nE9yPcj;w{rs%Exo*DEHu_rRjpwGG&{mTyygbAesA4le%%`?P?y*a%pfUlkpH z8eQNId-g|*e#@@gdNGQV{=Ps1x;Np|2k>6Z7{d5BUz?mft;rxWy_vko*RYck8@7N= z6Tm(+e#mb7aS(ZCW>i#Jq1Vscx86rbsi$LPGoR6~Vdm*Dw1H4)1G+aX~!^XEg%eX;q}v#*(5KCfdYi5ZHy~q z`*9q_rx@(9&)E{put9EEEgdCI=~gxQs)HmF`9L5u`=ixHEu&iF9d|ZzH49SN9M2b7#X^9_% zc$<+=+I}kqWqwLZBPPI?xjEC1I6dOmR8lWzoF(`^z@IHsk(vqXc`GRqZ0zpz92{F5 z8n7k^?X7yK`$h;Ty=EmwB@sLkYNCtHnniIZ5hWD(kd5i>nW97G=-5oCDn(gKOcLBm z&qE{5!=VydVd90PR4JCQ0SF=V*(+3|+@lQJ)AF05;1inDj~wF90o1#YsG*VEm{rJ? 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(#11041) * Make bilinear_interp_op support attrs from input. * Fix python api. --- paddle/fluid/operators/bilinear_interp_op.cc | 23 ++++++++++++ paddle/fluid/operators/bilinear_interp_op.cu | 25 ++++++++++++- paddle/fluid/operators/bilinear_interp_op.h | 22 +++++++++-- python/paddle/fluid/layers/nn.py | 19 +++++++--- .../unittests/test_bilinear_interp_op.py | 37 +++++++++++++++++-- 5 files changed, 111 insertions(+), 15 deletions(-) diff --git a/paddle/fluid/operators/bilinear_interp_op.cc b/paddle/fluid/operators/bilinear_interp_op.cc index d46fda54e7a..3321adf2743 100644 --- a/paddle/fluid/operators/bilinear_interp_op.cc +++ b/paddle/fluid/operators/bilinear_interp_op.cc @@ -34,9 +34,22 @@ class BilinearInterpOp : public framework::OperatorWithKernel { int out_w = ctx->Attrs().Get("out_w"); PADDLE_ENFORCE_EQ(dim_x.size(), 4, "X's dimension must be 4"); + if (ctx->HasInput("OutSize")) { + auto out_size_dim = ctx->GetInputDim("OutSize"); + PADDLE_ENFORCE_EQ(out_size_dim.size(), 1, + "OutSize's dimension size must be 1"); + PADDLE_ENFORCE_EQ(out_size_dim[0], 2, "OutSize's dim[0] must be 2"); + } std::vector dim_out({dim_x[0], dim_x[1], out_h, out_w}); ctx->SetOutputDim("Out", framework::make_ddim(dim_out)); } + + protected: + framework::OpKernelType GetExpectedKernelType( + const framework::ExecutionContext& ctx) const override { + return framework::OpKernelType( + framework::ToDataType(ctx.Input("X")->type()), ctx.GetPlace()); + } }; class BilinearInterpOpMaker : public framework::OpProtoAndCheckerMaker { @@ -45,6 +58,10 @@ class BilinearInterpOpMaker : public framework::OpProtoAndCheckerMaker { AddInput("X", "(Tensor) The input tensor of bilinear interpolation, " "This is a 4-D tensor with shape of (N x C x h x w)"); + AddInput("OutSize", + "(Tensor) This is a 1-D tensor with two number. " + "The first number is height and the second number is width.") + .AsDispensable(); AddOutput("Out", "(Tensor) The dimension of output is (N x C x out_h x out_w]"); @@ -78,6 +95,12 @@ class BilinearInterpOpGrad : public framework::OperatorWithKernel { ctx->SetOutputDim(framework::GradVarName("X"), dim_x); } } + + framework::OpKernelType GetExpectedKernelType( + const framework::ExecutionContext& ctx) const override { + return framework::OpKernelType( + framework::ToDataType(ctx.Input("X")->type()), ctx.GetPlace()); + } }; } // namespace operators diff --git a/paddle/fluid/operators/bilinear_interp_op.cu b/paddle/fluid/operators/bilinear_interp_op.cu index 510190f1aaf..4c197153849 100644 --- a/paddle/fluid/operators/bilinear_interp_op.cu +++ b/paddle/fluid/operators/bilinear_interp_op.cu @@ -102,10 +102,21 @@ class BilinearInterpOpCUDAKernel : public framework::OpKernel { auto* input_t = ctx.Input("X"); // float tensor auto* output_t = ctx.Output("Out"); // float tensor auto* input = input_t->data(); - auto* output = output_t->mutable_data(ctx.GetPlace()); int out_h = ctx.Attr("out_h"); int out_w = ctx.Attr("out_w"); + auto out_dims = output_t->dims(); + auto out_size_t = ctx.Input("OutSize"); + if (out_size_t != nullptr) { + Tensor sizes; + framework::TensorCopy(*out_size_t, platform::CPUPlace(), &sizes); + auto size_data = sizes.data(); + out_h = size_data[0]; + out_w = size_data[1]; + } + auto* output = output_t->mutable_data( + {out_dims[0], out_dims[1], out_h, out_w}, ctx.GetPlace()); + int batch_size = input_t->dims()[0]; int channels = input_t->dims()[1]; int in_h = input_t->dims()[2]; @@ -139,8 +150,8 @@ class BilinearInterpGradOpCUDAKernel : public framework::OpKernel { void Compute(const framework::ExecutionContext& ctx) const override { auto* d_input_t = ctx.Output(framework::GradVarName("X")); auto* d_output_t = ctx.Input(framework::GradVarName("Out")); - auto* d_input = d_input_t->mutable_data(ctx.GetPlace()); auto* d_output = d_output_t->data(); + auto* d_input = d_input_t->mutable_data(ctx.GetPlace()); auto& device_ctx = ctx.template device_context(); @@ -149,6 +160,16 @@ class BilinearInterpGradOpCUDAKernel : public framework::OpKernel { int out_h = ctx.Attr("out_h"); int out_w = ctx.Attr("out_w"); + + auto out_size_t = ctx.Input("OutSize"); + if (out_size_t != nullptr) { + Tensor sizes; + framework::TensorCopy(*out_size_t, platform::CPUPlace(), &sizes); + auto size_data = sizes.data(); + out_h = size_data[0]; + out_w = size_data[1]; + } + int batch_size = d_input_t->dims()[0]; int channels = d_input_t->dims()[1]; int in_h = d_input_t->dims()[2]; diff --git a/paddle/fluid/operators/bilinear_interp_op.h b/paddle/fluid/operators/bilinear_interp_op.h index f6cd77e4d49..8b03cd5a063 100644 --- a/paddle/fluid/operators/bilinear_interp_op.h +++ b/paddle/fluid/operators/bilinear_interp_op.h @@ -24,11 +24,18 @@ class BilinearInterpKernel : public framework::OpKernel { void Compute(const framework::ExecutionContext& ctx) const override { auto* input_t = ctx.Input("X"); // float tensor auto* output_t = ctx.Output("Out"); // float tensor + auto out_dims = output_t->dims(); auto* input = input_t->data(); - auto* output = output_t->mutable_data(ctx.GetPlace()); - int out_h = ctx.Attr("out_h"); int out_w = ctx.Attr("out_w"); + auto out_size_t = ctx.Input("OutSize"); + if (out_size_t != nullptr) { + auto out_size_data = out_size_t->data(); + out_h = out_size_data[0]; + out_w = out_size_data[1]; + } + auto* output = output_t->mutable_data( + {out_dims[0], out_dims[1], out_h, out_w}, ctx.GetPlace()); int batch_size = input_t->dims()[0]; int channels = input_t->dims()[1]; int in_h = input_t->dims()[2]; @@ -83,9 +90,8 @@ class BilinearInterpGradKernel : public framework::OpKernel { void Compute(const framework::ExecutionContext& ctx) const override { auto* d_input_t = ctx.Output(framework::GradVarName("X")); auto* d_output_t = ctx.Input(framework::GradVarName("Out")); - auto* d_input = d_input_t->mutable_data(ctx.GetPlace()); auto* d_output = d_output_t->data(); - + auto* d_input = d_input_t->mutable_data(ctx.GetPlace()); auto& device_ctx = ctx.template device_context(); math::SetConstant zero; @@ -93,6 +99,14 @@ class BilinearInterpGradKernel : public framework::OpKernel { int out_h = ctx.Attr("out_h"); int out_w = ctx.Attr("out_w"); + + auto out_size_t = ctx.Input("OutSize"); + if (out_size_t != nullptr) { + auto out_size_data = out_size_t->data(); + out_h = out_size_data[0]; + out_w = out_size_data[1]; + } + int batch_size = d_input_t->dims()[0]; int channels = d_input_t->dims()[1]; int in_h = d_input_t->dims()[2]; diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index 63ec8315147..cb87653c477 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -3944,7 +3944,7 @@ def upsampling_bilinear2d(input, out_shape=None, scale=None, name=None): input (Variable): The input tensor of bilinear interpolation, This is a 4-D tensor of the shape (num_batches, channels, in_h, in_w). - out_shape(list|tuple|None): Output shape of bilinear interpolation + out_shape(list|tuple|Variable|None): Output shape of bilinear interpolation layer, the shape is (out_h, out_w). Default: None scale(int|None): The multiplier for the input height or width. @@ -3971,13 +3971,20 @@ def upsampling_bilinear2d(input, out_shape=None, scale=None, name=None): def _is_list_or_turple_(data): return (isinstance(data, list) or isinstance(data, tuple)) + out_h = 0 + out_w = 0 + inputs = {"X": input} if out_shape is not None: - if not (_is_list_or_turple_(out_shape) and len(out_shape) == 2): + if not (_is_list_or_turple_(out_shape) and len(out_shape) == 2) and ( + out_shape is not Variable): raise ValueError('out_shape should be a list or tuple ', 'with length 2, (out_h, out_w).') - out_shape = list(map(int, out_shape)) - out_h = out_shape[0] - out_w = out_shape[1] + if _is_list_or_turple_(out_shape): + out_shape = list(map(int, out_shape)) + out_h = out_shape[0] + out_w = out_shape[1] + else: + inputs['OutSize'] = out_shape else: out_h = int(input.shape[2] * scale) out_w = int(input.shape[3] * scale) @@ -3985,7 +3992,7 @@ def upsampling_bilinear2d(input, out_shape=None, scale=None, name=None): out = helper.create_tmp_variable(dtype) helper.append_op( type="bilinear_interp", - inputs={"X": input}, + inputs=inputs, outputs={"Out": out}, attrs={"out_h": out_h, "out_w": out_w}) diff --git a/python/paddle/fluid/tests/unittests/test_bilinear_interp_op.py b/python/paddle/fluid/tests/unittests/test_bilinear_interp_op.py index bffb4f3b666..87c11e7880e 100644 --- a/python/paddle/fluid/tests/unittests/test_bilinear_interp_op.py +++ b/python/paddle/fluid/tests/unittests/test_bilinear_interp_op.py @@ -17,7 +17,10 @@ import numpy as np from op_test import OpTest -def bilinear_interp_np(input, out_h, out_w): +def bilinear_interp_np(input, out_h, out_w, out_size): + if out_size is not None: + out_h = out_size[0] + out_w = out_size[1] batch_size, channel, in_h, in_w = input.shape if out_h > 1: ratio_h = (in_h - 1.0) / (out_h - 1.0) @@ -49,12 +52,15 @@ def bilinear_interp_np(input, out_h, out_w): class TestBilinearInterpOp(OpTest): def setUp(self): + self.out_size = None self.init_test_case() self.op_type = "bilinear_interp" input_np = np.random.random(self.input_shape).astype("float32") - output_np = bilinear_interp_np(input_np, self.out_h, self.out_w) - + output_np = bilinear_interp_np(input_np, self.out_h, self.out_w, + self.out_size) self.inputs = {'X': input_np} + if self.out_size is not None: + self.inputs['OutSize'] = self.out_size self.attrs = {'out_h': self.out_h, 'out_w': self.out_w} self.outputs = {'Out': output_np} @@ -68,6 +74,7 @@ class TestBilinearInterpOp(OpTest): self.input_shape = [2, 3, 4, 4] self.out_h = 2 self.out_w = 2 + self.out_size = np.array([3, 3]).astype("int32") class TestCase1(TestBilinearInterpOp): @@ -91,5 +98,29 @@ class TestCase3(TestBilinearInterpOp): self.out_w = 128 +class TestCase4(TestBilinearInterpOp): + def init_test_case(self): + self.input_shape = [4, 1, 7, 8] + self.out_h = 1 + self.out_w = 1 + self.out_size = np.array([2, 2]).astype("int32") + + +class TestCase5(TestBilinearInterpOp): + def init_test_case(self): + self.input_shape = [3, 3, 9, 6] + self.out_h = 12 + self.out_w = 12 + self.out_size = np.array([11, 11]).astype("int32") + + +class TestCase6(TestBilinearInterpOp): + def init_test_case(self): + self.input_shape = [1, 1, 128, 64] + self.out_h = 64 + self.out_w = 128 + self.out_size = np.array([65, 129]).astype("int32") + + if __name__ == "__main__": unittest.main() -- GitLab From b33ea7be2d68e64c4a3844b7fbfa01f2697a7839 Mon Sep 17 00:00:00 2001 From: minqiyang Date: Fri, 1 Jun 2018 13:35:20 +0800 Subject: [PATCH 0071/1416] 1. change the variable name from align_var_to_block to slice_var_up 2. replace split_method with slice_var_up in func init_splited_variables --- .../unittests/test_simple_dist_transpiler.py | 2 +- .../fluid/transpiler/distribute_transpiler.py | 35 ++++++++++--------- 2 files changed, 20 insertions(+), 17 deletions(-) diff --git a/python/paddle/fluid/tests/unittests/test_simple_dist_transpiler.py b/python/paddle/fluid/tests/unittests/test_simple_dist_transpiler.py index 25d79b51f99..5ae2844e295 100644 --- a/python/paddle/fluid/tests/unittests/test_simple_dist_transpiler.py +++ b/python/paddle/fluid/tests/unittests/test_simple_dist_transpiler.py @@ -72,7 +72,7 @@ class TestSimpleDistTranspiler(TranspilerTest): program=main, pservers=self.pserver_eps, trainers=self.trainers, - align_var_to_block=False) + slice_var_up=False) return t diff --git a/python/paddle/fluid/transpiler/distribute_transpiler.py b/python/paddle/fluid/transpiler/distribute_transpiler.py index a116671c1b1..da001add8e1 100644 --- a/python/paddle/fluid/transpiler/distribute_transpiler.py +++ b/python/paddle/fluid/transpiler/distribute_transpiler.py @@ -71,7 +71,7 @@ def same_or_split_var(p_name, var_name): return p_name == var_name or p_name.startswith(var_name + ".block") -def split_variable(var_list, service_count, min_block_size=8192): +def slice_variable(var_list, slice_count, min_block_size=8192): """ We may need to split dense tensor to one or more blocks and put them equally onto parameter server. One block is a sub-tensor @@ -83,8 +83,8 @@ def split_variable(var_list, service_count, min_block_size=8192): Args: var_list (list): List of variables. - service_count (int): Numel of pserver services. A pserver may have two - or more listening ports. + slice_count (int): Numel of count that variables will be sliced, which + could be the pserver services' count. min_block_size (int): Minimum splitted block size. Returns: blocks (list[(varname, block_id, current_block_size)]): A list @@ -92,12 +92,12 @@ def split_variable(var_list, service_count, min_block_size=8192): """ blocks = [] for var in var_list: - split_count = service_count + split_count = slice_count var_numel = reduce(lambda x, y: x * y, var.shape) max_pserver_count = int(math.floor(var_numel / float(min_block_size))) if max_pserver_count == 0: max_pserver_count = 1 - if max_pserver_count < service_count: + if max_pserver_count < slice_count: split_count = max_pserver_count block_size = int(math.ceil(var_numel / float(split_count))) @@ -178,7 +178,7 @@ class DistributeTranspiler: for index in range(len(self.pserver_endpoints)) ] - def _init_splited_vars(self, split_method, align_var_to_block=True): + def _init_splited_vars(self, slice_var_up): # update these mappings for further transpile: # 1. param_var_mapping: param var name -> [splited params vars] # 2. grad_var_mapping: grad var name -> [splited grads vars] @@ -197,16 +197,19 @@ class DistributeTranspiler: self._update_dist_lookup_table_vars(param_list, grad_list, self.params_grads) - if align_var_to_block: - grad_blocks = split_variable(grad_list, len(self.pserver_endpoints)) - param_blocks = split_variable(param_list, + if slice_var_up: + # when we slice var up into blocks, we will slice the var according to + # pserver services' count. A pserver may have two or more listening ports. + grad_blocks = slice_variable(grad_list, len(self.pserver_endpoints)) + param_blocks = slice_variable(param_list, len(self.pserver_endpoints)) else: - # when we do NOT align var to block, we will always split params + # when we do NOT slice var up into blocks, we will always slice params # grads into one block. - grad_blocks = split_variable(grad_list, 1) - param_blocks = split_variable(param_list, 1) + grad_blocks = slice_variable(grad_list, 1) + param_blocks = slice_variable(param_list, 1) assert (len(grad_blocks) == len(param_blocks)) + # origin_varname -> [splited_var] self.param_var_mapping = self._create_vars_from_blocklist( self.origin_program, param_blocks) @@ -237,7 +240,7 @@ class DistributeTranspiler: program=None, pservers="127.0.0.1:6174", trainers=1, - align_var_to_block=True, + slice_var_up=True, split_method=RoundRobin, sync_mode=True): """ @@ -271,7 +274,7 @@ class DistributeTranspiler: self.has_distributed_lookup_table = self._has_distributed_lookup_table() # split and create vars, then put splited vars in dicts for later use. - self._init_splited_vars(split_method, align_var_to_block) + self._init_splited_vars(slice_var_up) # step 3.1: insert send op to send gradient vars to parameter servers ps_dispatcher.reset() @@ -283,13 +286,13 @@ class DistributeTranspiler: # fc_b@GRAD_trainer_0, fc_b@GRAD_trainer_1 --> pserver2 # shuffle the map will avoid the uneven distribution above grad_var_mapping_items = self.grad_var_mapping.items() - if not align_var_to_block: + if not slice_var_up: np.random.shuffle(grad_var_mapping_items) for orig_varname, splited_vars in grad_var_mapping_items: eplist = ps_dispatcher.dispatch(splited_vars) - if not align_var_to_block: + if not slice_var_up: assert (len(splited_vars) == 1) if len(splited_vars) == 1: -- GitLab From 5387562576de020a35f864a07f14802b68ee398d Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Fri, 1 Jun 2018 14:07:41 +0800 Subject: [PATCH 0072/1416] add multi-thread test --- .../tests/book/test_inference_nlp.cc | 157 ++++++++---------- 1 file changed, 72 insertions(+), 85 deletions(-) diff --git a/paddle/fluid/inference/tests/book/test_inference_nlp.cc b/paddle/fluid/inference/tests/book/test_inference_nlp.cc index 5241661fb31..4e92d6a17b0 100644 --- a/paddle/fluid/inference/tests/book/test_inference_nlp.cc +++ b/paddle/fluid/inference/tests/book/test_inference_nlp.cc @@ -15,11 +15,7 @@ limitations under the License. */ #include #include #include -#include -#include -#include #include // NOLINT -#include #include "gflags/gflags.h" #include "gtest/gtest.h" #include "paddle/fluid/inference/tests/test_helper.h" @@ -41,19 +37,18 @@ inline double get_current_ms() { // return size of total words size_t read_datasets(std::vector* out, const std::string& filename) { - using namespace std; // NOLINT size_t sz = 0; - fstream fin(filename); - string line; + std::fstream fin(filename); + std::string line; out->clear(); while (getline(fin, line)) { - istringstream iss(line); - vector ids; - string field; + std::istringstream iss(line); + std::vector ids; + std::string field; while (getline(iss, field, ' ')) { ids.push_back(stoi(field)); } - if (ids.size() >= 1024 ) { + if (ids.size() >= 1024) { continue; } @@ -69,72 +64,61 @@ size_t read_datasets(std::vector* out, return sz; } -void test_multi_threads() { - /* - size_t jobs_per_thread = std::min(inputdatas.size() / FLAGS_num_threads, - inputdatas.size()); - std::vector workers(FLAGS_num_threads, jobs_per_thread); - workers[FLAGS_num_threads - 1] += inputdatas.size() % FLAGS_num_threads; - - std::vector> infer_threads; - - for (size_t i = 0; i < workers.size(); ++i) { - infer_threads.emplace_back(new std::thread([&, i]() { - size_t start = i * jobs_per_thread; - for (size_t j = start; j < start + workers[i]; ++j ) { - // 0. Call `paddle::framework::InitDevices()` initialize all the - devices - // In unittests, this is done in paddle/testing/paddle_gtest_main.cc - paddle::framework::LoDTensor words; - auto& srcdata = inputdatas[j]; - paddle::framework::LoD lod{{0, srcdata.size()}}; - words.set_lod(lod); - int64_t* pdata = words.mutable_data( - {static_cast(srcdata.size()), 1}, - paddle::platform::CPUPlace()); - memcpy(pdata, srcdata.data(), words.numel() * sizeof(int64_t)); - - LOG(INFO) << "thread id: " << i << ", words size:" << words.numel(); - std::vector cpu_feeds; - cpu_feeds.push_back(&words); - - paddle::framework::LoDTensor output1; - std::vector cpu_fetchs1; - cpu_fetchs1.push_back(&output1); - - // Run inference on CPU - if (FLAGS_prepare_vars) { - if (FLAGS_prepare_context) { - TestInference( - dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, - FLAGS_use_mkldnn); - } else { - TestInference( - dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, - FLAGS_use_mkldnn); - } - } else { - if (FLAGS_prepare_context) { - TestInference( - dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, - FLAGS_use_mkldnn); - } else { - TestInference( - dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, model_combined, - FLAGS_use_mkldnn); - } - } - //LOG(INFO) << output1.lod(); - //LOG(INFO) << output1.dims(); - } - })); - } - auto start_ms = get_current_ms(); - for (int i = 0; i < FLAGS_num_threads; ++i) { - infer_threads[i]->join(); +void ThreadRunInfer( + const int tid, paddle::framework::Executor* executor, + paddle::framework::Scope* scope, + const std::unique_ptr& inference_program, + const std::vector>& jobs) { + auto copy_program = std::unique_ptr( + new paddle::framework::ProgramDesc(*inference_program)); + std::string feed_holder_name = "feed_" + paddle::string::to_string(tid); + std::string fetch_holder_name = "fetch_" + paddle::string::to_string(tid); + copy_program->SetFeedHolderName(feed_holder_name); + copy_program->SetFetchHolderName(fetch_holder_name); + + // 3. Get the feed_target_names and fetch_target_names + const std::vector& feed_target_names = + copy_program->GetFeedTargetNames(); + const std::vector& fetch_target_names = + copy_program->GetFetchTargetNames(); + + PADDLE_ENFORCE_EQ(fetch_target_names.size(), 1UL); + std::map fetch_targets; + paddle::framework::LoDTensor outtensor; + fetch_targets[fetch_target_names[0]] = &outtensor; + + std::map feed_targets; + PADDLE_ENFORCE_EQ(feed_target_names.size(), 1UL); + + auto& inputs = jobs[tid]; + auto start_ms = get_current_ms(); + for (size_t i = 0; i < inputs.size(); ++i) { + feed_targets[feed_target_names[0]] = inputs[i]; + executor->Run(*copy_program, scope, &feed_targets, &fetch_targets, true, + true, feed_holder_name, fetch_holder_name); + } + auto stop_ms = get_current_ms(); + LOG(INFO) << "Tid: " << tid << ", process " << inputs.size() + << " samples, avg time per sample: " + + << (stop_ms - start_ms) / inputs.size() << " ms"; +} + +void bcast_datasets( + const std::vector& datasets, + std::vector>* jobs, + const int num_threads) { + size_t s = 0; + jobs->resize(num_threads); + while (s < datasets.size()) { + for (auto it = jobs->begin(); it != jobs->end(); it++) { + it->emplace_back(&datasets[s]); + s++; + if (s >= datasets.size()) { + break; + } } - auto stop_ms = get_current_ms(); - LOG(INFO) << "total: " << stop_ms - start_ms << " ms";*/ + } } TEST(inference, nlp) { @@ -166,7 +150,18 @@ TEST(inference, nlp) { } if (FLAGS_num_threads > 1) { - test_multi_threads(); + std::vector> jobs; + bcast_datasets(datasets, &jobs, FLAGS_num_threads); + std::vector> threads; + for (int i = 0; i < FLAGS_num_threads; ++i) { + threads.emplace_back(new std::thread(ThreadRunInfer, i, &executor, scope, + std::ref(inference_program), + std::ref(jobs))); + } + for (int i = 0; i < FLAGS_num_threads; ++i) { + threads[i]->join(); + } + } else { if (FLAGS_prepare_vars) { executor.CreateVariables(*inference_program, scope, 0); @@ -200,14 +195,6 @@ TEST(inference, nlp) { LOG(INFO) << "Total infer time: " << (stop_ms - start_ms) / 1000.0 / 60 << " min, avg time per seq: " << (stop_ms - start_ms) / datasets.size() << " ms"; -// { // just for test -// auto* scope = new paddle::framework::Scope(); -// paddle::framework::LoDTensor outtensor; -// TestInference( -// dirname, {&(datasets[0])}, {&outtensor}, FLAGS_repeat, model_combined, -// false); -// delete scope; -// } } delete scope; } -- GitLab From a4822ed897cebe6a27bd61d82c5a1b43022d3760 Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Fri, 1 Jun 2018 14:37:35 +0800 Subject: [PATCH 0073/1416] add thread setting --- .../tests/book/test_inference_nlp.cc | 26 +++++++++++++++---- 1 file changed, 21 insertions(+), 5 deletions(-) diff --git a/paddle/fluid/inference/tests/book/test_inference_nlp.cc b/paddle/fluid/inference/tests/book/test_inference_nlp.cc index 4e92d6a17b0..fba64efece8 100644 --- a/paddle/fluid/inference/tests/book/test_inference_nlp.cc +++ b/paddle/fluid/inference/tests/book/test_inference_nlp.cc @@ -19,6 +19,10 @@ limitations under the License. */ #include "gflags/gflags.h" #include "gtest/gtest.h" #include "paddle/fluid/inference/tests/test_helper.h" +#ifdef PADDLE_WITH_MKLML +#include +#include +#endif DEFINE_string(dirname, "", "Directory of the inference model."); DEFINE_int32(repeat, 100, "Running the inference program repeat times"); @@ -149,6 +153,14 @@ TEST(inference, nlp) { EnableMKLDNN(inference_program); } +#ifdef PADDLE_WITH_MKLML + // only use 1 core per thread + omp_set_dynamic(0); + omp_set_num_threads(1); + mkl_set_num_threads(1); +#endif + + double start_ms = 0, stop_ms = 0; if (FLAGS_num_threads > 1) { std::vector> jobs; bcast_datasets(datasets, &jobs, FLAGS_num_threads); @@ -158,9 +170,11 @@ TEST(inference, nlp) { std::ref(inference_program), std::ref(jobs))); } + start_ms = get_current_ms(); for (int i = 0; i < FLAGS_num_threads; ++i) { threads[i]->join(); } + stop_ms = get_current_ms(); } else { if (FLAGS_prepare_vars) { @@ -185,16 +199,18 @@ TEST(inference, nlp) { std::map feed_targets; // for data and run - auto start_ms = get_current_ms(); + start_ms = get_current_ms(); for (size_t i = 0; i < datasets.size(); ++i) { feed_targets[feed_target_names[0]] = &(datasets[i]); executor.RunPreparedContext(ctx.get(), scope, &feed_targets, &fetch_targets, !FLAGS_prepare_vars); } - auto stop_ms = get_current_ms(); - LOG(INFO) << "Total infer time: " << (stop_ms - start_ms) / 1000.0 / 60 - << " min, avg time per seq: " - << (stop_ms - start_ms) / datasets.size() << " ms"; + stop_ms = get_current_ms(); } + + LOG(INFO) << "Total inference time with " << FLAGS_num_threads + << " threads : " << (stop_ms - start_ms) / 1000.0 + << " sec, avg time per seq: " + << (stop_ms - start_ms) / datasets.size() << " ms"; delete scope; } -- GitLab From ed365919b409749d903a2a5b4fbc4d3b00bb6f7c Mon Sep 17 00:00:00 2001 From: Wu Yi Date: Fri, 1 Jun 2018 14:46:19 +0800 Subject: [PATCH 0074/1416] Add fluid benchmark Dockerfile (#11095) * add fluid benchmark Dockerfile * add_fluid_benchmark_dockerfile --- benchmark/fluid/Dockerfile | 22 ++++++++++++++++++++++ benchmark/fluid/README.md | 16 +++++++++++++++- benchmark/fluid/run.sh | 26 ++++++++++++++------------ 3 files changed, 51 insertions(+), 13 deletions(-) create mode 100644 benchmark/fluid/Dockerfile diff --git a/benchmark/fluid/Dockerfile b/benchmark/fluid/Dockerfile new file mode 100644 index 00000000000..46140a9d1be --- /dev/null +++ b/benchmark/fluid/Dockerfile @@ -0,0 +1,22 @@ +FROM nvidia/cuda:9.0-cudnn7-devel-ubuntu16.04 +RUN apt-get update && apt-get install -y python python-pip iputils-ping libgtk2.0-dev wget vim net-tools iftop +RUN ln -s /usr/lib/x86_64-linux-gnu/libcudnn.so.7 /usr/lib/libcudnn.so && ln -s /usr/lib/x86_64-linux-gnu/libnccl.so.2 /usr/lib/libnccl.so +RUN pip install -U pip +RUN pip install -U kubernetes opencv-python paddlepaddle + +# IMPORTANT: +# Add "ENV http_proxy=http://ip:port" if your download is slow, and don't forget to unset it at runtime. + +RUN sh -c 'echo "import paddle.v2 as paddle\npaddle.dataset.cifar.train10()\npaddle.dataset.flowers.fetch()" | python' +RUN sh -c 'echo "import paddle.v2 as paddle\npaddle.dataset.mnist.train()\npaddle.dataset.mnist.test()\npaddle.dataset.imdb.fetch()" | python' +RUN sh -c 'echo "import paddle.v2 as paddle\npaddle.dataset.imikolov.fetch()" | python' +RUN pip uninstall -y paddlepaddle && mkdir /workspace + +ADD https://raw.githubusercontent.com/PaddlePaddle/cloud/develop/docker/paddle_k8s /usr/bin +ADD https://raw.githubusercontent.com/PaddlePaddle/cloud/develop/docker/k8s_tools.py /root + +ADD *.whl / +RUN pip install /*.whl && rm -f /*.whl && chmod +x /usr/bin/paddle_k8s + +ENV LD_LIBRARY_PATH=/usr/local/lib +ADD fluid_benchmark.py dataset.py models/ /workspace/ diff --git a/benchmark/fluid/README.md b/benchmark/fluid/README.md index 7071e9fdcd3..1b0c7dce8bd 100644 --- a/benchmark/fluid/README.md +++ b/benchmark/fluid/README.md @@ -44,11 +44,25 @@ Currently supported `--model` argument include: ## Run Distributed Benchmark on Kubernetes Cluster +You may need to build a Docker image before submitting a cluster job onto Kubernetes, or you will +have to start all those processes mannually on each node, which is not recommended. + +To build the Docker image, you need to choose a paddle "whl" package to run with, you may either +download it from +http://www.paddlepaddle.org/docs/develop/documentation/zh/build_and_install/pip_install_en.html or +build it by your own. Once you've got the "whl" package, put it under the current directory and run: + +```bash +docker build -t [your docker image name]:[your docker image tag] . +``` + +Then push the image to a Docker registry that your Kubernetes cluster can reach. + We provide a script `kube_gen_job.py` to generate Kubernetes yaml files to submit distributed benchmark jobs to your cluster. To generate a job yaml, just run: ```bash -python kube_gen_job.py --jobname myjob --pscpu 4 --cpu 8 --gpu 8 --psmemory 20 --memory 40 --pservers 4 --trainers 4 --entry "python fluid_benchmark.py --model mnist --parallel 1 --device GPU --update_method pserver " --disttype pserver +python kube_gen_job.py --jobname myjob --pscpu 4 --cpu 8 --gpu 8 --psmemory 20 --memory 40 --pservers 4 --trainers 4 --entry "python fluid_benchmark.py --model mnist --gpus 8 --device GPU --update_method pserver " --disttype pserver ``` Then the yaml files are generated under directory `myjob`, you can run: diff --git a/benchmark/fluid/run.sh b/benchmark/fluid/run.sh index f6dfd20bf2e..afaab5f4de4 100644 --- a/benchmark/fluid/run.sh +++ b/benchmark/fluid/run.sh @@ -37,7 +37,8 @@ nohup stdbuf -oL nvidia-smi \ -l 1 & # mnist # mnist gpu mnist 128 -FLAGS_benchmark=true stdbuf -oL python fluid/mnist.py \ +FLAGS_benchmark=true stdbuf -oL python fluid_benchmark.py \ + --model=mnist \ --device=GPU \ --batch_size=128 \ --skip_batch_num=5 \ @@ -46,7 +47,8 @@ FLAGS_benchmark=true stdbuf -oL python fluid/mnist.py \ # vgg16 # gpu cifar10 128 -FLAGS_benchmark=true stdbuf -oL python fluid/vgg16.py \ +FLAGS_benchmark=true stdbuf -oL python fluid_benchmark.py \ + --model=vgg16 \ --device=GPU \ --batch_size=128 \ --skip_batch_num=5 \ @@ -54,7 +56,8 @@ FLAGS_benchmark=true stdbuf -oL python fluid/vgg16.py \ 2>&1 | tee -a vgg16_gpu_128.log # flowers gpu 128 -FLAGS_benchmark=true stdbuf -oL python fluid/vgg16.py \ +FLAGS_benchmark=true stdbuf -oL python fluid_benchmark.py \ + --model=vgg16 \ --device=GPU \ --batch_size=32 \ --data_set=flowers \ @@ -64,40 +67,39 @@ FLAGS_benchmark=true stdbuf -oL python fluid/vgg16.py \ # resnet50 # resnet50 gpu cifar10 128 -FLAGS_benchmark=true stdbuf -oL python fluid/resnet50.py \ +FLAGS_benchmark=true stdbuf -oL python fluid_benchmark.py \ + --model=resnet50 \ --device=GPU \ --batch_size=128 \ --data_set=cifar10 \ - --model=resnet_cifar10 \ --skip_batch_num=5 \ --iterations=30 \ 2>&1 | tee -a resnet50_gpu_128.log # resnet50 gpu flowers 64 -FLAGS_benchmark=true stdbuf -oL python fluid/resnet50.py \ +FLAGS_benchmark=true stdbuf -oL python fluid_benchmark.py \ + --model=resnet50 \ --device=GPU \ --batch_size=64 \ --data_set=flowers \ - --model=resnet_imagenet \ --skip_batch_num=5 \ --iterations=30 \ 2>&1 | tee -a resnet50_gpu_flowers_64.log # lstm # lstm gpu imdb 32 # tensorflow only support batch=32 -FLAGS_benchmark=true stdbuf -oL python fluid/stacked_dynamic_lstm.py \ +FLAGS_benchmark=true stdbuf -oL python fluid_benchmark.py \ + --model=stacked_dynamic_lstm \ --device=GPU \ --batch_size=32 \ --skip_batch_num=5 \ --iterations=30 \ - --hidden_dim=512 \ - --emb_dim=512 \ - --crop_size=1500 \ 2>&1 | tee -a lstm_gpu_32.log # seq2seq # seq2seq gpu wmb 128 -FLAGS_benchmark=true stdbuf -oL python fluid/machine_translation.py \ +FLAGS_benchmark=true stdbuf -oL python fluid_benchmark.py \ + --model=machine_translation \ --device=GPU \ --batch_size=128 \ --skip_batch_num=5 \ -- GitLab From 15193c9e936270de7f39b1d738bbb3571adcd737 Mon Sep 17 00:00:00 2001 From: yuyang18 Date: Fri, 1 Jun 2018 14:48:24 +0800 Subject: [PATCH 0075/1416] Faster RecordIO Scanner --- paddle/fluid/recordio/chunk.cc | 58 ++++++++++++++++++++------------ paddle/fluid/recordio/chunk.h | 16 +++++++-- paddle/fluid/recordio/scanner.cc | 26 +++++++------- paddle/fluid/recordio/scanner.h | 6 +--- 4 files changed, 64 insertions(+), 42 deletions(-) diff --git a/paddle/fluid/recordio/chunk.cc b/paddle/fluid/recordio/chunk.cc index 82d9aa601cf..6c65d9160c0 100644 --- a/paddle/fluid/recordio/chunk.cc +++ b/paddle/fluid/recordio/chunk.cc @@ -119,40 +119,56 @@ bool Chunk::Write(std::ostream& os, Compressor ct) const { } bool Chunk::Parse(std::istream& sin) { - Header hdr; - bool ok = hdr.Parse(sin); + ChunkParser parser(sin); + if (!parser.Init()) { + return false; + } + Clear(); + while (parser.HasNext()) { + Add(parser.Next()); + } + return true; +} + +ChunkParser::ChunkParser(std::istream& sin) : in_(sin) {} +bool ChunkParser::Init() { + pos_ = 0; + bool ok = header_.Parse(in_); if (!ok) { return ok; } - auto beg_pos = sin.tellg(); - uint32_t crc = Crc32Stream(sin, hdr.CompressSize()); - PADDLE_ENFORCE_EQ(hdr.Checksum(), crc); - Clear(); - sin.seekg(beg_pos, sin.beg); - std::unique_ptr compressed_stream; - switch (hdr.CompressType()) { + auto beg_pos = in_.tellg(); + uint32_t crc = Crc32Stream(in_, header_.CompressSize()); + PADDLE_ENFORCE_EQ(header_.Checksum(), crc); + in_.seekg(beg_pos, in_.beg); + + switch (header_.CompressType()) { case Compressor::kNoCompress: break; case Compressor::kSnappy: - compressed_stream.reset(new snappy::iSnappyStream(sin)); + compressed_stream_.reset(new snappy::iSnappyStream(in_)); break; default: PADDLE_THROW("Not implemented"); } + return true; +} - std::istream& stream = compressed_stream ? *compressed_stream : sin; +bool ChunkParser::HasNext() const { return pos_ < header_.NumRecords(); } - for (uint32_t i = 0; i < hdr.NumRecords(); ++i) { - uint32_t rec_len; - stream.read(reinterpret_cast(&rec_len), sizeof(uint32_t)); - std::string buf; - buf.resize(rec_len); - stream.read(&buf[0], rec_len); - PADDLE_ENFORCE_EQ(rec_len, stream.gcount()); - Add(buf); +std::string ChunkParser::Next() { + if (!HasNext()) { + return ""; } - return true; + ++pos_; + std::istream& stream = compressed_stream_ ? *compressed_stream_ : in_; + uint32_t rec_len; + stream.read(reinterpret_cast(&rec_len), sizeof(uint32_t)); + std::string buf; + buf.resize(rec_len); + stream.read(&buf[0], rec_len); + PADDLE_ENFORCE_EQ(rec_len, stream.gcount()); + return buf; } - } // namespace recordio } // namespace paddle diff --git a/paddle/fluid/recordio/chunk.h b/paddle/fluid/recordio/chunk.h index 71a1556a33b..cfb954a5916 100644 --- a/paddle/fluid/recordio/chunk.h +++ b/paddle/fluid/recordio/chunk.h @@ -13,6 +13,7 @@ // limitations under the License. #pragma once +#include #include #include @@ -53,9 +54,20 @@ class Chunk { DISABLE_COPY_AND_ASSIGN(Chunk); }; -size_t CompressData(const char* in, size_t in_length, Compressor ct, char* out); +class ChunkParser { + public: + explicit ChunkParser(std::istream& sin); + + bool Init(); + std::string Next(); + bool HasNext() const; -void DeflateData(const char* in, size_t in_length, Compressor ct, char* out); + private: + Header header_; + uint32_t pos_{0}; + std::istream& in_; + std::unique_ptr compressed_stream_; +}; } // namespace recordio } // namespace paddle diff --git a/paddle/fluid/recordio/scanner.cc b/paddle/fluid/recordio/scanner.cc index 88b4d4001bc..06a13e6c5b6 100644 --- a/paddle/fluid/recordio/scanner.cc +++ b/paddle/fluid/recordio/scanner.cc @@ -22,35 +22,33 @@ namespace paddle { namespace recordio { Scanner::Scanner(std::unique_ptr &&stream) - : stream_(std::move(stream)) { + : stream_(std::move(stream)), parser_(*stream_) { Reset(); } -Scanner::Scanner(const std::string &filename) { - stream_.reset(new std::ifstream(filename)); +Scanner::Scanner(const std::string &filename) + : stream_(new std::ifstream(filename)), parser_(*stream_) { Reset(); } void Scanner::Reset() { stream_->clear(); stream_->seekg(0, std::ios::beg); - ParseNextChunk(); + parser_.Init(); } std::string Scanner::Next() { - PADDLE_ENFORCE(!eof_, "StopIteration"); - auto rec = cur_chunk_.Record(offset_++); - if (offset_ == cur_chunk_.NumRecords()) { - ParseNextChunk(); + if (stream_->eof()) { + return ""; } - return rec; -} -void Scanner::ParseNextChunk() { - eof_ = !cur_chunk_.Parse(*stream_); - offset_ = 0; + auto res = parser_.Next(); + if (!parser_.HasNext() && HasNext()) { + parser_.Init(); + } + return res; } -bool Scanner::HasNext() const { return !eof_; } +bool Scanner::HasNext() const { return !stream_->eof(); } } // namespace recordio } // namespace paddle diff --git a/paddle/fluid/recordio/scanner.h b/paddle/fluid/recordio/scanner.h index 34f1b0c78d6..0d885dd87a2 100644 --- a/paddle/fluid/recordio/scanner.h +++ b/paddle/fluid/recordio/scanner.h @@ -37,11 +37,7 @@ class Scanner { private: std::unique_ptr stream_; - Chunk cur_chunk_; - size_t offset_; - bool eof_; - - void ParseNextChunk(); + ChunkParser parser_; }; } // namespace recordio } // namespace paddle -- GitLab From 28dc9ba3c14edb2b3d8389080ba3ea06f60684c2 Mon Sep 17 00:00:00 2001 From: whs Date: Fri, 1 Jun 2018 15:13:48 +0800 Subject: [PATCH 0076/1416] Add shape op to get the shape of variable. (#11048) * Add shape op to get the shape of variable. * Rename get_shape to shape. * Add checker for output and fix comments. --- paddle/fluid/operators/shape_op.cc | 54 +++++++++++++++++++ paddle/fluid/operators/shape_op.cu | 20 +++++++ paddle/fluid/operators/shape_op.h | 38 +++++++++++++ python/paddle/fluid/layers/ops.py | 1 + .../fluid/tests/unittests/test_shape_op.py | 47 ++++++++++++++++ 5 files changed, 160 insertions(+) create mode 100644 paddle/fluid/operators/shape_op.cc create mode 100644 paddle/fluid/operators/shape_op.cu create mode 100644 paddle/fluid/operators/shape_op.h create mode 100644 python/paddle/fluid/tests/unittests/test_shape_op.py diff --git a/paddle/fluid/operators/shape_op.cc b/paddle/fluid/operators/shape_op.cc new file mode 100644 index 00000000000..c75fce7959d --- /dev/null +++ b/paddle/fluid/operators/shape_op.cc @@ -0,0 +1,54 @@ +/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#include "paddle/fluid/operators/shape_op.h" +#include "paddle/fluid/framework/op_registry.h" + +namespace paddle { +namespace operators { + +class ShapeOp : public framework::OperatorWithKernel { + public: + using framework::OperatorWithKernel::OperatorWithKernel; + + void InferShape(framework::InferShapeContext *ctx) const override { + PADDLE_ENFORCE(ctx->HasInput("Input"), + "Input (Input) of get_shape op should not be null."); + PADDLE_ENFORCE(ctx->HasOutput("Out"), + "Output (Out) of get_shape op should not be null."); + auto in_dim = ctx->GetInputDim("Input"); + ctx->SetOutputDim("Out", {in_dim.size()}); + } +}; + +class ShapeOpMaker : public framework::OpProtoAndCheckerMaker { + public: + void Make() override { + AddInput("Input", "(Tensor), The input tensor."); + AddOutput("Out", "(Tensor), The shape of input tensor."); + AddComment(R"DOC( +Shape Operator. +Get the shape of input tensor. +)DOC"); + } +}; + +} // namespace operators +} // namespace paddle + +namespace ops = paddle::operators; +REGISTER_OPERATOR(shape, ops::ShapeOp, ops::ShapeOpMaker, + paddle::framework::EmptyGradOpMaker); +REGISTER_OP_CPU_KERNEL(shape, ops::ShapeKernel, ops::ShapeKernel, + ops::ShapeKernel, ops::ShapeKernel); diff --git a/paddle/fluid/operators/shape_op.cu b/paddle/fluid/operators/shape_op.cu new file mode 100644 index 00000000000..7736a2a1e13 --- /dev/null +++ b/paddle/fluid/operators/shape_op.cu @@ -0,0 +1,20 @@ +/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#include "paddle/fluid/operators/shape_op.h" + +REGISTER_OP_CUDA_KERNEL(shape, paddle::operators::ShapeKernel, + paddle::operators::ShapeKernel, + paddle::operators::ShapeKernel, + paddle::operators::ShapeKernel); diff --git a/paddle/fluid/operators/shape_op.h b/paddle/fluid/operators/shape_op.h new file mode 100644 index 00000000000..3be86b66a53 --- /dev/null +++ b/paddle/fluid/operators/shape_op.h @@ -0,0 +1,38 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#pragma once +#include +#include "paddle/fluid/framework/op_registry.h" + +namespace paddle { +namespace operators { + +using Tensor = framework::Tensor; + +template +class ShapeKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& ctx) const override { + auto* in_t = ctx.Input("Input"); + auto* out_t = ctx.Output("Out"); + auto out_data = out_t->mutable_data(platform::CPUPlace()); + auto in_dims = in_t->dims(); + for (int i = 0; i < in_dims.size(); ++i) { + out_data[i] = in_dims[i]; + } + } +}; +} // namespace operators +} // namespace paddle diff --git a/python/paddle/fluid/layers/ops.py b/python/paddle/fluid/layers/ops.py index a9fe25744cc..60f8cbbfa71 100644 --- a/python/paddle/fluid/layers/ops.py +++ b/python/paddle/fluid/layers/ops.py @@ -71,6 +71,7 @@ __all__ = [ 'cumsum', 'scatter', 'sum', + 'shape', ] + __activations__ for _OP in set(__all__): diff --git a/python/paddle/fluid/tests/unittests/test_shape_op.py b/python/paddle/fluid/tests/unittests/test_shape_op.py new file mode 100644 index 00000000000..a62ee050075 --- /dev/null +++ b/python/paddle/fluid/tests/unittests/test_shape_op.py @@ -0,0 +1,47 @@ +# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import unittest +import numpy as np +from op_test import OpTest + + +class TestShapeOp(OpTest): + def setUp(self): + self.op_type = "shape" + self.config() + self.shape = [2, 3] + input = np.zeros(self.shape) + self.inputs = {'Input': input} + self.outputs = {'Out': np.array(self.shape)} + + def config(self): + self.shape = [2, 3] + + def test_check_output(self): + self.check_output() + + +class case1(TestShapeOp): + def config(self): + self.shape = [2] + + +class case2(TestShapeOp): + def config(self): + self.shape = [1, 2, 3] + + +if __name__ == '__main__': + unittest.main() -- GitLab From 86d8659c8de7e91c066935e723da29f31ffd6364 Mon Sep 17 00:00:00 2001 From: whs Date: Fri, 1 Jun 2018 15:14:08 +0800 Subject: [PATCH 0077/1416] Add python wrapper for gather op. (#11033) * Add python wrapper for gather op. * Add unitest for 'rank==1' and fix comments. * Fix comments. --- doc/fluid/api/layers.rst | 6 +++ paddle/fluid/operators/gather_op.cc | 1 - python/paddle/fluid/layers/nn.py | 51 ++++++++++++++++++- .../fluid/tests/unittests/test_gather_op.py | 15 +++++- 4 files changed, 69 insertions(+), 4 deletions(-) diff --git a/doc/fluid/api/layers.rst b/doc/fluid/api/layers.rst index f53da4d194f..dbb99d3c03f 100644 --- a/doc/fluid/api/layers.rst +++ b/doc/fluid/api/layers.rst @@ -1009,3 +1009,9 @@ ____ .. autofunction:: paddle.fluid.layers.upsampling_bilinear2d :noindex: +gather +____ + +.. autofunction:: paddle.fluid.layers.gather + :noindex: + diff --git a/paddle/fluid/operators/gather_op.cc b/paddle/fluid/operators/gather_op.cc index e21b5725892..aa3e05b83b2 100644 --- a/paddle/fluid/operators/gather_op.cc +++ b/paddle/fluid/operators/gather_op.cc @@ -33,7 +33,6 @@ class GatherOp : public framework::OperatorWithKernel { auto index_dims = ctx->GetInputDim("Index"); PADDLE_ENFORCE(index_dims.size() == 1); int batch_size = ctx->GetInputDim("Index")[0]; - PADDLE_ENFORCE_GE(batch_size, 0, "Batch size must be >0"); framework::DDim output_dims(ctx->GetInputDim("X")); output_dims[0] = batch_size; ctx->SetOutputDim("Out", output_dims); diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index cb87653c477..56f5c6b4bed 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -82,6 +82,7 @@ __all__ = [ 'roi_pool', 'dice_loss', 'upsampling_bilinear2d', + 'gather', 'random_crop', ] @@ -3889,7 +3890,6 @@ def roi_pool(input, rois, pooled_height=1, pooled_width=1, spatial_scale=1.0): def dice_loss(input, label, epsilon=0.00001): """ - **Dice loss Layer** Dice loss for comparing the similarity of two batch of data, usually is used for binary image segmentation i.e. labels are binary. The dice loss can be defined as below equation: @@ -3999,6 +3999,55 @@ def upsampling_bilinear2d(input, out_shape=None, scale=None, name=None): return out +def gather(input, index): + """ + Output is obtained by gathering entries of the outer-most dimension + of X indexed by `index` and concatenate them together. + + .. math:: + + Out = X[Index] + + + .. code-block:: text + + + Given: + + X = [[1, 2], + [3, 4], + [5, 6]] + + Index = [1, 2] + + Then: + + Out = [[3, 4], + [5, 6]] + + Args: + input (Variable): The source input with rank>=1. + index (Variable): The index input with rank=1. + + Returns: + output (Variable): The output is a tensor with the same rank as input. + + Examples: + .. code-block:: python + + output = fluid.layers.gather(x, index) + """ + helper = LayerHelper('gather', **locals()) + dtype = helper.input_dtype() + out = helper.create_tmp_variable(dtype) + helper.append_op( + type="gather", + inputs={"X": input, + "Index": index}, + outputs={"Out": out}) + return out + + def random_crop(input, shape, seed=1): helper = LayerHelper("random_crop", **locals()) dtype = helper.input_dtype() diff --git a/python/paddle/fluid/tests/unittests/test_gather_op.py b/python/paddle/fluid/tests/unittests/test_gather_op.py index 6fd043c27e2..4ae90864806 100644 --- a/python/paddle/fluid/tests/unittests/test_gather_op.py +++ b/python/paddle/fluid/tests/unittests/test_gather_op.py @@ -20,8 +20,9 @@ from op_test import OpTest class TestGatherOp(OpTest): def setUp(self): self.op_type = "gather" - xnp = np.random.random((10, 20)).astype("float32") - self.inputs = {'X': xnp, 'Index': np.array([1, 3, 5]).astype("int32")} + self.config() + xnp = np.random.random(self.x_shape).astype("float32") + self.inputs = {'X': xnp, 'Index': np.array(self.index).astype("int32")} self.outputs = {'Out': self.inputs["X"][self.inputs["Index"]]} def test_check_output(self): @@ -30,6 +31,16 @@ class TestGatherOp(OpTest): def test_check_grad(self): self.check_grad(['X'], 'Out') + def config(self): + self.x_shape = (10, 20) + self.index = [1, 3, 5] + + +class TestCase1(TestGatherOp): + def config(self): + self.x_shape = (10) + self.index = [1, 3, 5] + if __name__ == "__main__": unittest.main() -- GitLab From eacac49bcdd281f68d9fac2cba9dee2b245d0d17 Mon Sep 17 00:00:00 2001 From: minqiyang Date: Fri, 1 Jun 2018 15:15:26 +0800 Subject: [PATCH 0078/1416] 1. update test_split_var: replace split with slice --- .../{test_split_var.py => test_slice_var.py} | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) rename python/paddle/fluid/tests/unittests/{test_split_var.py => test_slice_var.py} (85%) diff --git a/python/paddle/fluid/tests/unittests/test_split_var.py b/python/paddle/fluid/tests/unittests/test_slice_var.py similarity index 85% rename from python/paddle/fluid/tests/unittests/test_split_var.py rename to python/paddle/fluid/tests/unittests/test_slice_var.py index 157def9b56e..82305b23a1a 100644 --- a/python/paddle/fluid/tests/unittests/test_split_var.py +++ b/python/paddle/fluid/tests/unittests/test_slice_var.py @@ -14,14 +14,14 @@ import math import unittest -from paddle.fluid.transpiler.distribute_transpiler import split_variable +from paddle.fluid.transpiler.distribute_transpiler import slice_variable import paddle.fluid as fluid import paddle.fluid.core as core import random -class TestSplitVar(unittest.TestCase): - def check_split_output(self, shapes, expected_sizes, min_size): +class TestSliceVar(unittest.TestCase): + def check_slice_output(self, shapes, expected_sizes, min_size): var_list = [] program = fluid.Program() for shape in shapes: @@ -31,7 +31,7 @@ class TestSplitVar(unittest.TestCase): # dtype=core.VarDesc.VarType.LOD_TENSOR, shape=shape) var_list.append(var) - blocks = split_variable(var_list, 10, min_size) + blocks = slice_variable(var_list, 10, min_size) all_sizes = [] for s in expected_sizes: for s2 in s: @@ -49,7 +49,7 @@ class TestSplitVar(unittest.TestCase): [1150, 1150, 1150, 1150, 1150, 1150, 1100] ] - self.check_split_output(shapes, expected_sizes, 1024) + self.check_slice_output(shapes, expected_sizes, 1024) def test_check_output_8k(self): shapes = [[3, 5], [1024], [28, 784], [8, 1020], [800, 10], @@ -57,7 +57,7 @@ class TestSplitVar(unittest.TestCase): expected_sizes = [[15], [1024], [10976, 10976], [8160], [8000], [35937, 35937, 35937, 35937, 35937, 35937]] - self.check_split_output(shapes, expected_sizes, 8192) + self.check_slice_output(shapes, expected_sizes, 8192) if __name__ == '__main__': -- GitLab From 18d640255efb6807a360c29d6e1c672aa679818a Mon Sep 17 00:00:00 2001 From: Yan Chunwei Date: Fri, 1 Jun 2018 15:38:45 +0800 Subject: [PATCH 0079/1416] simplify inference api (#11104) --- .../contrib/inference/paddle_inference_api.h | 40 +++++++++++-------- .../inference/paddle_inference_api_impl.cc | 22 +++++----- .../test_paddle_inference_api_impl.cc | 1 - 3 files changed, 36 insertions(+), 27 deletions(-) diff --git a/paddle/contrib/inference/paddle_inference_api.h b/paddle/contrib/inference/paddle_inference_api.h index b4c7f9bef4d..5fe8399762b 100644 --- a/paddle/contrib/inference/paddle_inference_api.h +++ b/paddle/contrib/inference/paddle_inference_api.h @@ -40,14 +40,23 @@ struct PaddleBuf { struct PaddleTensor { std::string name; // variable name. std::vector shape; + // TODO(Superjomn) for LoD support, add a vector> field if needed. PaddleBuf data; // blob of data. PaddleDType dtype; }; +enum class PaddleEngineKind { + kNative = 0, // Use the native Fluid facility. + // TODO(Superjomn) support following engines latter. + // kAnakin, // Use Anakin for inference. + // kTensorRT, // Use TensorRT for inference. + // kAutoMixedAnakin, // Automatically mix Fluid with Anakin. + // kAutoMixedTensorRT, // Automatically mix Fluid with TensorRT. +}; + /* * A simple Inference API for Paddle. Currently this API can be used by * non-sequence scenerios. - * TODO(Superjomn) Support another API for NLP-related usages. */ class PaddlePredictor { public: @@ -69,15 +78,6 @@ class PaddlePredictor { // Destroy the Predictor. virtual ~PaddlePredictor() {} - enum class EngineKind { - kNative = -1, // Use the native Fluid facility. - // TODO(Superjomn) support latter. - // kAnakin, // Use Anakin for inference. - // kTensorRT, // Use TensorRT for inference. - // kAutoMixedAnakin, // Automatically mix Fluid with Anakin. - // kAutoMixedTensorRT, // Automatically mix Fluid with TensorRT. - }; - // The common configs for all the predictors. struct Config { std::string model_dir; // path to the model directory. @@ -86,18 +86,24 @@ class PaddlePredictor { }; struct NativeConfig : public PaddlePredictor::Config { + // GPU related fields. bool use_gpu{false}; - int device; - float fraction_of_gpu_memory; + int device{0}; + float fraction_of_gpu_memory{-1.f}; // Negative to notify initialization. + std::string prog_file; std::string param_file; - bool share_variables; }; -// A factory to help create difference predictor. -template < - typename ConfigT, - PaddlePredictor::EngineKind engine = PaddlePredictor::EngineKind::kNative> +// A factory to help create different predictors. +// +// FOR EXTENSION DEVELOPER: +// Different predictors are designated by config type and engine kind. Similar +// configs can be merged, but there shouldn't be a huge config containing +// different fields for more than one kind of predictors. +// +// Similarly, each engine kind should map to a unique predictor implementation. +template std::unique_ptr CreatePaddlePredictor(const ConfigT& config); } // namespace paddle diff --git a/paddle/contrib/inference/paddle_inference_api_impl.cc b/paddle/contrib/inference/paddle_inference_api_impl.cc index 989252f69e4..99a64662d4d 100644 --- a/paddle/contrib/inference/paddle_inference_api_impl.cc +++ b/paddle/contrib/inference/paddle_inference_api_impl.cc @@ -57,8 +57,7 @@ std::string num2str(T a) { bool NativePaddlePredictor::Init() { VLOG(3) << "Predictor::init()"; - // TODO(panyx0718): Should CPU vs GPU device be decided by id? - if (config_.device >= 0) { + if (config_.use_gpu) { place_ = paddle::platform::CUDAPlace(config_.device); } else { place_ = paddle::platform::CPUPlace(); @@ -85,11 +84,13 @@ bool NativePaddlePredictor::Init() { } ctx_ = executor_->Prepare(*inference_program_, 0); - // Create variables - // TODO(panyx0718): Why need to test share_variables here? - if (config_.share_variables) { - executor_->CreateVariables(*inference_program_, scope_.get(), 0); - } + // Create temporary variables first, so that the first batch do not need to + // create variables in the runtime. This is the logics of the old inference + // API. + // TODO(Superjomn) this should be modified when `Clone` is valid for + // multi-thread application. + executor_->CreateVariables(*inference_program_, scope_.get(), 0); + // Get the feed_target_names and fetch_target_names feed_target_names_ = inference_program_->GetFeedTargetNames(); fetch_target_names_ = inference_program_->GetFetchTargetNames(); @@ -124,7 +125,7 @@ bool NativePaddlePredictor::Run(const std::vector &inputs, scope_.get(), &feed_targets, &fetch_targets, - !config_.share_variables); + false /* don't create variable eatch time */); if (!GetFetch(fetchs, output_data)) { LOG(ERROR) << "fail to get fetchs"; return false; @@ -242,11 +243,14 @@ bool NativePaddlePredictor::GetFetch( template <> std::unique_ptr -CreatePaddlePredictor( +CreatePaddlePredictor( const NativeConfig &config) { VLOG(3) << "create NativePaddlePredictor"; if (config.use_gpu) { // 1. GPU memeroy + PADDLE_ENFORCE( + config.fraction_of_gpu_memory > 0.f, + "fraction_of_gpu_memory in the config should be set to range (0., 1.]"); std::vector flags; if (config.fraction_of_gpu_memory >= 0.0f || config.fraction_of_gpu_memory <= 0.95f) { diff --git a/paddle/contrib/inference/test_paddle_inference_api_impl.cc b/paddle/contrib/inference/test_paddle_inference_api_impl.cc index 5240fc2f202..07b17acd484 100644 --- a/paddle/contrib/inference/test_paddle_inference_api_impl.cc +++ b/paddle/contrib/inference/test_paddle_inference_api_impl.cc @@ -47,7 +47,6 @@ NativeConfig GetConfig() { config.fraction_of_gpu_memory = 0.15; config.use_gpu = true; config.device = 0; - config.share_variables = true; return config; } -- GitLab From 0c0c5df4cbed8a9c947fd2819640e9d402555ed1 Mon Sep 17 00:00:00 2001 From: Yan Chunwei Date: Fri, 1 Jun 2018 15:39:30 +0800 Subject: [PATCH 0080/1416] feature/add TRT fc converter (#11043) --- .../inference/tensorrt/convert/CMakeLists.txt | 2 + .../inference/tensorrt/convert/conv2d_op.cc | 3 +- .../fluid/inference/tensorrt/convert/fc_op.cc | 119 ++++++++++++++++++ .../inference/tensorrt/convert/mul_op.cc | 5 +- .../inference/tensorrt/convert/op_converter.h | 41 ++++-- .../inference/tensorrt/convert/test_fc_op.cc | 46 +++++++ .../inference/tensorrt/convert/test_mul_op.cc | 4 +- .../tensorrt/convert/test_op_converter.cc | 7 +- .../inference/tensorrt/convert/ut_helper.h | 40 +++--- paddle/fluid/inference/tensorrt/engine.cc | 1 + paddle/fluid/inference/tensorrt/engine.h | 4 +- paddle/fluid/operators/tensorrt_engine_op.cc | 3 +- 12 files changed, 240 insertions(+), 35 deletions(-) create mode 100644 paddle/fluid/inference/tensorrt/convert/fc_op.cc create mode 100644 paddle/fluid/inference/tensorrt/convert/test_fc_op.cc diff --git a/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt b/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt index 5ada1d63126..23ca8bfac84 100644 --- a/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt +++ b/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt @@ -8,3 +8,5 @@ nv_test(test_op_converter SRCS test_op_converter.cc mul_op.cc conv2d_op.cc DEPS nv_test(test_io_converter SRCS test_io_converter.cc io_converter.cc DEPS dynload_cuda dynamic_loader lod_tensor) nv_test(test_trt_mul_op SRCS test_mul_op.cc mul_op.cc DEPS ${FLUID_CORE_MODULES} tensorrt_engine mul_op SERIAL) +nv_test(test_trt_fc_op SRCS test_fc_op.cc fc_op.cc + DEPS ${FLUID_CORE_MODULES} tensorrt_engine mul_op SERIAL) diff --git a/paddle/fluid/inference/tensorrt/convert/conv2d_op.cc b/paddle/fluid/inference/tensorrt/convert/conv2d_op.cc index 209936c3baf..668d344f1bb 100644 --- a/paddle/fluid/inference/tensorrt/convert/conv2d_op.cc +++ b/paddle/fluid/inference/tensorrt/convert/conv2d_op.cc @@ -21,7 +21,8 @@ namespace tensorrt { class Conv2dOpConverter : public OpConverter { public: Conv2dOpConverter() {} - void operator()(const framework::proto::OpDesc& op) override { + void operator()(const framework::proto::OpDesc& op, + const framework::Scope& scope) override { LOG(INFO) << "convert a fluid conv2d op to tensorrt conv layer without bias"; } diff --git a/paddle/fluid/inference/tensorrt/convert/fc_op.cc b/paddle/fluid/inference/tensorrt/convert/fc_op.cc new file mode 100644 index 00000000000..bd05608d762 --- /dev/null +++ b/paddle/fluid/inference/tensorrt/convert/fc_op.cc @@ -0,0 +1,119 @@ +/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + +http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#include "paddle/fluid/framework/eigen.h" +#include "paddle/fluid/framework/lod_tensor.h" +#include "paddle/fluid/framework/op_registry.h" +#include "paddle/fluid/inference/tensorrt/convert/op_converter.h" +#include "paddle/fluid/inference/tensorrt/engine.h" +#include "paddle/fluid/platform/place.h" + +namespace paddle { +namespace inference { +namespace tensorrt { + +// Reorder the elements from istrides to ostrides, borrowed from TRT convert in +// tensorflow. +// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/tensorrt/convert/convert_nodes.cc#L318 +template +void Reorder2(nvinfer1::DimsHW shape, const T* idata, nvinfer1::DimsHW istrides, + T* odata, nvinfer1::DimsHW ostrides) { + for (int h = 0; h < shape.h(); ++h) { + for (int w = 0; w < shape.w(); ++w) { + odata[h * ostrides.h() + w * ostrides.w()] = + idata[h * ostrides.h() + w * ostrides.w()]; + } + } +} + +// Reorder the data layout from CK to KC. +void ReorderCKtoKC(TensorRTEngine::Weight& iweights, + TensorRTEngine::Weight* oweights) { + int c = iweights.dims[0]; + int k = iweights.dims[1]; + oweights->dims.assign({k, c}); + nvinfer1::DimsHW istrides = {1, k}; + nvinfer1::DimsHW ostrides = {c, 1}; + Reorder2({k, c}, static_cast(iweights.get().values), istrides, + static_cast(const_cast(oweights->get().values)), + ostrides); +} + +/* + * FC converter convert a MUL op in Fluid to a FC layer in TRT. + */ +class FcOpConverter : public OpConverter { + public: + void operator()(const framework::proto::OpDesc& op, + const framework::Scope& scope) override { + VLOG(4) << "convert a fluid fc op to tensorrt fc layer without bias"; + + framework::OpDesc op_desc(op, nullptr, nullptr); + PADDLE_ENFORCE_EQ(op_desc.Input("X").size(), 1); + PADDLE_ENFORCE_EQ(op_desc.Input("Y").size(), 1); // Y is a weight + PADDLE_ENFORCE_EQ(op_desc.Output("Out").size(), 1); + + // Declare inputs + auto* X = engine_->GetITensor(op_desc.Input("X").front()); + + // Declare weights + auto* Y_v = scope.FindVar(op_desc.Input("Y").front()); + PADDLE_ENFORCE_NOT_NULL(Y_v); + auto* Y_t = Y_v->GetMutable(); + // This may trigger a GPU->CPU copy, because TRT's weight can only be + // assigned from CPU memory, that can't be avoided. + auto* weight_data = Y_t->mutable_data(platform::CPUPlace()); + PADDLE_ENFORCE_EQ(Y_t->dims().size(), 2UL); // a matrix + size_t n_output = Y_t->dims()[1]; + + framework::LoDTensor tmp; + tmp.Resize(Y_t->dims()); + memcpy(tmp.mutable_data(platform::CPUPlace()), Y_t->data(), + Y_t->dims()[0] * Y_t->dims()[1]); + + TensorRTEngine::Weight weight{nvinfer1::DataType::kFLOAT, + static_cast(weight_data), + Y_t->memory_size() / sizeof(float)}; + TensorRTEngine::Weight tmp_weight(nvinfer1::DataType::kFLOAT, + static_cast(tmp.data()), + Y_t->memory_size() / sizeof(float)); + weight.dims.assign({Y_t->dims()[0], Y_t->dims()[1]}); + tmp_weight.dims = weight.dims; + + // The data layout of TRT FC layer's weight is different from fluid's FC, + // need to reorder the elements. + ReorderCKtoKC(tmp_weight, &weight); + + // Currently, the framework can only handle one fluid op -> one TRT layer, + // but fc fuses `mul` and `bias` (2 fluid ops), so here is a trick, just + // handle `mul`, leave `add` as another layer. + // DEBUG + TensorRTEngine::Weight bias{nvinfer1::DataType::kFLOAT, nullptr, 0}; + + auto* layer = TRT_ENGINE_ADD_LAYER(engine_, FullyConnected, + *const_cast(X), + n_output, weight.get(), bias.get()); + + auto output_name = op_desc.Output("Out").front(); + engine_->DeclareOutput(layer, 0, output_name); + } +}; + +REGISTER_TRT_OP_CONVERTER(fc, FcOpConverter); + +} // namespace tensorrt +} // namespace inference +} // namespace paddle + +USE_OP(mul); diff --git a/paddle/fluid/inference/tensorrt/convert/mul_op.cc b/paddle/fluid/inference/tensorrt/convert/mul_op.cc index aa8e66490f7..6bb07709c7e 100644 --- a/paddle/fluid/inference/tensorrt/convert/mul_op.cc +++ b/paddle/fluid/inference/tensorrt/convert/mul_op.cc @@ -24,8 +24,9 @@ namespace tensorrt { class MulOpConverter : public OpConverter { public: MulOpConverter() {} - void operator()(const framework::proto::OpDesc& op) override { - VLOG(4) << "convert a fluid mul op to tensorrt fc layer without bias"; + void operator()(const framework::proto::OpDesc& op, + const framework::Scope& scope) override { + VLOG(4) << "convert a fluid mul op to tensorrt mul layer without bias"; framework::OpDesc op_desc(op, nullptr); // Declare inputs diff --git a/paddle/fluid/inference/tensorrt/convert/op_converter.h b/paddle/fluid/inference/tensorrt/convert/op_converter.h index 1cd3ed9a00a..4d21e241c0f 100644 --- a/paddle/fluid/inference/tensorrt/convert/op_converter.h +++ b/paddle/fluid/inference/tensorrt/convert/op_converter.h @@ -31,27 +31,42 @@ namespace tensorrt { class OpConverter { public: OpConverter() {} - virtual void operator()(const framework::proto::OpDesc& op) {} - void Run(const framework::proto::OpDesc& op, TensorRTEngine* engine) { - std::string type = op.type(); - auto* it = Registry::Lookup(type); - PADDLE_ENFORCE_NOT_NULL(it, "no OpConverter for optype [%s]", type); - it->SetEngine(engine); - (*it)(op); - } + // Converter logic for an op. + virtual void operator()(const framework::proto::OpDesc& op, + const framework::Scope& scope) {} + + // Convert a single fluid operaotr and add the corresponding layer to TRT. + void ConvertOp(const framework::proto::OpDesc& op, + const std::unordered_set& parameters, + const framework::Scope& scope, TensorRTEngine* engine) { + framework::OpDesc op_desc(op, nullptr, nullptr); + + OpConverter* it{nullptr}; - // convert fluid op to tensorrt layer - void ConvertOp(const framework::proto::OpDesc& op, TensorRTEngine* engine) { - OpConverter::Run(op, engine); + if (op_desc.Type() == "mul") { + PADDLE_ENFORCE_EQ(op_desc.Input("Y").size(), 1UL); + std::string Y = op_desc.Input("Y")[0]; + if (parameters.count(Y)) { + it = Registry::Lookup("fc"); + } + } + if (!it) { + it = Registry::Lookup(op_desc.Type()); + } + PADDLE_ENFORCE_NOT_NULL(it, "no OpConverter for optype [%s]", + op_desc.Type()); + it->SetEngine(engine); + (*it)(op, scope); } // convert fluid block to tensorrt network void ConvertBlock(const framework::proto::BlockDesc& block, - TensorRTEngine* engine) { + const std::unordered_set& parameters, + const framework::Scope& scope, TensorRTEngine* engine) { for (int i = 0; i < block.ops_size(); i++) { const auto& op = block.ops(i); - OpConverter::Run(op, engine); + ConvertOp(op, parameters, scope, engine); } } diff --git a/paddle/fluid/inference/tensorrt/convert/test_fc_op.cc b/paddle/fluid/inference/tensorrt/convert/test_fc_op.cc new file mode 100644 index 00000000000..a30253072ac --- /dev/null +++ b/paddle/fluid/inference/tensorrt/convert/test_fc_op.cc @@ -0,0 +1,46 @@ +/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + +http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#include +#include "paddle/fluid/inference/tensorrt/convert/op_converter.h" +#include "paddle/fluid/inference/tensorrt/convert/ut_helper.h" + +namespace paddle { +namespace inference { +namespace tensorrt { + +TEST(fc_op, test) { + std::unordered_set parameters({"mul-Y"}); + framework::Scope scope; + TRTConvertValidation validator(20, parameters, scope, 1000); + + validator.DeclInputVar("mul-X", nvinfer1::Dims4(8, 3, 1, 1)); + validator.DeclParamVar("mul-Y", nvinfer1::Dims2(3, 2)); + validator.DeclOutputVar("mul-Out", nvinfer1::Dims2(8, 2)); + + // Prepare Op description + framework::OpDesc desc; + desc.SetType("mul"); + desc.SetInput("X", {"mul-X"}); + desc.SetInput("Y", {"mul-Y"}); + desc.SetOutput("Out", {"mul-Out"}); + + validator.SetOp(*desc.Proto()); + + validator.Execute(10); +} + +} // namespace tensorrt +} // namespace inference +} // namespace paddle diff --git a/paddle/fluid/inference/tensorrt/convert/test_mul_op.cc b/paddle/fluid/inference/tensorrt/convert/test_mul_op.cc index d8b61d5f08f..1ce1130e5d6 100644 --- a/paddle/fluid/inference/tensorrt/convert/test_mul_op.cc +++ b/paddle/fluid/inference/tensorrt/convert/test_mul_op.cc @@ -21,7 +21,9 @@ namespace inference { namespace tensorrt { TEST(MulOpConverter, main) { - TRTConvertValidation validator(10, 1000); + framework::Scope scope; + std::unordered_set parameters; + TRTConvertValidation validator(10, parameters, scope, 1000); validator.DeclInputVar("mul-X", nvinfer1::Dims2(10, 6)); validator.DeclInputVar("mul-Y", nvinfer1::Dims2(6, 10)); validator.DeclOutputVar("mul-Out", nvinfer1::Dims2(10, 10)); diff --git a/paddle/fluid/inference/tensorrt/convert/test_op_converter.cc b/paddle/fluid/inference/tensorrt/convert/test_op_converter.cc index 9ae7de9cbfa..1d3f5eabb2f 100644 --- a/paddle/fluid/inference/tensorrt/convert/test_op_converter.cc +++ b/paddle/fluid/inference/tensorrt/convert/test_op_converter.cc @@ -12,9 +12,10 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ +#include "paddle/fluid/inference/tensorrt/convert/op_converter.h" + #include #include "paddle/fluid/framework/program_desc.h" -#include "paddle/fluid/inference/tensorrt/convert/op_converter.h" namespace paddle { namespace inference { @@ -27,7 +28,9 @@ TEST(OpConverter, ConvertBlock) { conv2d_op->SetType("conv2d"); OpConverter converter; - converter.ConvertBlock(*block->Proto(), nullptr /*TensorRTEngine*/); + framework::Scope scope; + converter.ConvertBlock(*block->Proto(), {}, scope, + nullptr /*TensorRTEngine*/); } } // namespace tensorrt diff --git a/paddle/fluid/inference/tensorrt/convert/ut_helper.h b/paddle/fluid/inference/tensorrt/convert/ut_helper.h index 684bbc208fc..d7e05dd5b5b 100644 --- a/paddle/fluid/inference/tensorrt/convert/ut_helper.h +++ b/paddle/fluid/inference/tensorrt/convert/ut_helper.h @@ -61,7 +61,10 @@ class TRTConvertValidation { public: TRTConvertValidation() = delete; - explicit TRTConvertValidation(int batch_size, int workspace_size = 1024) { + TRTConvertValidation(int batch_size, + const std::unordered_set& parameters, + framework::Scope& scope, int workspace_size = 1 << 10) + : parameters_(parameters), scope_(scope) { // create engine. engine_.reset(new TensorRTEngine(10, 1 << 10, &stream_)); engine_->InitNetwork(); @@ -76,19 +79,22 @@ class TRTConvertValidation { engine_->DeclareInput(name, nvinfer1::DataType::kFLOAT, dims); } + // Declare a parameter varaible in the scope. + void DeclParamVar(const std::string& name, const nvinfer1::Dims& dims) { + DeclVar(name, dims); + } + void DeclOutputVar(const std::string& name, const nvinfer1::Dims& dims) { DeclVar(name, dims); } + // Declare a variable in a fluid Scope. void DeclVar(const std::string& name, const nvinfer1::Dims& dims) { platform::CPUPlace place; platform::CPUDeviceContext ctx(place); // Init Fluid tensor. - std::vector dim_vec(dims.nbDims); - for (int i = 0; i < dims.nbDims; i++) { - dim_vec[i] = dims.d[i]; - } + std::vector dim_vec(dims.d, dims.d + dims.nbDims); auto* x = scope_.Var(name); auto* x_tensor = x->GetMutable(); x_tensor->Resize(framework::make_ddim(dim_vec)); @@ -99,7 +105,7 @@ class TRTConvertValidation { op_ = framework::OpRegistry::CreateOp(desc); OpConverter op_converter; - op_converter.ConvertOp(desc, engine_.get()); + op_converter.ConvertOp(desc, parameters_, scope_, engine_.get()); engine_->FreezeNetwork(); @@ -108,11 +114,13 @@ class TRTConvertValidation { // Set Inputs. for (const auto& input : op_desc_->InputArgumentNames()) { + if (parameters_.count(input)) continue; auto* var = scope_.FindVar(input); PADDLE_ENFORCE(var); auto tensor = var->GetMutable(); + engine_->SetInputFromCPU( - input, static_cast(tensor->data()), + input, static_cast(tensor->data()), sizeof(float) * analysis::AccuDims(tensor->dims(), tensor->dims().size())); } @@ -120,18 +128,21 @@ class TRTConvertValidation { void Execute(int batch_size) { // Execute Fluid Op - // Execute TRT platform::CPUPlace place; platform::CPUDeviceContext ctx(place); - engine_->Execute(batch_size); - op_->Run(scope_, place); + // Execute TRT. + engine_->Execute(batch_size); + cudaStreamSynchronize(*engine_->stream()); ASSERT_FALSE(op_desc_->OutputArgumentNames().empty()); + const size_t output_space_size = 200; for (const auto& output : op_desc_->OutputArgumentNames()) { std::vector fluid_out; - std::vector trt_out(200); - engine_->GetOutputInCPU(output, &trt_out[0], 200 * sizeof(float)); + std::vector trt_out(output_space_size); + engine_->GetOutputInCPU(output, &trt_out[0], + output_space_size * sizeof(float)); + cudaStreamSynchronize(*engine_->stream()); auto* var = scope_.FindVar(output); auto tensor = var->GetMutable(); @@ -139,7 +150,7 @@ class TRTConvertValidation { // Compare two output ASSERT_FALSE(fluid_out.empty()); for (size_t i = 0; i < fluid_out.size(); i++) { - EXPECT_LT(std::abs(fluid_out[i] - trt_out[i]), 0.001); + EXPECT_LT(std::abs(fluid_out[i] - trt_out[i]), 1e-6); } } } @@ -149,9 +160,10 @@ class TRTConvertValidation { private: std::unique_ptr engine_; cudaStream_t stream_; - framework::Scope scope_; std::unique_ptr op_; std::unique_ptr op_desc_; + const std::unordered_set& parameters_; + framework::Scope& scope_; }; } // namespace tensorrt diff --git a/paddle/fluid/inference/tensorrt/engine.cc b/paddle/fluid/inference/tensorrt/engine.cc index a88236ae98e..3d75fefc1a7 100644 --- a/paddle/fluid/inference/tensorrt/engine.cc +++ b/paddle/fluid/inference/tensorrt/engine.cc @@ -106,6 +106,7 @@ void TensorRTEngine::DeclareOutput(const nvinfer1::ILayer* layer, int offset, name); auto* output = layer->getOutput(offset); + SetITensor(name, output); PADDLE_ENFORCE(output != nullptr); output->setName(name.c_str()); infer_network_->markOutput(*output); diff --git a/paddle/fluid/inference/tensorrt/engine.h b/paddle/fluid/inference/tensorrt/engine.h index d9d3163b66d..fabcfd9e80c 100644 --- a/paddle/fluid/inference/tensorrt/engine.h +++ b/paddle/fluid/inference/tensorrt/engine.h @@ -37,13 +37,15 @@ class TensorRTEngine : public EngineBase { // Weight is model parameter. class Weight { public: - Weight(nvinfer1::DataType dtype, void* value, int num_elem) { + Weight(nvinfer1::DataType dtype, void* value, size_t num_elem) { w_.type = dtype; w_.values = value; w_.count = num_elem; } const nvinfer1::Weights& get() { return w_; } + std::vector dims; + private: nvinfer1::Weights w_; }; diff --git a/paddle/fluid/operators/tensorrt_engine_op.cc b/paddle/fluid/operators/tensorrt_engine_op.cc index 83e768b4dc9..855157e7c4c 100644 --- a/paddle/fluid/operators/tensorrt_engine_op.cc +++ b/paddle/fluid/operators/tensorrt_engine_op.cc @@ -31,8 +31,9 @@ void paddle::operators::TensorRTEngineKernel::Prepare( auto max_workspace = context.Attr("max_workspace"); engine_.reset(new inference::tensorrt::TensorRTEngine( max_batch_, max_workspace, nullptr)); + // TODO(Superjomn) parameters should be passed after analysised from outside. inference::Singleton::Global().ConvertBlock( - block, engine_.get()); + block, {}, context.scope(), engine_.get()); engine_->FreezeNetwork(); } -- GitLab From 4a24c238c15212dd921bd0199beca6fc145cd62a Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Fri, 1 Jun 2018 15:43:34 +0800 Subject: [PATCH 0081/1416] refine code --- paddle/fluid/inference/io.cc | 2 +- .../tests/book/test_inference_nlp.cc | 86 +++++++++---------- paddle/fluid/inference/tests/test_helper.h | 3 - 3 files changed, 42 insertions(+), 49 deletions(-) diff --git a/paddle/fluid/inference/io.cc b/paddle/fluid/inference/io.cc index 98780b6881c..65db7c7b500 100644 --- a/paddle/fluid/inference/io.cc +++ b/paddle/fluid/inference/io.cc @@ -117,7 +117,7 @@ std::unique_ptr Load(framework::Executor* executor, std::string program_desc_str; VLOG(3) << "loading model from " << model_filename; ReadBinaryFile(model_filename, &program_desc_str); - // LOG(INFO) << program_desc_str; + std::unique_ptr main_program( new framework::ProgramDesc(program_desc_str)); diff --git a/paddle/fluid/inference/tests/book/test_inference_nlp.cc b/paddle/fluid/inference/tests/book/test_inference_nlp.cc index fba64efece8..962358d761c 100644 --- a/paddle/fluid/inference/tests/book/test_inference_nlp.cc +++ b/paddle/fluid/inference/tests/book/test_inference_nlp.cc @@ -24,23 +24,22 @@ limitations under the License. */ #include #endif -DEFINE_string(dirname, "", "Directory of the inference model."); +DEFINE_string(modelpath, "", "Directory of the inference model."); +DEFINE_string(datafile, "", "File of input index data."); DEFINE_int32(repeat, 100, "Running the inference program repeat times"); DEFINE_bool(use_mkldnn, false, "Use MKLDNN to run inference"); DEFINE_bool(prepare_vars, true, "Prepare variables before executor"); -DEFINE_bool(prepare_context, true, "Prepare Context before executor"); - DEFINE_int32(num_threads, 1, "Number of threads should be used"); -inline double get_current_ms() { +inline double GetCurrentMs() { struct timeval time; gettimeofday(&time, NULL); return 1e+3 * time.tv_sec + 1e-3 * time.tv_usec; } // return size of total words -size_t read_datasets(std::vector* out, - const std::string& filename) { +size_t LoadData(std::vector* out, + const std::string& filename) { size_t sz = 0; std::fstream fin(filename); std::string line; @@ -68,6 +67,23 @@ size_t read_datasets(std::vector* out, return sz; } +void SplitData( + const std::vector& datasets, + std::vector>* jobs, + const int num_threads) { + size_t s = 0; + jobs->resize(num_threads); + while (s < datasets.size()) { + for (auto it = jobs->begin(); it != jobs->end(); it++) { + it->emplace_back(&datasets[s]); + s++; + if (s >= datasets.size()) { + break; + } + } + } +} + void ThreadRunInfer( const int tid, paddle::framework::Executor* executor, paddle::framework::Scope* scope, @@ -80,7 +96,6 @@ void ThreadRunInfer( copy_program->SetFeedHolderName(feed_holder_name); copy_program->SetFetchHolderName(fetch_holder_name); - // 3. Get the feed_target_names and fetch_target_names const std::vector& feed_target_names = copy_program->GetFeedTargetNames(); const std::vector& fetch_target_names = @@ -95,51 +110,32 @@ void ThreadRunInfer( PADDLE_ENFORCE_EQ(feed_target_names.size(), 1UL); auto& inputs = jobs[tid]; - auto start_ms = get_current_ms(); + auto start_ms = GetCurrentMs(); for (size_t i = 0; i < inputs.size(); ++i) { feed_targets[feed_target_names[0]] = inputs[i]; executor->Run(*copy_program, scope, &feed_targets, &fetch_targets, true, true, feed_holder_name, fetch_holder_name); } - auto stop_ms = get_current_ms(); + auto stop_ms = GetCurrentMs(); LOG(INFO) << "Tid: " << tid << ", process " << inputs.size() << " samples, avg time per sample: " - << (stop_ms - start_ms) / inputs.size() << " ms"; } -void bcast_datasets( - const std::vector& datasets, - std::vector>* jobs, - const int num_threads) { - size_t s = 0; - jobs->resize(num_threads); - while (s < datasets.size()) { - for (auto it = jobs->begin(); it != jobs->end(); it++) { - it->emplace_back(&datasets[s]); - s++; - if (s >= datasets.size()) { - break; - } - } - } -} - TEST(inference, nlp) { - if (FLAGS_dirname.empty()) { - LOG(FATAL) << "Usage: ./example --dirname=path/to/your/model"; + if (FLAGS_modelpath.empty() || FLAGS_datafile.empty()) { + LOG(FATAL) << "Usage: ./example --modelpath=path/to/your/model " + << "--datafile=path/to/your/data"; } - LOG(INFO) << "FLAGS_dirname: " << FLAGS_dirname << std::endl; - std::string dirname = FLAGS_dirname; + LOG(INFO) << "Model Path: " << FLAGS_modelpath; + LOG(INFO) << "Data File: " << FLAGS_datafile; std::vector datasets; - size_t num_total_words = - read_datasets(&datasets, "/home/tangjian/paddle-tj/out.ids.txt"); - LOG(INFO) << "Number of dataset samples(seq len<1024): " << datasets.size(); + size_t num_total_words = LoadData(&datasets, FLAGS_datafile); + LOG(INFO) << "Number of samples (seq_len<1024): " << datasets.size(); LOG(INFO) << "Total number of words: " << num_total_words; const bool model_combined = false; - // 0. Call `paddle::framework::InitDevices()` initialize all the devices // 1. Define place, executor, scope auto place = paddle::platform::CPUPlace(); @@ -148,13 +144,14 @@ TEST(inference, nlp) { // 2. Initialize the inference_program and load parameters std::unique_ptr inference_program; - inference_program = InitProgram(&executor, scope, dirname, model_combined); + inference_program = + InitProgram(&executor, scope, FLAGS_modelpath, model_combined); if (FLAGS_use_mkldnn) { EnableMKLDNN(inference_program); } #ifdef PADDLE_WITH_MKLML - // only use 1 core per thread + // only use 1 thread number per std::thread omp_set_dynamic(0); omp_set_num_threads(1); mkl_set_num_threads(1); @@ -163,24 +160,23 @@ TEST(inference, nlp) { double start_ms = 0, stop_ms = 0; if (FLAGS_num_threads > 1) { std::vector> jobs; - bcast_datasets(datasets, &jobs, FLAGS_num_threads); + SplitData(datasets, &jobs, FLAGS_num_threads); std::vector> threads; for (int i = 0; i < FLAGS_num_threads; ++i) { threads.emplace_back(new std::thread(ThreadRunInfer, i, &executor, scope, std::ref(inference_program), std::ref(jobs))); } - start_ms = get_current_ms(); + start_ms = GetCurrentMs(); for (int i = 0; i < FLAGS_num_threads; ++i) { threads[i]->join(); } - stop_ms = get_current_ms(); - + stop_ms = GetCurrentMs(); } else { if (FLAGS_prepare_vars) { executor.CreateVariables(*inference_program, scope, 0); } - // always prepare context and burning first time + // always prepare context std::unique_ptr ctx; ctx = executor.Prepare(*inference_program, 0); @@ -198,14 +194,14 @@ TEST(inference, nlp) { PADDLE_ENFORCE_EQ(feed_target_names.size(), 1UL); std::map feed_targets; - // for data and run - start_ms = get_current_ms(); + // feed data and run + start_ms = GetCurrentMs(); for (size_t i = 0; i < datasets.size(); ++i) { feed_targets[feed_target_names[0]] = &(datasets[i]); executor.RunPreparedContext(ctx.get(), scope, &feed_targets, &fetch_targets, !FLAGS_prepare_vars); } - stop_ms = get_current_ms(); + stop_ms = GetCurrentMs(); } LOG(INFO) << "Total inference time with " << FLAGS_num_threads diff --git a/paddle/fluid/inference/tests/test_helper.h b/paddle/fluid/inference/tests/test_helper.h index 1f5551567c6..01b8dc0be66 100644 --- a/paddle/fluid/inference/tests/test_helper.h +++ b/paddle/fluid/inference/tests/test_helper.h @@ -182,9 +182,6 @@ void TestInference(const std::string& dirname, "init_program", paddle::platform::DeviceContextPool::Instance().Get(place)); inference_program = InitProgram(&executor, scope, dirname, is_combined); - // std::string binary_str; - // inference_program->Proto()->SerializeToString(&binary_str); - // LOG(INFO) << binary_str; if (use_mkldnn) { EnableMKLDNN(inference_program); } -- GitLab From 3206bcd9291833518289e73e37513cdbc29e96c7 Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Fri, 1 Jun 2018 16:24:55 +0800 Subject: [PATCH 0082/1416] refine log and add QPS --- paddle/fluid/inference/tests/book/test_inference_nlp.cc | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/paddle/fluid/inference/tests/book/test_inference_nlp.cc b/paddle/fluid/inference/tests/book/test_inference_nlp.cc index 962358d761c..378e1620a09 100644 --- a/paddle/fluid/inference/tests/book/test_inference_nlp.cc +++ b/paddle/fluid/inference/tests/book/test_inference_nlp.cc @@ -202,11 +202,13 @@ TEST(inference, nlp) { &fetch_targets, !FLAGS_prepare_vars); } stop_ms = GetCurrentMs(); + LOG(INFO) << "Tid: 0, process " << datasets.size() + << " samples, avg time per sample: " + << (stop_ms - start_ms) / datasets.size() << " ms"; } LOG(INFO) << "Total inference time with " << FLAGS_num_threads << " threads : " << (stop_ms - start_ms) / 1000.0 - << " sec, avg time per seq: " - << (stop_ms - start_ms) / datasets.size() << " ms"; + << " sec, QPS: " << datasets.size() / ((stop_ms - start_ms) / 1000); delete scope; } -- GitLab From 9503dbb173f76f7b68d4a6edc18ce31cf7865c30 Mon Sep 17 00:00:00 2001 From: Yan Chunwei Date: Fri, 1 Jun 2018 17:14:18 +0800 Subject: [PATCH 0083/1416] fix compile error (#11119) --- paddle/fluid/inference/tensorrt/convert/fc_op.cc | 2 +- paddle/fluid/inference/tensorrt/convert/op_converter.h | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/paddle/fluid/inference/tensorrt/convert/fc_op.cc b/paddle/fluid/inference/tensorrt/convert/fc_op.cc index bd05608d762..45b07955975 100644 --- a/paddle/fluid/inference/tensorrt/convert/fc_op.cc +++ b/paddle/fluid/inference/tensorrt/convert/fc_op.cc @@ -59,7 +59,7 @@ class FcOpConverter : public OpConverter { const framework::Scope& scope) override { VLOG(4) << "convert a fluid fc op to tensorrt fc layer without bias"; - framework::OpDesc op_desc(op, nullptr, nullptr); + framework::OpDesc op_desc(op, nullptr); PADDLE_ENFORCE_EQ(op_desc.Input("X").size(), 1); PADDLE_ENFORCE_EQ(op_desc.Input("Y").size(), 1); // Y is a weight PADDLE_ENFORCE_EQ(op_desc.Output("Out").size(), 1); diff --git a/paddle/fluid/inference/tensorrt/convert/op_converter.h b/paddle/fluid/inference/tensorrt/convert/op_converter.h index 4d21e241c0f..3beafeefd06 100644 --- a/paddle/fluid/inference/tensorrt/convert/op_converter.h +++ b/paddle/fluid/inference/tensorrt/convert/op_converter.h @@ -40,7 +40,7 @@ class OpConverter { void ConvertOp(const framework::proto::OpDesc& op, const std::unordered_set& parameters, const framework::Scope& scope, TensorRTEngine* engine) { - framework::OpDesc op_desc(op, nullptr, nullptr); + framework::OpDesc op_desc(op, nullptr); OpConverter* it{nullptr}; -- GitLab From 7e9f0790e0366ef8db3f48f83635400d4742ad71 Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Fri, 1 Jun 2018 17:24:54 +0800 Subject: [PATCH 0084/1416] fix scope in thread --- paddle/fluid/inference/tests/book/test_inference_nlp.cc | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/paddle/fluid/inference/tests/book/test_inference_nlp.cc b/paddle/fluid/inference/tests/book/test_inference_nlp.cc index 378e1620a09..f7788ccbf40 100644 --- a/paddle/fluid/inference/tests/book/test_inference_nlp.cc +++ b/paddle/fluid/inference/tests/book/test_inference_nlp.cc @@ -91,6 +91,8 @@ void ThreadRunInfer( const std::vector>& jobs) { auto copy_program = std::unique_ptr( new paddle::framework::ProgramDesc(*inference_program)); + auto& sub_scope = scope->NewScope(); + std::string feed_holder_name = "feed_" + paddle::string::to_string(tid); std::string fetch_holder_name = "fetch_" + paddle::string::to_string(tid); copy_program->SetFeedHolderName(feed_holder_name); @@ -113,10 +115,11 @@ void ThreadRunInfer( auto start_ms = GetCurrentMs(); for (size_t i = 0; i < inputs.size(); ++i) { feed_targets[feed_target_names[0]] = inputs[i]; - executor->Run(*copy_program, scope, &feed_targets, &fetch_targets, true, - true, feed_holder_name, fetch_holder_name); + executor->Run(*copy_program, &sub_scope, &feed_targets, &fetch_targets, + true, true, feed_holder_name, fetch_holder_name); } auto stop_ms = GetCurrentMs(); + scope->DeleteScope(&sub_scope); LOG(INFO) << "Tid: " << tid << ", process " << inputs.size() << " samples, avg time per sample: " << (stop_ms - start_ms) / inputs.size() << " ms"; -- GitLab From 47630a4a9e8b54dc27184586d22559b427525785 Mon Sep 17 00:00:00 2001 From: "yi.wu" Date: Fri, 1 Jun 2018 17:28:24 +0800 Subject: [PATCH 0085/1416] fluid benchmark support recordio reader --- benchmark/fluid/Dockerfile | 2 +- benchmark/fluid/README.md | 9 ++ benchmark/fluid/fluid_benchmark.py | 55 +++++--- benchmark/fluid/models/machine_translation.py | 2 + benchmark/fluid/models/mnist.py | 21 ++- benchmark/fluid/models/resnet.py | 20 ++- .../fluid/models/stacked_dynamic_lstm.py | 3 + benchmark/fluid/models/vgg.py | 21 ++- benchmark/fluid/recordio_converter.py | 133 ++++++++++++++++++ python/paddle/fluid/layers/io.py | 2 +- 10 files changed, 241 insertions(+), 27 deletions(-) create mode 100644 benchmark/fluid/recordio_converter.py diff --git a/benchmark/fluid/Dockerfile b/benchmark/fluid/Dockerfile index 46140a9d1be..5d98a9b3c42 100644 --- a/benchmark/fluid/Dockerfile +++ b/benchmark/fluid/Dockerfile @@ -19,4 +19,4 @@ ADD *.whl / RUN pip install /*.whl && rm -f /*.whl && chmod +x /usr/bin/paddle_k8s ENV LD_LIBRARY_PATH=/usr/local/lib -ADD fluid_benchmark.py dataset.py models/ /workspace/ +ADD fluid_benchmark.py recordio_converter.py models/ /workspace/ diff --git a/benchmark/fluid/README.md b/benchmark/fluid/README.md index 1b0c7dce8bd..c17cab999b5 100644 --- a/benchmark/fluid/README.md +++ b/benchmark/fluid/README.md @@ -42,6 +42,15 @@ Currently supported `--model` argument include: PADDLE_PSERVER_PORT=7164 PADDLE_TRAINER_IPS=192.168.0.2,192.168.0.3 PADDLE_CURRENT_IP=127.0.0.1 PADDLE_TRAINER_ID=0 python fluid_benchmark.py --model mnist --device GPU --update_method nccl2 ``` +## Prepare the RecordIO file to Achieve Better Performance + +Run the following command will generate RecordIO files like "mnist.recordio" under the path +and batch_size you choose: + +```bash +python -c 'from recordio_converter import *; prepare_mnist("data", 32)' +``` + ## Run Distributed Benchmark on Kubernetes Cluster You may need to build a Docker image before submitting a cluster job onto Kubernetes, or you will diff --git a/benchmark/fluid/fluid_benchmark.py b/benchmark/fluid/fluid_benchmark.py index c1d458970a5..9dce7d56478 100644 --- a/benchmark/fluid/fluid_benchmark.py +++ b/benchmark/fluid/fluid_benchmark.py @@ -44,7 +44,6 @@ def parse_args(): type=float, default=0.001, help='The minibatch size.') - # TODO(wuyi): add "--use_fake_data" option back. parser.add_argument( '--skip_batch_num', type=int, @@ -106,6 +105,16 @@ def parse_args(): default='local', choices=['local', 'pserver', 'nccl2'], help='Choose parameter update method, can be local, pserver, nccl2.') + parser.add_argument( + '--use_reader_op', + action='store_true', + help='Whether to use reader op, and must specify the data path if set this to true.' + ) + parser.add_argument( + '--data_path', + type=str, + default="", + help='Directory that contains all the training recordio files.') args = parser.parse_args() return args @@ -208,11 +217,13 @@ def train(avg_loss, infer_prog, optimizer, train_reader, test_reader, batch_acc, place = core.CPUPlace() if args.device == 'CPU' else core.CUDAPlace(0) exe = fluid.Executor(place) exe.run(startup_prog) - feed_var_list = [ - var for var in train_prog.global_block().vars.itervalues() - if var.is_data - ] - feeder = fluid.DataFeeder(feed_var_list, place) + + if not args.use_reader_op: + feed_var_list = [ + var for var in train_prog.global_block().vars.itervalues() + if var.is_data + ] + feeder = fluid.DataFeeder(feed_var_list, place) iters, num_samples, start_time = 0, 0, time.time() for pass_id in range(args.pass_num): @@ -223,9 +234,12 @@ def train(avg_loss, infer_prog, optimizer, train_reader, test_reader, batch_acc, num_samples = 0 if iters == args.iterations: break - loss = exe.run(train_prog, - feed=feeder.feed(data), - fetch_list=[avg_loss]) + if args.use_reader_op: + loss = exe.run(train_prog, fetch_list=[avg_loss]) + else: + loss = exe.run(train_prog, + feed=feeder.feed(data), + fetch_list=[avg_loss]) iters += 1 num_samples += len(data) train_losses.append(loss) @@ -251,10 +265,14 @@ def train(avg_loss, infer_prog, optimizer, train_reader, test_reader, batch_acc, def train_parallel(avg_loss, infer_prog, optimizer, train_reader, test_reader, batch_acc, args, train_prog, startup_prog, nccl_id_var, num_trainers, trainer_id): - feed_var_list = [ - var for var in train_prog.global_block().vars.itervalues() - if var.is_data - ] + place = core.CPUPlace() if args.device == 'CPU' else core.CUDAPlace(0) + if not args.use_reader_op: + feed_var_list = [ + var for var in train_prog.global_block().vars.itervalues() + if var.is_data + ] + feeder = fluid.DataFeeder(feed_var_list, place) + # generate fake: if args.use_fake_data: for var in feed_var_list: @@ -271,7 +289,6 @@ def train_parallel(avg_loss, infer_prog, optimizer, train_reader, test_reader, "value": 1.0, "dtype": var.dtype}) - place = core.CPUPlace() if args.device == 'CPU' else core.CUDAPlace(0) if nccl_id_var and trainer_id == 0: #FIXME(wuyi): wait other trainer to start listening time.sleep(30) @@ -288,7 +305,6 @@ def train_parallel(avg_loss, infer_prog, optimizer, train_reader, test_reader, num_trainers=num_trainers, trainer_id=trainer_id) - feeder = fluid.DataFeeder(feed_var_list, place) for pass_id in range(args.pass_num): num_samples = 0 iters = 0 @@ -304,7 +320,10 @@ def train_parallel(avg_loss, infer_prog, optimizer, train_reader, test_reader, num_samples = 0 if iters == args.iterations: break - if args.use_fake_data: + # NOTE: if use reader ops, the input data is not splited to multiple cards + if args.use_reader_op and iters >= args.iterations / args.gpus: + break + if args.use_fake_data or args.use_reader_op: loss, = exe.run([avg_loss.name]) else: loss, = exe.run([avg_loss.name], feed=feeder.feed(data)) @@ -316,6 +335,8 @@ def train_parallel(avg_loss, infer_prog, optimizer, train_reader, test_reader, print("Pass %d, batch %d, loss %s" % (pass_id, batch_id, np.array(loss))) train_elapsed = time.time() - start_time + if args.use_reader_op: + num_samples = num_samples * args.gpus examples_per_sec = num_samples / train_elapsed print('\nTotal examples: %d, total time: %.5f, %.5f examples/sed\n' % (num_samples, train_elapsed, examples_per_sec)) @@ -342,7 +363,7 @@ def main(): # the unique trainer id, starting from 0, needed by trainer # only nccl_id_var, num_trainers, trainer_id = ( - None, 1, int(os.getenv("PADDLE_TRAINER_ID", "-1"))) + None, 1, int(os.getenv("PADDLE_TRAINER_ID", "0"))) if args.use_cprof: pr = cProfile.Profile() diff --git a/benchmark/fluid/models/machine_translation.py b/benchmark/fluid/models/machine_translation.py index 635b3373dd2..3024882725d 100644 --- a/benchmark/fluid/models/machine_translation.py +++ b/benchmark/fluid/models/machine_translation.py @@ -197,6 +197,8 @@ def lodtensor_to_ndarray(lod_tensor): def get_model(args): + if args.use_reader_op: + raise Exception("machine_translation do not support reader op for now.") embedding_dim = 512 encoder_size = 512 decoder_size = 512 diff --git a/benchmark/fluid/models/mnist.py b/benchmark/fluid/models/mnist.py index d264bfc12bd..5d3da68dafa 100644 --- a/benchmark/fluid/models/mnist.py +++ b/benchmark/fluid/models/mnist.py @@ -20,6 +20,7 @@ import numpy as np import argparse import time import cProfile +import os import paddle import paddle.fluid as fluid @@ -65,9 +66,23 @@ def cnn_model(data): def get_model(args): - # Input data - images = fluid.layers.data(name='pixel', shape=[1, 28, 28], dtype=DTYPE) - label = fluid.layers.data(name='label', shape=[1], dtype='int64') + if args.use_reader_op: + filelist = [ + os.path.join(args.data_path, f) for f in os.listdir(args.data_path) + ] + data_file = fluid.layers.open_files( + filenames=filelist, + shapes=[[-1, 1, 28, 28], (-1, 1)], + lod_levels=[0, 0], + dtypes=["float32", "int64"], + thread_num=args.gpus) + data_file = fluid.layers.double_buffer( + fluid.layers.batch( + data_file, batch_size=args.batch_size)) + images, label = fluid.layers.read_file(data_file) + else: + images = fluid.layers.data(name='pixel', shape=[1, 28, 28], dtype=DTYPE) + label = fluid.layers.data(name='label', shape=[1], dtype='int64') # Train program predict = cnn_model(images) diff --git a/benchmark/fluid/models/resnet.py b/benchmark/fluid/models/resnet.py index 9dec8911ed6..35daad6664b 100644 --- a/benchmark/fluid/models/resnet.py +++ b/benchmark/fluid/models/resnet.py @@ -19,6 +19,7 @@ from __future__ import print_function import functools import numpy as np import time +import os import cProfile, pstats, StringIO @@ -129,9 +130,24 @@ def get_model(args): else: dshape = [224, 224, 3] model = resnet_imagenet + if args.use_reader_op: + filelist = [ + os.path.join(args.data_path, f) for f in os.listdir(args.data_path) + ] + data_file = fluid.layers.open_files( + filenames=filelist, + shapes=[[-1] + dshape, (-1, 1)], + lod_levels=[0, 0], + dtypes=["float32", "int64"], + thread_num=args.gpus) + data_file = fluid.layers.double_buffer( + fluid.layers.batch( + data_file, batch_size=args.batch_size)) + input, label = fluid.layers.read_file(data_file) + else: + input = fluid.layers.data(name='data', shape=dshape, dtype='float32') + label = fluid.layers.data(name='label', shape=[1], dtype='int64') - input = fluid.layers.data(name='data', shape=dshape, dtype='float32') - label = fluid.layers.data(name='label', shape=[1], dtype='int64') predict = model(input, class_dim) cost = fluid.layers.cross_entropy(input=predict, label=label) avg_cost = fluid.layers.mean(x=cost) diff --git a/benchmark/fluid/models/stacked_dynamic_lstm.py b/benchmark/fluid/models/stacked_dynamic_lstm.py index 81a28b5f3ae..e2a8cf45ac3 100644 --- a/benchmark/fluid/models/stacked_dynamic_lstm.py +++ b/benchmark/fluid/models/stacked_dynamic_lstm.py @@ -44,6 +44,9 @@ def crop_sentence(reader, crop_size): def get_model(args): + if args.use_reader_op: + raise Exception( + "stacked_dynamic_lstm do not support reader op for now.") lstm_size = 512 emb_dim = 512 crop_size = 1500 diff --git a/benchmark/fluid/models/vgg.py b/benchmark/fluid/models/vgg.py index 53856c5f7ac..b84e118a88e 100644 --- a/benchmark/fluid/models/vgg.py +++ b/benchmark/fluid/models/vgg.py @@ -22,6 +22,7 @@ import paddle.fluid as fluid import paddle.fluid.core as core import argparse import functools +import os def vgg16_bn_drop(input): @@ -65,9 +66,23 @@ def get_model(args): else: data_shape = [224, 224, 3] - # Input data - images = fluid.layers.data(name='pixel', shape=data_shape, dtype='float32') - label = fluid.layers.data(name='label', shape=[1], dtype='int64') + if args.use_reader_op: + filelist = [ + os.path.join(args.data_path, f) for f in os.listdir(args.data_path) + ] + data_file = fluid.layers.open_files( + filenames=filelist, + shapes=[[-1] + data_shape, (-1, 1)], + lod_levels=[0, 0], + dtypes=["float32", "int64"], + thread_num=args.gpus) + data_file = fluid.layers.double_buffer( + fluid.layers.batch( + data_file, batch_size=args.batch_size)) + images, label = fluid.layers.read_file(data_file) + else: + images = fluid.layers.data(name='data', shape=dshape, dtype='float32') + label = fluid.layers.data(name='label', shape=[1], dtype='int64') # Train program net = vgg16_bn_drop(images) diff --git a/benchmark/fluid/recordio_converter.py b/benchmark/fluid/recordio_converter.py new file mode 100644 index 00000000000..c69062c4a1f --- /dev/null +++ b/benchmark/fluid/recordio_converter.py @@ -0,0 +1,133 @@ +# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import os +import paddle +import paddle.fluid as fluid +import paddle.fluid.core as core +from paddle.dataset import mnist, cifar, flowers, image + + +def convert_2_recordio(py_reader, outfilepath, batch_size, shape_data, + shape_label): + num_batches = 0 + with fluid.program_guard(fluid.Program(), fluid.Program()): + reader = paddle.batch(py_reader(), batch_size=batch_size) + feeder = fluid.DataFeeder( + feed_list=[ # order is image and label + fluid.layers.data( + name='image', shape=shape_data), + fluid.layers.data( + name='label', shape=shape_label, dtype='int64'), + ], + place=fluid.CPUPlace()) + num_batches = fluid.recordio_writer.convert_reader_to_recordio_file( + outfilepath, reader, feeder) + return num_batches + + +def prepare_mnist(outpath, batch_size): + outfilepath = os.path.join(outpath, "mnist.recordio") + convert_2_recordio(mnist.train, outfilepath, batch_size, [784], [1]) + + +def prepare_cifar10(outpath, batch_size): + outfilepath = os.path.join(outpath, "cifar.recordio") + convert_2_recordio(cifar.train10, outfilepath, batch_size, [3, 32, 32], [1]) + + +def prepare_flowers(outpath, batch_size): + outfilepath = os.path.join(outpath, "flowers.recordio") + convert_2_recordio(flowers.train, outfilepath, batch_size, [3, 224, 224], + [1]) + + +def imagenet_train(data_dir): + contents = os.listdir(data_dir) + if set(contents) != set( + ["train", "train.txt", "val", "val_set", "val.txt", "unzip.sh"]): + raise Exception("Imagenet data contents error!") + img2label = dict() + imgfilelist = [] + with open(os.path.join(data_dir, "train.txt")) as fn: + while 1: + l = fn.readline() + if not l: + break + img, lbl = l[:-1].split(" ") + img2label[img] = int(lbl) + imgfilelist.append(img) + + def train_reader(): + for idx, imgfile in enumerate(imgfilelist): + data = image.load_image( + os.path.join(data_dir, "train", imgfile.lower())) + label = [img2label[imgfile], ] + yield [data, label] + + def default_mapper(sample): + img, label = sample + img = image.simple_transform( + img, 256, 224, True, mean=[103.94, 116.78, 123.68]) + return img.flatten().astype('float32'), label + + return paddle.reader.map_readers(default_mapper, train_reader) + + +# FIXME(wuyi): delete this when https://github.com/PaddlePaddle/Paddle/pull/11066 is merged +def convert_reader_to_recordio_files( + filename, + batch_per_file, + reader_creator, + feeder, + compressor=core.RecordIOWriter.Compressor.Snappy, + max_num_records=1000, + feed_order=None): + if feed_order is None: + feed_order = feeder.feed_names + f_name, f_ext = os.path.splitext(filename) + assert (f_ext == ".recordio") + + lines = [] + f_idx = 0 + counter = 0 + for idx, batch in enumerate(reader_creator()): + lines.append(batch) + if idx >= batch_per_file and idx % batch_per_file == 0: + filename = "%s-%05d%s" % (f_name, f_idx, f_ext) + with fluid.recordio_writer.create_recordio_writer( + filename, compressor, max_num_records) as writer: + for l in lines: + res = feeder.feed(l) + for each in feed_order: + writer.append_tensor(res[each]) + writer.complete_append_tensor() + counter += 1 + lines = [] + f_idx += 1 + print("written file: ", filename) + return counter + + +def prepare_imagenet(inpath, outpath, batch_size): + r = paddle.batch(imagenet_train(inpath), batch_size=batch_size) + feeder = fluid.DataFeeder( + feed_list=[ + fluid.layers.data( + name="image", shape=[3, 224, 224]), fluid.layers.data( + name="label", shape=[1], dtype='int64') + ], + place=fluid.CPUPlace()) + outpath = os.path.join(outpath, "imagenet.recordio") + convert_reader_to_recordio_files(outpath, 10000, r, feeder) diff --git a/python/paddle/fluid/layers/io.py b/python/paddle/fluid/layers/io.py index 8758ac9f94a..a56f3ea9db6 100644 --- a/python/paddle/fluid/layers/io.py +++ b/python/paddle/fluid/layers/io.py @@ -434,7 +434,7 @@ def open_files(filenames, shapes, lod_levels, dtypes, - thread_num, + thread_num=1, buffer_size=None, pass_num=1, for_parallel=True): -- GitLab From 86a61c177f484f3f073449cbe2bbc581cc170650 Mon Sep 17 00:00:00 2001 From: yuyang18 Date: Thu, 31 May 2018 19:37:32 +0800 Subject: [PATCH 0086/1416] Add ScopeBufferedSSAGraphExecutor --- paddle/fluid/framework/CMakeLists.txt | 2 +- paddle/fluid/framework/details/CMakeLists.txt | 1 + .../framework/details/execution_strategy.h | 1 + .../scope_buffered_ssa_graph_executor.cc | 76 +++++++++++++++++++ .../scope_buffered_ssa_graph_executor.h | 53 +++++++++++++ .../framework/details/ssa_graph_executor.cc | 4 - .../framework/details/ssa_graph_executor.h | 6 +- .../details/threaded_ssa_graph_executor.cc | 6 +- .../details/threaded_ssa_graph_executor.h | 1 + paddle/fluid/framework/parallel_executor.cc | 58 ++++---------- paddle/fluid/pybind/pybind.cc | 8 ++ 11 files changed, 162 insertions(+), 54 deletions(-) create mode 100644 paddle/fluid/framework/details/scope_buffered_ssa_graph_executor.cc create mode 100644 paddle/fluid/framework/details/scope_buffered_ssa_graph_executor.h diff --git a/paddle/fluid/framework/CMakeLists.txt b/paddle/fluid/framework/CMakeLists.txt index ed1e70c6460..dbd375aa31b 100644 --- a/paddle/fluid/framework/CMakeLists.txt +++ b/paddle/fluid/framework/CMakeLists.txt @@ -87,7 +87,7 @@ cc_library(executor SRCS executor.cc DEPS op_registry device_context scope framework_proto glog lod_rank_table feed_fetch_method) -cc_library(parallel_executor SRCS parallel_executor.cc DEPS multi_devices_graph_builder threaded_ssa_graph_executor) +cc_library(parallel_executor SRCS parallel_executor.cc DEPS multi_devices_graph_builder threaded_ssa_graph_executor scope_buffered_ssa_graph_executor) cc_library(prune SRCS prune.cc DEPS framework_proto) cc_test(prune_test SRCS prune_test.cc DEPS op_info prune recurrent_op device_context) diff --git a/paddle/fluid/framework/details/CMakeLists.txt b/paddle/fluid/framework/details/CMakeLists.txt index 1bcd8412eb2..c026e6c100a 100644 --- a/paddle/fluid/framework/details/CMakeLists.txt +++ b/paddle/fluid/framework/details/CMakeLists.txt @@ -36,5 +36,6 @@ cc_test(broadcast_op_test SRCS broadcast_op_handle_test.cc DEPS var_handle op_ha device_context broadcast_op_handle) cc_test(gather_op_test SRCS gather_op_handle_test.cc DEPS var_handle op_handle_base scope ddim memory device_context gather_op_handle) +cc_library(scope_buffered_ssa_graph_executor SRCS scope_buffered_ssa_graph_executor.cc DEPS ssa_graph_executor) #cc_test(reduce_op_handle_test SRCS reduce_op_handle_test.cc DEPS var_handle op_handle_base scope ddim memory # device_context reduce_op_handle ) diff --git a/paddle/fluid/framework/details/execution_strategy.h b/paddle/fluid/framework/details/execution_strategy.h index e8d510ec955..e7aa74742f8 100644 --- a/paddle/fluid/framework/details/execution_strategy.h +++ b/paddle/fluid/framework/details/execution_strategy.h @@ -22,6 +22,7 @@ struct ExecutionStrategy { size_t num_threads_{0}; bool use_event_{true}; bool allow_op_delay_{false}; + size_t num_iteration_per_drop_scope_{100}; }; } // namespace details diff --git a/paddle/fluid/framework/details/scope_buffered_ssa_graph_executor.cc b/paddle/fluid/framework/details/scope_buffered_ssa_graph_executor.cc new file mode 100644 index 00000000000..eb4e7ec52f9 --- /dev/null +++ b/paddle/fluid/framework/details/scope_buffered_ssa_graph_executor.cc @@ -0,0 +1,76 @@ +// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "paddle/fluid/framework/details/scope_buffered_ssa_graph_executor.h" +#include +#include +#include "paddle/fluid/framework/executor.h" + +namespace paddle { +namespace framework { +namespace details { +ScopeBufferedSSAGraphExecutor::ScopeBufferedSSAGraphExecutor( + ExecutionStrategy strategy, std::vector local_scopes, + std::vector var_infos, std::vector places, + std::unique_ptr &&underlying_executor) + : strategy_(std::move(strategy)), + underlying_executor_(std::move(underlying_executor)), + local_scopes_(std::move(local_scopes)), + var_infos_(std::move(var_infos)), + places_(std::move(places)) {} + +FeedFetchList ScopeBufferedSSAGraphExecutor::Run( + const std::vector &fetch_tensors) { + if (drop_scope_counter_ == 0) { + // Create local scopes. + for (auto it = local_scopes_.rbegin(); it != local_scopes_.rend(); ++it) { + auto &scope = *it; + Scope &local_scope = scope->NewScope(); + *scope->Var(details::kLocalExecScopeName)->GetMutable() = + &local_scope; + + for (auto &info : var_infos_) { + if (scope->FindVar(info.name_) != nullptr) { + continue; + } + + if (info.persistable_) { // Persistable + InitializeVariable(scope->Var(info.name_), info.type_); + } else { + InitializeVariable(local_scope.Var(info.name_), info.type_); + } + } + } + } + + auto fetch_data = underlying_executor_->Run(fetch_tensors); + drop_scope_counter_ += 1; + if (!fetch_tensors.empty() || + drop_scope_counter_ == strategy_.num_iteration_per_drop_scope_) { + drop_scope_counter_ = 0; + // Wait All computational streams + for (auto p : places_) { + platform::DeviceContextPool::Instance().Get(p)->Wait(); + } + for (auto &scope : local_scopes_) { + auto &local_scope = + *scope->Var(details::kLocalExecScopeName)->GetMutable(); + scope->DeleteScope(local_scope); + } + } + return fetch_data; +} +} // namespace details +} // namespace framework +} // namespace paddle diff --git a/paddle/fluid/framework/details/scope_buffered_ssa_graph_executor.h b/paddle/fluid/framework/details/scope_buffered_ssa_graph_executor.h new file mode 100644 index 00000000000..20df7a4722d --- /dev/null +++ b/paddle/fluid/framework/details/scope_buffered_ssa_graph_executor.h @@ -0,0 +1,53 @@ +// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#pragma once + +#include +#include +#include +#include "paddle/fluid/framework/details/execution_strategy.h" +#include "paddle/fluid/framework/details/ssa_graph_executor.h" +#include "paddle/fluid/framework/scope.h" +#include "paddle/fluid/platform/place.h" +namespace paddle { +namespace framework { +namespace details { + +struct VariableInfo { + std::string name_; + proto::VarType::Type type_; + bool persistable_; +}; + +class ScopeBufferedSSAGraphExecutor : public SSAGraphExecutor { + public: + ScopeBufferedSSAGraphExecutor( + ExecutionStrategy strategy, std::vector local_scopes, + std::vector var_infos, std::vector places, + std::unique_ptr&& underlying_executor); + FeedFetchList Run(const std::vector& fetch_tensors) override; + + private: + size_t drop_scope_counter_{0}; + + ExecutionStrategy strategy_; + std::unique_ptr underlying_executor_; + std::vector local_scopes_; + std::vector var_infos_; + std::vector places_; +}; +} // namespace details +} // namespace framework +} // namespace paddle diff --git a/paddle/fluid/framework/details/ssa_graph_executor.cc b/paddle/fluid/framework/details/ssa_graph_executor.cc index 8da6ca889b8..09b97bd0d98 100644 --- a/paddle/fluid/framework/details/ssa_graph_executor.cc +++ b/paddle/fluid/framework/details/ssa_graph_executor.cc @@ -17,10 +17,6 @@ namespace paddle { namespace framework { namespace details { - -SSAGraphExecutor::SSAGraphExecutor(std::unique_ptr &&graph) - : graph_(std::move(graph)) {} - SSAGraphExecutor::~SSAGraphExecutor() {} } // namespace details diff --git a/paddle/fluid/framework/details/ssa_graph_executor.h b/paddle/fluid/framework/details/ssa_graph_executor.h index a8833b7388a..95808603360 100644 --- a/paddle/fluid/framework/details/ssa_graph_executor.h +++ b/paddle/fluid/framework/details/ssa_graph_executor.h @@ -28,15 +28,11 @@ class SSAGraphExecutor { DISABLE_COPY_AND_ASSIGN(SSAGraphExecutor); public: - // Steal graph inside - explicit SSAGraphExecutor(std::unique_ptr &&graph); + SSAGraphExecutor() {} virtual ~SSAGraphExecutor(); virtual FeedFetchList Run(const std::vector &fetch_tensors) = 0; - - protected: - std::unique_ptr graph_; }; } // namespace details } // namespace framework diff --git a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc index 815f739371e..496fadd04da 100644 --- a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc +++ b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc @@ -21,7 +21,7 @@ ThreadedSSAGraphExecutor::ThreadedSSAGraphExecutor( const ExecutionStrategy &strategy, const std::vector &local_scopes, const std::vector &places, std::unique_ptr &&graph) - : SSAGraphExecutor(std::move(graph)), + : graph_(std::move(graph)), pool_(strategy.num_threads_ >= 2 ? new ::ThreadPool(strategy.num_threads_) : nullptr), local_scopes_(local_scopes), @@ -189,7 +189,9 @@ void ThreadedSSAGraphExecutor::RunOp( BlockingQueue *ready_var_q, details::OpHandleBase *op) { auto op_run = [ready_var_q, op, this] { try { - VLOG(10) << op << " " << op->Name() << " : " << op->DebugString(); + if (VLOG_IS_ON(10)) { + VLOG(10) << op << " " << op->Name() << " : " << op->DebugString(); + } op->Run(strategy_.use_event_); VLOG(10) << op << " " << op->Name() << " Done "; running_ops_--; diff --git a/paddle/fluid/framework/details/threaded_ssa_graph_executor.h b/paddle/fluid/framework/details/threaded_ssa_graph_executor.h index 1f7f88d7521..4a2075f1ccc 100644 --- a/paddle/fluid/framework/details/threaded_ssa_graph_executor.h +++ b/paddle/fluid/framework/details/threaded_ssa_graph_executor.h @@ -51,6 +51,7 @@ class ThreadedSSAGraphExecutor : public SSAGraphExecutor { details::OpHandleBase *op); private: + std::unique_ptr graph_; std::unique_ptr<::ThreadPool> pool_; std::vector local_scopes_; std::vector places_; diff --git a/paddle/fluid/framework/parallel_executor.cc b/paddle/fluid/framework/parallel_executor.cc index 50c3468d556..003304b85af 100644 --- a/paddle/fluid/framework/parallel_executor.cc +++ b/paddle/fluid/framework/parallel_executor.cc @@ -23,6 +23,7 @@ limitations under the License. */ #endif #include "paddle/fluid/framework/details/multi_devices_graph_builder.h" +#include "paddle/fluid/framework/details/scope_buffered_ssa_graph_executor.h" #include "paddle/fluid/framework/details/threaded_ssa_graph_executor.h" #include "paddle/fluid/platform/profiler.h" @@ -42,8 +43,6 @@ class ParallelExecutorPrivate { #ifdef PADDLE_WITH_CUDA std::unique_ptr nccl_ctxs_; #endif - - std::vector> var_types_; bool own_local_scope; }; @@ -92,9 +91,18 @@ ParallelExecutor::ParallelExecutor( local_scopes.empty()) { // Is CUDA BCastParamsToGPUs(bcast_vars); } -// Startup Program has been run. All local scopes has correct parameters. + // Startup Program has been run. All local scopes has correct parameters. + + // Step 2. Create vars in each scope; + std::vector var_infos; + for (auto *var : main_program.Block(0).AllVars()) { + var_infos.emplace_back(); + var_infos.back().name_ = var->Name(); + var_infos.back().type_ = var->GetType(); + var_infos.back().persistable_ = var->Persistable(); + } -// Step 2. Convert main_program to SSA form and dependency graph. Also, insert +// Step 3. Convert main_program to SSA form and dependency graph. Also, insert // ncclOp #ifdef PADDLE_WITH_CUDA details::MultiDevSSAGraphBuilder builder( @@ -105,16 +113,15 @@ ParallelExecutor::ParallelExecutor( params, member_->local_scopes_, build_strategy); #endif + auto graph = builder.Build(main_program); member_->executor_.reset(new details::ThreadedSSAGraphExecutor( exec_strategy, member_->local_scopes_, places, std::move(graph))); - // Step 3. Create vars in each scope; - for (auto *var : main_program.Block(0).AllVars()) { - member_->var_types_.emplace_back(var->Name(), var->GetType(), - var->Persistable()); - } + member_->executor_.reset(new details::ScopeBufferedSSAGraphExecutor( + exec_strategy, member_->local_scopes_, std::move(var_infos), + member_->places_, std::move(member_->executor_))); } void ParallelExecutor::BCastParamsToGPUs( @@ -169,42 +176,9 @@ void ParallelExecutor::BCastParamsToGPUs( void ParallelExecutor::Run(const std::vector &fetch_tensors, const std::string &fetched_var_name) { platform::RecordBlock b(0); - // Create local scopes. - for (auto it = member_->local_scopes_.rbegin(); - it != member_->local_scopes_.rend(); ++it) { - auto &scope = *it; - Scope &local_scope = scope->NewScope(); - *scope->Var(details::kLocalExecScopeName)->GetMutable() = - &local_scope; - - for (auto &name_type_pair : member_->var_types_) { - if (scope->FindVar(std::get<0>(name_type_pair)) != nullptr) { - continue; - } - - if (std::get<2>(name_type_pair)) { // Persistable - InitializeVariable(scope->Var(std::get<0>(name_type_pair)), - std::get<1>(name_type_pair)); - } else { - InitializeVariable(local_scope.Var(std::get<0>(name_type_pair)), - std::get<1>(name_type_pair)); - } - } - } - auto fetch_data = member_->executor_->Run(fetch_tensors); *member_->global_scope_->Var(fetched_var_name)->GetMutable() = fetch_data; - - // Wait All computational streams - for (auto p : member_->places_) { - platform::DeviceContextPool::Instance().Get(p)->Wait(); - } - for (auto &scope : member_->local_scopes_) { - auto &local_scope = - *scope->Var(details::kLocalExecScopeName)->GetMutable(); - scope->DeleteScope(local_scope); - } } void ParallelExecutor::FeedTensorsIntoLocalScopes( diff --git a/paddle/fluid/pybind/pybind.cc b/paddle/fluid/pybind/pybind.cc index 3af8941be69..03cf417b62f 100644 --- a/paddle/fluid/pybind/pybind.cc +++ b/paddle/fluid/pybind/pybind.cc @@ -519,6 +519,14 @@ All parameter, weight, gradient are variables in Paddle. [](const ExecutionStrategy &self) { return self.allow_op_delay_; }, [](ExecutionStrategy &self, bool allow_op_delay) { self.allow_op_delay_ = allow_op_delay; + }) + .def_property( + "num_iteration_per_drop_scope", + [](const ExecutionStrategy &self) { + return self.num_iteration_per_drop_scope_; + }, + [](ExecutionStrategy &self, size_t num_iteration_per_drop_scope) { + self.num_iteration_per_drop_scope_ = num_iteration_per_drop_scope; }); py::class_ build_strategy(pe, "BuildStrategy"); -- GitLab From 7cf8b656a20578443694e4118464e06fb13f8539 Mon Sep 17 00:00:00 2001 From: yuyang18 Date: Thu, 31 May 2018 20:10:09 +0800 Subject: [PATCH 0087/1416] Remove lock in device context --- paddle/fluid/platform/device_context.cc | 1 - paddle/fluid/platform/device_context.h | 3 --- 2 files changed, 4 deletions(-) diff --git a/paddle/fluid/platform/device_context.cc b/paddle/fluid/platform/device_context.cc index 1f733d71bdf..6c50ab2685c 100644 --- a/paddle/fluid/platform/device_context.cc +++ b/paddle/fluid/platform/device_context.cc @@ -175,7 +175,6 @@ CUDADeviceContext::~CUDADeviceContext() { Place CUDADeviceContext::GetPlace() const { return place_; } void CUDADeviceContext::Wait() const { - std::lock_guard guard(mutex_); PADDLE_ENFORCE(cudaStreamSynchronize(stream_)); PADDLE_ENFORCE(cudaGetLastError()); } diff --git a/paddle/fluid/platform/device_context.h b/paddle/fluid/platform/device_context.h index a9c1984616b..6b82d93237b 100644 --- a/paddle/fluid/platform/device_context.h +++ b/paddle/fluid/platform/device_context.h @@ -100,7 +100,6 @@ class CUDADeviceContext : public DeviceContext { template void RecordEvent(cudaEvent_t ev, Callback callback) { - std::lock_guard guard(mutex_); callback(); PADDLE_ENFORCE(cudaEventRecord(ev, stream_)); } @@ -110,8 +109,6 @@ class CUDADeviceContext : public DeviceContext { std::unique_ptr eigen_device_; std::unique_ptr eigen_stream_; - - mutable std::recursive_mutex mutex_; cudaStream_t stream_; cudnnHandle_t cudnn_handle_; cublasHandle_t cublas_handle_; -- GitLab From c5115950a87df858f963a06b71282bcda2cce920 Mon Sep 17 00:00:00 2001 From: yuyang18 Date: Fri, 1 Jun 2018 11:17:50 +0800 Subject: [PATCH 0088/1416] Use static for dlsym --- paddle/fluid/platform/dynload/cublas.h | 2 +- paddle/fluid/platform/dynload/cudnn.h | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/paddle/fluid/platform/dynload/cublas.h b/paddle/fluid/platform/dynload/cublas.h index 81acaff87d3..25bcda7eedc 100644 --- a/paddle/fluid/platform/dynload/cublas.h +++ b/paddle/fluid/platform/dynload/cublas.h @@ -45,7 +45,7 @@ extern void *cublas_dso_handle; std::call_once(cublas_dso_flag, []() { \ cublas_dso_handle = paddle::platform::dynload::GetCublasDsoHandle(); \ }); \ - void *p_##__name = dlsym(cublas_dso_handle, #__name); \ + static void *p_##__name = dlsym(cublas_dso_handle, #__name); \ return reinterpret_cast(p_##__name)(args...); \ } \ }; \ diff --git a/paddle/fluid/platform/dynload/cudnn.h b/paddle/fluid/platform/dynload/cudnn.h index 34d83e39569..77e46fa768b 100644 --- a/paddle/fluid/platform/dynload/cudnn.h +++ b/paddle/fluid/platform/dynload/cudnn.h @@ -39,7 +39,7 @@ extern void EnforceCUDNNLoaded(const char* fn_name); cudnn_dso_handle = paddle::platform::dynload::GetCUDNNDsoHandle(); \ }); \ EnforceCUDNNLoaded(#__name); \ - void* p_##__name = dlsym(cudnn_dso_handle, #__name); \ + static void* p_##__name = dlsym(cudnn_dso_handle, #__name); \ return reinterpret_cast(p_##__name)(args...); \ } \ }; \ -- GitLab From 53dab95b7599e8cea50a886cf8bafd0e55beec36 Mon Sep 17 00:00:00 2001 From: yuyang18 Date: Fri, 1 Jun 2018 12:26:57 +0800 Subject: [PATCH 0089/1416] Static DSO handle --- paddle/fluid/platform/dynload/cupti.h | 2 +- paddle/fluid/platform/dynload/curand.h | 2 +- paddle/fluid/platform/dynload/nccl.h | 2 +- paddle/fluid/platform/dynload/tensorrt.h | 2 +- paddle/fluid/platform/dynload/warpctc.h | 2 +- 5 files changed, 5 insertions(+), 5 deletions(-) diff --git a/paddle/fluid/platform/dynload/cupti.h b/paddle/fluid/platform/dynload/cupti.h index e64de7c20fc..2ad52bc7d32 100644 --- a/paddle/fluid/platform/dynload/cupti.h +++ b/paddle/fluid/platform/dynload/cupti.h @@ -45,7 +45,7 @@ extern void *cupti_dso_handle; std::call_once(cupti_dso_flag, []() { \ cupti_dso_handle = paddle::platform::dynload::GetCUPTIDsoHandle(); \ }); \ - void *p_##__name = dlsym(cupti_dso_handle, #__name); \ + static void *p_##__name = dlsym(cupti_dso_handle, #__name); \ return reinterpret_cast(p_##__name)(args...); \ } \ }; \ diff --git a/paddle/fluid/platform/dynload/curand.h b/paddle/fluid/platform/dynload/curand.h index 46ad4379d5f..5b9e0820e0b 100644 --- a/paddle/fluid/platform/dynload/curand.h +++ b/paddle/fluid/platform/dynload/curand.h @@ -34,7 +34,7 @@ extern void *curand_dso_handle; std::call_once(curand_dso_flag, []() { \ curand_dso_handle = paddle::platform::dynload::GetCurandDsoHandle(); \ }); \ - void *p_##__name = dlsym(curand_dso_handle, #__name); \ + static void *p_##__name = dlsym(curand_dso_handle, #__name); \ return reinterpret_cast(p_##__name)(args...); \ } \ }; \ diff --git a/paddle/fluid/platform/dynload/nccl.h b/paddle/fluid/platform/dynload/nccl.h index 37902ae20c5..575516f8187 100644 --- a/paddle/fluid/platform/dynload/nccl.h +++ b/paddle/fluid/platform/dynload/nccl.h @@ -37,7 +37,7 @@ extern void* nccl_dso_handle; std::call_once(nccl_dso_flag, []() { \ nccl_dso_handle = paddle::platform::dynload::GetNCCLDsoHandle(); \ }); \ - void* p_##__name = dlsym(nccl_dso_handle, #__name); \ + static void* p_##__name = dlsym(nccl_dso_handle, #__name); \ return reinterpret_cast(p_##__name)(args...); \ } \ }; \ diff --git a/paddle/fluid/platform/dynload/tensorrt.h b/paddle/fluid/platform/dynload/tensorrt.h index f584a49da0f..5d67658b94a 100644 --- a/paddle/fluid/platform/dynload/tensorrt.h +++ b/paddle/fluid/platform/dynload/tensorrt.h @@ -40,7 +40,7 @@ extern void* tensorrt_dso_handle; paddle::platform::dynload::GetTensorRtDsoHandle(); \ PADDLE_ENFORCE(tensorrt_dso_handle, "load tensorrt so failed"); \ }); \ - void* p_##__name = dlsym(tensorrt_dso_handle, #__name); \ + static void* p_##__name = dlsym(tensorrt_dso_handle, #__name); \ PADDLE_ENFORCE(p_##__name, "load %s failed", #__name); \ return reinterpret_cast(p_##__name)(args...); \ } \ diff --git a/paddle/fluid/platform/dynload/warpctc.h b/paddle/fluid/platform/dynload/warpctc.h index 7c70649d21c..d157c1fda78 100644 --- a/paddle/fluid/platform/dynload/warpctc.h +++ b/paddle/fluid/platform/dynload/warpctc.h @@ -40,7 +40,7 @@ extern void* warpctc_dso_handle; std::call_once(warpctc_dso_flag, []() { \ warpctc_dso_handle = paddle::platform::dynload::GetWarpCTCDsoHandle(); \ }); \ - void* p_##_name = dlsym(warpctc_dso_handle, #__name); \ + static void* p_##_name = dlsym(warpctc_dso_handle, #__name); \ return reinterpret_cast(p_##_name)(args...); \ } \ }; \ -- GitLab From 663f4e6168ef9852991dc1ccfea462307d19a5d0 Mon Sep 17 00:00:00 2001 From: baiyf Date: Fri, 1 Jun 2018 19:30:59 +0800 Subject: [PATCH 0090/1416] Fix bilinear_op Python API (#11117) * fix conflict * code clean --- doc/fluid/api/layers.rst | 4 ++-- python/paddle/fluid/layers/nn.py | 21 +++++++++---------- .../fluid/tests/unittests/test_layers.py | 6 +++--- 3 files changed, 15 insertions(+), 16 deletions(-) diff --git a/doc/fluid/api/layers.rst b/doc/fluid/api/layers.rst index dbb99d3c03f..5329adaa18b 100644 --- a/doc/fluid/api/layers.rst +++ b/doc/fluid/api/layers.rst @@ -1003,10 +1003,10 @@ dice_loss .. autofunction:: paddle.fluid.layers.dice_loss :noindex: -upsampling_bilinear2d +resize_bilinear ____ -.. autofunction:: paddle.fluid.layers.upsampling_bilinear2d +.. autofunction:: paddle.fluid.layers.resize_bilinear :noindex: gather diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index 56f5c6b4bed..bd6ed0f30e4 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -81,7 +81,7 @@ __all__ = [ 'label_smooth', 'roi_pool', 'dice_loss', - 'upsampling_bilinear2d', + 'resize_bilinear', 'gather', 'random_crop', ] @@ -3929,9 +3929,9 @@ def dice_loss(input, label, epsilon=0.00001): return reduce_mean(dice_score) -def upsampling_bilinear2d(input, out_shape=None, scale=None, name=None): +def resize_bilinear(input, out_shape=None, scale=None, name=None): """ - The mathematical meaning of upsampling_bilinear2d is also called + The mathematical meaning of resize bilinear layer is Bilinear interpolation. Bilinear interpolation is an extension of linear interpolation for interpolating functions of two variables (e.g. H-direction and @@ -3941,13 +3941,13 @@ def upsampling_bilinear2d(input, out_shape=None, scale=None, name=None): https://en.wikipedia.org/wiki/Bilinear_interpolation Args: - input (Variable): The input tensor of bilinear interpolation, + input (Variable): The input tensor of resize bilinear layer, This is a 4-D tensor of the shape (num_batches, channels, in_h, in_w). - out_shape(list|tuple|Variable|None): Output shape of bilinear interpolation + out_shape(list|tuple|Variable|None): Output shape of resize bilinear layer, the shape is (out_h, out_w). Default: None - scale(int|None): The multiplier for the input height or width. + scale(float|None): The multiplier for the input height or width. At least one of out_shape or scale must be set. And out_shape has a higher priority than scale. Default: None @@ -3961,7 +3961,7 @@ def upsampling_bilinear2d(input, out_shape=None, scale=None, name=None): Examples: .. code-block:: python - out = fluid.layers.bilinear_interp(input, out_shape=[12, 12]) + out = fluid.layers.resize_bilinear(input, out_shape=[12, 12]) """ if out_shape is None and scale is None: raise ValueError("One of out_shape and scale must not be None") @@ -3975,10 +3975,9 @@ def upsampling_bilinear2d(input, out_shape=None, scale=None, name=None): out_w = 0 inputs = {"X": input} if out_shape is not None: - if not (_is_list_or_turple_(out_shape) and len(out_shape) == 2) and ( - out_shape is not Variable): - raise ValueError('out_shape should be a list or tuple ', - 'with length 2, (out_h, out_w).') + if not (_is_list_or_turple_(out_shape) and + len(out_shape) == 2) and not isinstance(out_shape, Variable): + raise ValueError('out_shape should be a list or tuple or variable') if _is_list_or_turple_(out_shape): out_shape = list(map(int, out_shape)) out_h = out_shape[0] diff --git a/python/paddle/fluid/tests/unittests/test_layers.py b/python/paddle/fluid/tests/unittests/test_layers.py index 60dc1f83fc3..ca08fd7fc8e 100644 --- a/python/paddle/fluid/tests/unittests/test_layers.py +++ b/python/paddle/fluid/tests/unittests/test_layers.py @@ -369,13 +369,13 @@ class TestBook(unittest.TestCase): self.assertIsNotNone(output) print(str(program)) - def test_upsampling_bilinear2d(self): + def test_resize_bilinear(self): program = Program() with program_guard(program): x = layers.data(name='x', shape=[3, 9, 6], dtype="float32") - output = layers.upsampling_bilinear2d(x, out_shape=[12, 12]) + output = layers.resize_bilinear(x, out_shape=[12, 12]) self.assertIsNotNone(output) - output = layers.upsampling_bilinear2d(x, scale=3) + output = layers.resize_bilinear(x, scale=3) self.assertIsNotNone(output) print(str(program)) -- GitLab From eaeb76c419fbad9b7d3dd083666f80d84f89f55f Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Fri, 1 Jun 2018 19:35:49 +0800 Subject: [PATCH 0091/1416] add some comments --- .../tests/book/test_inference_nlp.cc | 25 +++++++++++-------- 1 file changed, 14 insertions(+), 11 deletions(-) diff --git a/paddle/fluid/inference/tests/book/test_inference_nlp.cc b/paddle/fluid/inference/tests/book/test_inference_nlp.cc index f7788ccbf40..c4d7b0bbf01 100644 --- a/paddle/fluid/inference/tests/book/test_inference_nlp.cc +++ b/paddle/fluid/inference/tests/book/test_inference_nlp.cc @@ -37,7 +37,8 @@ inline double GetCurrentMs() { return 1e+3 * time.tv_sec + 1e-3 * time.tv_usec; } -// return size of total words +// Load the input word index data from file and save into LodTensor. +// Return the size of words. size_t LoadData(std::vector* out, const std::string& filename) { size_t sz = 0; @@ -67,6 +68,8 @@ size_t LoadData(std::vector* out, return sz; } +// Split input data samples into small pieces jobs as balanced as possible, +// according to the number of threads. void SplitData( const std::vector& datasets, std::vector>* jobs, @@ -116,7 +119,8 @@ void ThreadRunInfer( for (size_t i = 0; i < inputs.size(); ++i) { feed_targets[feed_target_names[0]] = inputs[i]; executor->Run(*copy_program, &sub_scope, &feed_targets, &fetch_targets, - true, true, feed_holder_name, fetch_holder_name); + true /*create_local_scope*/, true /*create_vars*/, + feed_holder_name, fetch_holder_name); } auto stop_ms = GetCurrentMs(); scope->DeleteScope(&sub_scope); @@ -143,12 +147,13 @@ TEST(inference, nlp) { // 1. Define place, executor, scope auto place = paddle::platform::CPUPlace(); auto executor = paddle::framework::Executor(place); - auto* scope = new paddle::framework::Scope(); + std::unique_ptr scope( + new paddle::framework::Scope()); // 2. Initialize the inference_program and load parameters std::unique_ptr inference_program; inference_program = - InitProgram(&executor, scope, FLAGS_modelpath, model_combined); + InitProgram(&executor, scope.get(), FLAGS_modelpath, model_combined); if (FLAGS_use_mkldnn) { EnableMKLDNN(inference_program); } @@ -166,9 +171,9 @@ TEST(inference, nlp) { SplitData(datasets, &jobs, FLAGS_num_threads); std::vector> threads; for (int i = 0; i < FLAGS_num_threads; ++i) { - threads.emplace_back(new std::thread(ThreadRunInfer, i, &executor, scope, - std::ref(inference_program), - std::ref(jobs))); + threads.emplace_back( + new std::thread(ThreadRunInfer, i, &executor, scope.get(), + std::ref(inference_program), std::ref(jobs))); } start_ms = GetCurrentMs(); for (int i = 0; i < FLAGS_num_threads; ++i) { @@ -177,7 +182,7 @@ TEST(inference, nlp) { stop_ms = GetCurrentMs(); } else { if (FLAGS_prepare_vars) { - executor.CreateVariables(*inference_program, scope, 0); + executor.CreateVariables(*inference_program, scope.get(), 0); } // always prepare context std::unique_ptr ctx; @@ -201,7 +206,7 @@ TEST(inference, nlp) { start_ms = GetCurrentMs(); for (size_t i = 0; i < datasets.size(); ++i) { feed_targets[feed_target_names[0]] = &(datasets[i]); - executor.RunPreparedContext(ctx.get(), scope, &feed_targets, + executor.RunPreparedContext(ctx.get(), scope.get(), &feed_targets, &fetch_targets, !FLAGS_prepare_vars); } stop_ms = GetCurrentMs(); @@ -209,9 +214,7 @@ TEST(inference, nlp) { << " samples, avg time per sample: " << (stop_ms - start_ms) / datasets.size() << " ms"; } - LOG(INFO) << "Total inference time with " << FLAGS_num_threads << " threads : " << (stop_ms - start_ms) / 1000.0 << " sec, QPS: " << datasets.size() / ((stop_ms - start_ms) / 1000); - delete scope; } -- GitLab From 8939f17d304dd407efef3466a7bc96c6bb8747fe Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Fri, 1 Jun 2018 19:48:57 +0800 Subject: [PATCH 0092/1416] sppedup test_listen_and_serv_op --- .../fluid/tests/unittests/CMakeLists.txt | 6 +- .../unittests/test_listen_and_serv_op.py | 59 ++++++++----------- 2 files changed, 30 insertions(+), 35 deletions(-) diff --git a/python/paddle/fluid/tests/unittests/CMakeLists.txt b/python/paddle/fluid/tests/unittests/CMakeLists.txt index fead95ffdab..c33539f6b50 100644 --- a/python/paddle/fluid/tests/unittests/CMakeLists.txt +++ b/python/paddle/fluid/tests/unittests/CMakeLists.txt @@ -48,5 +48,7 @@ foreach(TEST_OP ${TEST_OPS}) endforeach(TEST_OP) py_test_modules(test_warpctc_op MODULES test_warpctc_op ENVS FLAGS_warpctc_dir=${WARPCTC_LIB_DIR} SERIAL) py_test_modules(test_dist_train MODULES test_dist_train SERIAL) -# tests that need to be done in fixed timeout -set_tests_properties(test_listen_and_serv_op PROPERTIES TIMEOUT 20) +# FIXME(Yancey1989): this test would cost much more time on CUDAPlace +# since load cudnn libraries, so we use a longer timeout to make this +# unit test stability. +set_tests_properties(test_listen_and_serv_op PROPERTIES TIMEOUT 30) diff --git a/python/paddle/fluid/tests/unittests/test_listen_and_serv_op.py b/python/paddle/fluid/tests/unittests/test_listen_and_serv_op.py index cf89f9d0ebf..ad479657cc2 100644 --- a/python/paddle/fluid/tests/unittests/test_listen_and_serv_op.py +++ b/python/paddle/fluid/tests/unittests/test_listen_and_serv_op.py @@ -23,7 +23,7 @@ from multiprocessing import Process from op_test import OpTest -def run_pserver(use_cuda, sync_mode, ip, port, trainer_count, trainer_id): +def run_pserver(use_cuda, sync_mode, ip, port, trainers, trainer_id): x = fluid.layers.data(name='x', shape=[1], dtype='float32') y_predict = fluid.layers.fc(input=x, size=1, act=None) y = fluid.layers.data(name='y', shape=[1], dtype='float32') @@ -39,15 +39,8 @@ def run_pserver(use_cuda, sync_mode, ip, port, trainer_count, trainer_id): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() exe = fluid.Executor(place) - port = os.getenv("PADDLE_INIT_PORT", port) - pserver_ips = os.getenv("PADDLE_INIT_PSERVERS", ip) # ip,ip... - eplist = [] - for ip in pserver_ips.split(","): - eplist.append(':'.join([ip, port])) - pserver_endpoints = ",".join(eplist) # ip:port,ip:port... - trainers = int(os.getenv("TRAINERS", trainer_count)) - current_endpoint = os.getenv("POD_IP", ip) + ":" + port - trainer_id = int(os.getenv("PADDLE_INIT_TRAINER_ID", trainer_id)) + pserver_endpoints = ip + ":" + port + current_endpoint = ip + ":" + port t = fluid.DistributeTranspiler() t.transpile( trainer_id, @@ -62,47 +55,47 @@ def run_pserver(use_cuda, sync_mode, ip, port, trainer_count, trainer_id): class TestListenAndServOp(OpTest): def setUp(self): - self.sleep_time = 5 + self.ps_timeout = 5 self.ip = "127.0.0.1" self.port = "6173" - self.trainer_count = 1 + self.trainers = 1 self.trainer_id = 1 - def _raise_signal(self, parent_pid, raised_signal): - time.sleep(self.sleep_time) - ps_command = subprocess.Popen( - "ps -o pid --ppid %d --noheaders" % parent_pid, - shell=True, - stdout=subprocess.PIPE) - ps_output = ps_command.stdout.read() - retcode = ps_command.wait() - assert retcode == 0, "ps command returned %d" % retcode - - for pid_str in ps_output.split("\n")[:-1]: - try: - os.kill(int(pid_str), raised_signal) - except Exception: - continue - def _start_pserver(self, use_cuda, sync_mode): p = Process( target=run_pserver, - args=(use_cuda, sync_mode, self.ip, self.port, self.trainer_count, + args=(use_cuda, sync_mode, self.ip, self.port, self.trainers, self.trainer_id)) p.start() + return p.pid + + def _wait_ps_ready(self, pid): + retry_times = self.ps_timeout + while True: + time.sleep(1) + assert retry_times >= 0, "wait ps ready failed" + try: + # the listen_and_serv_op would touch a file which contains the listen port + # on the /tmp directory until it was ready to process all the RPC call. + os.stat("/tmp/paddle.%d.port" % pid) + return + except os.error: + retry_times -= 1 def test_handle_signal_in_serv_op(self): # run pserver on CPU in sync mode - self._start_pserver(False, True) + pid = self._start_pserver(False, True) + self._wait_ps_ready(pid) # raise SIGINT to pserver - self._raise_signal(os.getpid(), signal.SIGINT) + os.kill(pid, signal.SIGINT) # run pserver on CPU in async mode - self._start_pserver(False, False) + pid = self._start_pserver(False, False) + self._wait_ps_ready(pid) # raise SIGTERM to pserver - self._raise_signal(os.getpid(), signal.SIGTERM) + os.kill(pid, signal.SIGINT) if __name__ == '__main__': -- GitLab From b5b666185720c241aad2421ffb2497dd92d159e5 Mon Sep 17 00:00:00 2001 From: Yan Chunwei Date: Fri, 1 Jun 2018 20:36:34 +0800 Subject: [PATCH 0093/1416] feature/simple inference demo (#11105) --- paddle/contrib/inference/CMakeLists.txt | 43 +++++------ paddle/contrib/inference/demo/CMakeLists.txt | 16 +++++ .../inference/demo/simple_on_word2vec.cc | 71 +++++++++++++++++++ .../inference/paddle_inference_api_impl.cc | 6 +- .../test_paddle_inference_api_impl.cc | 4 +- 5 files changed, 116 insertions(+), 24 deletions(-) create mode 100644 paddle/contrib/inference/demo/CMakeLists.txt create mode 100644 paddle/contrib/inference/demo/simple_on_word2vec.cc diff --git a/paddle/contrib/inference/CMakeLists.txt b/paddle/contrib/inference/CMakeLists.txt index 6847f7db7fc..8ca34465395 100644 --- a/paddle/contrib/inference/CMakeLists.txt +++ b/paddle/contrib/inference/CMakeLists.txt @@ -18,32 +18,35 @@ if(APPLE) endif(APPLE) function(inference_api_test TARGET_NAME) - set(options "") - set(oneValueArgs "") - set(multiValueArgs ARGS) - cmake_parse_arguments(inference_test "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN}) + if (WITH_TESTING) + set(options "") + set(oneValueArgs "") + set(multiValueArgs ARGS) + cmake_parse_arguments(inference_test "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN}) - set(PYTHON_TESTS_DIR ${PADDLE_BINARY_DIR}/python/paddle/fluid/tests) - cc_test(test_paddle_inference_${TARGET_NAME} - SRCS test_paddle_inference_${TARGET_NAME}.cc - DEPS paddle_fluid_api paddle_inference_api - ARGS --dirname=${PYTHON_TESTS_DIR}/book/) - if(inference_test_ARGS) - set_tests_properties(test_paddle_inference_${TARGET_NAME} - PROPERTIES DEPENDS "${inference_test_ARGS}") - endif() + set(PYTHON_TESTS_DIR ${PADDLE_BINARY_DIR}/python/paddle/fluid/tests) + cc_test(${TARGET_NAME} + SRCS ${TARGET_NAME}.cc + DEPS paddle_fluid paddle_inference_api + ARGS --dirname=${PYTHON_TESTS_DIR}/book/) + if(inference_test_ARGS) + set_tests_properties(${TARGET_NAME} + PROPERTIES DEPENDS "${inference_test_ARGS}") + endif() + endif(WITH_TESTING) endfunction(inference_api_test) - cc_library(paddle_inference_api SRCS paddle_inference_api.cc paddle_inference_api_impl.cc DEPS ${FLUID_CORE_MODULES} ${GLOB_OP_LIB}) -if(WITH_TESTING) - cc_test(test_paddle_inference_api - SRCS test_paddle_inference_api.cc - DEPS paddle_inference_api) +cc_test(test_paddle_inference_api + SRCS test_paddle_inference_api.cc + DEPS paddle_inference_api) - inference_api_test(api_impl - ARGS test_word2vec test_image_classification) +inference_api_test(test_paddle_inference_api_impl + ARGS test_word2vec test_image_classification) + +if(WITH_TESTING) + add_subdirectory(demo) endif() diff --git a/paddle/contrib/inference/demo/CMakeLists.txt b/paddle/contrib/inference/demo/CMakeLists.txt new file mode 100644 index 00000000000..7b0fa77ad13 --- /dev/null +++ b/paddle/contrib/inference/demo/CMakeLists.txt @@ -0,0 +1,16 @@ +# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +inference_api_test(simple_on_word2vec ARGS test_word2vec) diff --git a/paddle/contrib/inference/demo/simple_on_word2vec.cc b/paddle/contrib/inference/demo/simple_on_word2vec.cc new file mode 100644 index 00000000000..165d2e196b3 --- /dev/null +++ b/paddle/contrib/inference/demo/simple_on_word2vec.cc @@ -0,0 +1,71 @@ +/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + +http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +/* + * This file contains a simple demo for how to take a model for inference. + */ + +#include +#include +#include +#include "paddle/contrib/inference/paddle_inference_api.h" + +namespace paddle { +namespace demo { + +DEFINE_string(dirname, "", "Directory of the inference model."); + +void Main(bool use_gpu) { + //# 1. Create PaddlePredictor with a config. + NativeConfig config; + config.model_dir = FLAGS_dirname + "word2vec.inference.model"; + config.use_gpu = use_gpu; + config.fraction_of_gpu_memory = 0.15; + config.device = 0; + auto predictor = + CreatePaddlePredictor(config); + + for (int batch_id = 0; batch_id < 3; batch_id++) { + //# 2. Prepare input. + int64_t data[4] = {1, 2, 3, 4}; + + PaddleBuf buf{.data = data, .length = sizeof(data)}; + PaddleTensor tensor{.name = "", + .shape = std::vector({4, 1}), + .data = buf, + .dtype = PaddleDType::INT64}; + + // For simplicity, we set all the slots with the same data. + std::vector slots(4, tensor); + + //# 3. Run + std::vector outputs; + CHECK(predictor->Run(slots, &outputs)); + + //# 4. Get output. + ASSERT_EQ(outputs.size(), 1); + LOG(INFO) << "output buffer size: " << outputs.front().data.length; + const size_t num_elements = outputs.front().data.length / sizeof(float); + // The outputs' buffers are in CPU memory. + for (size_t i = 0; i < std::min(5UL, num_elements); i++) { + LOG(INFO) << static_cast(outputs.front().data.data)[i]; + } + } +} + +TEST(demo, word2vec_cpu) { Main(false /*use_gpu*/); } +TEST(demo, word2vec_gpu) { Main(true /*use_gpu*/); } + +} // namespace demo +} // namespace paddle diff --git a/paddle/contrib/inference/paddle_inference_api_impl.cc b/paddle/contrib/inference/paddle_inference_api_impl.cc index 99a64662d4d..e7a8fa68b7f 100644 --- a/paddle/contrib/inference/paddle_inference_api_impl.cc +++ b/paddle/contrib/inference/paddle_inference_api_impl.cc @@ -248,9 +248,11 @@ CreatePaddlePredictor( VLOG(3) << "create NativePaddlePredictor"; if (config.use_gpu) { // 1. GPU memeroy - PADDLE_ENFORCE( - config.fraction_of_gpu_memory > 0.f, + PADDLE_ENFORCE_GT( + config.fraction_of_gpu_memory, + 0.f, "fraction_of_gpu_memory in the config should be set to range (0., 1.]"); + PADDLE_ENFORCE_GE(config.device, 0, "Invalid device id %d", config.device); std::vector flags; if (config.fraction_of_gpu_memory >= 0.0f || config.fraction_of_gpu_memory <= 0.95f) { diff --git a/paddle/contrib/inference/test_paddle_inference_api_impl.cc b/paddle/contrib/inference/test_paddle_inference_api_impl.cc index 07b17acd484..1f960677163 100644 --- a/paddle/contrib/inference/test_paddle_inference_api_impl.cc +++ b/paddle/contrib/inference/test_paddle_inference_api_impl.cc @@ -74,7 +74,7 @@ TEST(paddle_inference_api_impl, word2vec) { ASSERT_EQ(outputs.size(), 1UL); size_t len = outputs[0].data.length; float* data = static_cast(outputs[0].data.data); - for (int j = 0; j < len / sizeof(float); ++j) { + for (size_t j = 0; j < len / sizeof(float); ++j) { ASSERT_LT(data[j], 1.0); ASSERT_GT(data[j], -1.0); } @@ -92,7 +92,7 @@ TEST(paddle_inference_api_impl, word2vec) { TestInference(config.model_dir, cpu_feeds, cpu_fetchs1); float* lod_data = output1.data(); - for (size_t i = 0; i < output1.numel(); ++i) { + for (int i = 0; i < output1.numel(); ++i) { EXPECT_LT(lod_data[i] - data[i], 1e-3); EXPECT_GT(lod_data[i] - data[i], -1e-3); } -- GitLab From 38f8182df63d33ff619297d95f5a4431bf8d5362 Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Fri, 1 Jun 2018 20:41:18 +0800 Subject: [PATCH 0094/1416] work around with dummy test --- .../fluid/inference/tests/book/CMakeLists.txt | 8 ++++++- .../tests/book/test_inference_nlp.cc | 21 ++++++++++++++++--- 2 files changed, 25 insertions(+), 4 deletions(-) diff --git a/paddle/fluid/inference/tests/book/CMakeLists.txt b/paddle/fluid/inference/tests/book/CMakeLists.txt index 90357f99d1d..b33df2942a8 100644 --- a/paddle/fluid/inference/tests/book/CMakeLists.txt +++ b/paddle/fluid/inference/tests/book/CMakeLists.txt @@ -35,7 +35,13 @@ inference_test(image_classification ARGS vgg resnet) inference_test(label_semantic_roles) inference_test(recognize_digits ARGS mlp conv) inference_test(recommender_system) -inference_test(nlp) #inference_test(rnn_encoder_decoder) #inference_test(understand_sentiment ARGS conv) inference_test(word2vec) + +# This is an unly work around to make this test run +cc_test(test_inference_nlp + SRCS test_inference_nlp.cc + DEPS paddle_fluid + ARGS + --modelpath=${PADDLE_BINARY_DIR}/python/paddle/fluid/tests/book/recognize_digits_mlp.inference.model) diff --git a/paddle/fluid/inference/tests/book/test_inference_nlp.cc b/paddle/fluid/inference/tests/book/test_inference_nlp.cc index c4d7b0bbf01..5ece6084df2 100644 --- a/paddle/fluid/inference/tests/book/test_inference_nlp.cc +++ b/paddle/fluid/inference/tests/book/test_inference_nlp.cc @@ -37,10 +37,22 @@ inline double GetCurrentMs() { return 1e+3 * time.tv_sec + 1e-3 * time.tv_usec; } +// This function just give dummy data for recognize_digits model. +size_t DummyData(std::vector* out) { + paddle::framework::LoDTensor input; + SetupTensor(&input, {1, 1, 28, 28}, -1.f, 1.f); + out->emplace_back(input); + return 1; +} + // Load the input word index data from file and save into LodTensor. // Return the size of words. size_t LoadData(std::vector* out, const std::string& filename) { + if (filename.empty()) { + return DummyData(out); + } + size_t sz = 0; std::fstream fin(filename); std::string line; @@ -130,9 +142,12 @@ void ThreadRunInfer( } TEST(inference, nlp) { - if (FLAGS_modelpath.empty() || FLAGS_datafile.empty()) { - LOG(FATAL) << "Usage: ./example --modelpath=path/to/your/model " - << "--datafile=path/to/your/data"; + if (FLAGS_modelpath.empty()) { + LOG(FATAL) << "Usage: ./example --modelpath=path/to/your/model"; + } + if (FLAGS_datafile.empty()) { + LOG(WARNING) << " Not data file provided, will use dummy data!" + << "Note: if you use nlp model, please provide data file."; } LOG(INFO) << "Model Path: " << FLAGS_modelpath; LOG(INFO) << "Data File: " << FLAGS_datafile; -- GitLab From 99d00cce9330dac56aac52788d7fba76d0137430 Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Fri, 1 Jun 2018 21:04:51 +0800 Subject: [PATCH 0095/1416] follow comment: refine where time started --- paddle/fluid/inference/tests/book/test_inference_nlp.cc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/paddle/fluid/inference/tests/book/test_inference_nlp.cc b/paddle/fluid/inference/tests/book/test_inference_nlp.cc index 5ece6084df2..c3bec279252 100644 --- a/paddle/fluid/inference/tests/book/test_inference_nlp.cc +++ b/paddle/fluid/inference/tests/book/test_inference_nlp.cc @@ -185,12 +185,12 @@ TEST(inference, nlp) { std::vector> jobs; SplitData(datasets, &jobs, FLAGS_num_threads); std::vector> threads; + start_ms = GetCurrentMs(); for (int i = 0; i < FLAGS_num_threads; ++i) { threads.emplace_back( new std::thread(ThreadRunInfer, i, &executor, scope.get(), std::ref(inference_program), std::ref(jobs))); } - start_ms = GetCurrentMs(); for (int i = 0; i < FLAGS_num_threads; ++i) { threads[i]->join(); } -- GitLab From e0a8c584701299017dda12214fed1bb108d8a9e9 Mon Sep 17 00:00:00 2001 From: Lei Wang Date: Fri, 1 Jun 2018 15:55:21 -0700 Subject: [PATCH 0096/1416] Doc: fix typo in var_desc.md. (#11130) --- doc/fluid/design/concepts/var_desc.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/fluid/design/concepts/var_desc.md b/doc/fluid/design/concepts/var_desc.md index 6750323c016..8db67f6703d 100644 --- a/doc/fluid/design/concepts/var_desc.md +++ b/doc/fluid/design/concepts/var_desc.md @@ -35,7 +35,7 @@ The computation `Program` consists of nested `Blocks`. Each `Block` will consist ## Definition of VarType -A VarDesc should have a name, type and whether or not it is persistable. The are different kinds of variable types supported in PaddlePaddle, apart from the POD_Types like: `LOD_TENSOR`, `SELECTED_ROWS`, `FEED_MINIBATCH`, `FETCH_LIST`, `STEP_SCOPES`, `LOD_RANK_TABLE`, `LOD_TENSOR_ARRAY`, `PLACE_LIST`, `READER` and `CHANNEL`. These are declared inside `VarType`. A `VarDesc` then looks as the following: +A VarDesc should have a name, type and whether or not it is persistable. There are different kinds of variable types supported in PaddlePaddle, apart from the POD_Types like: `LOD_TENSOR`, `SELECTED_ROWS`, `FEED_MINIBATCH`, `FETCH_LIST`, `STEP_SCOPES`, `LOD_RANK_TABLE`, `LOD_TENSOR_ARRAY`, `PLACE_LIST`, `READER` and `CHANNEL`. These are declared inside `VarType`. A `VarDesc` then looks as the following: ```proto message VarDesc { -- GitLab From 906334a6a493b5f47cdb52fc93688ee945f96f27 Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Sun, 3 Jun 2018 16:12:38 +0800 Subject: [PATCH 0097/1416] fix build error on mac --- paddle/fluid/operators/detail/grpc_server.h | 4 ++-- paddle/fluid/operators/listen_and_serv_op.cc | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/paddle/fluid/operators/detail/grpc_server.h b/paddle/fluid/operators/detail/grpc_server.h index d1fcbc414f1..eae87de4201 100644 --- a/paddle/fluid/operators/detail/grpc_server.h +++ b/paddle/fluid/operators/detail/grpc_server.h @@ -71,8 +71,8 @@ class AsyncGRPCServer final : public RPCServer { std::unique_ptr<::grpc::Server> server_; // condition of the sub program - std::mutex barrier_mutex_; - mutable int barrier_cond_step_; + // std::mutex barrier_mutex_; + // mutable int barrier_cond_step_; std::condition_variable barrier_condition_; std::mutex mutex_ready_; diff --git a/paddle/fluid/operators/listen_and_serv_op.cc b/paddle/fluid/operators/listen_and_serv_op.cc index 71e75c25321..66a0f87b46c 100644 --- a/paddle/fluid/operators/listen_and_serv_op.cc +++ b/paddle/fluid/operators/listen_and_serv_op.cc @@ -222,8 +222,8 @@ static void FillRequestCtx(detail::RequestHandler *h, framework::Scope *scope, h->SetDevCtx(dev_ctx); h->SetExecutor(executor); h->SetProgram(program); - h->SetPrefetchPreparedCtx(std::move( - std::unique_ptr(prefetch_ctx))); + h->SetPrefetchPreparedCtx( + std::unique_ptr(prefetch_ctx)); h->SetRPCServer(rpc_server); } -- GitLab From d3e99aeec33475cdb4a06bb0867f28503e91b3c7 Mon Sep 17 00:00:00 2001 From: Yuan Gao Date: Mon, 4 Jun 2018 09:46:49 +0800 Subject: [PATCH 0098/1416] add normalize switch to box_coder_op (#11129) --- .../fluid/operators/detection/box_coder_op.cc | 4 ++ .../fluid/operators/detection/box_coder_op.cu | 42 ++++++++++-------- .../fluid/operators/detection/box_coder_op.h | 44 +++++++++++-------- .../tests/unittests/test_box_coder_op.py | 32 ++++++++++---- 4 files changed, 78 insertions(+), 44 deletions(-) diff --git a/paddle/fluid/operators/detection/box_coder_op.cc b/paddle/fluid/operators/detection/box_coder_op.cc index 74848005d0b..76ef08cb9ad 100644 --- a/paddle/fluid/operators/detection/box_coder_op.cc +++ b/paddle/fluid/operators/detection/box_coder_op.cc @@ -91,6 +91,10 @@ class BoxCoderOpMaker : public framework::OpProtoAndCheckerMaker { "the code type used with the target box") .SetDefault("encode_center_size") .InEnum({"encode_center_size", "decode_center_size"}); + AddAttr("box_normalized", + "(bool, default true) " + "whether treat the priorbox as a noramlized box") + .SetDefault(true); AddOutput("OutputBox", "(LoDTensor or Tensor) " "When code_type is 'encode_center_size', the output tensor of " diff --git a/paddle/fluid/operators/detection/box_coder_op.cu b/paddle/fluid/operators/detection/box_coder_op.cu index 8cef8e03439..fc7eb5d1ed7 100644 --- a/paddle/fluid/operators/detection/box_coder_op.cu +++ b/paddle/fluid/operators/detection/box_coder_op.cu @@ -20,15 +20,16 @@ __global__ void EncodeCenterSizeKernel(const T* prior_box_data, const T* prior_box_var_data, const T* target_box_data, const int row, const int col, const int len, - T* output) { + const bool normalized, T* output) { const int idx = threadIdx.x + blockIdx.x * blockDim.x; if (idx < row * col) { const int row_idx = idx / col; const int col_idx = idx % col; - T prior_box_width = - prior_box_data[col_idx * len + 2] - prior_box_data[col_idx * len]; - T prior_box_height = - prior_box_data[col_idx * len + 3] - prior_box_data[col_idx * len + 1]; + T prior_box_width = prior_box_data[col_idx * len + 2] - + prior_box_data[col_idx * len] + (normalized == false); + T prior_box_height = prior_box_data[col_idx * len + 3] - + prior_box_data[col_idx * len + 1] + + (normalized == false); T prior_box_center_x = (prior_box_data[col_idx * len + 2] + prior_box_data[col_idx * len]) / 2; T prior_box_center_y = (prior_box_data[col_idx * len + 3] + @@ -41,10 +42,11 @@ __global__ void EncodeCenterSizeKernel(const T* prior_box_data, T target_box_center_y = (target_box_data[row_idx * len + 3] + target_box_data[row_idx * len + 1]) / 2; - T target_box_width = - target_box_data[row_idx * len + 2] - target_box_data[row_idx * len]; - T target_box_height = - target_box_data[row_idx * len + 3] - target_box_data[row_idx * len + 1]; + T target_box_width = target_box_data[row_idx * len + 2] - + target_box_data[row_idx * len] + (normalized == false); + T target_box_height = target_box_data[row_idx * len + 3] - + target_box_data[row_idx * len + 1] + + (normalized == false); output[idx * len] = (target_box_center_x - prior_box_center_x) / prior_box_width / prior_box_var_data[col_idx * len]; @@ -63,14 +65,15 @@ __global__ void DecodeCenterSizeKernel(const T* prior_box_data, const T* prior_box_var_data, const T* target_box_data, const int row, const int col, const int len, - T* output) { + const bool normalized, T* output) { const int idx = threadIdx.x + blockIdx.x * blockDim.x; if (idx < row * col) { const int col_idx = idx % col; - T prior_box_width = - prior_box_data[col_idx * len + 2] - prior_box_data[col_idx * len]; - T prior_box_height = - prior_box_data[col_idx * len + 3] - prior_box_data[col_idx * len + 1]; + T prior_box_width = prior_box_data[col_idx * len + 2] - + prior_box_data[col_idx * len] + (normalized == false); + T prior_box_height = prior_box_data[col_idx * len + 3] - + prior_box_data[col_idx * len + 1] + + (normalized == false); T prior_box_center_x = (prior_box_data[col_idx * len + 2] + prior_box_data[col_idx * len]) / 2; T prior_box_center_y = (prior_box_data[col_idx * len + 3] + @@ -93,8 +96,10 @@ __global__ void DecodeCenterSizeKernel(const T* prior_box_data, output[idx * len] = target_box_center_x - target_box_width / 2; output[idx * len + 1] = target_box_center_y - target_box_height / 2; - output[idx * len + 2] = target_box_center_x + target_box_width / 2; - output[idx * len + 3] = target_box_center_y + target_box_height / 2; + output[idx * len + 2] = + target_box_center_x + target_box_width / 2 - (normalized == false); + output[idx * len + 3] = + target_box_center_y + target_box_height / 2 - (normalized == false); } } @@ -128,14 +133,15 @@ class BoxCoderCUDAKernel : public framework::OpKernel { T* output = output_box->data(); auto code_type = GetBoxCodeType(context.Attr("code_type")); + bool normalized = context.Attr("box_normalized"); if (code_type == BoxCodeType::kEncodeCenterSize) { EncodeCenterSizeKernel<<>>( prior_box_data, prior_box_var_data, target_box_data, row, col, len, - output); + normalized, output); } else if (code_type == BoxCodeType::kDecodeCenterSize) { DecodeCenterSizeKernel<<>>( prior_box_data, prior_box_var_data, target_box_data, row, col, len, - output); + normalized, output); } } }; diff --git a/paddle/fluid/operators/detection/box_coder_op.h b/paddle/fluid/operators/detection/box_coder_op.h index 77fc6c2b62a..3dc68935ac1 100644 --- a/paddle/fluid/operators/detection/box_coder_op.h +++ b/paddle/fluid/operators/detection/box_coder_op.h @@ -34,7 +34,7 @@ class BoxCoderKernel : public framework::OpKernel { void EncodeCenterSize(const framework::Tensor& target_box, const framework::Tensor& prior_box, const framework::Tensor& prior_box_var, - T* output) const { + const bool normalized, T* output) const { int64_t row = target_box.dims()[0]; int64_t col = prior_box.dims()[0]; int64_t len = prior_box.dims()[1]; @@ -44,10 +44,11 @@ class BoxCoderKernel : public framework::OpKernel { for (int64_t i = 0; i < row; ++i) { for (int64_t j = 0; j < col; ++j) { - T prior_box_width = - prior_box_data[j * len + 2] - prior_box_data[j * len]; - T prior_box_height = - prior_box_data[j * len + 3] - prior_box_data[j * len + 1]; + T prior_box_width = prior_box_data[j * len + 2] - + prior_box_data[j * len] + (normalized == false); + T prior_box_height = prior_box_data[j * len + 3] - + prior_box_data[j * len + 1] + + (normalized == false); T prior_box_center_x = (prior_box_data[j * len + 2] + prior_box_data[j * len]) / 2; T prior_box_center_y = @@ -57,10 +58,11 @@ class BoxCoderKernel : public framework::OpKernel { (target_box_data[i * len + 2] + target_box_data[i * len]) / 2; T target_box_center_y = (target_box_data[i * len + 3] + target_box_data[i * len + 1]) / 2; - T target_box_width = - target_box_data[i * len + 2] - target_box_data[i * len]; - T target_box_height = - target_box_data[i * len + 3] - target_box_data[i * len + 1]; + T target_box_width = target_box_data[i * len + 2] - + target_box_data[i * len] + (normalized == false); + T target_box_height = target_box_data[i * len + 3] - + target_box_data[i * len + 1] + + (normalized == false); size_t offset = i * col * len + j * len; output[offset] = (target_box_center_x - prior_box_center_x) / @@ -79,7 +81,7 @@ class BoxCoderKernel : public framework::OpKernel { void DecodeCenterSize(const framework::Tensor& target_box, const framework::Tensor& prior_box, const framework::Tensor& prior_box_var, - T* output) const { + const bool normalized, T* output) const { int64_t row = target_box.dims()[0]; int64_t col = prior_box.dims()[0]; int64_t len = prior_box.dims()[1]; @@ -91,10 +93,11 @@ class BoxCoderKernel : public framework::OpKernel { for (int64_t i = 0; i < row; ++i) { for (int64_t j = 0; j < col; ++j) { size_t offset = i * col * len + j * len; - T prior_box_width = - prior_box_data[j * len + 2] - prior_box_data[j * len]; - T prior_box_height = - prior_box_data[j * len + 3] - prior_box_data[j * len + 1]; + T prior_box_width = prior_box_data[j * len + 2] - + prior_box_data[j * len] + (normalized == false); + T prior_box_height = prior_box_data[j * len + 3] - + prior_box_data[j * len + 1] + + (normalized == false); T prior_box_center_x = (prior_box_data[j * len + 2] + prior_box_data[j * len]) / 2; T prior_box_center_y = @@ -116,8 +119,10 @@ class BoxCoderKernel : public framework::OpKernel { output[offset] = target_box_center_x - target_box_width / 2; output[offset + 1] = target_box_center_y - target_box_height / 2; - output[offset + 2] = target_box_center_x + target_box_width / 2; - output[offset + 3] = target_box_center_y + target_box_height / 2; + output[offset + 2] = + target_box_center_x + target_box_width / 2 - (normalized == false); + output[offset + 3] = + target_box_center_y + target_box_height / 2 - (normalized == false); } } } @@ -139,11 +144,14 @@ class BoxCoderKernel : public framework::OpKernel { output_box->mutable_data({row, col, len}, context.GetPlace()); auto code_type = GetBoxCodeType(context.Attr("code_type")); + bool normalized = context.Attr("box_normalized"); T* output = output_box->data(); if (code_type == BoxCodeType::kEncodeCenterSize) { - EncodeCenterSize(*target_box, *prior_box, *prior_box_var, output); + EncodeCenterSize(*target_box, *prior_box, *prior_box_var, normalized, + output); } else if (code_type == BoxCodeType::kDecodeCenterSize) { - DecodeCenterSize(*target_box, *prior_box, *prior_box_var, output); + DecodeCenterSize(*target_box, *prior_box, *prior_box_var, normalized, + output); } } }; diff --git a/python/paddle/fluid/tests/unittests/test_box_coder_op.py b/python/paddle/fluid/tests/unittests/test_box_coder_op.py index 56f5af91d8e..a31b7ea322f 100644 --- a/python/paddle/fluid/tests/unittests/test_box_coder_op.py +++ b/python/paddle/fluid/tests/unittests/test_box_coder_op.py @@ -19,7 +19,8 @@ import math from op_test import OpTest -def box_coder(target_box, prior_box, prior_box_var, output_box, code_type): +def box_coder(target_box, prior_box, prior_box_var, output_box, code_type, + box_normalized): prior_box_x = ( (prior_box[:, 2] + prior_box[:, 0]) / 2).reshape(1, prior_box.shape[0]) prior_box_y = ( @@ -30,6 +31,9 @@ def box_coder(target_box, prior_box, prior_box_var, output_box, code_type): (prior_box[:, 3] - prior_box[:, 1])).reshape(1, prior_box.shape[0]) prior_box_var = prior_box_var.reshape(1, prior_box_var.shape[0], prior_box_var.shape[1]) + if not box_normalized: + prior_box_height = prior_box_height + 1 + prior_box_width = prior_box_width + 1 if (code_type == "EncodeCenterSize"): target_box_x = ((target_box[:, 2] + target_box[:, 0]) / 2).reshape( @@ -40,6 +44,9 @@ def box_coder(target_box, prior_box, prior_box_var, output_box, code_type): target_box.shape[0], 1) target_box_height = ((target_box[:, 3] - target_box[:, 1])).reshape( target_box.shape[0], 1) + if not box_normalized: + target_box_height = target_box_height + 1 + target_box_width = target_box_width + 1 output_box[:,:,0] = (target_box_x - prior_box_x) / prior_box_width / \ prior_box_var[:,:,0] @@ -64,9 +71,13 @@ def box_coder(target_box, prior_box, prior_box_var, output_box, code_type): output_box[:, :, 1] = target_box_y - target_box_height / 2 output_box[:, :, 2] = target_box_x + target_box_width / 2 output_box[:, :, 3] = target_box_y + target_box_height / 2 + if not box_normalized: + output_box[:, :, 2] = output_box[:, :, 2] - 1 + output_box[:, :, 3] = output_box[:, :, 3] - 1 -def batch_box_coder(prior_box, prior_box_var, target_box, lod, code_type): +def batch_box_coder(prior_box, prior_box_var, target_box, lod, code_type, + box_normalized): n = target_box.shape[0] m = prior_box.shape[0] output_box = np.zeros((n, m, 4), dtype=np.float32) @@ -74,11 +85,11 @@ def batch_box_coder(prior_box, prior_box_var, target_box, lod, code_type): if (code_type == "EncodeCenterSize"): box_coder(target_box[lod[i]:lod[i + 1], :], prior_box, prior_box_var, output_box[lod[i]:lod[i + 1], :, :], - code_type) + code_type, box_normalized) elif (code_type == "DecodeCenterSize"): box_coder(target_box[lod[i]:lod[i + 1], :, :], prior_box, prior_box_var, output_box[lod[i]:lod[i + 1], :, :], - code_type) + code_type, box_normalized) return output_box @@ -93,15 +104,19 @@ class TestBoxCoderOp(OpTest): prior_box_var = np.random.random((10, 4)).astype('float32') target_box = np.random.random((5, 10, 4)).astype('float32') code_type = "DecodeCenterSize" + box_normalized = False output_box = batch_box_coder(prior_box, prior_box_var, target_box, - lod[0], code_type) + lod[0], code_type, box_normalized) self.inputs = { 'PriorBox': prior_box, 'PriorBoxVar': prior_box_var, 'TargetBox': target_box, } - self.attrs = {'code_type': 'decode_center_size'} + self.attrs = { + 'code_type': 'decode_center_size', + 'box_normalized': False + } self.outputs = {'OutputBox': output_box} @@ -116,15 +131,16 @@ class TestBoxCoderOpWithLoD(OpTest): prior_box_var = np.random.random((10, 4)).astype('float32') target_box = np.random.random((20, 4)).astype('float32') code_type = "EncodeCenterSize" + box_normalized = True output_box = batch_box_coder(prior_box, prior_box_var, target_box, - lod[0], code_type) + lod[0], code_type, box_normalized) self.inputs = { 'PriorBox': prior_box, 'PriorBoxVar': prior_box_var, 'TargetBox': (target_box, lod), } - self.attrs = {'code_type': 'encode_center_size'} + self.attrs = {'code_type': 'encode_center_size', 'box_normalized': True} self.outputs = {'OutputBox': output_box} -- GitLab From 7218f4feb28e295b55e0eedd1d0e437e190c4de8 Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Mon, 4 Jun 2018 10:42:26 +0800 Subject: [PATCH 0099/1416] update by comment --- .../fluid/tests/unittests/test_listen_and_serv_op.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/python/paddle/fluid/tests/unittests/test_listen_and_serv_op.py b/python/paddle/fluid/tests/unittests/test_listen_and_serv_op.py index ad479657cc2..6be24b09447 100644 --- a/python/paddle/fluid/tests/unittests/test_listen_and_serv_op.py +++ b/python/paddle/fluid/tests/unittests/test_listen_and_serv_op.py @@ -72,8 +72,8 @@ class TestListenAndServOp(OpTest): def _wait_ps_ready(self, pid): retry_times = self.ps_timeout while True: - time.sleep(1) assert retry_times >= 0, "wait ps ready failed" + time.sleep(0.5) try: # the listen_and_serv_op would touch a file which contains the listen port # on the /tmp directory until it was ready to process all the RPC call. @@ -87,15 +87,15 @@ class TestListenAndServOp(OpTest): pid = self._start_pserver(False, True) self._wait_ps_ready(pid) - # raise SIGINT to pserver - os.kill(pid, signal.SIGINT) + # raise SIGTERM to pserver + os.kill(pid, signal.SIGTERM) # run pserver on CPU in async mode pid = self._start_pserver(False, False) self._wait_ps_ready(pid) # raise SIGTERM to pserver - os.kill(pid, signal.SIGINT) + os.kill(pid, signal.SIGTERM) if __name__ == '__main__': -- GitLab From ee4e567dea8074245c89be79b0267a515a84c6b6 Mon Sep 17 00:00:00 2001 From: fengjiayi Date: Mon, 4 Jun 2018 10:45:59 +0800 Subject: [PATCH 0100/1416] Creating readers before training begining --- .../fluid/operators/reader/open_files_op.cc | 52 ++++++++++--------- 1 file changed, 28 insertions(+), 24 deletions(-) diff --git a/paddle/fluid/operators/reader/open_files_op.cc b/paddle/fluid/operators/reader/open_files_op.cc index 8c0dac65dd6..c0526e45f4d 100644 --- a/paddle/fluid/operators/reader/open_files_op.cc +++ b/paddle/fluid/operators/reader/open_files_op.cc @@ -26,7 +26,11 @@ class MultiFileReader : public framework::ReaderBase { MultiFileReader(const std::vector& file_names, const std::vector& dims, size_t thread_num, size_t buffer_size) - : file_names_(file_names), dims_(dims), buffer_size_(buffer_size) { + : buffer_size_(buffer_size) { + readers_.resize(file_names.size()); + for (const std::string& f_name : file_names) { + readers_.emplace_back(CreateReaderByFileName(f_name, dims)); + } prefetchers_.resize(thread_num); StartNewScheduler(); } @@ -40,14 +44,13 @@ class MultiFileReader : public framework::ReaderBase { void StartNewScheduler(); void EndScheduler(); void ScheduleThreadFunc(); - void PrefetchThreadFunc(std::string file_name, size_t thread_idx); + void PrefetchThreadFunc(size_t reader_idx, size_t thread_idx); - std::vector file_names_; - std::vector dims_; + std::vector> readers_; std::thread scheduler_; std::vector prefetchers_; size_t buffer_size_; - reader::BlockingQueue* waiting_file_idx_; + reader::BlockingQueue* waiting_reader_idx_; reader::BlockingQueue* available_thread_idx_; reader::BlockingQueue>* buffer_; }; @@ -60,20 +63,23 @@ void MultiFileReader::ReadNext(std::vector* out) { void MultiFileReader::ReInit() { EndScheduler(); + for (auto& reader : readers_) { + reader->ReInit(); + } StartNewScheduler(); } void MultiFileReader::StartNewScheduler() { size_t thread_num = prefetchers_.size(); - waiting_file_idx_ = new reader::BlockingQueue(file_names_.size()); + waiting_reader_idx_ = new reader::BlockingQueue(readers_.size()); available_thread_idx_ = new reader::BlockingQueue(thread_num); buffer_ = new reader::BlockingQueue>( buffer_size_); - for (size_t i = 0; i < file_names_.size(); ++i) { - waiting_file_idx_->Send(i); + for (size_t i = 0; i < readers_.size(); ++i) { + waiting_reader_idx_->Send(i); } - waiting_file_idx_->Close(); + waiting_reader_idx_->Close(); for (size_t i = 0; i < thread_num; ++i) { available_thread_idx_->Send(i); } @@ -84,13 +90,13 @@ void MultiFileReader::StartNewScheduler() { void MultiFileReader::EndScheduler() { available_thread_idx_->Close(); buffer_->Close(); - waiting_file_idx_->Close(); + waiting_reader_idx_->Close(); if (scheduler_.joinable()) { scheduler_.join(); } delete buffer_; delete available_thread_idx_; - delete waiting_file_idx_; + delete waiting_reader_idx_; } void MultiFileReader::ScheduleThreadFunc() { @@ -102,12 +108,11 @@ void MultiFileReader::ScheduleThreadFunc() { if (prefetcher.joinable()) { prefetcher.join(); } - size_t file_idx; - if (waiting_file_idx_->Receive(&file_idx)) { + size_t reader_idx; + if (waiting_reader_idx_->Receive(&reader_idx)) { // Still have files to read. Start a new prefetch thread. - std::string file_name = file_names_[file_idx]; - prefetcher = std::thread([this, file_name, thread_idx] { - PrefetchThreadFunc(file_name, thread_idx); + prefetcher = std::thread([this, reader_idx, thread_idx] { + PrefetchThreadFunc(reader_idx, thread_idx); }); } else { // No more file to read. @@ -129,11 +134,9 @@ void MultiFileReader::ScheduleThreadFunc() { VLOG(5) << "MultiFileReader schedule thread terminates."; } -void MultiFileReader::PrefetchThreadFunc(std::string file_name, - size_t thread_idx) { - VLOG(5) << "The prefetch thread of file '" << file_name << "' starts."; - std::unique_ptr reader = - CreateReaderByFileName(file_name, dims_); +void MultiFileReader::PrefetchThreadFunc(size_t reader_idx, size_t thread_idx) { + VLOG(5) << "The prefetch thread of file idx '" << reader_idx << "' starts."; + std::unique_ptr& reader = readers_[reader_idx]; while (true) { std::vector ins; reader->ReadNext(&ins); @@ -144,8 +147,8 @@ void MultiFileReader::PrefetchThreadFunc(std::string file_name, buffer_->Send(std::move(ins)); } catch (paddle::platform::EnforceNotMet e) { VLOG(5) << "WARNING: The buffer channel has been closed. The prefetch " - "thread of file '" - << file_name << "' will terminate."; + "thread of file idx '" + << reader_idx << "' will terminate."; break; } } @@ -154,7 +157,8 @@ void MultiFileReader::PrefetchThreadFunc(std::string file_name, VLOG(5) << "WARNING: The available_thread_idx_ channel has been closed. " "Fail to send thread_idx."; } - VLOG(5) << "The prefetch thread of file '" << file_name << "' terminates."; + VLOG(5) << "The prefetch thread of file idx '" << reader_idx + << "' terminates."; } class OpenFilesOp : public framework::OperatorBase { -- GitLab From 7f5eb9f68743093ed14d5c35ebd0d266800ac939 Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Mon, 4 Jun 2018 10:46:02 +0800 Subject: [PATCH 0101/1416] update by comment --- .../paddle/fluid/tests/unittests/test_listen_and_serv_op.py | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/python/paddle/fluid/tests/unittests/test_listen_and_serv_op.py b/python/paddle/fluid/tests/unittests/test_listen_and_serv_op.py index 6be24b09447..1226027ddc9 100644 --- a/python/paddle/fluid/tests/unittests/test_listen_and_serv_op.py +++ b/python/paddle/fluid/tests/unittests/test_listen_and_serv_op.py @@ -82,6 +82,10 @@ class TestListenAndServOp(OpTest): except os.error: retry_times -= 1 + def test_rpc_interfaces(self): + # TODO(Yancey1989): need to make sure the rpc interface correctly. + pass + def test_handle_signal_in_serv_op(self): # run pserver on CPU in sync mode pid = self._start_pserver(False, True) -- GitLab From 6ae7cbe252178e7bd3e5c3b7cde21581948b478f Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Mon, 4 Jun 2018 11:08:08 +0800 Subject: [PATCH 0102/1416] follow comments --- .../fluid/inference/tests/book/CMakeLists.txt | 3 ++- .../tests/book/test_inference_nlp.cc | 21 ++++++++++--------- 2 files changed, 13 insertions(+), 11 deletions(-) diff --git a/paddle/fluid/inference/tests/book/CMakeLists.txt b/paddle/fluid/inference/tests/book/CMakeLists.txt index b33df2942a8..2fa5a9540ba 100644 --- a/paddle/fluid/inference/tests/book/CMakeLists.txt +++ b/paddle/fluid/inference/tests/book/CMakeLists.txt @@ -40,8 +40,9 @@ inference_test(recommender_system) inference_test(word2vec) # This is an unly work around to make this test run +# TODO(TJ): clean me up cc_test(test_inference_nlp SRCS test_inference_nlp.cc DEPS paddle_fluid ARGS - --modelpath=${PADDLE_BINARY_DIR}/python/paddle/fluid/tests/book/recognize_digits_mlp.inference.model) + --model_path=${PADDLE_BINARY_DIR}/python/paddle/fluid/tests/book/recognize_digits_mlp.inference.model) diff --git a/paddle/fluid/inference/tests/book/test_inference_nlp.cc b/paddle/fluid/inference/tests/book/test_inference_nlp.cc index c3bec279252..70aa42ac411 100644 --- a/paddle/fluid/inference/tests/book/test_inference_nlp.cc +++ b/paddle/fluid/inference/tests/book/test_inference_nlp.cc @@ -24,8 +24,8 @@ limitations under the License. */ #include #endif -DEFINE_string(modelpath, "", "Directory of the inference model."); -DEFINE_string(datafile, "", "File of input index data."); +DEFINE_string(model_path, "", "Directory of the inference model."); +DEFINE_string(data_file, "", "File of input index data."); DEFINE_int32(repeat, 100, "Running the inference program repeat times"); DEFINE_bool(use_mkldnn, false, "Use MKLDNN to run inference"); DEFINE_bool(prepare_vars, true, "Prepare variables before executor"); @@ -65,6 +65,7 @@ size_t LoadData(std::vector* out, ids.push_back(stoi(field)); } if (ids.size() >= 1024) { + // Synced with NLP guys, they will ignore input larger then 1024 continue; } @@ -142,18 +143,18 @@ void ThreadRunInfer( } TEST(inference, nlp) { - if (FLAGS_modelpath.empty()) { - LOG(FATAL) << "Usage: ./example --modelpath=path/to/your/model"; + if (FLAGS_model_path.empty()) { + LOG(FATAL) << "Usage: ./example --model_path=path/to/your/model"; } - if (FLAGS_datafile.empty()) { - LOG(WARNING) << " Not data file provided, will use dummy data!" + if (FLAGS_data_file.empty()) { + LOG(WARNING) << "No data file provided, will use dummy data!" << "Note: if you use nlp model, please provide data file."; } - LOG(INFO) << "Model Path: " << FLAGS_modelpath; - LOG(INFO) << "Data File: " << FLAGS_datafile; + LOG(INFO) << "Model Path: " << FLAGS_model_path; + LOG(INFO) << "Data File: " << FLAGS_data_file; std::vector datasets; - size_t num_total_words = LoadData(&datasets, FLAGS_datafile); + size_t num_total_words = LoadData(&datasets, FLAGS_data_file); LOG(INFO) << "Number of samples (seq_len<1024): " << datasets.size(); LOG(INFO) << "Total number of words: " << num_total_words; @@ -168,7 +169,7 @@ TEST(inference, nlp) { // 2. Initialize the inference_program and load parameters std::unique_ptr inference_program; inference_program = - InitProgram(&executor, scope.get(), FLAGS_modelpath, model_combined); + InitProgram(&executor, scope.get(), FLAGS_model_path, model_combined); if (FLAGS_use_mkldnn) { EnableMKLDNN(inference_program); } -- GitLab From f1facb7a3c8b61d9231d27408b173e388818f44b Mon Sep 17 00:00:00 2001 From: weixing02 Date: Mon, 4 Jun 2018 11:33:35 +0800 Subject: [PATCH 0103/1416] Fix links --- doc/v2/build_and_install/build_from_source_cn.rst | 12 ++++++------ doc/v2/build_and_install/build_from_source_en.rst | 12 +++++++----- 2 files changed, 13 insertions(+), 11 deletions(-) diff --git a/doc/v2/build_and_install/build_from_source_cn.rst b/doc/v2/build_and_install/build_from_source_cn.rst index 741c01ce542..de7e9eb75c3 100644 --- a/doc/v2/build_and_install/build_from_source_cn.rst +++ b/doc/v2/build_and_install/build_from_source_cn.rst @@ -23,7 +23,7 @@ PaddlePaddle需要使用Docker环境完成编译，这样可以免去单独安 在 `这里 `__ 找到 paddle_manylinux_devel 镜像的编译以及使用方法。或者参考下述可选步骤，从源码中构建用于编译PaddlePaddle的Docker镜像。 -如果您选择不使用Docker镜像，则需要在本机安装下面章节列出的 `编译依赖`_ 之后才能开始编译的步骤。 +如果您选择不使用Docker镜像，则需要在本机安装下面章节列出的 :ref:`编译依赖 <_compile_deps>` 之后才能开始编译的步骤。 编译PaddlePaddle，需要执行： @@ -106,7 +106,7 @@ PaddlePaddle需要使用Docker环境完成编译，这样可以免去单独安 - 学习 Docker 有多难？ - 理解 Docker 并不难，大概花十分钟看一下[这篇文章](https://zhuanlan.zhihu.com/p/19902938)。这可以帮您省掉花一小时安装和配置各种开发工具，以及切换机器时需要新安装的辛苦。别忘了 PaddlePaddle 更新可能导致需要新的开发工具。更别提简化问题复现带来的好处了。 + 理解 Docker 并不难，大概花十分钟看一下 `这篇文章 `_ 。这可以帮您省掉花一小时安装和配置各种开发工具，以及切换机器时需要新安装的辛苦。别忘了 PaddlePaddle 更新可能导致需要新的开发工具。更别提简化问题复现带来的好处了。 - 我可以用 IDE 吗？ @@ -123,7 +123,7 @@ PaddlePaddle需要使用Docker环境完成编译，这样可以免去单独安 - 可以并行编译吗？ - 是的。我们的 Docker image 运行一个 [Bash 脚本](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/scripts/docker/build.sh)。这个脚本调用 `make -j$(nproc)` 来启动和 CPU 核一样多的进程来并行编译。 + 是的。我们的 Docker image 运行一个 `Bash脚本 `_ 。这个脚本调用 `make -j$(nproc)` 来启动和 CPU 核一样多的进程来并行编译。 - Docker 需要 sudo @@ -131,11 +131,11 @@ PaddlePaddle需要使用Docker环境完成编译，这样可以免去单独安 - 在 Windows/MacOS 上编译很慢 - Docker 在 Windows 和 MacOS 都可以运行。不过实际上是运行在一个 Linux 虚拟机上。可能需要注意给这个虚拟机多分配一些 CPU 和内存，以保证编译高效。具体做法请参考[这个issue](https://github.com/PaddlePaddle/Paddle/issues/627)。 + Docker 在 Windows 和 MacOS 都可以运行。不过实际上是运行在一个 Linux 虚拟机上。可能需要注意给这个虚拟机多分配一些 CPU 和内存，以保证编译高效。具体做法请参考 `这个issue `_ 。 - 磁盘不够 - 本文中的例子里，`docker run` 命令里都用了 `--rm` 参数，这样保证运行结束之后的 containers 不会保留在磁盘上。可以用 `docker ps -a` 命令看到停止后但是没有删除的 containers。`docker build` 命令有时候会产生一些中间结果，是没有名字的 images，也会占用磁盘。可以参考[这篇文章](https://zaiste.net/posts/removing_docker_containers/)来清理这些内容。 + 本文中的例子里，`docker run` 命令里都用了 `--rm` 参数，这样保证运行结束之后的 containers 不会保留在磁盘上。可以用 `docker ps -a` 命令看到停止后但是没有删除的 containers。`docker build` 命令有时候会产生一些中间结果，是没有名字的 images，也会占用磁盘。可以参考 `这篇文章 `_ 来清理这些内容。 .. _compile_deps: @@ -211,7 +211,7 @@ PaddlePaddle可以使用cuDNN v5.1之后的任何一个版本来编译运行， 编译选项的设置 ++++++++++++++ -PaddePaddle通过编译时指定路径来实现引用各种BLAS/CUDA/cuDNN库。cmake编译时，首先在系统路径（ :code:`/usr/lib:/usr/local/lib` ）中搜索这几个库，同时也会读取相关路径变量来进行搜索。 通过使用 ``-D`` 命令可以设置，例如 +PaddePaddle通过编译时指定路径来实现引用各种BLAS/CUDA/cuDNN库。cmake编译时，首先在系统路径（ :code:`/usr/lib:/usr/local/lib` ）中搜索这几个库，同时也会读取相关路径变量来进行搜索。 通过使用 ``-D`` 命令可以设置，例如 .. code-block:: bash diff --git a/doc/v2/build_and_install/build_from_source_en.rst b/doc/v2/build_and_install/build_from_source_en.rst index b06c43e19dc..b08b45d43ec 100644 --- a/doc/v2/build_and_install/build_from_source_en.rst +++ b/doc/v2/build_and_install/build_from_source_en.rst @@ -11,7 +11,7 @@ To build PaddlePaddle, you need 1. A computer -- Linux, Windows, MacOS. 2. Docker. -Nothing else. Not even Python and GCC, because you can install all build tools into a Docker image. +Nothing else. Not even Python and GCC, because you can install all build tools into a Docker image. We run all the tools by running this image. .. _build_step: @@ -26,6 +26,8 @@ you can also find how to build and use paddle_manylinux_devel Docker image from `here `__ Or you can build your own image from source as the optional step below: +If you don't wish to use docker，you need to install several compile dependencies manually as :ref:`Compile Dependencies <_compile_deps>` shows to start compilation. + .. code-block:: bash # 1. clone the source code @@ -108,7 +110,7 @@ Frequently Asked Questions - How difficult is it to learn Docker? - It takes you ten minutes to read [an introductory article](https://docs.docker.com/get-started) and saves you more than one hour to install all required build tools, configure them, especially when new versions of PaddlePaddle require some new tools. Not even to mention the time saved when other people trying to reproduce the issue you have. + It takes you ten minutes to read `an introductory article `_ and saves you more than one hour to install all required build tools, configure them, especially when new versions of PaddlePaddle require some new tools. Not even to mention the time saved when other people trying to reproduce the issue you have. - Can I use my favorite IDE? @@ -125,7 +127,7 @@ Frequently Asked Questions - Does Docker do parallel building? - Our building Docker image runs a [Bash script](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/scripts/docker/build.sh), which calls `make -j$(nproc)` to starts as many processes as the number of your CPU cores. + Our building Docker image runs a `Bash script `_ , which calls `make -j$(nproc)` to starts as many processes as the number of your CPU cores. - Docker requires sudo @@ -133,11 +135,11 @@ Frequently Asked Questions - Docker on Windows/MacOS builds slowly - On Windows and MacOS, Docker containers run in a Linux VM. You might want to give this VM some more memory and CPUs so to make the building efficient. Please refer to [this issue](https://github.com/PaddlePaddle/Paddle/issues/627) for details. + On Windows and MacOS, Docker containers run in a Linux VM. You might want to give this VM some more memory and CPUs so to make the building efficient. Please refer to `this issue `_ for details. - Not enough disk space - Examples in this article use option `--rm` with the `docker run` command. This option ensures that stopped containers do not exist on hard disks. We can use `docker ps -a` to list all containers, including stopped. Sometimes `docker build` generates some intermediate dangling images, which also take disk space. To clean them, please refer to [this article](https://zaiste.net/posts/removing_docker_containers/). + Examples in this article use option `--rm` with the `docker run` command. This option ensures that stopped containers do not exist on hard disks. We can use `docker ps -a` to list all containers, including stopped. Sometimes `docker build` generates some intermediate dangling images, which also take disk space. To clean them, please refer to `this article `_ . .. _compile_deps: -- GitLab From 05a2a1a9064cdd1bf02f46603b2ee814bee4031d Mon Sep 17 00:00:00 2001 From: weixing02 Date: Mon, 4 Jun 2018 05:24:31 +0000 Subject: [PATCH 0104/1416] update apis --- doc/fluid/api/io.rst | 18 ++++++++++ doc/fluid/api/layers.rst | 72 ++++++++++++++++++++++++------------- doc/fluid/api/optimizer.rst | 44 ++++++++--------------- doc/fluid/api/profiler.rst | 12 +++++++ 4 files changed, 92 insertions(+), 54 deletions(-) diff --git a/doc/fluid/api/io.rst b/doc/fluid/api/io.rst index dd9d88b6699..3e956f8302d 100644 --- a/doc/fluid/api/io.rst +++ b/doc/fluid/api/io.rst @@ -59,3 +59,21 @@ get_inference_program .. autofunction:: paddle.fluid.io.get_inference_program :noindex: +save_checkpoint +--------------- + +.. autofunction:: paddle.fluid.io.save_checkpoint + :noindex: + +load_checkpoint +--------------- + +.. autofunction:: paddle.fluid.io.load_checkpoint + :noindex: + +clean_checkpoint +---------------- + +.. autofunction:: paddle.fluid.io.clean_checkpoint + :noindex: + diff --git a/doc/fluid/api/layers.rst b/doc/fluid/api/layers.rst index 5329adaa18b..f78e6db3268 100644 --- a/doc/fluid/api/layers.rst +++ b/doc/fluid/api/layers.rst @@ -181,6 +181,12 @@ Print .. autofunction:: paddle.fluid.layers.Print :noindex: +is_empty +-------- + +.. autofunction:: paddle.fluid.layers.is_empty + :noindex: + device ====== @@ -255,6 +261,19 @@ double_buffer .. autofunction:: paddle.fluid.layers.double_buffer :noindex: +random_data_generator +--------------------- + +.. autofunction:: paddle.fluid.layers.random_data_generator + :noindex: + +Preprocessor +------------ + +.. autoclass:: paddle.fluid.layers.Preprocessor + :members: + :noindex: + nn == @@ -594,6 +613,29 @@ roi_pool .. autofunction:: paddle.fluid.layers.roi_pool :noindex: +dice_loss +--------- + +.. autofunction:: paddle.fluid.layers.dice_loss + :noindex: + +resize_bilinear +--------------- + +.. autofunction:: paddle.fluid.layers.resize_bilinear + :noindex: + +gather +------ + +.. autofunction:: paddle.fluid.layers.gather + :noindex: + +random_crop +----------- + +.. autofunction:: paddle.fluid.layers.random_crop + :noindex: ops === @@ -742,6 +784,12 @@ sum .. autofunction:: paddle.fluid.layers.sum :noindex: +shape +----- + +.. autofunction:: paddle.fluid.layers.shape + :noindex: + sigmoid ------- @@ -991,27 +1039,3 @@ zeros .. autofunction:: paddle.fluid.layers.zeros :noindex: -topk ----- - -.. autofunction:: paddle.fluid.layers.topk - :noindex: - -dice_loss ----- - -.. autofunction:: paddle.fluid.layers.dice_loss - :noindex: - -resize_bilinear -____ - -.. autofunction:: paddle.fluid.layers.resize_bilinear - :noindex: - -gather -____ - -.. autofunction:: paddle.fluid.layers.gather - :noindex: - diff --git a/doc/fluid/api/optimizer.rst b/doc/fluid/api/optimizer.rst index df2bd2eace5..6ad44bb6905 100644 --- a/doc/fluid/api/optimizer.rst +++ b/doc/fluid/api/optimizer.rst @@ -47,28 +47,6 @@ DecayedAdagrad :members: :noindex: -Adadelta ------------------ - -.. autoclass:: paddle.fluid.optimizer.Adadelta - :members: - :noindex: - -RMSProp ------------------ - -.. autoclass:: paddle.fluid.optimizer.RMSProp - :members: - :noindex: - -ModelAverage ------------------ - -.. autoclass:: paddle.fluid.optimizer.ModelAverage - :members: - :noindex: - - SGDOptimizer ------------ @@ -111,25 +89,31 @@ DecayedAdagradOptimizer :members: :noindex: +RMSPropOptimizer +---------------- -AdadeltaOptimizer ------------------ - -.. autoclass:: paddle.fluid.optimizer.AdadeltaOptimizer +.. autoclass:: paddle.fluid.optimizer.RMSPropOptimizer :members: :noindex: +Adadelta +-------- -RMSPropOptimizer ------------------ +.. autoclass:: paddle.fluid.optimizer.Adadelta + :members: + :noindex: -.. autoclass:: paddle.fluid.optimizer.RMSPropOptimizer +ModelAverage +------------ + +.. autoclass:: paddle.fluid.optimizer.ModelAverage :members: :noindex: - + Optimizer --------- .. autoclass:: paddle.fluid.optimizer.Optimizer :members: :noindex: + diff --git a/doc/fluid/api/profiler.rst b/doc/fluid/api/profiler.rst index 74d102dcb0d..39fda658634 100644 --- a/doc/fluid/api/profiler.rst +++ b/doc/fluid/api/profiler.rst @@ -23,3 +23,15 @@ profiler .. autofunction:: paddle.fluid.profiler.profiler :noindex: +start_profiler +-------------- + +.. autofunction:: paddle.fluid.profiler.start_profiler + :noindex: + +stop_profiler +------------- + +.. autofunction:: paddle.fluid.profiler.stop_profiler + :noindex: + -- GitLab From 744cc412b779333f2869653d9c6d462fba3521eb Mon Sep 17 00:00:00 2001 From: fengjiayi Date: Mon, 4 Jun 2018 14:11:25 +0800 Subject: [PATCH 0105/1416] fix a bug --- paddle/fluid/operators/reader/open_files_op.cc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/paddle/fluid/operators/reader/open_files_op.cc b/paddle/fluid/operators/reader/open_files_op.cc index c0526e45f4d..2cbae8a90a9 100644 --- a/paddle/fluid/operators/reader/open_files_op.cc +++ b/paddle/fluid/operators/reader/open_files_op.cc @@ -27,7 +27,7 @@ class MultiFileReader : public framework::ReaderBase { const std::vector& dims, size_t thread_num, size_t buffer_size) : buffer_size_(buffer_size) { - readers_.resize(file_names.size()); + readers_.reserve(file_names.size()); for (const std::string& f_name : file_names) { readers_.emplace_back(CreateReaderByFileName(f_name, dims)); } -- GitLab From 6ac47a3d90c64f283fb4b5ab30acac46efb2fe91 Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Mon, 4 Jun 2018 14:48:02 +0800 Subject: [PATCH 0106/1416] rename Mkldnn to MKLDNN --- .../fluid/operators/activation_mkldnn_op.cc | 24 +++++++++---------- 1 file changed, 12 insertions(+), 12 deletions(-) diff --git a/paddle/fluid/operators/activation_mkldnn_op.cc b/paddle/fluid/operators/activation_mkldnn_op.cc index b892ac77d9e..46ed99bcf22 100644 --- a/paddle/fluid/operators/activation_mkldnn_op.cc +++ b/paddle/fluid/operators/activation_mkldnn_op.cc @@ -222,35 +222,35 @@ struct MKLDNNActivationGradFunc : public BaseActivationFunctor { }; template -using ReluMkldnnFunctor = +using ReluMKLDNNFunctor = MKLDNNActivationFunc; template -using TanhMkldnnFunctor = +using TanhMKLDNNFunctor = MKLDNNActivationFunc; template -using SqrtMkldnnFunctor = +using SqrtMKLDNNFunctor = MKLDNNActivationFunc; template -using AbsMkldnnFunctor = +using AbsMKLDNNFunctor = MKLDNNActivationFunc; template -using ReluMkldnnGradFunctor = +using ReluMKLDNNGradFunctor = MKLDNNActivationGradFunc; template -using TanhMkldnnGradFunctor = +using TanhMKLDNNGradFunctor = MKLDNNActivationGradFunc; template -using SqrtMkldnnGradFunctor = +using SqrtMKLDNNGradFunctor = MKLDNNActivationGradFunc; template -using AbsMkldnnGradFunctor = +using AbsMKLDNNGradFunctor = MKLDNNActivationGradFunc; } // namespace operators } // namespace paddle @@ -265,9 +265,9 @@ namespace ops = paddle::operators; ops::MKLDNNActivationGradKernel>); #define FOR_EACH_MKLDNN_KERNEL_FUNCTOR(__macro) \ - __macro(relu, ReluMkldnnFunctor, ReluMkldnnGradFunctor); \ - __macro(tanh, TanhMkldnnFunctor, TanhMkldnnGradFunctor); \ - __macro(sqrt, SqrtMkldnnFunctor, SqrtMkldnnGradFunctor); \ - __macro(abs, AbsMkldnnFunctor, AbsMkldnnGradFunctor); + __macro(relu, ReluMKLDNNFunctor, ReluMKLDNNGradFunctor); \ + __macro(tanh, TanhMKLDNNFunctor, TanhMKLDNNGradFunctor); \ + __macro(sqrt, SqrtMKLDNNFunctor, SqrtMKLDNNGradFunctor); \ + __macro(abs, AbsMKLDNNFunctor, AbsMKLDNNGradFunctor); FOR_EACH_MKLDNN_KERNEL_FUNCTOR(REGISTER_ACTIVATION_MKLDNN_KERNEL); -- GitLab From 1666cf96bfed426be8debdefa9a8a561f5a8a13f Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Mon, 4 Jun 2018 14:53:24 +0800 Subject: [PATCH 0107/1416] update by comment --- doc/fluid/howto/cluster/fluid_recordio.md | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/doc/fluid/howto/cluster/fluid_recordio.md b/doc/fluid/howto/cluster/fluid_recordio.md index 0e8b98542d1..55ce63ec193 100644 --- a/doc/fluid/howto/cluster/fluid_recordio.md +++ b/doc/fluid/howto/cluster/fluid_recordio.md @@ -23,7 +23,10 @@ as follows: fluid.recordio_writer.convert_reader_to_recordio_file('./mnist.recordio', reader, feeder) ``` -The above codes would generate a RecordIO `./mnist.recordio` on your host. +The above code snippet would generate a RecordIO `./mnist.recordio` on your host. + +**NOTE**: we recommend users to set `batch_size=1` when generating the recordio files so that users can +adjust it flexibly while reading it. ## Use the RecordIO file in a Local Training Job @@ -96,7 +99,7 @@ The above codes would generate multiple RecordIO files on your host like: |-mnist-00004.recordio ``` -1. open multiple RecordIO files by `fluid.layers.io.open_files` +2. open multiple RecordIO files by `fluid.layers.io.open_files` For a distributed training job, the distributed operator system will schedule trainer process on multiple nodes, each trainer process reads parts of the whole training data, we usually take the following approach to make the training -- GitLab From c06f43bbb6aec4ae12d514ca92a77aed0d473882 Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Mon, 4 Jun 2018 15:20:06 +0800 Subject: [PATCH 0108/1416] add annotation about _is_checkpoint_var --- python/paddle/fluid/io.py | 5 +++-- tools/codestyle/docstring_checker.pyc | Bin 12561 -> 12561 bytes 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/python/paddle/fluid/io.py b/python/paddle/fluid/io.py index 62e3046db64..75146fe3269 100644 --- a/python/paddle/fluid/io.py +++ b/python/paddle/fluid/io.py @@ -639,13 +639,14 @@ def _is_checkpoint_var(var): var.desc.type() == core.VarDesc.VarType.FETCH_LIST or \ var.desc.type() == core.VarDesc.VarType.RAW: return False - + # @GRAD are named for gradient varibales, checkpoint will not save it. if "@GRAD" in var.name: return False - + # .trainer_ are named for distribute trian variables, checkpoint will not save it. if ".trainer_" in var.name: return False + # .block is named for distribute trian variables, checkpoint will not save it. if ".block" in var.name: return False diff --git a/tools/codestyle/docstring_checker.pyc b/tools/codestyle/docstring_checker.pyc index 1f0255b763c8d154b7cc17d2d525148dfea3b42d..a27d3c9a8cccab8552d510578debb2df04eb53bb 100644 GIT binary patch delta 16 XcmbQ3G%<;t`7|BNbF9rm> delta 16 XcmbQ3G%<;t`7|BNbF*pSi -- GitLab From 3526ac1136eb51decb567b4cd0230ac9bae5c244 Mon Sep 17 00:00:00 2001 From: fengjiayi Date: Mon, 4 Jun 2018 15:35:06 +0800 Subject: [PATCH 0109/1416] refine code --- paddle/fluid/operators/reader/open_files_op.cc | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/paddle/fluid/operators/reader/open_files_op.cc b/paddle/fluid/operators/reader/open_files_op.cc index 2cbae8a90a9..31e5d81e55e 100644 --- a/paddle/fluid/operators/reader/open_files_op.cc +++ b/paddle/fluid/operators/reader/open_files_op.cc @@ -63,9 +63,6 @@ void MultiFileReader::ReadNext(std::vector* out) { void MultiFileReader::ReInit() { EndScheduler(); - for (auto& reader : readers_) { - reader->ReInit(); - } StartNewScheduler(); } @@ -141,6 +138,7 @@ void MultiFileReader::PrefetchThreadFunc(size_t reader_idx, size_t thread_idx) { std::vector ins; reader->ReadNext(&ins); if (ins.empty()) { + reader->ReInit(); break; } try { -- GitLab From 08e5f0ae482c1e70dc74c4677e5cb699b38c433e Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Mon, 4 Jun 2018 16:10:11 +0800 Subject: [PATCH 0110/1416] rename need_load_checkpoint to get_latest_checkpoint_serial --- python/paddle/fluid/io.py | 4 ++-- python/paddle/fluid/trainer.py | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/python/paddle/fluid/io.py b/python/paddle/fluid/io.py index 75146fe3269..111907b5751 100644 --- a/python/paddle/fluid/io.py +++ b/python/paddle/fluid/io.py @@ -25,7 +25,7 @@ __all__ = [ 'load_persistables', 'save_inference_model', 'load_inference_model', 'get_inference_program', 'save_checkpoint', 'load_checkpoint', 'clean_checkpoint', 'load_persist_vars_without_grad', - 'save_persist_vars_without_grad' + 'save_persist_vars_without_grad', 'get_latest_checkpoint_serial' ] @@ -503,7 +503,7 @@ def save_checkpoint(executor, _lru_delete(checkpoint_dir, max_num_checkpoints) -def need_load_checkpoint(checkpoint_dir): +def get_latest_checkpoint_serial(checkpoint_dir): """ If the directory have checkpoint files, it will return lastest checkpoint directory serial number diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py index 72168886fdb..3c32ec1de8a 100644 --- a/python/paddle/fluid/trainer.py +++ b/python/paddle/fluid/trainer.py @@ -146,7 +146,7 @@ class Trainer(object): "The checkpoint_config shoule be an instance of CheckpointConfig" ) else: - self.checkpoint.load_serial = io.need_load_checkpoint( + self.checkpoint.load_serial = io.get_latest_checkpoint_serial( self.checkpoint.checkpoint_dir) self.scope = core.Scope() -- GitLab From 97b2f6f5f961575633b3ba0e8ea7b5c2fd5d4396 Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Mon, 4 Jun 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z*2=5ec|4ib=HU3?r4fZ;`ZP;kemW=ElZck%FlLvD*mGM?1AlV(QzjUFVJjw0uhfUF QVT9NjS|84r2F9-c7hLv=%K!iX -- GitLab From 9d3114c8c99b46a90b76811b3a2b19b1c1e31919 Mon Sep 17 00:00:00 2001 From: "yi.wu" Date: Mon, 4 Jun 2018 18:42:44 +0800 Subject: [PATCH 0112/1416] fix transpiler error --- .../paddle/fluid/transpiler/distribute_transpiler.py | 12 ++++++++++-- 1 file changed, 10 insertions(+), 2 deletions(-) diff --git a/python/paddle/fluid/transpiler/distribute_transpiler.py b/python/paddle/fluid/transpiler/distribute_transpiler.py index da001add8e1..27992df462f 100644 --- a/python/paddle/fluid/transpiler/distribute_transpiler.py +++ b/python/paddle/fluid/transpiler/distribute_transpiler.py @@ -187,12 +187,17 @@ class DistributeTranspiler: param_list = [] grad_list = [] + param_grad_set = set() for p, g in self.params_grads: # skip parameter marked not trainable if type(p) == Parameter and p.trainable == False: continue - param_list.append(p) - grad_list.append(g) + if p.name not in param_grad_set: + param_list.append(p) + param_grad_set.add(p.name) + if g.name not in param_grad_set: + grad_list.append(g) + param_grad_set.add(g.name) self._update_dist_lookup_table_vars(param_list, grad_list, self.params_grads) @@ -829,6 +834,9 @@ class DistributeTranspiler: if not block_map.has_key(varname): block_map[varname] = [] block_map[varname].append((long(offset), long(size))) + # Do not remove this important debug message: + print("block map: %s" % block_map) + for varname, splited in block_map.iteritems(): orig_var = program.global_block().var(varname) if len(splited) == 1: -- GitLab From 1766406f76ebf93f3ff1acc57c15019c4a2dacdd Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Mon, 4 Jun 2018 19:47:16 +0800 Subject: [PATCH 0113/1416] delete unused code --- paddle/fluid/operators/detail/grpc_server.h | 2 -- 1 file changed, 2 deletions(-) diff --git a/paddle/fluid/operators/detail/grpc_server.h b/paddle/fluid/operators/detail/grpc_server.h index eae87de4201..e6ffc7066f2 100644 --- a/paddle/fluid/operators/detail/grpc_server.h +++ b/paddle/fluid/operators/detail/grpc_server.h @@ -71,8 +71,6 @@ class AsyncGRPCServer final : public RPCServer { std::unique_ptr<::grpc::Server> server_; // condition of the sub program - // std::mutex barrier_mutex_; - // mutable int barrier_cond_step_; std::condition_variable barrier_condition_; std::mutex mutex_ready_; -- GitLab From dcf40fd0bc5a7ed48e954feb591c63defd689f45 Mon Sep 17 00:00:00 2001 From: Luo Tao Date: Mon, 4 Jun 2018 20:39:34 +0800 Subject: [PATCH 0114/1416] refine benchmark --- benchmark/.gitignore | 3 +++ benchmark/fluid/fluid_benchmark.py | 31 ++++++++++++++++-------------- benchmark/fluid/run.sh | 20 ++++++++++--------- 3 files changed, 31 insertions(+), 23 deletions(-) diff --git a/benchmark/.gitignore b/benchmark/.gitignore index 7b66e8a5b50..fb4114356d4 100644 --- a/benchmark/.gitignore +++ b/benchmark/.gitignore @@ -7,3 +7,6 @@ paddle/rnn/imdb.pkl caffe/image/logs tensorflow/image/logs tensorflow/rnn/logs +fluid/models/*.pyc +fluid/logs +fluid/nohup.out diff --git a/benchmark/fluid/fluid_benchmark.py b/benchmark/fluid/fluid_benchmark.py index c1d458970a5..cac1b0fad00 100644 --- a/benchmark/fluid/fluid_benchmark.py +++ b/benchmark/fluid/fluid_benchmark.py @@ -40,10 +40,7 @@ def parse_args(): parser.add_argument( '--batch_size', type=int, default=32, help='The minibatch size.') parser.add_argument( - '--learning_rate', - type=float, - default=0.001, - help='The minibatch size.') + '--learning_rate', type=float, default=0.001, help='The learning rate.') # TODO(wuyi): add "--use_fake_data" option back. parser.add_argument( '--skip_batch_num', @@ -72,6 +69,11 @@ def parse_args(): type=int, default=1, help='If gpus > 1, will use ParallelExecutor to run, else use Executor.') + parser.add_argument( + '--cpus', + type=int, + default=1, + help='If cpus > 1, will use ParallelDo to run, else use Executor.') parser.add_argument( '--data_set', type=str, @@ -231,10 +233,7 @@ def train(avg_loss, infer_prog, optimizer, train_reader, test_reader, batch_acc, train_losses.append(loss) print("Pass: %d, Iter: %d, Loss: %f\n" % (pass_id, iters, np.mean(train_losses))) - train_elapsed = time.time() - start_time - examples_per_sec = num_samples / train_elapsed - print('\nTotal examples: %d, total time: %.5f, %.5f examples/sec\n' % - (num_samples, train_elapsed, examples_per_sec)) + print_train_time(start_time, time.time(), num_samples) print("Pass: %d, Loss: %f" % (pass_id, np.mean(train_losses))) # evaluation if not args.no_test and batch_acc != None: @@ -315,10 +314,7 @@ def train_parallel(avg_loss, infer_prog, optimizer, train_reader, test_reader, if batch_id % 1 == 0: print("Pass %d, batch %d, loss %s" % (pass_id, batch_id, np.array(loss))) - train_elapsed = time.time() - start_time - examples_per_sec = num_samples / train_elapsed - print('\nTotal examples: %d, total time: %.5f, %.5f examples/sed\n' % - (num_samples, train_elapsed, examples_per_sec)) + print_train_time(start_time, time.time(), num_samples) if not args.no_test and batch_acc != None: test_acc = test(startup_exe, infer_prog, test_reader, feeder, batch_acc) @@ -329,12 +325,19 @@ def train_parallel(avg_loss, infer_prog, optimizer, train_reader, test_reader, def print_arguments(args): vars(args)['use_nvprof'] = (vars(args)['use_nvprof'] and vars(args)['device'] == 'GPU') - print('----------- resnet Configuration Arguments -----------') + print('----------- Configuration Arguments -----------') for arg, value in sorted(vars(args).iteritems()): print('%s: %s' % (arg, value)) print('------------------------------------------------') +def print_train_time(start_time, end_time, num_samples): + train_elapsed = end_time - start_time + examples_per_sec = num_samples / train_elapsed + print('\nTotal examples: %d, total time: %.5f, %.5f examples/sed\n' % + (num_samples, train_elapsed, examples_per_sec)) + + def main(): args = parse_args() print_arguments(args) @@ -342,7 +345,7 @@ def main(): # the unique trainer id, starting from 0, needed by trainer # only nccl_id_var, num_trainers, trainer_id = ( - None, 1, int(os.getenv("PADDLE_TRAINER_ID", "-1"))) + None, 1, int(os.getenv("PADDLE_TRAINER_ID", "0"))) if args.use_cprof: pr = cProfile.Profile() diff --git a/benchmark/fluid/run.sh b/benchmark/fluid/run.sh index afaab5f4de4..5d9b2db8713 100644 --- a/benchmark/fluid/run.sh +++ b/benchmark/fluid/run.sh @@ -2,6 +2,7 @@ # This script benchmarking the PaddlePaddle Fluid on # single thread single GPU. +mkdir -p logs #export FLAGS_fraction_of_gpu_memory_to_use=0.0 export CUDNN_PATH=/paddle/cudnn_v5 @@ -35,6 +36,7 @@ nohup stdbuf -oL nvidia-smi \ --format=csv \ --filename=mem.log \ -l 1 & + # mnist # mnist gpu mnist 128 FLAGS_benchmark=true stdbuf -oL python fluid_benchmark.py \ @@ -43,7 +45,7 @@ FLAGS_benchmark=true stdbuf -oL python fluid_benchmark.py \ --batch_size=128 \ --skip_batch_num=5 \ --iterations=500 \ - 2>&1 | tee -a mnist_gpu_128.log + 2>&1 | tee -a logs/mnist_gpu_128.log # vgg16 # gpu cifar10 128 @@ -53,7 +55,7 @@ FLAGS_benchmark=true stdbuf -oL python fluid_benchmark.py \ --batch_size=128 \ --skip_batch_num=5 \ --iterations=30 \ - 2>&1 | tee -a vgg16_gpu_128.log + 2>&1 | tee -a logs/vgg16_gpu_128.log # flowers gpu 128 FLAGS_benchmark=true stdbuf -oL python fluid_benchmark.py \ @@ -63,28 +65,28 @@ FLAGS_benchmark=true stdbuf -oL python fluid_benchmark.py \ --data_set=flowers \ --skip_batch_num=5 \ --iterations=30 \ - 2>&1 | tee -a vgg16_gpu_flowers_32.log + 2>&1 | tee -a logs/vgg16_gpu_flowers_32.log # resnet50 # resnet50 gpu cifar10 128 FLAGS_benchmark=true stdbuf -oL python fluid_benchmark.py \ - --model=resnet50 \ + --model=resnet \ --device=GPU \ --batch_size=128 \ --data_set=cifar10 \ --skip_batch_num=5 \ --iterations=30 \ - 2>&1 | tee -a resnet50_gpu_128.log + 2>&1 | tee -a logs/resnet50_gpu_128.log # resnet50 gpu flowers 64 FLAGS_benchmark=true stdbuf -oL python fluid_benchmark.py \ - --model=resnet50 \ + --model=resnet \ --device=GPU \ --batch_size=64 \ --data_set=flowers \ --skip_batch_num=5 \ --iterations=30 \ - 2>&1 | tee -a resnet50_gpu_flowers_64.log + 2>&1 | tee -a logs/resnet50_gpu_flowers_64.log # lstm # lstm gpu imdb 32 # tensorflow only support batch=32 @@ -94,7 +96,7 @@ FLAGS_benchmark=true stdbuf -oL python fluid_benchmark.py \ --batch_size=32 \ --skip_batch_num=5 \ --iterations=30 \ - 2>&1 | tee -a lstm_gpu_32.log + 2>&1 | tee -a logs/lstm_gpu_32.log # seq2seq # seq2seq gpu wmb 128 @@ -104,4 +106,4 @@ FLAGS_benchmark=true stdbuf -oL python fluid_benchmark.py \ --batch_size=128 \ --skip_batch_num=5 \ --iterations=30 \ - 2>&1 | tee -a lstm_gpu_128.log + 2>&1 | tee -a logs/lstm_gpu_128.log -- GitLab From d58955997e946f1d2c91849a935917e2643f4374 Mon Sep 17 00:00:00 2001 From: "yi.wu" Date: Mon, 4 Jun 2018 20:50:22 +0800 Subject: [PATCH 0115/1416] fix term core only --- cmake/external/grpc.cmake | 11 +++++++++-- 1 file changed, 9 insertions(+), 2 deletions(-) diff --git a/cmake/external/grpc.cmake b/cmake/external/grpc.cmake index 9459f1ddfe8..4b6840578fd 100644 --- a/cmake/external/grpc.cmake +++ b/cmake/external/grpc.cmake @@ -33,10 +33,18 @@ ELSE() SET(BUILD_CMD make HAS_SYSTEM_PROTOBUF=false -s -j ${NUM_OF_PROCESSOR} static grpc_cpp_plugin) ENDIF() +# FIXME(wuyi): do not build zlib cares protobuf twice, find a way to build grpc with them ExternalProject_Add( extern_grpc DEPENDS protobuf zlib - URL "http://paddlepaddledeps.bj.bcebos.com/grpc.tar.xz" + # NOTE(wuyi): + # this package is generated by following steps: + # 1. git clone -b v1.8.x https://github.com/grpc/grpc.git + # 2. submodule update --init + # 3. keep only zlib, cares, protobuf, boringssl under "third_party", + # checkout and clean other dirs under third_party + # 4. remove .git, and package the directory. + URL "http://paddlepaddledeps.bj.bcebos.com/grpc-v1.8.x.tar.gz" PREFIX ${GRPC_SOURCES_DIR} UPDATE_COMMAND "" CONFIGURE_COMMAND "" @@ -49,7 +57,6 @@ ExternalProject_Add( INSTALL_COMMAND make prefix=${GRPC_INSTALL_DIR} install ) -# FIXME(typhoonzero): hack to get static lib path, try a better way like merge them. ADD_LIBRARY(grpc++_unsecure STATIC IMPORTED GLOBAL) SET_PROPERTY(TARGET grpc++_unsecure PROPERTY IMPORTED_LOCATION "${GRPC_INSTALL_DIR}/lib/libgrpc++_unsecure.a") -- GitLab From bfdcf18707c79f2cc29b0903cb9f4fab2e907490 Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Mon, 4 Jun 2018 21:10:38 +0800 Subject: [PATCH 0116/1416] grammar optimized. --- python/paddle/fluid/io.py | 15 +++++++-------- 1 file changed, 7 insertions(+), 8 deletions(-) diff --git a/python/paddle/fluid/io.py b/python/paddle/fluid/io.py index 111907b5751..b5d96441bcf 100644 --- a/python/paddle/fluid/io.py +++ b/python/paddle/fluid/io.py @@ -492,7 +492,7 @@ def save_checkpoint(executor, if not os.path.isdir(checkpoint_dir): os.makedirs(checkpoint_dir) - serial = _get_lastest_checkpoint_dir(checkpoint_dir) + 1 + serial = _get_latest_checkpoint_dir(checkpoint_dir) + 1 cur_dir = _get_serial_dir(checkpoint_dir, serial) save_trainer_args(cur_dir, trainer_id, trainer_args) @@ -505,11 +505,11 @@ def save_checkpoint(executor, def get_latest_checkpoint_serial(checkpoint_dir): """ - If the directory have checkpoint files, it will return lastest checkpoint directory serial number + If the directory have checkpoint files, it will return latest checkpoint directory serial number :param checkpoint_dir """ - serial = _get_lastest_checkpoint_dir(checkpoint_dir) + serial = _get_latest_checkpoint_dir(checkpoint_dir) if serial < 0: return None return serial @@ -639,14 +639,14 @@ def _is_checkpoint_var(var): var.desc.type() == core.VarDesc.VarType.FETCH_LIST or \ var.desc.type() == core.VarDesc.VarType.RAW: return False - # @GRAD are named for gradient varibales, checkpoint will not save it. + # @GRAD are named for gradient variables, checkpoint will not save it. if "@GRAD" in var.name: return False - # .trainer_ are named for distribute trian variables, checkpoint will not save it. + # .trainer_ are named for distribute train variables, checkpoint will not save it. if ".trainer_" in var.name: return False - # .block is named for distribute trian variables, checkpoint will not save it. + # .block is named for distribute train variables, checkpoint will not save it. if ".block" in var.name: return False @@ -656,7 +656,6 @@ def _is_checkpoint_var(var): def _get_dir_serial(dirname): _, serial = dirname.split(CHECKPOINT_SEPARATOR) - serial_num = -1 try: serial_num = int(serial) except ValueError: @@ -723,7 +722,7 @@ def _write_success(dirname): f.write(now) -def _get_lastest_checkpoint_dir(checkpoint_dir): +def _get_latest_checkpoint_dir(checkpoint_dir): """ get the latest file in checkpoint directory, the _SUCCESS file must exist in the directory -- GitLab From 418c41d8fb4a9dd0f221e7c3e3b94d5433493ded Mon Sep 17 00:00:00 2001 From: Yan Chunwei Date: Mon, 4 Jun 2018 22:01:14 +0800 Subject: [PATCH 0117/1416] Feature/anakin embed (#11135) --- paddle/contrib/inference/CMakeLists.txt | 43 +++++++++- .../inference/demo/simple_on_word2vec.cc | 2 +- .../contrib/inference/paddle_inference_api.h | 27 +++--- .../paddle_inference_api_anakin_engine.cc | 82 +++++++++++++++++++ .../paddle_inference_api_anakin_engine.h | 51 ++++++++++++ ...ddle_inference_api_anakin_engine_tester.cc | 27 ++++++ .../inference/paddle_inference_api_impl.cc | 18 ++-- 7 files changed, 229 insertions(+), 21 deletions(-) create mode 100644 paddle/contrib/inference/paddle_inference_api_anakin_engine.cc create mode 100644 paddle/contrib/inference/paddle_inference_api_anakin_engine.h create mode 100644 paddle/contrib/inference/paddle_inference_api_anakin_engine_tester.cc diff --git a/paddle/contrib/inference/CMakeLists.txt b/paddle/contrib/inference/CMakeLists.txt index 8ca34465395..1e3bb7bf16f 100644 --- a/paddle/contrib/inference/CMakeLists.txt +++ b/paddle/contrib/inference/CMakeLists.txt @@ -17,6 +17,42 @@ if(APPLE) set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-error=pessimizing-move") endif(APPLE) +set(ANAKIN_INCLUDE "" CACHE STRING "root of Anakin header files") +set(ANAKIN_LIBRARY "" CACHE STRING "path of Anakin library") + + +set(inference_deps paddle_inference_api paddle_fluid_api) + +# if anakin is set enable anakin api implementation +if(ANAKIN_INCLUDE_DIR AND ANAKIN_LIBRARY) + set(ANAKIN_FOUND ON) +else() + set(ANAKIN_FOUND OFF) +endif() + +if (ANAKIN_FOUND) + # Anakin's code style doesn't follow google c style. + set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-error=comment + -Wno-error=reorder + -Wno-error=format + -Wno-error=switch + -Wno-error=return-type + -Wno-error=non-virtual-dtor + -Wno-error=cpp") + + message(STATUS "Anakin for inference is enabled") + message(STATUS "Anakin is set INCLUDE:${ANAKIN_INCLUDE} LIBRARY:${ANAKIN_LIBRARY}") + include_directories("${ANAKIN_INCLUDE}") + # Anakin's source path is a mass, need to set sub-directories trivially. + include_directories("${ANAKIN_INCLUDE}/saber") + link_directories("${ANAKIN_LIBRARY}") + + nv_library(inference_anakin_api SRCS paddle_inference_api_anakin_engine.cc) + target_link_libraries(inference_anakin_api anakin) + list(APPEND inference_deps inference_anakin_api) +endif() + + function(inference_api_test TARGET_NAME) if (WITH_TESTING) set(options "") @@ -27,7 +63,7 @@ function(inference_api_test TARGET_NAME) set(PYTHON_TESTS_DIR ${PADDLE_BINARY_DIR}/python/paddle/fluid/tests) cc_test(${TARGET_NAME} SRCS ${TARGET_NAME}.cc - DEPS paddle_fluid paddle_inference_api + DEPS "${inference_deps}" ARGS --dirname=${PYTHON_TESTS_DIR}/book/) if(inference_test_ARGS) set_tests_properties(${TARGET_NAME} @@ -47,6 +83,11 @@ cc_test(test_paddle_inference_api inference_api_test(test_paddle_inference_api_impl ARGS test_word2vec test_image_classification) +if (ANAKIN_FOUND) + nv_test(inference_anakin_test SRCS paddle_inference_api_anakin_engine_tester.cc + DEPS ${inference_deps} protobuf) +endif() + if(WITH_TESTING) add_subdirectory(demo) endif() diff --git a/paddle/contrib/inference/demo/simple_on_word2vec.cc b/paddle/contrib/inference/demo/simple_on_word2vec.cc index 165d2e196b3..ee865f37900 100644 --- a/paddle/contrib/inference/demo/simple_on_word2vec.cc +++ b/paddle/contrib/inference/demo/simple_on_word2vec.cc @@ -54,7 +54,7 @@ void Main(bool use_gpu) { CHECK(predictor->Run(slots, &outputs)); //# 4. Get output. - ASSERT_EQ(outputs.size(), 1); + ASSERT_EQ(outputs.size(), 1UL); LOG(INFO) << "output buffer size: " << outputs.front().data.length; const size_t num_elements = outputs.front().data.length / sizeof(float); // The outputs' buffers are in CPU memory. diff --git a/paddle/contrib/inference/paddle_inference_api.h b/paddle/contrib/inference/paddle_inference_api.h index 5fe8399762b..b5cd0d603f1 100644 --- a/paddle/contrib/inference/paddle_inference_api.h +++ b/paddle/contrib/inference/paddle_inference_api.h @@ -1,16 +1,16 @@ /* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. - Licensed under the Apache License, Version 2.0 (the "License"); - you may not use this file except in compliance with the License. - You may obtain a copy of the License at +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at - http://www.apache.org/licenses/LICENSE-2.0 +http://www.apache.org/licenses/LICENSE-2.0 - Unless required by applicable law or agreed to in writing, software - distributed under the License is distributed on an "AS IS" BASIS, - WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - See the License for the specific language governing permissions and - limitations under the License. */ +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ /* * This file contains the definition of a simple Inference API for Paddle. @@ -47,8 +47,8 @@ struct PaddleTensor { enum class PaddleEngineKind { kNative = 0, // Use the native Fluid facility. + kAnakin, // Use Anakin for inference. // TODO(Superjomn) support following engines latter. - // kAnakin, // Use Anakin for inference. // kTensorRT, // Use TensorRT for inference. // kAutoMixedAnakin, // Automatically mix Fluid with Anakin. // kAutoMixedTensorRT, // Automatically mix Fluid with TensorRT. @@ -95,6 +95,13 @@ struct NativeConfig : public PaddlePredictor::Config { std::string param_file; }; +// Configurations for Anakin engine. +struct AnakinConfig : public PaddlePredictor::Config { + int device; + std::string model_file; + int max_batch_size{-1}; +}; + // A factory to help create different predictors. // // FOR EXTENSION DEVELOPER: diff --git a/paddle/contrib/inference/paddle_inference_api_anakin_engine.cc b/paddle/contrib/inference/paddle_inference_api_anakin_engine.cc new file mode 100644 index 00000000000..865d7ac10db --- /dev/null +++ b/paddle/contrib/inference/paddle_inference_api_anakin_engine.cc @@ -0,0 +1,82 @@ +// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include + +#include "paddle/contrib/inference/paddle_inference_api_anakin_engine.h" + +namespace paddle { + +PaddleInferenceAnakinPredictor::PaddleInferenceAnakinPredictor( + const AnakinConfig &config) { + CHECK(Init(config)); +} + +bool PaddleInferenceAnakinPredictor::Init(const AnakinConfig &config) { + // TODO(Superjomn) Tell anakin to support return code. + engine_.Build(config.model_file, config.max_batch_size); + return true; +} + +bool PaddleInferenceAnakinPredictor::Run( + const std::vector &inputs, + std::vector *output_data) { + for (const auto &input : inputs) { + if (input.dtype != PaddleDType::FLOAT32) { + LOG(ERROR) << "Only support float type inputs. " << input.name + << "'s type is not float"; + return false; + } + engine_.SetInputFromCPU( + input.name, static_cast(input.data.data), input.data.length); + } + + // TODO(Superjomn) Tell anakin to support return code. + engine_.Execute(); + + if (output_data->empty()) { + LOG(ERROR) << "At least one output should be set with tensors' names."; + return false; + } + for (auto &output : *output_data) { + auto *tensor = engine_.GetOutputInGPU(output.name); + output.shape = tensor->shape(); + // Copy data from GPU -> CPU + if (cudaMemcpy(output.data.data, + tensor->data(), + tensor->size(), + cudaMemcpyDeviceToHost) != 0) { + LOG(ERROR) << "copy data from GPU to CPU error"; + return false; + } + } + return true; +} + +// TODO(Superjomn) To implement latter. +std::unique_ptr PaddleInferenceAnakinPredictor::Clone() { + return nullptr; +} + +// A factory to help create difference predictor. +template <> +std::unique_ptr +CreatePaddlePredictor( + const AnakinConfig &config) { + std::unique_ptr x( + new PaddleInferenceAnakinPredictor(config)); + return x; +}; + +} // namespace paddle diff --git a/paddle/contrib/inference/paddle_inference_api_anakin_engine.h b/paddle/contrib/inference/paddle_inference_api_anakin_engine.h new file mode 100644 index 00000000000..fe9f562e9d1 --- /dev/null +++ b/paddle/contrib/inference/paddle_inference_api_anakin_engine.h @@ -0,0 +1,51 @@ +/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + +http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +/* + * This file contains the implementation of inference API with Anakin engine + * embeded, this API can only support Anakin models. + */ + +#pragma once + +// NOTE This header file do not have namespace. +// TODO(Superjomn) Tell Anakin to provide better APIs. +#include +#include "paddle/contrib/inference/paddle_inference_api.h" + +namespace paddle { + +class PaddleInferenceAnakinPredictor : public PaddlePredictor { + public: + PaddleInferenceAnakinPredictor(const AnakinConfig& config); + + // NOTE Unlike the native engine, the buffers of anakin engine's output_data + // should be allocated first. + // TODO(Superjomn) should unify all the behaviors of output_data accross all + // the engines. + bool Run(const std::vector& inputs, + std::vector* output_data) override; + + std::unique_ptr Clone() override; + + private: + bool Init(const AnakinConfig& config); + + anakin::AnakinEngine + engine_; +}; + +} // namespace paddle diff --git a/paddle/contrib/inference/paddle_inference_api_anakin_engine_tester.cc b/paddle/contrib/inference/paddle_inference_api_anakin_engine_tester.cc new file mode 100644 index 00000000000..43324bc67cb --- /dev/null +++ b/paddle/contrib/inference/paddle_inference_api_anakin_engine_tester.cc @@ -0,0 +1,27 @@ +/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + +http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#include "paddle/contrib/inference/paddle_inference_api.h" +#include + +namespace paddle { + +TEST(inference, anakin) { + AnakinConfig config; + + auto engine = + CreatePaddlePredictor(config); +} + +} // namespace paddle diff --git a/paddle/contrib/inference/paddle_inference_api_impl.cc b/paddle/contrib/inference/paddle_inference_api_impl.cc index e7a8fa68b7f..b52a43a463d 100644 --- a/paddle/contrib/inference/paddle_inference_api_impl.cc +++ b/paddle/contrib/inference/paddle_inference_api_impl.cc @@ -1,16 +1,16 @@ /* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. - Licensed under the Apache License, Version 2.0 (the "License"); - you may not use this file except in compliance with the License. - You may obtain a copy of the License at +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at - http://www.apache.org/licenses/LICENSE-2.0 +http://www.apache.org/licenses/LICENSE-2.0 - Unless required by applicable law or agreed to in writing, software - distributed under the License is distributed on an "AS IS" BASIS, - WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - See the License for the specific language governing permissions and - limitations under the License. */ +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ #include #include -- GitLab From 79bda2c46d265f6d064d7e176535d1fdcbb055c6 Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Mon, 4 Jun 2018 22:11:08 +0800 Subject: [PATCH 0118/1416] enable infer api with multi-threads --- .../contrib/inference/paddle_inference_api.h | 3 +- .../inference/paddle_inference_api_impl.cc | 41 +++++++++++-------- .../inference/paddle_inference_api_impl.h | 9 ++-- 3 files changed, 33 insertions(+), 20 deletions(-) diff --git a/paddle/contrib/inference/paddle_inference_api.h b/paddle/contrib/inference/paddle_inference_api.h index b5cd0d603f1..c4588cf0403 100644 --- a/paddle/contrib/inference/paddle_inference_api.h +++ b/paddle/contrib/inference/paddle_inference_api.h @@ -63,6 +63,7 @@ class PaddlePredictor { struct Config; PaddlePredictor() = default; PaddlePredictor(const PaddlePredictor&) = delete; + PaddlePredictor& operator=(const PaddlePredictor&) = delete; // Predict an record. // The caller should be responsible for allocating and releasing the memory of @@ -76,7 +77,7 @@ class PaddlePredictor { virtual std::unique_ptr Clone() = 0; // Destroy the Predictor. - virtual ~PaddlePredictor() {} + virtual ~PaddlePredictor() = default; // The common configs for all the predictors. struct Config { diff --git a/paddle/contrib/inference/paddle_inference_api_impl.cc b/paddle/contrib/inference/paddle_inference_api_impl.cc index b52a43a463d..2d710727e23 100644 --- a/paddle/contrib/inference/paddle_inference_api_impl.cc +++ b/paddle/contrib/inference/paddle_inference_api_impl.cc @@ -54,7 +54,7 @@ std::string num2str(T a) { } } // namespace -bool NativePaddlePredictor::Init() { +bool NativePaddlePredictor::Init(std::shared_ptr scope) { VLOG(3) << "Predictor::init()"; if (config_.use_gpu) { @@ -62,9 +62,15 @@ bool NativePaddlePredictor::Init() { } else { place_ = paddle::platform::CPUPlace(); } - paddle::framework::InitDevices(false); + if (scope) { + scope_ = scope; + sub_scope_ = &(scope->NewScope()); + } else { + paddle::framework::InitDevices(false); + scope_.reset(new paddle::framework::Scope()); + } + executor_.reset(new paddle::framework::Executor(place_)); - scope_.reset(new paddle::framework::Scope()); // Initialize the inference program if (!config_.model_dir.empty()) { @@ -83,13 +89,8 @@ bool NativePaddlePredictor::Init() { return false; } ctx_ = executor_->Prepare(*inference_program_, 0); - - // Create temporary variables first, so that the first batch do not need to - // create variables in the runtime. This is the logics of the old inference - // API. - // TODO(Superjomn) this should be modified when `Clone` is valid for - // multi-thread application. - executor_->CreateVariables(*inference_program_, scope_.get(), 0); + executor_->CreateVariables( + *inference_program_, sub_scope_ ? sub_scope_ : scope_.get(), 0); // Get the feed_target_names and fetch_target_names feed_target_names_ = inference_program_->GetFeedTargetNames(); @@ -97,6 +98,13 @@ bool NativePaddlePredictor::Init() { return true; } +NativePaddlePredictor::~NativePaddlePredictor() { + if (sub_scope_) { + PADDLE_ENFORCE_NOT_NULL(scope_, "Should have parent scope!"); + scope_->DeleteScope(sub_scope_); + } +}; + bool NativePaddlePredictor::Run(const std::vector &inputs, std::vector *output_data) { VLOG(3) << "Predictor::predict"; @@ -121,11 +129,12 @@ bool NativePaddlePredictor::Run(const std::vector &inputs, } // Run the inference program // if share variables, we need not create variables - executor_->RunPreparedContext(ctx_.get(), - scope_.get(), - &feed_targets, - &fetch_targets, - false /* don't create variable eatch time */); + executor_->RunPreparedContext( + ctx_.get(), + sub_scope_ != nullptr ? sub_scope_ : scope_.get(), + &feed_targets, + &fetch_targets, + false /* don't create variable eatch time */); if (!GetFetch(fetchs, output_data)) { LOG(ERROR) << "fail to get fetchs"; return false; @@ -138,7 +147,7 @@ std::unique_ptr NativePaddlePredictor::Clone() { VLOG(3) << "Predictor::clone"; std::unique_ptr cls(new NativePaddlePredictor(config_)); - if (!dynamic_cast(cls.get())->Init()) { + if (!dynamic_cast(cls.get())->Init(scope_)) { LOG(ERROR) << "fail to call Init"; return nullptr; } diff --git a/paddle/contrib/inference/paddle_inference_api_impl.h b/paddle/contrib/inference/paddle_inference_api_impl.h index 84707e223d7..dfb34a8631e 100644 --- a/paddle/contrib/inference/paddle_inference_api_impl.h +++ b/paddle/contrib/inference/paddle_inference_api_impl.h @@ -34,14 +34,15 @@ class NativePaddlePredictor : public PaddlePredictor { explicit NativePaddlePredictor(const NativeConfig &config) : config_(config) {} - bool Init(); + // will only create sub scope if have global scope + bool Init(std::shared_ptr scope = nullptr); bool Run(const std::vector &inputs, std::vector *output_data) override; std::unique_ptr Clone() override; - ~NativePaddlePredictor() override{}; + ~NativePaddlePredictor() override; private: bool SetFeed(const std::vector &input_datas, @@ -52,11 +53,13 @@ class NativePaddlePredictor : public PaddlePredictor { NativeConfig config_; platform::Place place_; std::unique_ptr executor_; - std::unique_ptr scope_; + std::shared_ptr scope_; std::unique_ptr ctx_; std::unique_ptr inference_program_; std::vector feed_target_names_; std::vector fetch_target_names_; + // Do not use unique_ptr, use parent scope to delete + framework::Scope *sub_scope_{nullptr}; }; } // namespace paddle -- GitLab From 4760f2851ef37186c836a1cf46fea87f5a806fb2 Mon Sep 17 00:00:00 2001 From: Yibing Liu Date: Mon, 4 Jun 2018 10:31:32 -0700 Subject: [PATCH 0119/1416] Add the argsort operator --- paddle/fluid/operators/argsort_op.cc | 83 ++++++++++++++++++ paddle/fluid/operators/argsort_op.h | 86 +++++++++++++++++++ .../fluid/tests/unittests/test_argsort_op.py | 49 +++++++++++ 3 files changed, 218 insertions(+) create mode 100644 paddle/fluid/operators/argsort_op.cc create mode 100644 paddle/fluid/operators/argsort_op.h create mode 100644 python/paddle/fluid/tests/unittests/test_argsort_op.py diff --git a/paddle/fluid/operators/argsort_op.cc b/paddle/fluid/operators/argsort_op.cc new file mode 100644 index 00000000000..aead4e2e00f --- /dev/null +++ b/paddle/fluid/operators/argsort_op.cc @@ -0,0 +1,83 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#include "paddle/fluid/operators/argsort_op.h" + +namespace paddle { +namespace operators { + +class ArgsortOp : public framework::OperatorWithKernel { + public: + using framework::OperatorWithKernel::OperatorWithKernel; + + void InferShape(framework::InferShapeContext *ctx) const override { + PADDLE_ENFORCE(ctx->HasInput("X"), + "Input(X) of ArgsortOp should not be null."); + PADDLE_ENFORCE(ctx->HasOutput("Out"), + "Output(Out) of ArgsortOp should not be null."); + PADDLE_ENFORCE(ctx->HasOutput("Indices"), + "Output(Indices) of ArgsortOp should not be null."); + + auto in_dims = ctx->GetInputDim("X"); + int axis = static_cast(ctx->Attrs().Get("axis")); + + auto num_dims = in_dims.size(); + PADDLE_ENFORCE(axis < num_dims, + "Attr(axis) %d of ArgsortOp is out of bounds for Input(X) " + "dimension %d.", + axis, num_dims); + PADDLE_ENFORCE(axis >= 0 || axis == -1, + "Attr(axis) %d of ArgsortOp must be nonnegative or equal to " + "-1.", + axis); + + ctx->SetOutputDim("Out", in_dims); + ctx->SetOutputDim("Indices", in_dims); + ctx->ShareLoD("X", "Out"); + ctx->ShareLoD("X", "Indices"); + } +}; + +class ArgsortOpMaker : public framework::OpProtoAndCheckerMaker { + public: + void Make() override { + AddInput("X", "(Tensor) The input of Argsort op."); + AddOutput("Out", "(Tensor) The sorted tensor of Argsort op."); + AddOutput("Indices", + "(Tensor) The indices of a tensor giving the sorted order."); + AddComment(R"DOC( +Argsort operator + +Performs sorting on the input tensor along the given axis and outputs two +tensors, Output(Out) and Output(Indices). They reserve the same shape +with Input(X), and Output(Out) represents the sorted tensor while +Output(Indices) gives the sorted order along the given axis Attr(axis). + + )DOC"); + AddAttr("axis", + "(int, default -1) The axis along which to sort the tensor, " + "default -1, the last dimension.") + .SetDefault(-1); + } +}; + +} // namespace operators +} // namespace paddle + +namespace ops = paddle::operators; +REGISTER_OPERATOR(argsort, ops::ArgsortOp, ops::ArgsortOpMaker, + paddle::framework::EmptyGradOpMaker); +REGISTER_OP_CPU_KERNEL(argsort, + ops::ArgsortKernel, + ops::ArgsortKernel); diff --git a/paddle/fluid/operators/argsort_op.h b/paddle/fluid/operators/argsort_op.h new file mode 100644 index 00000000000..a9fe22c4ce1 --- /dev/null +++ b/paddle/fluid/operators/argsort_op.h @@ -0,0 +1,86 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#pragma once +#include +#include +#include +#include +#include "paddle/fluid/framework/eigen.h" +#include "paddle/fluid/framework/op_registry.h" + +namespace paddle { +namespace operators { + +using Tensor = framework::Tensor; + +template +using EigenMatrix = framework::EigenMatrix; + +template +class ArgsortKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& ctx) const override { + auto* input = ctx.Input("X"); + auto* output = ctx.Output("Out"); + auto* indices = ctx.Output("Indices"); + int axis = static_cast(ctx.Attr("axis")); + + auto in_dims = input->dims(); + axis = (axis == -1) ? (in_dims.size() - 1) : axis; + + const T* in_data = input->data(); + T* out_data = output->mutable_data(ctx.GetPlace()); + int64_t* idx_data = indices->mutable_data(ctx.GetPlace()); + + int64_t part_dims_prod = input->numel() / in_dims[axis]; + for (int64_t i = 0; i < part_dims_prod; ++i) { + int64_t idx = i; + std::vector idx_vec(in_dims.size(), 0); + for (int64_t dim = in_dims.size() - 1; dim >= 0; --dim) { + if (dim != axis) { + idx_vec[dim] = idx % in_dims[dim]; + idx /= in_dims[dim]; + } + } + std::vector> in_vec; + std::vector org_index_vec(in_dims[axis], 0); + for (int64_t j = 0; j < in_dims[axis]; ++j) { + idx_vec[axis] = j; + int64_t index = idx_vec[0]; + for (int64_t dim = 0; dim < in_dims.size() - 1; ++dim) { + index = index * in_dims[dim + 1] + idx_vec[dim + 1]; + } + in_vec.push_back(std::pair(in_data[index], j)); + org_index_vec[j] = index; + } + + std::sort( + in_vec.begin(), in_vec.end(), + [](const std::pair& v1, const std::pair& v2) { + return v1.first < v2.first; + }); + + for (size_t j = 0; j < org_index_vec.size(); ++j) { + int64_t index = org_index_vec[j]; + out_data[index] = in_vec[j].first; + idx_data[index] = in_vec[j].second; + } + } + } +}; + +} // namespace operators +} // namespace paddle diff --git a/python/paddle/fluid/tests/unittests/test_argsort_op.py b/python/paddle/fluid/tests/unittests/test_argsort_op.py new file mode 100644 index 00000000000..6995621ba8c --- /dev/null +++ b/python/paddle/fluid/tests/unittests/test_argsort_op.py @@ -0,0 +1,49 @@ +# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import unittest +import numpy as np +from op_test import OpTest + + +class TestArgsortOp(OpTest): + def setUp(self): + self.init_axis() + x = np.random.random((2, 3, 4, 5)).astype("float32") + self.indices = np.argsort(x, kind='quicksort', axis=self.axis) + self.out = np.sort(x, kind='quicksort', axis=self.axis) + self.op_type = "argsort" + self.inputs = {'X': x} + self.attrs = {'axis': self.axis} + self.outputs = {'Indices': self.indices, 'Out': self.out} + + def init_axis(self): + self.axis = -1 + + def test_check_output(self): + self.check_output() + + +class TestArgsortOpAxis0(TestArgsortOp): + def init_axis(self): + self.axis = 0 + + +class TestArgsortOpAxis1(TestArgsortOp): + def init_axis(self): + self.axis = 1 + + +if __name__ == "__main__": + unittest.main() -- GitLab From 71b6bdb5d4dc090f8746845bf7bba9f62415e9f3 Mon Sep 17 00:00:00 2001 From: Siddharth Goyal Date: Mon, 4 Jun 2018 13:15:05 -0700 Subject: [PATCH 0120/1416] Fix signed-unsigned comparison warning (#11167) --- paddle/fluid/operators/sgd_op.h | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/paddle/fluid/operators/sgd_op.h b/paddle/fluid/operators/sgd_op.h index f9e0596191d..2685ce217ee 100644 --- a/paddle/fluid/operators/sgd_op.h +++ b/paddle/fluid/operators/sgd_op.h @@ -114,7 +114,7 @@ class SGDOpKernel : public framework::OpKernel { int64_t id_index = param.Index(grad.rows()[i]); PADDLE_ENFORCE_GE(id_index, static_cast(0), "id should be in the table"); - for (size_t j = 0; j < grad_row_width; j++) { + for (int64_t j = 0; j < grad_row_width; j++) { out_data[id_index * grad_row_width + j] -= lr[0] * grad_data[i * grad_row_width + j]; } -- GitLab From 95ba67a30cfe7395d2ed2f1e8193a88a4569fb22 Mon Sep 17 00:00:00 2001 From: Lei Wang Date: Mon, 4 Jun 2018 14:28:47 -0700 Subject: [PATCH 0121/1416] Build: fix go package installation path. (#11166) --- paddle/scripts/paddle_build.sh | 14 ++++++-------- 1 file changed, 6 insertions(+), 8 deletions(-) diff --git a/paddle/scripts/paddle_build.sh b/paddle/scripts/paddle_build.sh index 8eeea1805d8..113d02ce486 100755 --- a/paddle/scripts/paddle_build.sh +++ b/paddle/scripts/paddle_build.sh @@ -145,19 +145,17 @@ function check_style() { trap 'abort' 0 set -e - # install glide - curl https://glide.sh/get | bash - eval "$(GIMME_GO_VERSION=1.8.3 gimme)" + if [ -x "$(command -v gimme)" ]; then + eval "$(GIMME_GO_VERSION=1.8.3 gimme)" + fi # set up go environment for running gometalinter mkdir -p $GOPATH/src/github.com/PaddlePaddle/ ln -sf ${PADDLE_ROOT} $GOPATH/src/github.com/PaddlePaddle/Paddle - cd $GOPATH/src/github.com/PaddlePaddle/Paddle/go; glide install; cd - - - go get github.com/alecthomas/gometalinter - gometalinter --install + mkdir -p ./build/go + cp go/glide.* build/go + cd build/go; glide install; cd - - cd ${PADDLE_ROOT} export PATH=/usr/bin:$PATH pre-commit install clang-format --version -- GitLab From a4237171a5f647f5c841e61d5d61f2ff8f8e80f7 Mon Sep 17 00:00:00 2001 From: Siddharth Goyal Date: Mon, 4 Jun 2018 14:29:19 -0700 Subject: [PATCH 0122/1416] Modify optimizer in new API to support more usecases (#11168) * Modify optimizer in new API to support more usecase * Modify CMake to include only modified examples --- .../fluid/tests/book/high-level-api/CMakeLists.txt | 12 ++++++------ .../high-level-api/fit_a_line/test_fit_a_line.py | 8 +++++--- .../test_label_semantic_roles_newapi.py | 10 +++++++--- python/paddle/fluid/trainer.py | 13 +++++++------ 4 files changed, 25 insertions(+), 18 deletions(-) diff --git a/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt b/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt index efa5ee2d06a..07da382867e 100644 --- a/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt +++ b/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt @@ -7,10 +7,10 @@ foreach(src ${TEST_OPS}) endforeach() add_subdirectory(fit_a_line) -add_subdirectory(recognize_digits) -add_subdirectory(image_classification) -add_subdirectory(understand_sentiment) +#add_subdirectory(recognize_digits) +#add_subdirectory(image_classification) +#add_subdirectory(understand_sentiment) add_subdirectory(label_semantic_roles) -add_subdirectory(word2vec) -add_subdirectory(recommender_system) -add_subdirectory(machine_translation) +#add_subdirectory(word2vec) +#add_subdirectory(recommender_system) +#add_subdirectory(machine_translation) diff --git a/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py b/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py index de3906fc6a0..b3117cf2e5e 100644 --- a/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py +++ b/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py @@ -48,13 +48,15 @@ def linear(): return avg_loss +def optimizer_func(): + return fluid.optimizer.SGD(learning_rate=0.001) + + def train(use_cuda, train_program, params_dirname): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() trainer = fluid.Trainer( - train_func=train_program, - place=place, - optimizer=fluid.optimizer.SGD(learning_rate=0.001)) + train_func=train_program, place=place, optimizer_func=optimizer_func) def event_handler(event): if isinstance(event, fluid.EndStepEvent): diff --git a/python/paddle/fluid/tests/book/high-level-api/label_semantic_roles/test_label_semantic_roles_newapi.py b/python/paddle/fluid/tests/book/high-level-api/label_semantic_roles/test_label_semantic_roles_newapi.py index 8cce398ff33..0ccb3a39e02 100755 --- a/python/paddle/fluid/tests/book/high-level-api/label_semantic_roles/test_label_semantic_roles_newapi.py +++ b/python/paddle/fluid/tests/book/high-level-api/label_semantic_roles/test_label_semantic_roles_newapi.py @@ -141,12 +141,16 @@ def train_program(): return [avg_cost] +def optimize_func(): + return fluid.optimizer.SGD(learning_rate=fluid.layers.exponential_decay( + learning_rate=0.01, decay_steps=100000, decay_rate=0.5, staircase=True)) + + def train(use_cuda, train_program, params_dirname): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() - optimizer = fluid.optimizer.SGD(learning_rate=0.01) trainer = fluid.Trainer( - train_func=train_program, place=place, optimizer=optimizer) + train_func=train_program, place=place, optimizer_func=optimize_func) feed_order = [ 'word_data', 'ctx_n2_data', 'ctx_n1_data', 'ctx_0_data', 'ctx_p1_data', @@ -245,7 +249,7 @@ def infer(use_cuda, inference_program, params_dirname): }, return_numpy=False) - print("infer results: ", np.array(results[0])) + print("infer results: ", np.array(results[0]).shape) def main(use_cuda): diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py index 7da123dd92e..cdacb419863 100644 --- a/python/paddle/fluid/trainer.py +++ b/python/paddle/fluid/trainer.py @@ -90,13 +90,13 @@ class Trainer(object): Args: train_func(callable): A function which will return loss. The loss must be a scalar. - optimizer(optimizer.Optimizer): The optimizer should be an instance of Optimizer + optimizer_func(callable): A function that returns an Optimizer object. place: The device place of this trainer. """ def __init__(self, train_func, - optimizer, + optimizer_func, param_path=None, place=None, parallel=False): @@ -105,8 +105,6 @@ class Trainer(object): # 1. we need to generate a framework.Program by calling # program_func. Reference: fluid.program_guard in # test_word2vec.py - if not isinstance(optimizer, opt_module.Optimizer): - raise TypeError("The optimizer should be an instance of Optimizer") self.scope = core.Scope() @@ -118,11 +116,14 @@ class Trainer(object): self.train_func_outputs = program_func_outs if isinstance( program_func_outs, list) else [program_func_outs] self.test_program = self.train_program.clone() + + # The fisrt element of program_func_outs is loss. + loss = self.train_func_outputs[0] + + optimizer = optimizer_func() if not isinstance(optimizer, opt_module.Optimizer): raise TypeError( "The optimizer should be an instance of Optimizer") - # The fisrt element of program_func_outs is loss. - loss = self.train_func_outputs[0] optimize_ops, params_grads = optimizer.minimize(loss) self.place = check_and_get_place(place) -- GitLab From f3d14c3bed9cc783fa6089819ddb54236e6e67f2 Mon Sep 17 00:00:00 2001 From: Lei Wang Date: Mon, 4 Jun 2018 15:04:21 -0700 Subject: [PATCH 0123/1416] Doc: fix android cross_compiling documents. (#11169) --- doc/mobile/cross_compiling_for_android_cn.md | 6 +++--- doc/mobile/cross_compiling_for_android_en.md | 4 ++-- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/doc/mobile/cross_compiling_for_android_cn.md b/doc/mobile/cross_compiling_for_android_cn.md index cdd69172393..0607748b751 100644 --- a/doc/mobile/cross_compiling_for_android_cn.md +++ b/doc/mobile/cross_compiling_for_android_cn.md @@ -63,16 +63,16 @@ Android的Docker开发镜像向用户提供两个可配置的参数： - 编译`armeabi-v7a`，`Android API 21`的PaddlePaddle库 ```bash -$ docker run -it --rm -v $PWD:/paddle -e "ANDROID_ABI=armeabi-v7a" -e "ANDROID_API=21" username/paddle-android:dev +$ docker run -it --rm -v $PWD:/paddle -w /paddle -e "ANDROID_ABI=armeabi-v7a" -e "ANDROID_API=21" username/paddle-android:dev ./paddle/scripts/paddle_build.sh build_android ``` - 编译`arm64-v8a`，`Android API 21`的PaddlePaddle库 ```bash -$ docker run -it --rm -v $PWD:/paddle -e "ANDROID_ABI=arm64-v8a" -e "ANDROID_API=21" username/paddle-android:dev +$ docker run -it --rm -v $PWD:/paddle -w /paddle -e "ANDROID_ABI=arm64-v8a" -e "ANDROID_API=21" username/paddle-android:dev ./paddle/scripts/paddle_build.sh build_android ``` -执行上述`docker run`命令时，容器默认执行[paddle/scripts/docker/build_android.sh](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/scripts/docker/build_android.sh)脚本。该脚本中记录了交叉编译Android版PaddlePaddle库常用的CMake配置，并且会根据`ANDROID_ABI`和`ANDROID_API`自动构建独立工具链、进行编译和安装。由于arm64架构要求Android API不小于21。因此当`ANDROID_ABI=arm64-v8a`，`ANDROID_API<21`时，Docker容器中将默认使用`Android API 21`的编译工具链。用户可以参考下文[配置交叉编译参数](#配置交叉编译参数)章节，根据个人的需求修改定制Docker容器所执行的脚本。编译安装结束之后，PaddlePaddle的C-API库将被安装到`$PWD/install_android`目录，所依赖的第三方库同时也被安装到`$PWD/install_android/third_party`目录。 +执行上述`docker run`命令时，容器执行[paddle/scripts/paddle_build.sh build_android](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/scripts/paddle_build.sh)脚本。该脚本中记录了交叉编译Android版PaddlePaddle库常用的CMake配置，并且会根据`ANDROID_ABI`和`ANDROID_API`自动构建独立工具链、进行编译和安装。由于arm64架构要求Android API不小于21。因此当`ANDROID_ABI=arm64-v8a`，`ANDROID_API<21`时，Docker容器中将默认使用`Android API 21`的编译工具链。用户可以参考下文[配置交叉编译参数](#配置交叉编译参数)章节，根据个人的需求修改定制Docker容器所执行的脚本。编译安装结束之后，PaddlePaddle的C-API库将被安装到`$PWD/install_android`目录，所依赖的第三方库同时也被安装到`$PWD/install_android/third_party`目录。 ## 基于Linux交叉编译环境的编译方式 本文档将以Linux x86-64平台为例，介绍交叉编译Android平台上适用的PaddlePaddle库的方法和步骤。 diff --git a/doc/mobile/cross_compiling_for_android_en.md b/doc/mobile/cross_compiling_for_android_en.md index 6af16fc114a..572063e8012 100644 --- a/doc/mobile/cross_compiling_for_android_en.md +++ b/doc/mobile/cross_compiling_for_android_en.md @@ -36,7 +36,7 @@ $ docker pull docker.paddlepaddlehub.com/paddle:latest-dev-android We can run the Docker image we just created to build the inference library of PaddlePaddle for Android using the command below: ```bash -$ docker run -it --rm -v $PWD:/paddle -e "ANDROID_ABI=armeabi-v7a" -e "ANDROID_API=21" paddle:dev-android +$ docker run -it --rm -v $PWD:/paddle -w /paddle -e "ANDROID_ABI=armeabi-v7a" -e "ANDROID_API=21" paddle:dev-android ./paddle/scripts/paddle_build.sh build_android ``` The Docker image accepts two arguments `ANDROID_ABI` and `ANDROID_API`: @@ -70,7 +70,7 @@ The Docker image accepts two arguments `ANDROID_ABI` and `ANDROID_API`: The ARM-64 architecture (`arm64-v8a`) requires at least level 21 of Android API. -The default entry-point of the Docker image, [`paddle/scripts/docker/build_android.sh`](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/scripts/docker/build_android.sh) generates the [Android cross-compiling standalone toolchain](https://developer.android.com/ndk/guides/standalone_toolchain.html) based on the argument: `ANDROID_ABI` or `ANDROID_API`. For information about other configuration arguments, please continue reading. +The build command, [`paddle/scripts/paddle_build.sh build_android`](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/scripts/paddle_build.sh) generates the [Android cross-compiling standalone toolchain](https://developer.android.com/ndk/guides/standalone_toolchain.html) based on the argument: `ANDROID_ABI` or `ANDROID_API`. For information about other configuration arguments, please continue reading. The above command generates and outputs the inference library in `$PWD/install_android` and puts third-party libraries in `$PWD/install_android/third_party`. -- GitLab From c9067bef99acf7b4903de86470437b39e55d4d53 Mon Sep 17 00:00:00 2001 From: Lei Wang Date: Mon, 4 Jun 2018 16:37:27 -0700 Subject: [PATCH 0124/1416] Doc: remove broken symbol links. (#11170) --- doc/fluid/howto/optimization/benchmark/README.md | 1 - doc/fluid/howto/optimization/benchmark/vgg16/README.md | 1 - 2 files changed, 2 deletions(-) delete mode 120000 doc/fluid/howto/optimization/benchmark/README.md delete mode 120000 doc/fluid/howto/optimization/benchmark/vgg16/README.md diff --git a/doc/fluid/howto/optimization/benchmark/README.md b/doc/fluid/howto/optimization/benchmark/README.md deleted file mode 120000 index db30af7f532..00000000000 --- a/doc/fluid/howto/optimization/benchmark/README.md +++ /dev/null @@ -1 +0,0 @@ -../../../../../benchmark/cluster/README.md \ No newline at end of file diff --git a/doc/fluid/howto/optimization/benchmark/vgg16/README.md b/doc/fluid/howto/optimization/benchmark/vgg16/README.md deleted file mode 120000 index ca963ef5f06..00000000000 --- a/doc/fluid/howto/optimization/benchmark/vgg16/README.md +++ /dev/null @@ -1 +0,0 @@ -../../../../../../benchmark/cluster/vgg16/README.md \ No newline at end of file -- GitLab From 99a5a3d8d3f1f2ab08b2e04828b812890bb29a73 Mon Sep 17 00:00:00 2001 From: Siddharth Goyal Date: Mon, 4 Jun 2018 17:17:57 -0700 Subject: [PATCH 0125/1416] Fix optimizer in remaining chapters with high level API (#11172) --- .../fluid/tests/book/high-level-api/CMakeLists.txt | 12 ++++++------ .../test_image_classification_resnet.py | 8 +++++--- .../test_image_classification_vgg.py | 8 +++++--- .../test_machine_translation.py | 14 +++++++++----- .../recognize_digits/test_recognize_digits_conv.py | 7 +++++-- .../recognize_digits/test_recognize_digits_mlp.py | 7 +++++-- .../test_recommender_system_newapi.py | 7 +++++-- .../test_understand_sentiment_conv.py | 7 +++++-- .../test_understand_sentiment_dynamic_rnn.py | 7 +++++-- .../test_understand_sentiment_stacked_lstm.py | 7 +++++-- .../word2vec/test_word2vec_new_api.py | 8 +++++--- 11 files changed, 60 insertions(+), 32 deletions(-) diff --git a/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt b/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt index 07da382867e..efa5ee2d06a 100644 --- a/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt +++ b/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt @@ -7,10 +7,10 @@ foreach(src ${TEST_OPS}) endforeach() add_subdirectory(fit_a_line) -#add_subdirectory(recognize_digits) -#add_subdirectory(image_classification) -#add_subdirectory(understand_sentiment) +add_subdirectory(recognize_digits) +add_subdirectory(image_classification) +add_subdirectory(understand_sentiment) add_subdirectory(label_semantic_roles) -#add_subdirectory(word2vec) -#add_subdirectory(recommender_system) -#add_subdirectory(machine_translation) +add_subdirectory(word2vec) +add_subdirectory(recommender_system) +add_subdirectory(machine_translation) diff --git a/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_resnet.py b/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_resnet.py index 63dc1b6ce30..2df3da9cca7 100644 --- a/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_resnet.py +++ b/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_resnet.py @@ -85,6 +85,10 @@ def train_network(): return [avg_cost, accuracy] +def optimizer_func(): + return fluid.optimizer.Adam(learning_rate=0.001) + + def train(use_cuda, train_program, params_dirname): BATCH_SIZE = 128 EPOCH_NUM = 1 @@ -111,9 +115,7 @@ def train(use_cuda, train_program, params_dirname): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() trainer = fluid.Trainer( - train_func=train_program, - optimizer=fluid.optimizer.Adam(learning_rate=0.001), - place=place) + train_func=train_program, optimizer_func=optimizer_func, place=place) trainer.train( reader=train_reader, diff --git a/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_vgg.py b/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_vgg.py index 0bf8f265a1c..224cca417e7 100644 --- a/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_vgg.py +++ b/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_vgg.py @@ -64,6 +64,10 @@ def train_network(): return [avg_cost, accuracy] +def optimizer_func(): + return fluid.optimizer.Adam(learning_rate=0.001) + + def train(use_cuda, train_program, params_dirname): BATCH_SIZE = 128 train_reader = paddle.batch( @@ -88,9 +92,7 @@ def train(use_cuda, train_program, params_dirname): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() trainer = fluid.Trainer( - train_func=train_program, - place=place, - optimizer=fluid.optimizer.Adam(learning_rate=0.001)) + train_func=train_program, place=place, optimizer_func=optimizer_func) trainer.train( reader=train_reader, diff --git a/python/paddle/fluid/tests/book/high-level-api/machine_translation/test_machine_translation.py b/python/paddle/fluid/tests/book/high-level-api/machine_translation/test_machine_translation.py index d4b723d3e6b..c4b37df3a09 100644 --- a/python/paddle/fluid/tests/book/high-level-api/machine_translation/test_machine_translation.py +++ b/python/paddle/fluid/tests/book/high-level-api/machine_translation/test_machine_translation.py @@ -158,6 +158,13 @@ def train_program(is_sparse): return avg_cost +def optimizer_func(): + return fluid.optimizer.Adagrad( + learning_rate=1e-4, + regularization=fluid.regularizer.L2DecayRegularizer( + regularization_coeff=0.1)) + + def train(use_cuda, is_sparse, is_local=True): EPOCH_NUM = 1 @@ -182,11 +189,8 @@ def train(use_cuda, is_sparse, is_local=True): trainer = fluid.Trainer( train_func=partial(train_program, is_sparse), - optimizer=fluid.optimizer.Adagrad( - learning_rate=1e-4, - regularization=fluid.regularizer.L2DecayRegularizer( - regularization_coeff=0.1)), - place=place) + place=place, + optimizer_func=optimizer_func) trainer.train( reader=train_reader, diff --git a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py index 03439cbd376..9a09db25dc0 100644 --- a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py +++ b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py @@ -57,14 +57,17 @@ def train_program(): return [avg_cost, acc] +def optimizer_func(): + return fluid.optimizer.Adam(learning_rate=0.001) + + def train(use_cuda, train_program, params_dirname): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() - optimizer = fluid.optimizer.Adam(learning_rate=0.001) trainer = fluid.Trainer( train_func=train_program, place=place, - optimizer=optimizer, + optimizer_func=optimizer_func, parallel=True) def event_handler(event): diff --git a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py index 89bbd21bea7..b2b544e791d 100644 --- a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py +++ b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py @@ -44,12 +44,15 @@ def train_program(): return [avg_cost, acc] +def optimizer_func(): + return fluid.optimizer.Adam(learning_rate=0.001) + + def train(use_cuda, train_program, params_dirname): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() - optimizer = fluid.optimizer.Adam(learning_rate=0.001) trainer = fluid.Trainer( - train_func=train_program, place=place, optimizer=optimizer) + train_func=train_program, place=place, optimizer_func=optimizer_func) def event_handler(event): if isinstance(event, fluid.EndEpochEvent): diff --git a/python/paddle/fluid/tests/book/high-level-api/recommender_system/test_recommender_system_newapi.py b/python/paddle/fluid/tests/book/high-level-api/recommender_system/test_recommender_system_newapi.py index dfc7325acf2..090c11ce1e7 100644 --- a/python/paddle/fluid/tests/book/high-level-api/recommender_system/test_recommender_system_newapi.py +++ b/python/paddle/fluid/tests/book/high-level-api/recommender_system/test_recommender_system_newapi.py @@ -155,12 +155,15 @@ def train_program(): return [avg_cost, scale_infer] +def optimizer_func(): + return fluid.optimizer.SGD(learning_rate=0.2) + + def train(use_cuda, train_program, params_dirname): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() - optimizer = fluid.optimizer.SGD(learning_rate=0.2) trainer = fluid.Trainer( - train_func=train_program, place=place, optimizer=optimizer) + train_func=train_program, place=place, optimizer_func=optimizer_func) feed_order = [ 'user_id', 'gender_id', 'age_id', 'job_id', 'movie_id', 'category_id', diff --git a/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/test_understand_sentiment_conv.py b/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/test_understand_sentiment_conv.py index 11e9fd1bec1..9b61f7a00ce 100644 --- a/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/test_understand_sentiment_conv.py +++ b/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/test_understand_sentiment_conv.py @@ -64,15 +64,18 @@ def train_program(word_dict): return [avg_cost, accuracy] +def optimizer_func(): + return fluid.optimizer.Adagrad(learning_rate=0.002) + + def train(use_cuda, train_program, params_dirname): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() - optimizer = fluid.optimizer.Adagrad(learning_rate=0.002) word_dict = paddle.dataset.imdb.word_dict() trainer = fluid.Trainer( train_func=partial(train_program, word_dict), place=place, - optimizer=optimizer) + optimizer_func=optimizer_func) def event_handler(event): if isinstance(event, fluid.EndEpochEvent): diff --git a/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/test_understand_sentiment_dynamic_rnn.py b/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/test_understand_sentiment_dynamic_rnn.py index 90757d54f99..aa7c567b4d6 100644 --- a/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/test_understand_sentiment_dynamic_rnn.py +++ b/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/test_understand_sentiment_dynamic_rnn.py @@ -79,15 +79,18 @@ def train_program(word_dict): return [avg_cost, accuracy] +def optimizer_func(): + return fluid.optimizer.Adagrad(learning_rate=0.002) + + def train(use_cuda, train_program, params_dirname): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() - optimizer = fluid.optimizer.Adagrad(learning_rate=0.002) word_dict = paddle.dataset.imdb.word_dict() trainer = fluid.Trainer( train_func=partial(train_program, word_dict), place=place, - optimizer=optimizer) + optimizer_func=optimizer_func) def event_handler(event): if isinstance(event, fluid.EndEpochEvent): diff --git a/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/test_understand_sentiment_stacked_lstm.py b/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/test_understand_sentiment_stacked_lstm.py index 52b7d4a8377..113dda88ca9 100644 --- a/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/test_understand_sentiment_stacked_lstm.py +++ b/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/test_understand_sentiment_stacked_lstm.py @@ -71,15 +71,18 @@ def train_program(word_dict): return [avg_cost, accuracy] +def optimizer_func(): + return fluid.optimizer.Adagrad(learning_rate=0.002) + + def train(use_cuda, train_program, params_dirname): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() - optimizer = fluid.optimizer.Adagrad(learning_rate=0.002) word_dict = paddle.dataset.imdb.word_dict() trainer = fluid.Trainer( train_func=partial(train_program, word_dict), place=place, - optimizer=optimizer) + optimizer_func=optimizer_func) def event_handler(event): if isinstance(event, fluid.EndEpochEvent): diff --git a/python/paddle/fluid/tests/book/high-level-api/word2vec/test_word2vec_new_api.py b/python/paddle/fluid/tests/book/high-level-api/word2vec/test_word2vec_new_api.py index eeb8e670873..ba44f72d9b0 100644 --- a/python/paddle/fluid/tests/book/high-level-api/word2vec/test_word2vec_new_api.py +++ b/python/paddle/fluid/tests/book/high-level-api/word2vec/test_word2vec_new_api.py @@ -80,6 +80,10 @@ def train_program(is_sparse): return avg_cost +def optimizer_func(): + return fluid.optimizer.SGD(learning_rate=0.001) + + def train(use_cuda, train_program, params_dirname): train_reader = paddle.batch( paddle.dataset.imikolov.train(word_dict, N), BATCH_SIZE) @@ -104,9 +108,7 @@ def train(use_cuda, train_program, params_dirname): sys.exit("got NaN loss, training failed.") trainer = fluid.Trainer( - train_func=train_program, - optimizer=fluid.optimizer.SGD(learning_rate=0.001), - place=place) + train_func=train_program, optimizer_func=optimizer_func, place=place) trainer.train( reader=train_reader, -- GitLab From 5713a0bf5eef095ee2e1d6006add1574fca8de63 Mon Sep 17 00:00:00 2001 From: Kexin Zhao Date: Mon, 4 Jun 2018 17:46:12 -0700 Subject: [PATCH 0126/1416] fix lodtensor api in memory opt machine trans (#11171) --- .../test_memopt_machine_translation.py | 34 ++++++------------- 1 file changed, 11 insertions(+), 23 deletions(-) diff --git a/python/paddle/fluid/tests/book_memory_optimization/test_memopt_machine_translation.py b/python/paddle/fluid/tests/book_memory_optimization/test_memopt_machine_translation.py index a1ca6d981fa..fa696acdfa9 100644 --- a/python/paddle/fluid/tests/book_memory_optimization/test_memopt_machine_translation.py +++ b/python/paddle/fluid/tests/book_memory_optimization/test_memopt_machine_translation.py @@ -80,21 +80,6 @@ def encoder_decoder(): return rnn() -def to_lodtensor(data, place): - seq_lens = [len(seq) for seq in data] - cur_len = 0 - lod = [cur_len] - for l in seq_lens: - cur_len += l - lod.append(cur_len) - flattened_data = np.concatenate(data, axis=0).astype("int64") - flattened_data = flattened_data.reshape([len(flattened_data), 1]) - res = core.LoDTensor() - res.set(flattened_data, place) - res.set_lod([lod]) - return res - - def main(): rnn_out = encoder_decoder() label = layers.data( @@ -122,18 +107,21 @@ def main(): exe.run(framework.default_startup_program()) + feed_order = [ + 'src_word_id', 'target_language_word', 'target_language_next_word' + ] + + feed_list = [ + fluid.default_main_program().global_block().var(var_name) + for var_name in feed_order + ] + feeder = fluid.DataFeeder(feed_list, place) + batch_id = 0 for pass_id in xrange(10): for data in train_data(): - word_data = to_lodtensor(map(lambda x: x[0], data), place) - trg_word = to_lodtensor(map(lambda x: x[1], data), place) - trg_word_next = to_lodtensor(map(lambda x: x[2], data), place) outs = exe.run(fluid.default_main_program(), - feed={ - 'src_word_id': word_data, - 'target_language_word': trg_word, - 'target_language_next_word': trg_word_next - }, + feed=feeder.feed(data), fetch_list=[avg_cost]) avg_cost_val = np.array(outs[0]) print('pass_id=' + str(pass_id) + ' batch=' + str(batch_id) + -- GitLab From c8d6c1d09c46457bbb68665108b3468de5a064fa Mon Sep 17 00:00:00 2001 From: whs Date: Tue, 5 Jun 2018 10:09:22 +0800 Subject: [PATCH 0127/1416] Auto generate python api for polygon_box_transform op. (#11074) * Auto generate python api for polygon_box_transform op. * Add unitest. --- python/paddle/fluid/layers/ops.py | 1 + python/paddle/fluid/tests/unittests/test_layers.py | 8 ++++++++ 2 files changed, 9 insertions(+) diff --git a/python/paddle/fluid/layers/ops.py b/python/paddle/fluid/layers/ops.py index 60f8cbbfa71..69cfde852dd 100644 --- a/python/paddle/fluid/layers/ops.py +++ b/python/paddle/fluid/layers/ops.py @@ -71,6 +71,7 @@ __all__ = [ 'cumsum', 'scatter', 'sum', + 'polygon_box_transform', 'shape', ] + __activations__ diff --git a/python/paddle/fluid/tests/unittests/test_layers.py b/python/paddle/fluid/tests/unittests/test_layers.py index ca08fd7fc8e..621a450fa6a 100644 --- a/python/paddle/fluid/tests/unittests/test_layers.py +++ b/python/paddle/fluid/tests/unittests/test_layers.py @@ -379,6 +379,14 @@ class TestBook(unittest.TestCase): self.assertIsNotNone(output) print(str(program)) + def test_polygon_box_transform(self): + program = Program() + with program_guard(program): + x = layers.data(name='x', shape=[8, 4, 4], dtype="float32") + output = layers.polygon_box_transform(input=x) + self.assertIsNotNone(output) + print(str(program)) + if __name__ == '__main__': unittest.main() -- GitLab From 9d1dae3987abcef8a77f07e9e86e96de27b1cd46 Mon Sep 17 00:00:00 2001 From: Luo Tao Date: Tue, 5 Jun 2018 10:20:40 +0800 Subject: [PATCH 0128/1416] remove argument cpus, and will add in next PR --- benchmark/fluid/fluid_benchmark.py | 5 ----- 1 file changed, 5 deletions(-) diff --git a/benchmark/fluid/fluid_benchmark.py b/benchmark/fluid/fluid_benchmark.py index cac1b0fad00..9d33a841cdd 100644 --- a/benchmark/fluid/fluid_benchmark.py +++ b/benchmark/fluid/fluid_benchmark.py @@ -69,11 +69,6 @@ def parse_args(): type=int, default=1, help='If gpus > 1, will use ParallelExecutor to run, else use Executor.') - parser.add_argument( - '--cpus', - type=int, - default=1, - help='If cpus > 1, will use ParallelDo to run, else use Executor.') parser.add_argument( '--data_set', type=str, -- GitLab From 02cc80b30d5b5d6152171427ed8be8c8f91616e6 Mon Sep 17 00:00:00 2001 From: sneaxiy Date: Tue, 5 Jun 2018 10:33:20 +0800 Subject: [PATCH 0129/1416] Fix dangling pointer bug --- paddle/fluid/framework/executor.cc | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/paddle/fluid/framework/executor.cc b/paddle/fluid/framework/executor.cc index 863053c32b1..3d68c5fb870 100644 --- a/paddle/fluid/framework/executor.cc +++ b/paddle/fluid/framework/executor.cc @@ -220,8 +220,10 @@ void Executor::Run(const ProgramDesc& program, Scope* scope, has_fetch_operators(program.Block(0), *fetch_targets, fetch_holder_name); ProgramDesc* copy_program = const_cast(&program); + std::unique_ptr unique_ptr_of_copy_program; if (!has_feed_ops || !has_fetch_ops) { - copy_program = std::unique_ptr(new ProgramDesc(program)).get(); + unique_ptr_of_copy_program.reset(new ProgramDesc(program)); + copy_program = unique_ptr_of_copy_program.get(); } auto* global_block = copy_program->MutableBlock(0); -- GitLab From 211b707b30929ebd8a1e3fb5fabfb848f0617095 Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Tue, 5 Jun 2018 11:19:30 +0800 Subject: [PATCH 0130/1416] fix unknown gpu flag when cpu only --- paddle/contrib/inference/demo/simple_on_word2vec.cc | 3 +++ 1 file changed, 3 insertions(+) diff --git a/paddle/contrib/inference/demo/simple_on_word2vec.cc b/paddle/contrib/inference/demo/simple_on_word2vec.cc index ee865f37900..9b4843f714f 100644 --- a/paddle/contrib/inference/demo/simple_on_word2vec.cc +++ b/paddle/contrib/inference/demo/simple_on_word2vec.cc @@ -65,7 +65,10 @@ void Main(bool use_gpu) { } TEST(demo, word2vec_cpu) { Main(false /*use_gpu*/); } + +#ifdef PADDLE_WITH_CUDA TEST(demo, word2vec_gpu) { Main(true /*use_gpu*/); } +#endif } // namespace demo } // namespace paddle -- GitLab From 2c2120c8a269080a883ad4b1eb8022d71f3d2cf8 Mon Sep 17 00:00:00 2001 From: Yibing Liu Date: Mon, 4 Jun 2018 20:25:25 -0700 Subject: [PATCH 0131/1416] Remove redundant code --- paddle/fluid/operators/argsort_op.h | 14 +++----------- 1 file changed, 3 insertions(+), 11 deletions(-) diff --git a/paddle/fluid/operators/argsort_op.h b/paddle/fluid/operators/argsort_op.h index a9fe22c4ce1..51d2b89f94d 100644 --- a/paddle/fluid/operators/argsort_op.h +++ b/paddle/fluid/operators/argsort_op.h @@ -14,28 +14,20 @@ limitations under the License. */ #pragma once #include -#include #include #include -#include "paddle/fluid/framework/eigen.h" #include "paddle/fluid/framework/op_registry.h" namespace paddle { namespace operators { -using Tensor = framework::Tensor; - -template -using EigenMatrix = framework::EigenMatrix; - template class ArgsortKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& ctx) const override { - auto* input = ctx.Input("X"); - auto* output = ctx.Output("Out"); - auto* indices = ctx.Output("Indices"); + auto* input = ctx.Input("X"); + auto* output = ctx.Output("Out"); + auto* indices = ctx.Output("Indices"); int axis = static_cast(ctx.Attr("axis")); auto in_dims = input->dims(); -- GitLab From 238124909e978b3e581c214859cf7aea5df57b31 Mon Sep 17 00:00:00 2001 From: Qiao Longfei Date: Tue, 5 Jun 2018 13:01:21 +0800 Subject: [PATCH 0132/1416] fix protobuf memory leak (#11177) fix protobuf memory leak --- paddle/fluid/framework/block_desc.cc | 28 ++++------------------------ paddle/fluid/framework/block_desc.h | 9 --------- 2 files changed, 4 insertions(+), 33 deletions(-) diff --git a/paddle/fluid/framework/block_desc.cc b/paddle/fluid/framework/block_desc.cc index e7842e9b813..f537e4b9e56 100644 --- a/paddle/fluid/framework/block_desc.cc +++ b/paddle/fluid/framework/block_desc.cc @@ -169,17 +169,13 @@ void BlockDesc::Flush() { } if (need_update_) { - auto &op_field = *this->desc_->mutable_ops(); - this->ClearPBOps(); - op_field.Reserve(static_cast(ops_.size())); + this->desc_->mutable_ops()->Clear(); for (auto &op_desc : ops_) { - op_field.AddAllocated(op_desc->Proto()); + this->desc_->mutable_ops()->Add()->CopyFrom(*op_desc->Proto()); } - auto &var_field = *this->desc_->mutable_vars(); - this->ClearPBVars(); - var_field.Reserve(static_cast(vars_.size())); + this->desc_->mutable_vars()->Clear(); for (auto &var_desc : vars_) { - var_field.AddAllocated(var_desc.second->Proto()); + this->desc_->mutable_vars()->Add()->CopyFrom(*var_desc.second->Proto()); } need_update_ = false; } @@ -217,22 +213,6 @@ BlockDesc::BlockDesc(const BlockDesc &other, proto::BlockDesc *desc, } } -void BlockDesc::ClearPBOps() { - auto ops = this->desc_->mutable_ops(); - while (!ops->empty()) { - // we do not own the OpDesc, so release the ownership. - ops->ReleaseLast(); - } -} - -void BlockDesc::ClearPBVars() { - auto vars = this->desc_->mutable_vars(); - while (!vars->empty()) { - // we do not own the VarDesc, so release the ownership. - vars->ReleaseLast(); - } -} - void BlockDesc::SetForwardBlockID(int32_t forward_block_id) { PADDLE_ENFORCE(!desc_->has_forward_block_idx(), "Parent block ID has been set to %d. Cannot set to %d", diff --git a/paddle/fluid/framework/block_desc.h b/paddle/fluid/framework/block_desc.h index 189dd6c52f8..ce485484184 100644 --- a/paddle/fluid/framework/block_desc.h +++ b/paddle/fluid/framework/block_desc.h @@ -41,11 +41,6 @@ class BlockDesc { BlockDesc(const BlockDesc &other, proto::BlockDesc *desc, ProgramDesc *prog); - ~BlockDesc() { - this->ClearPBVars(); - this->ClearPBOps(); - } - int32_t ID() const { return desc_->idx(); } int32_t Parent() const { return desc_->parent_idx(); } @@ -113,10 +108,6 @@ class BlockDesc { ProgramDesc *Program() const { return this->prog_; } - private: - void ClearPBOps(); - void ClearPBVars(); - private: ProgramDesc *prog_; // not_own proto::BlockDesc *desc_; // not_own -- GitLab From 9630aa0e525c9a60790b22b3dffe0b90e8bb02c2 Mon Sep 17 00:00:00 2001 From: Luo Tao Date: Tue, 5 Jun 2018 13:45:29 +0800 Subject: [PATCH 0133/1416] fix test error in fluid_benchmark.py --- benchmark/fluid/fluid_benchmark.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/benchmark/fluid/fluid_benchmark.py b/benchmark/fluid/fluid_benchmark.py index 9d33a841cdd..8e6bfcbd301 100644 --- a/benchmark/fluid/fluid_benchmark.py +++ b/benchmark/fluid/fluid_benchmark.py @@ -85,8 +85,8 @@ def parse_args(): help='If set, use nvprof for CUDA.') parser.add_argument( '--no_test', - action='store_false', - help='If set, test the testset during training.') + action='store_true', + help='If set, do not test the testset during training.') parser.add_argument( '--memory_optimize', action='store_true', @@ -229,9 +229,9 @@ def train(avg_loss, infer_prog, optimizer, train_reader, test_reader, batch_acc, print("Pass: %d, Iter: %d, Loss: %f\n" % (pass_id, iters, np.mean(train_losses))) print_train_time(start_time, time.time(), num_samples) - print("Pass: %d, Loss: %f" % (pass_id, np.mean(train_losses))) + print("Pass: %d, Loss: %f" % (pass_id, np.mean(train_losses))), # evaluation - if not args.no_test and batch_acc != None: + if not args.no_test and batch_acc: pass_test_acc = test(exe, infer_prog, test_reader, feeder, batch_acc) print(", Test Accuracy: %f" % pass_test_acc) @@ -310,7 +310,7 @@ def train_parallel(avg_loss, infer_prog, optimizer, train_reader, test_reader, print("Pass %d, batch %d, loss %s" % (pass_id, batch_id, np.array(loss))) print_train_time(start_time, time.time(), num_samples) - if not args.no_test and batch_acc != None: + if not args.no_test and batch_acc: test_acc = test(startup_exe, infer_prog, test_reader, feeder, batch_acc) print("Pass: %d, Test Accuracy: %f\n" % (pass_id, test_acc)) -- GitLab From 36594017dd8d6654221c109c4637dd7189b176cf Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Tue, 5 Jun 2018 14:32:01 +0800 Subject: [PATCH 0134/1416] make infer init explicit --- paddle/contrib/inference/paddle_inference_api_impl.cc | 11 ++++++----- paddle/contrib/inference/paddle_inference_api_impl.h | 2 +- 2 files changed, 7 insertions(+), 6 deletions(-) diff --git a/paddle/contrib/inference/paddle_inference_api_impl.cc b/paddle/contrib/inference/paddle_inference_api_impl.cc index 2d710727e23..bda2981a144 100644 --- a/paddle/contrib/inference/paddle_inference_api_impl.cc +++ b/paddle/contrib/inference/paddle_inference_api_impl.cc @@ -54,7 +54,8 @@ std::string num2str(T a) { } } // namespace -bool NativePaddlePredictor::Init(std::shared_ptr scope) { +bool NativePaddlePredictor::Init( + std::shared_ptr parent_scope) { VLOG(3) << "Predictor::init()"; if (config_.use_gpu) { @@ -62,9 +63,9 @@ bool NativePaddlePredictor::Init(std::shared_ptr scope) { } else { place_ = paddle::platform::CPUPlace(); } - if (scope) { - scope_ = scope; - sub_scope_ = &(scope->NewScope()); + if (parent_scope) { + scope_ = parent_scope; + sub_scope_ = &(parent_scope->NewScope()); } else { paddle::framework::InitDevices(false); scope_.reset(new paddle::framework::Scope()); @@ -275,7 +276,7 @@ CreatePaddlePredictor( } std::unique_ptr predictor(new NativePaddlePredictor(config)); - if (!dynamic_cast(predictor.get())->Init()) { + if (!dynamic_cast(predictor.get())->Init(nullptr)) { return nullptr; } return std::move(predictor); diff --git a/paddle/contrib/inference/paddle_inference_api_impl.h b/paddle/contrib/inference/paddle_inference_api_impl.h index dfb34a8631e..86d1db7bcc7 100644 --- a/paddle/contrib/inference/paddle_inference_api_impl.h +++ b/paddle/contrib/inference/paddle_inference_api_impl.h @@ -35,7 +35,7 @@ class NativePaddlePredictor : public PaddlePredictor { : config_(config) {} // will only create sub scope if have global scope - bool Init(std::shared_ptr scope = nullptr); + bool Init(std::shared_ptr parent_scope); bool Run(const std::vector &inputs, std::vector *output_data) override; -- GitLab From 9735f25011b04116d271861fde8df05def81c3ce Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Tue, 5 Jun 2018 14:47:13 +0800 Subject: [PATCH 0135/1416] optimized --- python/paddle/fluid/io.py | 44 +++++++++++++--------------------- python/paddle/fluid/trainer.py | 8 +++---- 2 files changed, 20 insertions(+), 32 deletions(-) diff --git a/python/paddle/fluid/io.py b/python/paddle/fluid/io.py index b5d96441bcf..5abadc73f76 100644 --- a/python/paddle/fluid/io.py +++ b/python/paddle/fluid/io.py @@ -492,7 +492,7 @@ def save_checkpoint(executor, if not os.path.isdir(checkpoint_dir): os.makedirs(checkpoint_dir) - serial = _get_latest_checkpoint_dir(checkpoint_dir) + 1 + serial = get_latest_checkpoint_serial(checkpoint_dir) + 1 cur_dir = _get_serial_dir(checkpoint_dir, serial) save_trainer_args(cur_dir, trainer_id, trainer_args) @@ -503,18 +503,6 @@ def save_checkpoint(executor, _lru_delete(checkpoint_dir, max_num_checkpoints) -def get_latest_checkpoint_serial(checkpoint_dir): - """ - If the directory have checkpoint files, it will return latest checkpoint directory serial number - - :param checkpoint_dir - """ - serial = _get_latest_checkpoint_dir(checkpoint_dir) - if serial < 0: - return None - return serial - - def load_checkpoint(executor, checkpoint_dir, serial, main_program): """ Load checkpoint from a directory by executor, @@ -527,17 +515,16 @@ def load_checkpoint(executor, checkpoint_dir, serial, main_program): """ if checkpoint_dir is None: - raise ValueError( - "The values of 'checkpoint_dir' or 'serial' should not be None") + raise ValueError("The values of 'checkpoint_dir' should not be None") if serial is None or serial < 0: raise ValueError("The values of 'serial' should not be None or <0 ") if main_program is None: - raise ValueError("The values of 'main_program'should not be None") + raise ValueError('main_program should not be None.') cur_dir = _get_serial_dir(checkpoint_dir, serial) - load_persist_vars_without_grad(executor, cur_dir, main_program) + load_persist_vars_without_grad(executor, cur_dir, main_program, True) def clean_checkpoint(checkpoint_dir, delete_dir=False): @@ -557,18 +544,21 @@ def clean_checkpoint(checkpoint_dir, delete_dir=False): os.rmdir(checkpoint_dir) -def load_persist_vars_without_grad(executor, dirname, program, nest=True): +def load_persist_vars_without_grad(executor, + dirname, + program, + has_model_dir=False): """ load_persist_vars_without_grad will load variables from a directory by an executor, the variable named end with "@GRAD" will not be loaded. - :param executor - :param dirname - :param program - :param nest + :param executor executor for load the value + :param dirname the checkpoint directory + :param program will load all variables in program + :param has_model_dir if has_model_dir is True, will load variables from sub directory named __model__ """ - if nest: + if has_model_dir: dirname = _get_model_dir(dirname) load_vars( @@ -584,9 +574,9 @@ def save_persist_vars_without_grad(executor, dirname, program): save_persist_vars_without_grad will save variables to a directory by an executor, the variable named end with "@GRAD" will not be saved. - :param executor - :param dirname - :param program + :param executor executor for load the value + :param dirname the checkpoint directory + :param program will load all variables in program """ cur_dir = _get_model_dir(dirname) save_vars( @@ -722,7 +712,7 @@ def _write_success(dirname): f.write(now) -def _get_latest_checkpoint_dir(checkpoint_dir): +def get_latest_checkpoint_serial(checkpoint_dir): """ get the latest file in checkpoint directory, the _SUCCESS file must exist in the directory diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py index 3c32ec1de8a..fbdd28f53ef 100644 --- a/python/paddle/fluid/trainer.py +++ b/python/paddle/fluid/trainer.py @@ -146,8 +146,9 @@ class Trainer(object): "The checkpoint_config shoule be an instance of CheckpointConfig" ) else: - self.checkpoint.load_serial = io.get_latest_checkpoint_serial( + serial = io.get_latest_checkpoint_serial( self.checkpoint.checkpoint_dir) + self.checkpoint.load_serial = serial if serial >= 0 else None self.scope = core.Scope() @@ -194,10 +195,7 @@ class Trainer(object): if param_path and os.path.isdir(param_path): # load params from param_path into scope io.load_persist_vars_without_grad( - exe, - dirname=param_path, - program=self.startup_program, - nest=False) + exe, dirname=param_path, program=self.startup_program) def _transpile_nccl2_dist(self): # PADDLE_TRAINER_IPS -- GitLab From be16af3b04b3052e35e6d9157cec302274a629a4 Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Tue, 5 Jun 2018 14:48:15 +0800 Subject: [PATCH 0136/1416] delete pyc --- tools/codestyle/docstring_checker.pyc | Bin 12561 -> 0 bytes 1 file changed, 0 insertions(+), 0 deletions(-) delete mode 100644 tools/codestyle/docstring_checker.pyc diff --git a/tools/codestyle/docstring_checker.pyc b/tools/codestyle/docstring_checker.pyc deleted file mode 100644 index a27d3c9a8cccab8552d510578debb2df04eb53bb..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 12561 zcmdT~%WoUU8J{I7N~9&rPx%oi-uOw^rX)Y&B&yDAw|-TX1?xj-N!7Warm=5bYj{N50^(C+V(2Hze+imT+b{yJug6!5>yc9NV zH>}%c|-bj7cn3o>=@Nnkurg-h%;-x9IB_yO%9{kseL9wF{k5 z(pgP9V*)px+w3Nfp1^NnrV?sO3cZ5b*n1kYj>Wa+;zyo8cGvtrf8pwU&3D_Q^{_Fv z=*MG=;h2uz%QP)JX z%ESef>E`Q%@rRw)@aX#}JkSJ40i_TbNhHf_XClMO0$BUR*40xSEj*&ytKSSK*#X5HqD5N+-*~tOdAmPz0z)XssT2wa8o|d$kuV zY>O+bR{f?QSF6XlDeg>J!&Zs|p5{7xrcf+)2pzON*==Nc8`<7QPEGpqPE~HZQXjap;KBS9)Z5cSyI%a3`ND`oLViZM`P=n*s;#+9nybV24qje+-}7YM7idHdS`*xPDk z%5E0DxGH-a#bGq>SXp^%(AsMit(}=V(MUQWoeEiA!10aneS(p|;WDJJQjZ~5hKS_V zJ_{I~p8K3w27Z@;adh{oIIAA@5&Muf4=okFt5%MyrkPAe@?!EFvkWPe^VE(QB;IM&)FRgwsrajM^2|QyuX|cAw1Z%+JAu%Bh_xau#(?mQCP&H^ot;DkHCbmRhq_mb zERy3*IJ*g;QtO;^!Xf$$_%o>A869#(2w<90a%*v?Tr;#NWuW(v7N|6rkTvXJGk!z-=hkssPg*YN0zxHRA? z^}4()-EKNt#?6Ai4<9Q_haScby(>8T1?8ieS00-E>Hu8#1<+p#2{K?(QJtM$9%Kes9_A2+RRQ4(N zoK*HJw=9(r`jcZs-VGGfp*Ge_5*(lj(^{h|-f`&>kPwSUoOl{1W_%KgkSKlA)@2n>*M3+H92UyyOJAv8rEKH!=kZi$k@k5kJ&9R@Fw6Yfd9!*1yhYKp(I zsh4G>rgey0-(+yQ(q(-DgYJiIZnhn`Ho{2u2Z>N$5x(l1! z>%5GcsP(*^xFWr?qzk_)czkMMF*82sI5E9%iWh0_GLlh(qs^B8;yKdQUlSKJi~aMt zjz|9hg|RuQ%MtlAUMS0qItcmt5U%5Cn&uV4a!Oy42IhPso+>pwd^_or_u;F-!Gi$+ zXElTQ#CKcYhA)}+OT3iZ(VwFD(1%E=F0`BC%^`AW~Tm51wQ0p`mCnuP&qm_3#v-d<`Ufnx6*&oh<9({{~(t+4=N+Wb%5^3MR&`%tKXq0ESt%M|3<1&3*uB}7XLkB<;7=U7LyZa0ic z`_6d{g>h$zC+7;Ac(yd+%$=Bn8#C@#Xm|Xj&gs6{C#2djCzPl)xcApzc1B*(x?5xe zav_mJXcz~BLJ19oh)hqZR?D22G7NBp6MPv;_j^2v3LO^ZIhYx;jzE1Lu?9@)fy#xa&T`}$3PZRc;h(_U zDhl}?67q$$2T&p>5Wyca(46`)Y!yh4jQSDY*rBE|groA3^?A>bK14Ng4sg8(xB&A8 zkSI(tWGspkAyn!@{YMlX0o@@|6BtiyyAtw2_N0Aj{0#k7IBFOzK3dmWdk%X~48e}k z*PY?HsBcqqkJn$P*+B#oxfk(h#&)2#=JqjQ25cH34QzeSS`n$-$-DAR5ta*}CXt3f zky4}M@~;_~Frp0*7gAeewuyT?x#%^$)mC)nuiS?rC(Z2_r5qAaamfE1$pnWUa4$Cs z)jd7f=ntENyIi^#O-Tmmc4H%Va#@Mw$>f5PE{3)SInH(L=}&kP{wpBHOqh;JOaB2y*AVJqyAE$jc%&1@uuqSkw!6IYjNFD$g>loswf_%>6OLgq>M*R) zOJ($?jIdr$O^yiu7tkx-7tUw$RBv;9SM+a2To|!MOy^8v>A!J#ru9@m<@yVF4nn4b zrpQq=qbSo!f%^L>Vlg{b$AthaSQ{s4df@(HdVsh{RvBiiR(3I83^NQy${jSAnb+3| zs343^ryll2N`Q#&e zZo;9w`8H!F_`DEFGO-3=q;s?UVh1+C4pmvb$+f2E-jpwe&tE+{{)gYL@Ilj2=U9FY{SOn#q;{1Uv6bQ6Z51?er5457O9WZD^0oWdh_kY ziR9ZJ99vJ=&PBkxj3uTb!pBG=m6+5y1B)q!i)@$Z8%feyqEyV)*O&ajjl5J6$P@8n!7>8nbH&Hg6BL@@;HxoP0{@ zq6YHT2tKGAMy7lpZES>!Pgn)9i1^(NecpkLQHA`r*%@WQl#Mgaf)<|n8ma2@%S}o0 zAfrw%|IY2ot-H5w&rH2jefLJCGIjGt_13h67r%Ss{=M7IbPw3M&xvSy>9xju7>HTf zLMAZs<2AXDhQ>Fdlp0}6zD#r8MBTZ{Vu}UBpUyQFbl=5?5QER58g(d~9G<+Z)upyY z9uDoy5Rd*2ihMS26`<0o+WDKs=Z!^t(NsjOU&`I6@iDD_YlxZt1Cry<7Yc(Tg^|ME z!r{VU`IJvC#<+X_s!=Y(SjFV0M>{EDsvqTm43wl0l3w|kd;uvzZElvIP}RdANWKP? y@0p!5e3LgJ_hn2!lV0JmwgrNPd?rm|;L1+yD)~TS&>BQOgn5v`Y@u)D&VK>kVxyJ- -- GitLab From d74838bda08f4331eba4d84c70e5cdbbf3a32868 Mon Sep 17 00:00:00 2001 From: whs Date: Tue, 5 Jun 2018 15:22:30 +0800 Subject: [PATCH 0137/1416] Prune dims supported by reduce op. (#11113) --- paddle/fluid/operators/reduce_op.h | 19 ++++++++++--------- 1 file changed, 10 insertions(+), 9 deletions(-) diff --git a/paddle/fluid/operators/reduce_op.h b/paddle/fluid/operators/reduce_op.h index cd19cc1460a..7df47f316c3 100644 --- a/paddle/fluid/operators/reduce_op.h +++ b/paddle/fluid/operators/reduce_op.h @@ -135,15 +135,16 @@ class ReduceKernel : public framework::OpKernel { } else { int ndim = context.Input("X")->dims().size(); int rdim = context.Attr>("dim").size(); - HANDLE_DIM(6, 5); - HANDLE_DIM(6, 4); - HANDLE_DIM(6, 3); - HANDLE_DIM(6, 2); - HANDLE_DIM(6, 1); - HANDLE_DIM(5, 4); - HANDLE_DIM(5, 3); - HANDLE_DIM(5, 2); - HANDLE_DIM(5, 1); + // comments for accelerating compiling temporarily. + // HANDLE_DIM(6, 5); + // HANDLE_DIM(6, 4); + // HANDLE_DIM(6, 3); + // HANDLE_DIM(6, 2); + // HANDLE_DIM(6, 1); + // HANDLE_DIM(5, 4); + // HANDLE_DIM(5, 3); + // HANDLE_DIM(5, 2); + // HANDLE_DIM(5, 1); HANDLE_DIM(4, 3); HANDLE_DIM(4, 2); HANDLE_DIM(4, 1); -- GitLab From 2e0d851685402e4e9d1835824f956326e9f2b0fd Mon Sep 17 00:00:00 2001 From: "yi.wu" Date: Tue, 5 Jun 2018 15:39:49 +0800 Subject: [PATCH 0138/1416] update readme --- benchmark/fluid/README.md | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/benchmark/fluid/README.md b/benchmark/fluid/README.md index c17cab999b5..48280a5621b 100644 --- a/benchmark/fluid/README.md +++ b/benchmark/fluid/README.md @@ -45,10 +45,11 @@ Currently supported `--model` argument include: ## Prepare the RecordIO file to Achieve Better Performance Run the following command will generate RecordIO files like "mnist.recordio" under the path -and batch_size you choose: +and batch_size you choose, you can use batch_size=1 so that later reader can change the batch_size +at any time using `fluid.batch`. ```bash -python -c 'from recordio_converter import *; prepare_mnist("data", 32)' +python -c 'from recordio_converter import *; prepare_mnist("data", 1)' ``` ## Run Distributed Benchmark on Kubernetes Cluster -- GitLab From e896926b9c3c8bed544f92ad82d42daac9fac0c0 Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Tue, 5 Jun 2018 15:42:29 +0800 Subject: [PATCH 0139/1416] add unit test for dist mnist --- .../fluid/tests/unittests/CMakeLists.txt | 1 + .../fluid/tests/unittests/test_dist_mnist.py | 208 ++++++++++++++++++ 2 files changed, 209 insertions(+) create mode 100644 python/paddle/fluid/tests/unittests/test_dist_mnist.py diff --git a/python/paddle/fluid/tests/unittests/CMakeLists.txt b/python/paddle/fluid/tests/unittests/CMakeLists.txt index c33539f6b50..2f2e9c96c1b 100644 --- a/python/paddle/fluid/tests/unittests/CMakeLists.txt +++ b/python/paddle/fluid/tests/unittests/CMakeLists.txt @@ -52,3 +52,4 @@ py_test_modules(test_dist_train MODULES test_dist_train SERIAL) # since load cudnn libraries, so we use a longer timeout to make this # unit test stability. set_tests_properties(test_listen_and_serv_op PROPERTIES TIMEOUT 30) +set_tests_properties(test_dist_mnist PROPERTIES TIMEOUT 60) diff --git a/python/paddle/fluid/tests/unittests/test_dist_mnist.py b/python/paddle/fluid/tests/unittests/test_dist_mnist.py new file mode 100644 index 00000000000..e6bc56cce10 --- /dev/null +++ b/python/paddle/fluid/tests/unittests/test_dist_mnist.py @@ -0,0 +1,208 @@ +# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import numpy as np +import argparse +import time + +import paddle +import paddle.fluid as fluid +import paddle.fluid.profiler as profiler +from paddle.fluid import core +import unittest +from multiprocessing import Process +import os +import signal + +SEED = 1 +DTYPE = "float32" + + +# random seed must set before configuring the network. +# fluid.default_startup_program().random_seed = SEED +def cnn_model(data): + conv_pool_1 = fluid.nets.simple_img_conv_pool( + input=data, + filter_size=5, + num_filters=20, + pool_size=2, + pool_stride=2, + act="relu") + conv_pool_2 = fluid.nets.simple_img_conv_pool( + input=conv_pool_1, + filter_size=5, + num_filters=50, + pool_size=2, + pool_stride=2, + act="relu") + + # TODO(dzhwinter) : refine the initializer and random seed settting + SIZE = 10 + input_shape = conv_pool_2.shape + param_shape = [reduce(lambda a, b: a * b, input_shape[1:], 1)] + [SIZE] + scale = (2.0 / (param_shape[0]**2 * SIZE))**0.5 + + predict = fluid.layers.fc( + input=conv_pool_2, + size=SIZE, + act="softmax", + param_attr=fluid.param_attr.ParamAttr( + initializer=fluid.initializer.NormalInitializer( + loc=0.0, scale=scale))) + return predict + + +def get_model(batch_size): + # Input data + images = fluid.layers.data(name='pixel', shape=[1, 28, 28], dtype=DTYPE) + label = fluid.layers.data(name='label', shape=[1], dtype='int64') + + # Train program + predict = cnn_model(images) + cost = fluid.layers.cross_entropy(input=predict, label=label) + avg_cost = fluid.layers.mean(x=cost) + + # Evaluator + batch_size_tensor = fluid.layers.create_tensor(dtype='int64') + batch_acc = fluid.layers.accuracy( + input=predict, label=label, total=batch_size_tensor) + + inference_program = fluid.default_main_program().clone() + # Optimization + opt = fluid.optimizer.AdamOptimizer( + learning_rate=0.001, beta1=0.9, beta2=0.999) + + # Reader + train_reader = paddle.batch( + paddle.dataset.mnist.train(), batch_size=batch_size) + test_reader = paddle.batch( + paddle.dataset.mnist.test(), batch_size=batch_size) + opt.minimize(avg_cost) + return inference_program, avg_cost, train_reader, test_reader, batch_acc, predict + + +def get_transpiler(trainer_id, main_program, pserver_endpoints, trainers): + t = fluid.DistributeTranspiler() + t.transpile( + trainer_id=trainer_id, + program=main_program, + pservers=pserver_endpoints, + trainers=trainers) + return t + + +def run_pserver(pserver_endpoints, trainers, current_endpoint): + get_model(batch_size=20) + t = get_transpiler(0, + fluid.default_main_program(), pserver_endpoints, + trainers) + pserver_prog = t.get_pserver_program(current_endpoint) + startup_prog = t.get_startup_program(current_endpoint, pserver_prog) + + place = fluid.CPUPlace() + exe = fluid.Executor(place) + exe.run(startup_prog) + + exe.run(pserver_prog) + + +class TestDistMnist(unittest.TestCase): + def setUp(self): + self._trainers = 1 + self._pservers = 1 + self._ps_endpoints = "127.0.0.1:9123" + + def start_pserver(self, endpoint): + p = Process( + target=run_pserver, + args=(self._ps_endpoints, self._trainers, endpoint)) + p.start() + return p.pid + + def _wait_ps_ready(self, pid): + retry_times = 5 + while True: + assert retry_times >= 0, "wait ps ready failed" + time.sleep(1) + try: + # the listen_and_serv_op would touch a file which contains the listen port + # on the /tmp directory until it was ready to process all the RPC call. + os.stat("/tmp/paddle.%d.port" % pid) + return + except os.error: + retry_times -= 1 + + def stop_pserver(self, pid): + os.kill(pid, signal.SIGTERM) + + def test_with_place(self): + p = fluid.CUDAPlace() if core.is_compiled_with_cuda( + ) else fluid.CPUPlace() + + pserver_pid = self.start_pserver(self._ps_endpoints) + self._wait_ps_ready(pserver_pid) + + self.run_trainer(p, 0) + + self.stop_pserver(pserver_pid) + + def run_trainer(self, place, trainer_id): + test_program, avg_cost, train_reader, test_reader, batch_acc, predict = get_model( + batch_size=20) + t = get_transpiler(trainer_id, + fluid.default_main_program(), self._ps_endpoints, + self._trainers) + + trainer_prog = t.get_trainer_program() + + exe = fluid.Executor(place) + exe.run(fluid.default_startup_program()) + + feed_var_list = [ + var for var in trainer_prog.global_block().vars.itervalues() + if var.is_data + ] + + feeder = fluid.DataFeeder(feed_var_list, place) + for pass_id in xrange(10): + for batch_id, data in enumerate(train_reader()): + exe.run(trainer_prog, feed=feeder.feed(data)) + + if (batch_id + 1) % 10 == 0: + acc_set = [] + avg_loss_set = [] + for test_data in test_reader(): + acc_np, avg_loss_np = exe.run( + program=test_program, + feed=feeder.feed(test_data), + fetch_list=[batch_acc, avg_cost]) + acc_set.append(float(acc_np)) + avg_loss_set.append(float(avg_loss_np)) + # get test acc and loss + acc_val = np.array(acc_set).mean() + avg_loss_val = np.array(avg_loss_set).mean() + if float(acc_val + ) > 0.2: # Smaller value to increase CI speed + return + else: + print( + 'PassID {0:1}, BatchID {1:04}, Test Loss {2:2.2}, Acc {3:2.2}'. + format(pass_id, batch_id + 1, + float(avg_loss_val), float(acc_val))) + if math.isnan(float(avg_loss_val)): + assert ("got Nan loss, training failed.") + + +if __name__ == "__main__": + unittest.main() -- GitLab From bd2ea0e1f84bb6522a66d44a072598153634cade Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Tue, 5 Jun 2018 15:48:25 +0800 Subject: [PATCH 0140/1416] add host_memory_profiling_cn.md --- .../optimization/host_memory_profiling_cn.md | 89 ++++++++++++++++++ .../optimization/memory_cpu_allocator.jpg | Bin 0 -> 77570 bytes .../optimization/memory_cpu_allocator.pdf | Bin 0 -> 26831 bytes .../optimization/memory_leak_protobuf.pdf | Bin 0 -> 40244 bytes .../optimization/memory_program_desc.png | Bin 0 -> 30768 bytes .../optimization/memory_protobuf_arena.png | Bin 0 -> 32597 bytes 6 files changed, 89 insertions(+) create mode 100644 doc/fluid/howto/optimization/host_memory_profiling_cn.md create mode 100644 doc/fluid/howto/optimization/memory_cpu_allocator.jpg create mode 100644 doc/fluid/howto/optimization/memory_cpu_allocator.pdf create mode 100644 doc/fluid/howto/optimization/memory_leak_protobuf.pdf create mode 100644 doc/fluid/howto/optimization/memory_program_desc.png create mode 100644 doc/fluid/howto/optimization/memory_protobuf_arena.png diff --git a/doc/fluid/howto/optimization/host_memory_profiling_cn.md b/doc/fluid/howto/optimization/host_memory_profiling_cn.md new file mode 100644 index 00000000000..464368ec028 --- /dev/null +++ b/doc/fluid/howto/optimization/host_memory_profiling_cn.md @@ -0,0 +1,89 @@ +## 堆内存分析和优化 + +计算机程序都可能有内存泄露的风险。**内存泄露**一般是由于程序在堆(heap)上分配了内存而没有释放，随着程序的运行占用的内存越来越大，一方面会影响程序的稳定性，可能让运行速度越来越慢，或者造成oom，甚至会影响运行程序的机器的稳定性，造成宕机。 + + +目前有很多内存泄露分析工具，比较经典的有[valgrind](http://valgrind.org/docs/manual/quick-start.html#quick-start.intro), [gperftools](https://gperftools.github.io/gperftools/)。 + +因为Fluid是用Python驱动C++ core来运行，valgrind直接分析非常困难，需要自己编译debug版本的、带valgrind支持的专用版本，而且输出的信息中大部分是Python自己的符号和调用信息，分析起来很困难，所以不建议使用。 + +本教程主要介绍[gperftools](https://gperftools.github.io/gperftools/)的使用。 + +gperftool主要支持以下四个功能： + +- thread-caching malloc +- heap-checking using tcmalloc +- heap-profiling using tcmalloc +- CPU profiler + +Paddle也提供了基于gperftool的[CPU性能分析教程](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/fluid/howto/optimization/cpu_profiling_cn.md)。 + +对于堆内存的分析，主要用到thread-caching malloc和heap-profiling using tcmalloc。 + +## 使用流程 +#### 环境 +本教程基于paddle提供的Docker开发环境paddlepaddle/paddle:latest-dev，基于Ubuntu 16.04.4 LTS环境。 + +#### 使用流程 + +- 安装google-perftools + +``` +apt-get install libunwind-dev +apt-get install google-perftools +``` + +- 安装pprof + +``` +go get -u github.com/google/pprof +``` + +- 设置运行环境 + +``` +export PPROF_PATH=/root/gopath/bin/pprof +export PPROF_BINARY_PATH=/root/gopath/bin/pprof +export LD_PRELOAD=/usr/lib/libtcmalloc.so.4 +``` + +- 使用heap profile来运行python程序。本质上是周期性的对堆的分配情况做一次快照。 + +``` +# HEAPPROFILE 设置生成的堆分析文件的目录和文件前缀 +# HEAP_PROFILE_ALLOCATION_INTERVAL 设置每分配多少存储dump一次dump，默认1GB +env HEAPPROFILE="./perf_log/test.log" HEAP_PROFILE_ALLOCATION_INTERVAL=209715200 python trainer.py +``` + +随着程序的运行，会在perf_log这个文件夹下生成很多文件，如下： + +``` +-rw-r--r-- 1 root root 1.0M Jun 1 15:00 test.log.0001.heap +-rw-r--r-- 1 root root 1.0M Jun 1 15:00 test.log.0002.heap +-rw-r--r-- 1 root root 1.0M Jun 1 15:00 test.log.0003.heap +-rw-r--r-- 1 root root 1.0M Jun 1 15:00 test.log.0004.heap +-rw-r--r-- 1 root root 1.0M Jun 1 15:00 test.log.0005.heap +-rw-r--r-- 1 root root 1.0M Jun 1 15:00 test.log.0006.heap +``` + +- 使用pprof对heap文件进行分析。分析有两种模式： + - 完整模式。会对当前heap做一个分析，显示目前分配内存一些调用路径。 + + ``` + pprof --pdf python test.log.0012.heap + ``` + 上述命令会生成一个profile00x.pdf的文件，可以直接打开，例如：[allocator](./memory_cpu_allocator.pdf)。从下图可以看出，在CPU版本fluid的运行过程中，分配存储最多的模块式CPUAllocator. 而别的模块相对而言分配内存较少，所以被忽略了，这对于分配内存泄露是很不方便的，因为泄露是一个缓慢的过程，在这种图中是无法看到的。 + + ![result](memory_cpu_allocator.jpg) + + - Diff模式。可以对两个时刻的heap做diff，把一些内存分配没有发生变化的模块去掉，而把增量部分显示出来。 + ``` + pprof --pdf --base test.log.0010.heap python test.log.1045.heap + ``` + 生成的结果为：[`memory_leak_protobuf`](./memory_leak_protobuf.pdf) + + 从图中可以看出：ProgramDesc这个结构，在两个版本之间增长了200MB+，所以这里有很大的内存泄露的可能性，最终结果也确实证明是这里造成了泄露。 + + ![result](memory_program_desc.png) + ![result](memory_protobuf_arena.png) + diff --git a/doc/fluid/howto/optimization/memory_cpu_allocator.jpg 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