From 550ab8d7236b30d716ce4a44d2a679cee16434a5 Mon Sep 17 00:00:00 2001 From: yuyang18 Date: Mon, 2 Jul 2018 17:23:42 +0800 Subject: [PATCH] Use single file than multiple files --- paddle/fluid/operators/reshape_op.cc | 216 ++++++++++++++++++------ paddle/fluid/operators/reshape_op.cu.cc | 24 --- paddle/fluid/operators/reshape_op.h | 132 --------------- 3 files changed, 164 insertions(+), 208 deletions(-) delete mode 100644 paddle/fluid/operators/reshape_op.cu.cc delete mode 100644 paddle/fluid/operators/reshape_op.h diff --git a/paddle/fluid/operators/reshape_op.cc b/paddle/fluid/operators/reshape_op.cc index 6e384e9060..918f3be533 100644 --- a/paddle/fluid/operators/reshape_op.cc +++ b/paddle/fluid/operators/reshape_op.cc @@ -12,14 +12,108 @@ 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/reshape_op.h" - #include #include +#include "paddle/fluid/framework/op_registry.h" namespace paddle { namespace operators { +class ReshapeOp : public framework::OperatorWithKernel { + public: + ReshapeOp(const std::string &type, const framework::VariableNameMap &inputs, + const framework::VariableNameMap &outputs, + const framework::AttributeMap &attrs) + : OperatorWithKernel(type, inputs, outputs, attrs) {} + + void InferShape(framework::InferShapeContext *ctx) const override { + PADDLE_ENFORCE(ctx->HasInput("X"), + "Input(X) of ReshapeOp should not be null."); + PADDLE_ENFORCE(ctx->HasOutput("Out"), + "Output(Out) of ReshapeOp should not be null."); + + const std::vector &shape = ctx->Attrs().Get>("shape"); + PADDLE_ENFORCE(!shape.empty(), + "The shape information must be set by Attr(shape)."); + + if (ctx->HasInput("Shape") && ctx->IsRuntime()) { + // If true, set the shape of Output(Out) according to Input(Shape) in + // ReshapeKernel with ExecutionContext. Also check LoD in ReshapeKernel. + ctx->ShareLoD("X", /*->*/ "Out"); + return; + } + + auto x_dims = ctx->GetInputDim("X"); + auto out_dims = ValidateShape(shape, x_dims); + ctx->SetOutputDim("Out", out_dims); + if (x_dims[0] == out_dims[0]) { + // Only pass LoD when the first dimension of output and Input(X) + // are the same. + ctx->ShareLoD("X", /*->*/ "Out"); + } + } + + static framework::DDim ValidateShape(const std::vector shape, + const framework::DDim &in_dims) { + const int64_t in_size = framework::product(in_dims); + // only one dimension can be set to -1, whose size will be automatically + // infered. + const int64_t unk_dim_val = -1; + const int64_t copy_dim_val = 0; + + std::vector output_shape(shape.size(), 0); + int64_t capacity = 1; + int unk_dim_idx = -1; + for (size_t i = 0; i < shape.size(); ++i) { + if (shape[i] == unk_dim_val) { + PADDLE_ENFORCE( + unk_dim_idx == -1, + "Only one input dimension of Attr(shape) can be unknown."); + unk_dim_idx = i; + } else if (shape[i] == copy_dim_val) { + PADDLE_ENFORCE( + static_cast(i) < in_dims.size(), + "The index of dimension to copy from input shape must be less " + "than the size of input shape."); + } else { + PADDLE_ENFORCE( + shape[i] > 0, + "Each input dimension of Attr(shape) must not be negtive except " + "one unknown dimension."); + } + + capacity *= (shape[i] ? shape[i] : in_dims[i]); + output_shape[i] = + (shape[i] ? static_cast(shape[i]) : in_dims[i]); + } + + if (unk_dim_idx != -1) { + if (in_size > 0) { + // in_size < 0 and is un-determinate in compile time, skip the check, + // for example, in_dims = [-1, 8, 1, 1], shape = [-1, 3, 8], + // capacity = -24, in_size = -8, output_shape[0] = 0 + // the following check will fail. + output_shape[unk_dim_idx] = -in_size / capacity; + PADDLE_ENFORCE_EQ(output_shape[unk_dim_idx] * capacity, -in_size, + "Invalid shape is given."); + } else { + output_shape[unk_dim_idx] = -1; + } + } else { + PADDLE_ENFORCE_EQ(capacity, in_size, "Invalid shape is given."); + } + return framework::make_ddim(output_shape); + } + + protected: + framework::OpKernelType GetExpectedKernelType( + const framework::ExecutionContext &ctx) const override { + return framework::OpKernelType( + framework::ToDataType(ctx.Input("X")->type()), + ctx.device_context()); + } +}; + class ReshapeOpMaker : public framework::OpProtoAndCheckerMaker { public: void Make() override { @@ -107,64 +201,72 @@ class ReshapeGradOp : public framework::OperatorWithKernel { } }; -void ReshapeKernel::operator()(const framework::ExecutionContext &ctx) const { - auto *out = ctx.Output("Out"); - auto *in = ctx.Input("X"); +class ReshapeKernel { + public: + void operator()(const framework::ExecutionContext &ctx) const { + auto *out = ctx.Output("Out"); + auto *in = ctx.Input("X"); - auto *shape_tensor = ctx.HasInput("Shape") - ? ctx.Input("Shape") - : nullptr; + auto *shape_tensor = ctx.HasInput("Shape") + ? ctx.Input("Shape") + : nullptr; - framework::DDim out_dims = out->dims(); + framework::DDim out_dims = out->dims(); - if (shape_tensor) { - auto *shape_data = shape_tensor->data(); - framework::Tensor cpu_shape_tensor; - if (platform::is_gpu_place(ctx.GetPlace())) { - TensorCopySync(*shape_tensor, platform::CPUPlace(), &cpu_shape_tensor); - shape_data = cpu_shape_tensor.data(); + if (shape_tensor) { + auto *shape_data = shape_tensor->data(); + framework::Tensor cpu_shape_tensor; + if (platform::is_gpu_place(ctx.GetPlace())) { + TensorCopySync(*shape_tensor, platform::CPUPlace(), &cpu_shape_tensor); + shape_data = cpu_shape_tensor.data(); + } + auto shape = + std::vector(shape_data, shape_data + shape_tensor->numel()); + out_dims = ReshapeOp::ValidateShape(shape, in->dims()); + } + if (!in->lod().empty()) { + PADDLE_ENFORCE_EQ( + out_dims[0], in->dims()[0], + "Reshape operator cannot reshape an input sequence batch " + "into an output sequence batch that has a different " + "number of time steps. Please consider using " + "sequence_reshape op."); } - auto shape = - std::vector(shape_data, shape_data + shape_tensor->numel()); - out_dims = ReshapeOp::ValidateShape(shape, in->dims()); - } - if (!in->lod().empty()) { - PADDLE_ENFORCE_EQ(out_dims[0], in->dims()[0], - "Reshape operator cannot reshape an input sequence batch " - "into an output sequence batch that has a different " - "number of time steps. Please consider using " - "sequence_reshape op."); - } - bool inplace = ctx.Attr("inplace"); - out->Resize(out_dims); - if (!inplace) { - out->mutable_data(ctx.GetPlace(), in->type()); - framework::TensorCopySync(*in, ctx.GetPlace(), out); - out->Resize(out_dims); - } else { - out->ShareDataWith(*in); + bool inplace = ctx.Attr("inplace"); out->Resize(out_dims); + if (!inplace) { + out->mutable_data(ctx.GetPlace(), in->type()); + framework::TensorCopySync(*in, ctx.GetPlace(), out); + out->Resize(out_dims); + } else { + out->ShareDataWith(*in); + out->Resize(out_dims); + } } -} -void ReshapeGradKernel::operator()( - const framework::ExecutionContext &ctx) const { - auto *d_out = ctx.Input(framework::GradVarName("Out")); - auto *d_x = ctx.Output(framework::GradVarName("X")); - - d_x->mutable_data(ctx.GetPlace(), d_out->type()); - bool inplace = ctx.Attr("inplace"); - - auto in_dims = d_x->dims(); - if (!inplace) { - framework::TensorCopy(*d_out, ctx.GetPlace(), ctx.device_context(), d_x); - ctx.device_context().Wait(); - d_x->Resize(in_dims); - } else { - d_x->ShareDataWith(*d_out); - d_x->Resize(in_dims); +}; + +class ReshapeGradKernel { + public: + void operator()(const framework::ExecutionContext &ctx) const { + auto *d_out = ctx.Input(framework::GradVarName("Out")); + auto *d_x = ctx.Output(framework::GradVarName("X")); + + d_x->mutable_data(ctx.GetPlace(), d_out->type()); + bool inplace = ctx.Attr("inplace"); + + auto in_dims = d_x->dims(); + if (!inplace) { + framework::TensorCopy(*d_out, ctx.GetPlace(), ctx.device_context(), d_x); + ctx.device_context().Wait(); + d_x->Resize(in_dims); + } else { + d_x->ShareDataWith(*d_out); + d_x->Resize(in_dims); + } } -} +}; + } // namespace operators } // namespace paddle namespace ops = paddle::operators; @@ -179,3 +281,13 @@ REGISTER_OP_CPU_KERNEL_FUNCTOR(reshape_grad, float, ops::ReshapeGradKernel, double, ops::ReshapeGradKernel, int, ops::ReshapeGradKernel, int64_t, ops::ReshapeGradKernel); + +#ifdef PADDLE_WITH_CUDA +REGISTER_OP_CUDA_KERNEL_FUNCTOR(reshape, float, ops::ReshapeKernel, double, + ops::ReshapeKernel, int, ops::ReshapeKernel, + int64_t, ops::ReshapeKernel); +REGISTER_OP_CUDA_KERNEL_FUNCTOR(reshape_grad, float, ops::ReshapeGradKernel, + double, ops::ReshapeGradKernel, int, + ops::ReshapeGradKernel, int64_t, + ops::ReshapeGradKernel); +#endif diff --git a/paddle/fluid/operators/reshape_op.cu.cc b/paddle/fluid/operators/reshape_op.cu.cc deleted file mode 100644 index 374b2dbc6a..0000000000 --- a/paddle/fluid/operators/reshape_op.cu.cc +++ /dev/null @@ -1,24 +0,0 @@ -/* 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/reshape_op.h" -namespace ops = paddle::operators; - -REGISTER_OP_CUDA_KERNEL_FUNCTOR(reshape, float, ops::ReshapeKernel, double, - ops::ReshapeKernel, int, ops::ReshapeKernel, - int64_t, ops::ReshapeKernel); -REGISTER_OP_CUDA_KERNEL_FUNCTOR(reshape_grad, float, ops::ReshapeGradKernel, - double, ops::ReshapeGradKernel, int, - ops::ReshapeGradKernel, int64_t, - ops::ReshapeGradKernel); diff --git a/paddle/fluid/operators/reshape_op.h b/paddle/fluid/operators/reshape_op.h deleted file mode 100644 index 68e1690a53..0000000000 --- a/paddle/fluid/operators/reshape_op.h +++ /dev/null @@ -1,132 +0,0 @@ -/* 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 "paddle/fluid/framework/eigen.h" -#include "paddle/fluid/framework/op_registry.h" - -namespace paddle { -namespace operators { - -class ReshapeOp : public framework::OperatorWithKernel { - public: - ReshapeOp(const std::string &type, const framework::VariableNameMap &inputs, - const framework::VariableNameMap &outputs, - const framework::AttributeMap &attrs) - : OperatorWithKernel(type, inputs, outputs, attrs) {} - - void InferShape(framework::InferShapeContext *ctx) const override { - PADDLE_ENFORCE(ctx->HasInput("X"), - "Input(X) of ReshapeOp should not be null."); - PADDLE_ENFORCE(ctx->HasOutput("Out"), - "Output(Out) of ReshapeOp should not be null."); - - const std::vector &shape = ctx->Attrs().Get>("shape"); - PADDLE_ENFORCE(!shape.empty(), - "The shape information must be set by Attr(shape)."); - - if (ctx->HasInput("Shape") && ctx->IsRuntime()) { - // If true, set the shape of Output(Out) according to Input(Shape) in - // ReshapeKernel with ExecutionContext. Also check LoD in ReshapeKernel. - ctx->ShareLoD("X", /*->*/ "Out"); - return; - } - - auto x_dims = ctx->GetInputDim("X"); - auto out_dims = ValidateShape(shape, x_dims); - ctx->SetOutputDim("Out", out_dims); - if (x_dims[0] == out_dims[0]) { - // Only pass LoD when the first dimension of output and Input(X) - // are the same. - ctx->ShareLoD("X", /*->*/ "Out"); - } - } - - static framework::DDim ValidateShape(const std::vector shape, - const framework::DDim &in_dims) { - const int64_t in_size = framework::product(in_dims); - // only one dimension can be set to -1, whose size will be automatically - // infered. - const int64_t unk_dim_val = -1; - const int64_t copy_dim_val = 0; - - std::vector output_shape(shape.size(), 0); - int64_t capacity = 1; - int unk_dim_idx = -1; - for (size_t i = 0; i < shape.size(); ++i) { - if (shape[i] == unk_dim_val) { - PADDLE_ENFORCE( - unk_dim_idx == -1, - "Only one input dimension of Attr(shape) can be unknown."); - unk_dim_idx = i; - } else if (shape[i] == copy_dim_val) { - PADDLE_ENFORCE( - static_cast(i) < in_dims.size(), - "The index of dimension to copy from input shape must be less " - "than the size of input shape."); - } else { - PADDLE_ENFORCE( - shape[i] > 0, - "Each input dimension of Attr(shape) must not be negtive except " - "one unknown dimension."); - } - - capacity *= (shape[i] ? shape[i] : in_dims[i]); - output_shape[i] = - (shape[i] ? static_cast(shape[i]) : in_dims[i]); - } - - if (unk_dim_idx != -1) { - if (in_size > 0) { - // in_size < 0 and is un-determinate in compile time, skip the check, - // for example, in_dims = [-1, 8, 1, 1], shape = [-1, 3, 8], - // capacity = -24, in_size = -8, output_shape[0] = 0 - // the following check will fail. - output_shape[unk_dim_idx] = -in_size / capacity; - PADDLE_ENFORCE_EQ(output_shape[unk_dim_idx] * capacity, -in_size, - "Invalid shape is given."); - } else { - output_shape[unk_dim_idx] = -1; - } - } else { - PADDLE_ENFORCE_EQ(capacity, in_size, "Invalid shape is given."); - } - return framework::make_ddim(output_shape); - } - - protected: - framework::OpKernelType GetExpectedKernelType( - const framework::ExecutionContext &ctx) const override { - return framework::OpKernelType( - framework::ToDataType(ctx.Input("X")->type()), - ctx.device_context()); - } -}; - -class ReshapeKernel { - public: - void operator()(const framework::ExecutionContext &ctx) const; -}; - -class ReshapeGradKernel { - public: - void operator()(const framework::ExecutionContext &ctx) const; -}; - -} // namespace operators -} // namespace paddle -- GitLab