diff --git a/cmake/external/mkldnn.cmake b/cmake/external/mkldnn.cmake index 5759e5c489724332793bf103b7aacf7ffb068611..83c1cf1457dfc2d98039b7a03e8a569a0352991a 100644 --- a/cmake/external/mkldnn.cmake +++ b/cmake/external/mkldnn.cmake @@ -53,7 +53,7 @@ ExternalProject_Add( ${EXTERNAL_PROJECT_LOG_ARGS} DEPENDS ${MKLDNN_DEPENDS} GIT_REPOSITORY "https://github.com/01org/mkl-dnn.git" - GIT_TAG "v0.11" + GIT_TAG "v0.14" PREFIX ${MKLDNN_SOURCES_DIR} UPDATE_COMMAND "" CMAKE_ARGS -DCMAKE_INSTALL_PREFIX=${MKLDNN_INSTALL_DIR} diff --git a/doc/fluid/build_and_install/paddleci.png b/doc/fluid/build_and_install/paddleci.png new file mode 120000 index 0000000000000000000000000000000000000000..c3eb1457acc77cab9360e654240d1e8f548035b4 --- /dev/null +++ b/doc/fluid/build_and_install/paddleci.png @@ -0,0 +1 @@ +../../v2/build_and_install/paddleci.png \ No newline at end of file diff --git a/doc/fluid/design/motivation/refactorization.md b/doc/fluid/design/motivation/refactorization.md index 4e1d660cef6369f04db8e1e83360f6af25259f96..ad9d0f6d3f3ad9884f108826e8410871fffd51bf 100644 --- a/doc/fluid/design/motivation/refactorization.md +++ b/doc/fluid/design/motivation/refactorization.md @@ -125,12 +125,12 @@ Compile Time -> IR -> Runtime ## Operator/OpWithKernel/OpKernel -![class_diagram](http://api.paddlepaddle.org/graphviz?dot=https://gist.githubusercontent.com/reyoung/53df507f6749762675dff3e7ce53372f/raw/49caf1fb70820fb4a6c217634317c9306f361f36/op_op_with_kern_class_diagram.dot) +![class_diagram](https://raw.githubusercontent.com/PaddlePaddle/Paddle/develop/doc/fluid/images/op_op_with_kern_class_diagram.dot) --- ## Operator -![class_diagram](http://api.paddlepaddle.org/graphviz?dot=https://gist.githubusercontent.com/reyoung/53df507f6749762675dff3e7ce53372f/raw/dd598e8f1976f5759f58af5e5ef94738a6b2e661/op.dot) +![class_diagram](https://raw.githubusercontent.com/PaddlePaddle/Paddle/develop/doc/fluid/images/op.dot) * `Operator` is the fundamental building block of the user interface. * Operator stores input/output variable names and attributes. @@ -141,7 +141,7 @@ Compile Time -> IR -> Runtime ## OpWithKernel/Kernel -![class_diagram](http://api.paddlepaddle.org/graphviz?dot=https://gist.githubusercontent.com/reyoung/53df507f6749762675dff3e7ce53372f/raw/9d7f4eba185cf41c8e2fbfb40ae21890dbddcd39/op_with_kernel.dot) +![class_diagram](https://raw.githubusercontent.com/PaddlePaddle/Paddle/develop/doc/fluid/images/op_with_kernel.dot) * `OpWithKernel` inherits `Operator`. * `OpWithKernel` contains a Kernel map. diff --git a/doc/fluid/images/op.dot b/doc/fluid/images/op.dot new file mode 100644 index 0000000000000000000000000000000000000000..c8ad839cb88788e9b5906402257cc7bbc3ddcb54 --- /dev/null +++ b/doc/fluid/images/op.dot @@ -0,0 +1,4 @@ +digraph sample { + graph [rankdir=TD]; node [shape=record]; + op [label="{Operator| InferShape()=0\lRun()=0\l | map<string, string[]> inputs_\lmap<string, string[]> outputs_ \l AttributeMap attrs_\l}"]; +} \ No newline at end of file diff --git a/doc/fluid/images/op_op_with_kern_class_diagram.dot b/doc/fluid/images/op_op_with_kern_class_diagram.dot new file mode 100644 index 0000000000000000000000000000000000000000..8f24e9ea83acf879c7008f2d97113c0a4cc111c3 --- /dev/null +++ b/doc/fluid/images/op_op_with_kern_class_diagram.dot @@ -0,0 +1,38 @@ +digraph sample { + graph [rankdir=TD]; node [shape=record]; + op [label="{Operator| InferShape()=0\lRun()=0\l | map<string, string[]> inputs_\lmap<string, string[]> outputs_ \l AttributeMap attrs_\l}"]; + op_with_kern [label="{OpWithKernel | InferShape()=0\lRun()\l | map<OpKernelKey,OpKernel>kernels_ }"] + op_kernel [label="{OpKernel | Compute()=0}"] + op_kernel_key [label="{OpKernelKey| Place place\n...}"] + + op -> op_with_kern [dir=back, arrowtail=onormal] + op_with_kern -> op_kernel [arrowhead=vee, label="contains many"] + + { + rank=same; + op_with_kern + op_kernel + } + + op_kernel -> op_kernel_key [style=invis] + + { + rank=same; + op_kernel + op_kernel_key + } + + op_with_kern -> op_kernel_key [arrowhead=vee, label ="\nas map key"] + + mul_op [label="MulOp"] + op_with_kern -> mul_op [dir=back, arrowtail=onormal] + mul_kernel [label="template <typename Place>\lclass MulOpKernel\l"] + op_kernel -> mul_kernel [dir=back, arrowtail=onormal] + mul_op -> mul_kernel [arrowhead=vee, label="register many"] + + { + rank=same; + mul_op; + mul_kernel; + } +} \ No newline at end of file diff --git a/doc/fluid/images/op_with_kernel.dot b/doc/fluid/images/op_with_kernel.dot new file mode 100644 index 0000000000000000000000000000000000000000..4f5af4f7b5f5a69693a058c99eb658900136077a --- /dev/null +++ b/doc/fluid/images/op_with_kernel.dot @@ -0,0 +1,26 @@ +digraph sample { + graph [rankdir=TD]; node [shape=record]; + op [label="{Operator}"]; + op_with_kern [label="{OpWithKernel | InferShape()=0\lRun()\l | map<OpKernelKey,OpKernel>kernels_ }"] + op_kernel [label="{OpKernel | Compute()=0}"] + op_kernel_key [label="{OpKernelKey| Place place\n...}"] + + op -> op_with_kern [dir=back, arrowtail=onormal] + op_with_kern -> op_kernel [arrowhead=vee, label="contains many"] + + { + rank=same; + op_with_kern + op_kernel + } + + op_kernel -> op_kernel_key [style=invis] + + { + rank=same; + op_kernel + op_kernel_key + } + + op_with_kern -> op_kernel_key [arrowhead=vee, label ="\nas map key"] +} \ No newline at end of file diff --git a/doc/v2/api/config/layer.rst b/doc/v2/api/config/layer.rst index 29388f5005bf779a1bfa63c0d46d35996c0c792d..1a6496968cae1fef88142ba9ca3f9e63a81b196d 100644 --- a/doc/v2/api/config/layer.rst +++ b/doc/v2/api/config/layer.rst @@ -142,7 +142,7 @@ gated_unit ----------- .. autoclass:: paddle.v2.layer.gated_unit :noindex: - + Recurrent Layer Group ===================== @@ -354,7 +354,7 @@ dropout -------- .. autoclass:: paddle.v2.layer.dropout :noindex: - + dot_prod --------- .. autoclass:: paddle.v2.layer.dot_prod @@ -460,6 +460,11 @@ multi_binary_label_cross_entropy_cost .. autoclass:: paddle.v2.layer.multi_binary_label_cross_entropy_cost :noindex: +classification_cost +------------------- +.. autoclass:: paddle.v2.layer.classification_cost + :noindex: + huber_regression_cost ------------------------- .. autoclass:: paddle.v2.layer.huber_regression_cost @@ -534,7 +539,7 @@ detection_output ---------------- .. autoclass:: paddle.v2.layer.detection_output :noindex: - + Check Layer ============ diff --git a/doc/v2/design/mkl/mkldnn.md b/doc/v2/design/mkl/mkldnn.md index 1bd2e7bc34ee79eb753b3520d97e5e7beca89b0b..bd5bcf6f67168c21cebb046a629b948d1661e75c 100644 --- a/doc/v2/design/mkl/mkldnn.md +++ b/doc/v2/design/mkl/mkldnn.md @@ -5,7 +5,7 @@ 充分展现英特尔平台的优势，有效提升PaddlePaddle在英特尔架构上的性能。
-
+
Figure 1. PaddlePaddle on IA
@@ -42,16 +42,43 @@ Figure 1. PaddlePaddle on IA MKL，MKLML以及MKL-DNN三者关系如下表： -| Name | Open Source | License | Descriptions | -| :---------- | :--------------- | :---------- | :------------ | -| MKL | No | Proprietary | Accelerate math processing routines | -| MKLML | No | Proprietary | Small package of MKL, especially for Machine Learning | -| MKL-DNN | Yes | Apache 2.0 | Accelerate primitives processing routines especially for Deep Neural Networks | + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameOpen SourceLicenseDescriptions
MKLNoProprietaryAccelerate math processing routines
MKLMLNoProprietarySmall package of MKL, especially for Machine Learning
MKL-DNNYesApache 2.0Accelerate primitives processing routines especially for Deep Neural Networks
MKLML可以与MKL-DNN共同使用，以此达到最好的性能。
-
+
Figure 2. PaddlePaddle with MKL Engines
@@ -103,7 +130,7 @@ MKL-DNN的库目前只有动态库`libmkldnn.so`。 所以我们定义了一个`MKLDNNMatrix`用于管理MKL-DNN数据的不同格式以及相互之间的转换。
-
+
Figure 3. MKLDNNMatrix
@@ -113,7 +140,7 @@ Figure 3. MKLDNNMatrix 子类只需要使用定义好的接口，实现具体的函数功能即可。
-
+
Figure 4. MKLDNNLayer
@@ -150,7 +177,7 @@ Figure 4. MKLDNNLayer 所以整体上，在实现每个子类的时候就不需要关心分支的事情了。
-
+
Figure 5. Merge Gradients
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0000000000000000000000000000000000000000..2cd0fb1820c44b0e8e0b869f9d39fcad27efa758 --- /dev/null +++ b/doc/v2/images/glossary_rnn.dot @@ -0,0 +1,42 @@ +digraph G{ + subgraph cluster_timestep0 { + label="recurrent timestep i-1" + bgcolor=lightgray + node [style=filled,color=white] + fc0_0 [label="fc 0"] + fc0_1 [label="fc 1"] + fc0_2 [label="fc 2"] + + fc0_0 -> fc0_1 + fc0_1 -> fc0_2 + } + + subgraph cluster_timestep1 { + label="recurrent timestep i" + node [style=filled]; + fc1_0 [label="fc 0"] + fc1_1 [label="fc 1"] + fc1_2 [label="fc 2"] + color=blue + + fc1_0 -> fc1_1 + fc1_1 -> fc1_2 + } + + subgraph cluster_timestep2 { + label="recurrent timestep i+1" + bgcolor=lightgray + node [style=filled,color=white] + fc2_0 [label="fc 0"] + fc2_1 [label="fc 1"] + fc2_2 [label="fc 2"] + + fc2_0 -> fc2_1 + fc2_1 -> fc2_2 + } + + + fc0_1 -> fc1_1 [style="dotted" constraint=false] + fc1_1 -> fc2_1 [style="dotted" constraint=false] + +} \ No newline at end of file diff --git a/doc/v2/images/glossary_rnn_with_memory.dot b/doc/v2/images/glossary_rnn_with_memory.dot new file mode 100644 index 0000000000000000000000000000000000000000..0f101ec2d8f15aec76c57f328046b6b55cf0c7eb --- /dev/null +++ b/doc/v2/images/glossary_rnn_with_memory.dot @@ -0,0 +1,48 @@ +digraph G{ + subgraph cluster_timestep0 { + label="recurrent timestep i-1" + bgcolor=lightgray + node [style=filled,color=white] + fc0_0 [label="fc 0"] + fc0_1 [label="fc 1"] + fc0_2 [label="fc 2"] + m0 [label="memory"] + fc0_0 -> fc0_1 + fc0_1 -> fc0_2 + fc0_1 -> m0 + m0 -> fc0_1 + } + + subgraph cluster_timestep1 { + label="recurrent timestep i" + node [style=filled]; + fc1_0 [label="fc 0"] + fc1_1 [label="fc 1"] + fc1_2 [label="fc 2"] + m1 [label="memory"] + color=blue + fc1_0 -> fc1_1 + fc1_1 -> fc1_2 + fc1_1 -> m1 + m1 -> fc1_1 + } + + subgraph cluster_timestep2 { + label="recurrent timestep i+1" + bgcolor=lightgray + node [style=filled,color=white] + fc2_0 [label="fc 0"] + fc2_1 [label="fc 1"] + fc2_2 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[label="9"] + } + + subgraph cluster_t2 { + f [label="8"] + g [label="1"] + h [label="4"] + } + + a -> b; + b -> c; + c -> d [constraint=false]; + + d -> e; + e -> f [constraint=false]; + + f -> g; + g -> h; +} \ No newline at end of file diff --git a/doc/v2/images/simple_full_recurrent.dot b/doc/v2/images/simple_full_recurrent.dot new file mode 100644 index 0000000000000000000000000000000000000000..cee281fbac993afbd0cc3416570f95965cdf0a59 --- /dev/null +++ b/doc/v2/images/simple_full_recurrent.dot @@ -0,0 +1,19 @@ +digraph G { + rankdir=LR; + a [label="4"] + b [label="5"] + c [label="2"] + d [label="0"] + e [label="9"] + f [label="8"] + g [label="1"] + h [label="4"] + + a -> b; + b -> c; + c -> d; + d -> e; + e -> f; + f -> g; + g -> h; +} \ No newline at end of file diff --git a/doc/v2/images/submit-job.graffle b/doc/v2/images/submit-job.graffle new file mode 100644 index 0000000000000000000000000000000000000000..677cdfb6d9a32168bf71729eb841fa1ca0dd31d6 Binary files /dev/null and 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b/doc/v2/images/trainer_cn.png differ diff --git a/doc/v2/images/worker_security_group.png b/doc/v2/images/worker_security_group.png new file mode 100644 index 0000000000000000000000000000000000000000..57eb0265a34ad4223b69600d2a3dd355482e0bf5 Binary files /dev/null and b/doc/v2/images/worker_security_group.png differ diff --git a/doc/v2/images/workflow_of_CAPI.png b/doc/v2/images/workflow_of_CAPI.png new file mode 100644 index 0000000000000000000000000000000000000000..a4399ade048b3fe10d2d9c714bc34333ca068edb Binary files /dev/null and b/doc/v2/images/workflow_of_CAPI.png differ diff --git a/paddle/fluid/framework/details/fetch_op_handle.cc b/paddle/fluid/framework/details/fetch_op_handle.cc index 1e8ca20b51d43554cf1898b41b31c27b90e6c642..a3cae8c64cdff8594c8971b0458c443f54375f11 100644 --- a/paddle/fluid/framework/details/fetch_op_handle.cc +++ b/paddle/fluid/framework/details/fetch_op_handle.cc @@ -49,7 +49,9 @@ void FetchOpHandle::RunImpl() { platform::DeviceContextPool::Instance().Get(platform::CPUPlace()); for (auto *input : inputs_) { auto *var = static_cast(input); - var->generated_op_->Wait(cpu_ctx); + if (var->generated_op_) { + var->generated_op_->Wait(cpu_ctx); + } } tensors_.resize(inputs_.size()); auto *var_handle = static_cast(inputs_[0]); diff --git a/paddle/fluid/framework/details/nccl_all_reduce_op_handle.cc b/paddle/fluid/framework/details/nccl_all_reduce_op_handle.cc index b055bb48f608c9fd9cc671d175cb463d25dc489b..16aa5d067ab7a222af8fbb6ca8ec18222ecd799b 100644 --- a/paddle/fluid/framework/details/nccl_all_reduce_op_handle.cc +++ b/paddle/fluid/framework/details/nccl_all_reduce_op_handle.cc @@ -36,7 +36,9 @@ void NCCLAllReduceOpHandle::RunImpl() { // Wait input done for (auto *in : inputs_) { auto &p = static_cast(in)->place_; - in->generated_op_->Wait(dev_ctxes_[p]); + if (in->generated_op_) { + in->generated_op_->Wait(dev_ctxes_[p]); + } } auto &var_name = static_cast(this->inputs_[0])->name_; diff --git a/paddle/fluid/framework/details/send_op_handle.cc b/paddle/fluid/framework/details/send_op_handle.cc index 0763f92171e7813ec0ee8ca4f3aa42b76205130a..bd97c5260dbba935e422793e0aa6aac8b6875627 100644 --- a/paddle/fluid/framework/details/send_op_handle.cc +++ b/paddle/fluid/framework/details/send_op_handle.cc @@ -32,7 +32,9 @@ void SendOpHandle::RunImpl() { if (in->DebugString() == "dummy") { // HACK continue; } - in->generated_op_->Wait(dev_ctxes_[p]); + if (in->generated_op_) { + in->generated_op_->Wait(dev_ctxes_[p]); + } } auto &tmp_scope = local_scope_->FindVar(kLocalExecScopeName)->Get(); // FIXME(wuyi): can not use RunAndRecordEvent here, for it will cause dead diff --git a/paddle/fluid/inference/CMakeLists.txt b/paddle/fluid/inference/CMakeLists.txt index 50f635a41a99b2ae292d13afde5637a3bf4e6f8c..b98aeed8a0aaabfd39560fad3c074a6668b4f024 100644 --- a/paddle/fluid/inference/CMakeLists.txt +++ b/paddle/fluid/inference/CMakeLists.txt @@ -20,7 +20,9 @@ if(NOT APPLE) endif() if(WITH_TESTING) + # both tests/book and analysis depends the models that generated by python/paddle/fluid/tests/book add_subdirectory(tests/book) + add_subdirectory(analysis) endif() if (TENSORRT_FOUND) diff --git a/paddle/fluid/inference/analysis/CMakeLists.txt b/paddle/fluid/inference/analysis/CMakeLists.txt new file mode 100644 index 0000000000000000000000000000000000000000..de7becae4d25d48111fea8d2123bc85aef70230a --- /dev/null +++ b/paddle/fluid/inference/analysis/CMakeLists.txt @@ -0,0 +1 @@ +cc_library(dot SRCS dot.cc) diff --git a/paddle/fluid/inference/analysis/dot.cc b/paddle/fluid/inference/analysis/dot.cc new file mode 100644 index 0000000000000000000000000000000000000000..d5471ffcb594a6915e9e65c0fee5adc5f5bdf40c --- /dev/null +++ b/paddle/fluid/inference/analysis/dot.cc @@ -0,0 +1,23 @@ +// 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/inference/analysis/dot.h" + +namespace paddle { +namespace inference { +namespace analysis { +size_t Dot::counter = 0; +} // namespace analysis +} // namespace inference +} // namespace paddle diff --git a/paddle/fluid/inference/analysis/dot.h b/paddle/fluid/inference/analysis/dot.h new file mode 100644 index 0000000000000000000000000000000000000000..3359987874f2d74d7e4646baa38790431c4b28fd --- /dev/null +++ b/paddle/fluid/inference/analysis/dot.h @@ -0,0 +1,154 @@ +// 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 implements some helper classes and methods for DOT programming + * support. It will give a visualization of the graph and that helps to debug + * the logics of each Pass. + */ +#pragma once + +#include +#include +#include +#include + +namespace paddle { +namespace inference { +namespace analysis { + +/* + * A Dot template that helps to build a DOT graph definition. + */ +class Dot { + public: + static size_t counter; + + struct Attr { + std::string key; + std::string value; + + Attr(const std::string& key, const std::string& value) + : key(key), value(value) {} + + std::string repr() const { + std::stringstream ss; + ss << key << "=" << '"' << value << '"'; + return ss.str(); + } + }; + + struct Node { + std::string name; + std::vector attrs; + + Node(const std::string& name, const std::vector& attrs) + : name(name), + attrs(attrs), + id_("node_" + std::to_string(Dot::counter++)) {} + + std::string id() const { return id_; } + + std::string repr() const { + std::stringstream ss; + CHECK(!name.empty()); + ss << id_; + for (size_t i = 0; i < attrs.size(); i++) { + if (i == 0) { + ss << "[label=" << '"' << name << '"' << " "; + } + ss << attrs[i].repr(); + ss << ((i < attrs.size() - 1) ? " " : "]"); + } + return ss.str(); + } + + private: + std::string id_; + }; + + struct Edge { + std::string source; + std::string target; + std::vector attrs; + + Edge(const std::string& source, const std::string& target, + const std::vector& attrs) + : source(source), target(target), attrs(attrs) {} + + std::string repr() const { + std::stringstream ss; + CHECK(!source.empty()); + CHECK(!target.empty()); + ss << source << "->" << target; + for (size_t i = 0; i < attrs.size(); i++) { + if (i == 0) { + ss << "["; + } + ss << attrs[i].repr(); + ss << ((i < attrs.size() - 1) ? " " : "]"); + } + return ss.str(); + } + }; + + Dot() = default; + + explicit Dot(const std::vector& attrs) : attrs_(attrs) {} + + void AddNode(const std::string& name, const std::vector& attrs) { + CHECK(!nodes_.count(name)) << "duplicate Node '" << name << "'"; + nodes_.emplace(name, Node{name, attrs}); + } + + void AddEdge(const std::string& source, const std::string& target, + const std::vector& attrs) { + CHECK(!source.empty()); + CHECK(!target.empty()); + auto sid = nodes_.at(source).id(); + auto tid = nodes_.at(target).id(); + edges_.emplace_back(sid, tid, attrs); + } + + // Compile to DOT language codes. + std::string Build() const { + std::stringstream ss; + const std::string indent = " "; + ss << "digraph G {" << '\n'; + + // Add graph attrs + for (const auto& attr : attrs_) { + ss << indent << attr.repr() << '\n'; + } + // add nodes + for (auto& item : nodes_) { + ss << indent << item.second.repr() << '\n'; + } + // add edges + for (auto& edge : edges_) { + ss << indent << edge.repr() << '\n'; + } + ss << "} // end G"; + return ss.str(); + } + + private: + std::unordered_map nodes_; + std::vector edges_; + std::vector attrs_; +}; + +} // namespace analysis +} // namespace inference +} // namespace paddle diff --git a/paddle/fluid/inference/engine.h b/paddle/fluid/inference/engine.h index 6b0ac92fa908427a89a6a5fa74dacc3b24abd1c3..de0375551e16ec53b90414c7446234fda98bf706 100644 --- a/paddle/fluid/inference/engine.h +++ b/paddle/fluid/inference/engine.h @@ -19,6 +19,9 @@ limitations under the License. */ namespace paddle { namespace inference { +struct Buffer; +enum class DeviceType { UNK = -1, CPU, GPU }; + /* * EngineBase is the base class of all inference engines. An inference engine * takes a paddle program as input, and outputs the result in fluid Tensor @@ -45,8 +48,20 @@ class EngineBase { // Execute the engine, that will run the inference network. virtual void Execute(int batch_size) = 0; + // Return the IO buffer that allocated in engine. One can read/write directly + // on the buffer. If the buffer's buffer is nullptr, one can also allocate + // memory and maintain it outside the engine. + virtual Buffer& buffer(const std::string& name) = 0; + virtual ~EngineBase() {} }; // class EngineBase +struct Buffer { + void* buffer{nullptr}; // buffer should be allocated only once. + int max_size; // buffer allocated space. + int size; // data size. + DeviceType device{DeviceType::UNK}; // tells which device this buffer is on. +}; + } // namespace inference } // namespace paddle diff --git a/paddle/fluid/inference/tensorrt/CMakeLists.txt b/paddle/fluid/inference/tensorrt/CMakeLists.txt index 288789d6e484100820c937e6081701f1e9245706..677b3e04af8e7f5662a15fb32e3b03f45d262733 100644 --- a/paddle/fluid/inference/tensorrt/CMakeLists.txt +++ b/paddle/fluid/inference/tensorrt/CMakeLists.txt @@ -1,4 +1,5 @@ +nv_library(tensorrt_engine SRCS engine.cc DEPS framework_proto) nv_test(test_tensorrt SRCS test_tensorrt.cc DEPS dynload_cuda device_context dynamic_loader) -nv_test(test_tensorrt_engine SRCS test_engine.cc engine.cc DEPS dynload_cuda) -set(ENGINE_FILE ${CMAKE_CURRENT_SOURCE_DIR}/engine.cc) +nv_test(test_tensorrt_engine SRCS test_engine.cc DEPS dynload_cuda tensorrt_engine) + add_subdirectory(convert) diff --git a/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt b/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt index 3c5909c0be1c690d5148ecfb32b1b6c2dd6f3211..5178c54c08400125d190078dac6c52d021f8488b 100644 --- a/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt +++ b/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt @@ -1,4 +1,4 @@ nv_test(test_op_converter SRCS test_op_converter.cc mul_op.cc conv2d_op.cc DEPS ${FLUID_CORE_MODULES}) -nv_test(test_trt_activation_op SRCS test_activation_op.cc ${ENGINE_FILE} activation_op.cc - DEPS ${FLUID_CORE_MODULES} activation_op) +nv_test(test_trt_activation_op SRCS test_activation_op.cc activation_op.cc + DEPS ${FLUID_CORE_MODULES} activation_op tensorrt_engine) nv_test(test_io_converter SRCS test_io_converter.cc io_converter.cc DEPS dynload_cuda dynamic_loader lod_tensor) diff --git a/paddle/fluid/inference/tensorrt/engine.cc b/paddle/fluid/inference/tensorrt/engine.cc index df123a59079acc5f549e733b412ab302aa397a92..1c296e33a610493b889359c43629003fd76b893c 100644 --- a/paddle/fluid/inference/tensorrt/engine.cc +++ b/paddle/fluid/inference/tensorrt/engine.cc @@ -30,16 +30,24 @@ void TensorRTEngine::Build(const DescType& paddle_model) { } void TensorRTEngine::Execute(int batch_size) { - infer_context_->enqueue(batch_size, buffers_.data(), *stream_, nullptr); + std::vector buffers; + for (auto& buf : buffers_) { + PADDLE_ENFORCE_NOT_NULL(buf.buffer, "buffer should be allocated"); + PADDLE_ENFORCE_GT(buf.max_size, 0); + PADDLE_ENFORCE(buf.device == DeviceType::GPU); + buffers.push_back(buf.buffer); + } + infer_context_->enqueue(batch_size, buffers.data(), *stream_, nullptr); cudaStreamSynchronize(*stream_); } TensorRTEngine::~TensorRTEngine() { // clean buffer - for (auto& buffer : buffers_) { - if (buffer != nullptr) { - PADDLE_ENFORCE_EQ(0, cudaFree(buffer)); - buffer = nullptr; + for (auto& buf : buffers_) { + if (buf.buffer != nullptr) { + PADDLE_ENFORCE_EQ(0, cudaFree(buf.buffer)); + buf.buffer = nullptr; + buf.max_size = 0; } } } @@ -59,7 +67,7 @@ void TensorRTEngine::FreezeNetwork() { infer_context_.reset(infer_engine_->createExecutionContext()); // allocate GPU buffers. - buffers_.resize(buffer_sizes_.size(), nullptr); + buffers_.resize(buffer_sizes_.size()); for (auto& item : buffer_sizes_) { if (item.second == 0) { auto slot_offset = infer_engine_->getBindingIndex(item.first.c_str()); @@ -67,7 +75,11 @@ void TensorRTEngine::FreezeNetwork() { infer_engine_->getBindingDataType(slot_offset))] * AccumDims(infer_engine_->getBindingDimensions(slot_offset)); } - PADDLE_ENFORCE_EQ(0, cudaMalloc(&buffer(item.first), item.second)); + auto& buf = buffer(item.first); + CHECK(buf.buffer == nullptr); // buffer should be allocated only once. + PADDLE_ENFORCE_EQ(0, cudaMalloc(&buf.buffer, item.second)); + buf.size = buf.max_size = item.second; + buf.device = DeviceType::GPU; } } @@ -113,7 +125,7 @@ void TensorRTEngine::DeclareOutput(const std::string& name) { } void* TensorRTEngine::GetOutputInGPU(const std::string& name) { - return buffer(name); + return buffer(name).buffer; } void TensorRTEngine::GetOutputInCPU(const std::string& name, void* dst, @@ -123,11 +135,13 @@ void TensorRTEngine::GetOutputInCPU(const std::string& name, void* dst, PADDLE_ENFORCE(it != buffer_sizes_.end()); PADDLE_ENFORCE_GT(it->second, 0); PADDLE_ENFORCE_GE(max_size, it->second); - PADDLE_ENFORCE_EQ(0, cudaMemcpyAsync(dst, buffer(name), it->second, + auto& buf = buffer(name); + PADDLE_ENFORCE_NOT_NULL(buf.buffer, "buffer should be allocated before"); + PADDLE_ENFORCE_EQ(0, cudaMemcpyAsync(dst, buf.buffer, it->second, cudaMemcpyDeviceToHost, *stream_)); } -void*& TensorRTEngine::buffer(const std::string& name) { +Buffer& TensorRTEngine::buffer(const std::string& name) { PADDLE_ENFORCE(infer_engine_ != nullptr, "call FreezeNetwork first."); auto it = buffer_sizes_.find(name); PADDLE_ENFORCE(it != buffer_sizes_.end()); @@ -137,10 +151,12 @@ void*& TensorRTEngine::buffer(const std::string& name) { void TensorRTEngine::SetInputFromCPU(const std::string& name, void* data, size_t size) { - void* buf = buffer(name); - cudaMemcpyAsync(buf, data, size, cudaMemcpyHostToDevice, *stream_); - PADDLE_ENFORCE_EQ( - 0, cudaMemcpyAsync(buf, data, size, cudaMemcpyHostToDevice, *stream_)); + auto& buf = buffer(name); + PADDLE_ENFORCE_NOT_NULL(buf.buffer); + PADDLE_ENFORCE_LE(size, buf.max_size, "buffer is too small"); + PADDLE_ENFORCE(buf.device == DeviceType::GPU); + PADDLE_ENFORCE_EQ(0, cudaMemcpyAsync(buf.buffer, data, size, + cudaMemcpyHostToDevice, *stream_)); } void TensorRTEngine::SetITensor(const std::string& name, diff --git a/paddle/fluid/inference/tensorrt/engine.h b/paddle/fluid/inference/tensorrt/engine.h index ec919b943d3281dd675b15e2f14adb7b3487f46f..b8298c6059e8644327194a1fcf7a7438cc9a7286 100644 --- a/paddle/fluid/inference/tensorrt/engine.h +++ b/paddle/fluid/inference/tensorrt/engine.h @@ -87,7 +87,9 @@ class TensorRTEngine : public EngineBase { // these memory directly for acceleration, for example, output the converted // data directly to the buffer to save data copy overhead. // NOTE this should be used after calling `FreezeNetwork`. - void*& buffer(const std::string& name); + Buffer& buffer(const std::string& name) override; + + cudaStream_t* stream() { return stream_; } // Fill an input from CPU memory with name and size. void SetInputFromCPU(const std::string& name, void* data, size_t size); @@ -116,7 +118,7 @@ class TensorRTEngine : public EngineBase { cudaStream_t* stream_; nvinfer1::ILogger& logger_; - std::vector buffers_; + std::vector buffers_; // max data size for the buffers. std::unordered_map buffer_sizes_; std::unordered_map diff --git a/paddle/fluid/inference/tensorrt/test_engine.cc b/paddle/fluid/inference/tensorrt/test_engine.cc index a08b78f930d30d674247a713fadd3e42e5ada350..69dbb9a3f2b92c97813f31e179a35a753bbb62d9 100644 --- a/paddle/fluid/inference/tensorrt/test_engine.cc +++ b/paddle/fluid/inference/tensorrt/test_engine.cc @@ -77,6 +77,37 @@ TEST_F(TensorRTEngineTest, add_layer) { ASSERT_EQ(y_cpu, x_v * 2 + 3); } +TEST_F(TensorRTEngineTest, add_layer_multi_dim) { + // Weight in CPU memory. + // It seems tensorrt FC use col-major: [[1.0, 3.3], [1.1, 4.4]] + // instead of row-major, which is [[1.0, 1.1], [3.3, 4.4]] + float raw_weight[4] = {1.0, 1.1, 3.3, 4.4}; + float raw_bias[2] = {1.3, 2.4}; + + TensorRTEngine::Weight weight(nvinfer1::DataType::kFLOAT, raw_weight, 4); + TensorRTEngine::Weight bias(nvinfer1::DataType::kFLOAT, raw_bias, 2); + auto* x = engine_->DeclareInput("x", nvinfer1::DataType::kFLOAT, + nvinfer1::DimsCHW{1, 2, 1}); + auto* fc_layer = TRT_ENGINE_ADD_LAYER(engine_, FullyConnected, *x, 2, + weight.get(), bias.get()); + PADDLE_ENFORCE(fc_layer != nullptr); + + engine_->DeclareOutput(fc_layer, 0, "y"); + engine_->FreezeNetwork(); + ASSERT_EQ(engine_->engine()->getNbBindings(), 2); + + float x_v[2] = {1.0, 2.0}; + engine_->SetInputFromCPU("x", reinterpret_cast(&x_v), + 2 * sizeof(float)); + engine_->Execute(1); + + LOG(INFO) << "to get output"; + float y_cpu[2] = {-1., -1.}; + engine_->GetOutputInCPU("y", &y_cpu[0], sizeof(float) * 2); + ASSERT_EQ(y_cpu[0], 4.5); + ASSERT_EQ(y_cpu[1], 14.5); +} + } // namespace tensorrt } // namespace inference } // namespace paddle diff --git a/paddle/fluid/inference/tests/book/CMakeLists.txt b/paddle/fluid/inference/tests/book/CMakeLists.txt index cc179a86256e6b552c08a091402157bdcc86b383..dbb81462b8273bd701e9c9f530eaf69817abd6a1 100644 --- a/paddle/fluid/inference/tests/book/CMakeLists.txt +++ b/paddle/fluid/inference/tests/book/CMakeLists.txt @@ -36,5 +36,5 @@ inference_test(label_semantic_roles) inference_test(recognize_digits ARGS mlp conv) inference_test(recommender_system) #inference_test(rnn_encoder_decoder) -inference_test(understand_sentiment ARGS conv) +#inference_test(understand_sentiment ARGS conv) inference_test(word2vec) diff --git a/paddle/fluid/operators/conv_op.h b/paddle/fluid/operators/conv_op.h index c51898abb422663a6731a17e0717c62ebf0701f8..f462f00c0803c12ee2f2b0f94dc90afdca500da3 100644 --- a/paddle/fluid/operators/conv_op.h +++ b/paddle/fluid/operators/conv_op.h @@ -187,7 +187,8 @@ class GemmConvKernel : public framework::OpKernel { // gemm Tensor out_slice = out_batch.Slice(g * out_step, (g + 1) * out_step); Tensor filter_slice = filter.Slice(g * out_step, (g + 1) * out_step); - blas.MatMul(filter_slice, col_matrix, &out_slice); + blas.MatMul(filter_slice, false, col_matrix, false, T(1.0), &out_slice, + T(0.0)); } } } @@ -304,7 +305,8 @@ class GemmConvGradKernel : public framework::OpKernel { col_matrix.ShareDataWith(in_grad_slice); col_matrix.Resize(col_matrix_shape); } - blas.MatMul(filter_slice, true, out_grad_slice, false, &col_matrix); + blas.MatMul(filter_slice, true, out_grad_slice, false, T(1.0), + &col_matrix, T(0.0)); if (is_expand && data_dim == 2U) { col2im(dev_ctx, col, dilations, strides, @@ -351,8 +353,8 @@ class GemmConvGradKernel : public framework::OpKernel { // gemm Tensor filter_grad_slice = filter_grad_.Slice(g * out_step, (g + 1) * out_step); - blas.MatMul(out_grad_slice, false, col_matrix, true, - &filter_grad_slice); + blas.MatMul(out_grad_slice, false, col_matrix, true, T(1.0), + &filter_grad_slice, T(1.0)); } } } diff --git a/paddle/fluid/operators/conv_transpose_op.h b/paddle/fluid/operators/conv_transpose_op.h index 9276e5bfef71a58741c2dfa25b31c2bd07c309b8..898121412b17cd6fbbbeb57e9d63842e592703ac 100644 --- a/paddle/fluid/operators/conv_transpose_op.h +++ b/paddle/fluid/operators/conv_transpose_op.h @@ -135,7 +135,8 @@ class GemmConvTransposeKernel : public framework::OpKernel { // col_matrix = filter * input_batch // of shape (c * k_h * k_w, h * w) or (c * k_d * k_h * k_w, d * h * w) - blas.MatMul(filter, true, input_batch, false, &col_matrix); + blas.MatMul(filter, true, input_batch, false, static_cast(1.0), + &col_matrix, static_cast(0.0)); if (data_dim == 2U) { // col2im: col_matrix -> dy @@ -267,7 +268,8 @@ class GemmConvTransposeGradKernel : public framework::OpKernel { // or // (m, c * k_d * k_h * k_w) * (c * k_d * k_h * k_w, d * h * w) -> (m, // d, h, w) - blas.MatMul(filter, false, col_matrix, false, &input_grad_batch); + blas.MatMul(filter, false, col_matrix, false, static_cast(1.0), + &input_grad_batch, static_cast(0.0)); } if (filter_grad) { // input batch @@ -277,7 +279,8 @@ class GemmConvTransposeGradKernel : public framework::OpKernel { // or // (m, d * h * w) * (d * h * w, c * k_d * k_h * k_w) -> (m, c * k_d * // k_h * k_w) - blas.MatMul(in_batch, false, col_matrix, true, &filter_grad_); + blas.MatMul(in_batch, false, col_matrix, true, static_cast(1.0), + &filter_grad_, static_cast(1.0)); } } } diff --git a/paddle/fluid/operators/load_op.cc b/paddle/fluid/operators/load_op.cc index 6ffe0bec5e38432676ecadfa1abbbe70a1425bb1..c6bd2bf3dfca77dc078eb04b1d90c7d90883203f 100644 --- a/paddle/fluid/operators/load_op.cc +++ b/paddle/fluid/operators/load_op.cc @@ -46,19 +46,6 @@ class LoadOp : public framework::OperatorBase { auto *tensor = out_var->GetMutable(); DeserializeFromStream(fin, tensor, *dev_ctx); - - if (platform::is_gpu_place(place)) { - // copy CPU to GPU - framework::LoDTensor cpu_tensor; - cpu_tensor.ShareDataWith(*tensor); - cpu_tensor.set_lod(tensor->lod()); - - // reset tensor - out_var->Clear(); - tensor = out_var->GetMutable(); - tensor->set_lod(cpu_tensor.lod()); - TensorCopy(cpu_tensor, place, *dev_ctx, tensor); - } } }; diff --git a/paddle/fluid/platform/cuda_device_function.h b/paddle/fluid/platform/cuda_device_function.h index e81c385727be5c2ba3f02bfbd86168cb4650dfda..ecec4178f2d9937920e52eb74bf9068b84e741a0 100644 --- a/paddle/fluid/platform/cuda_device_function.h +++ b/paddle/fluid/platform/cuda_device_function.h @@ -63,6 +63,7 @@ __device__ T reduceSum(T val, int tid, int len) { val += platform::CudaShuffleDownSync(mask, val, offset); if (tid < warpSize) shm[tid] = 0; + __syncthreads(); if (tid % warpSize == 0) { shm[tid / warpSize] = val; diff --git a/paddle/fluid/platform/profiler.cc b/paddle/fluid/platform/profiler.cc index cfddd8e8711f8005e0eff7ef7a2980f535b2f851..50bc0aba6aa0f056dc0b2d49f6b3b745433e0756 100644 --- a/paddle/fluid/platform/profiler.cc +++ b/paddle/fluid/platform/profiler.cc @@ -463,7 +463,7 @@ void SetProfileListener() { std::mt19937 rng; rng.seed(std::random_device()()); std::uniform_int_distribution dist6( - 1, std::numeric_limits::max()); + 1, std::numeric_limits::max()); profiler_lister_id = dist6(rng); } int64_t ListenerId() { return profiler_lister_id; } diff --git a/paddle/scripts/paddle_build.sh b/paddle/scripts/paddle_build.sh index 1595cc9e8aad4d143ca62f84f812dbc791dc1d26..c9b49adef7061d2cfa504258cfc589346c27e192 100755 --- a/paddle/scripts/paddle_build.sh +++ b/paddle/scripts/paddle_build.sh @@ -398,7 +398,7 @@ function gen_dockerfile() { cat <> /paddle/build/Dockerfile <> ${PADDLE_ROOT}/build/Dockerfile <> ${PADDLE_ROOT}/build/Dockerfile <> ${PADDLE_ROOT}/build/Dockerfile < Variable(learning_rate) self._learning_rate_map = dict() @@ -77,7 +79,7 @@ class Optimizer(object): name=unique_name.generate("learning_rate"), shape=[1], value=float(self._learning_rate), - dtype='float32', + dtype='float32' if self._dtype == None else self._dtype, persistable=True) def global_learning_rate(self, program=None): @@ -200,6 +202,7 @@ class Optimizer(object): # Create any accumulators program = loss.block.program + self._dtype = loss.dtype with program_guard(program, startup_program): global_block = framework.default_main_program().global_block() start = len(global_block.ops) @@ -391,7 +394,7 @@ class AdamOptimizer(Optimizer): beta_shape = [1] self._beta1_pow_acc = self.helper.create_global_variable( name=unique_name.generate('beta1_pow_acc'), - dtype='float32', + dtype='float32' if self._dtype == None else self._dtype, shape=beta_shape, lod_level=0, persistable=True) @@ -400,7 +403,7 @@ class AdamOptimizer(Optimizer): self._beta2_pow_acc = self.helper.create_global_variable( name=unique_name.generate('beta2_pow_acc'), - dtype='float32', + dtype='float32' if self._dtype == None else self._dtype, shape=beta_shape, lod_level=0, persistable=True) @@ -493,7 +496,7 @@ class AdamaxOptimizer(Optimizer): beta_shape = [1] self._beta1_pow_acc = self.helper.create_global_variable( name=unique_name.generate('beta1_pow_acc'), - dtype='float32', + dtype='float32' if self._dtype == None else self._dtype, shape=beta_shape, lod_level=0, persistable=True) @@ -900,8 +903,10 @@ class ModelAverage(Optimizer): # param = (sum_1 + sum_2 + sum_3) / (num_accumulates + old_num_accumulates) tmp = layers.sum(x=[num_accumulates, old_num_accumulates]) sum = layers.sum(x=[sum_1, sum_2, sum_3]) - tmp = layers.cast(x=tmp, dtype='float32') - sum = layers.cast(x=sum, dtype='float32') + tmp = layers.cast( + x=tmp, dtype='float32' if self._dtype == None else self._dtype) + sum = layers.cast( + x=sum, dtype='float32' if self._dtype == None else self._dtype) layers.elementwise_div(x=sum, y=tmp, out=param) def _add_average_restore_op(self, block, param_grad): diff --git a/python/paddle/fluid/tests/book/image_classification/notest_image_classification_resnet.py b/python/paddle/fluid/tests/book/high-level-api/image_classification/notest_image_classification_resnet.py similarity index 100% rename from python/paddle/fluid/tests/book/image_classification/notest_image_classification_resnet.py rename to python/paddle/fluid/tests/book/high-level-api/image_classification/notest_image_classification_resnet.py diff --git a/python/paddle/fluid/tests/book/image_classification/notest_image_classification_vgg.py b/python/paddle/fluid/tests/book/high-level-api/image_classification/notest_image_classification_vgg.py similarity index 100% rename from python/paddle/fluid/tests/book/image_classification/notest_image_classification_vgg.py rename to python/paddle/fluid/tests/book/high-level-api/image_classification/notest_image_classification_vgg.py diff --git a/python/paddle/fluid/tests/book/label_semantic_roles/no_test_label_semantic_roles.py b/python/paddle/fluid/tests/book/high-level-api/label_semantic_roles/no_test_label_semantic_roles.py similarity index 100% rename from python/paddle/fluid/tests/book/label_semantic_roles/no_test_label_semantic_roles.py rename to python/paddle/fluid/tests/book/high-level-api/label_semantic_roles/no_test_label_semantic_roles.py diff --git a/python/paddle/fluid/tests/book/notest_recognize_digits/notest_recognize_digits_conv.py b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/notest_recognize_digits_conv.py similarity index 100% rename from python/paddle/fluid/tests/book/notest_recognize_digits/notest_recognize_digits_conv.py rename to python/paddle/fluid/tests/book/high-level-api/recognize_digits/notest_recognize_digits_conv.py diff --git a/python/paddle/fluid/tests/book/notest_recognize_digits/notest_recognize_digits_mlp.py b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/notest_recognize_digits_mlp.py similarity index 100% rename from python/paddle/fluid/tests/book/notest_recognize_digits/notest_recognize_digits_mlp.py rename to python/paddle/fluid/tests/book/high-level-api/recognize_digits/notest_recognize_digits_mlp.py diff --git a/python/paddle/fluid/tests/book/understand_sentiment/notest_understand_sentiment_stacked_lstm.py b/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/notest_understand_sentiment_stacked_lstm.py similarity index 100% rename from python/paddle/fluid/tests/book/understand_sentiment/notest_understand_sentiment_stacked_lstm.py rename to python/paddle/fluid/tests/book/high-level-api/understand_sentiment/notest_understand_sentiment_stacked_lstm.py diff --git a/python/paddle/fluid/tests/book/word2vec/no_test_word2vec_new_api.py b/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py similarity index 100% rename from python/paddle/fluid/tests/book/word2vec/no_test_word2vec_new_api.py rename to python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py diff --git a/python/paddle/fluid/tests/book/test_understand_sentiment.py b/python/paddle/fluid/tests/book/notest_understand_sentiment.py similarity index 100% rename from python/paddle/fluid/tests/book/test_understand_sentiment.py rename to python/paddle/fluid/tests/book/notest_understand_sentiment.py diff --git a/python/paddle/fluid/tests/book/test_label_semantic_roles.py b/python/paddle/fluid/tests/book/test_label_semantic_roles.py index 50ef29c4572f1b12fe9793bbf037cd7fe71a9e53..0faba33032d5dfc0b751a5191e7b2ae0c1f172bf 100644 --- a/python/paddle/fluid/tests/book/test_label_semantic_roles.py +++ b/python/paddle/fluid/tests/book/test_label_semantic_roles.py @@ -36,7 +36,7 @@ depth = 8 mix_hidden_lr = 1e-3 IS_SPARSE = True -PASS_NUM = 100 +PASS_NUM = 10 BATCH_SIZE = 10 embedding_name = 'emb' diff --git a/python/paddle/fluid/tests/unittests/test_memory_optimization_transpiler.py b/python/paddle/fluid/tests/unittests/test_memory_optimization_transpiler.py index f3dcca6b0107a9c4a6efcb0c0fd50324aaf92648..cfd6e63e12258a92447e68b4afbc7ead91b68cc1 100644 --- a/python/paddle/fluid/tests/unittests/test_memory_optimization_transpiler.py +++ b/python/paddle/fluid/tests/unittests/test_memory_optimization_transpiler.py @@ -18,7 +18,7 @@ import unittest import paddle.fluid.layers as layers import paddle.fluid.optimizer as optimizer from paddle.fluid.framework import Program, program_guard -from paddle.fluid.memory_optimization_transpiler import memory_optimize +from paddle.fluid.transpiler import memory_optimize class TestControlFlowGraph(unittest.TestCase): diff --git a/python/paddle/fluid/tests/unittests/test_network_with_dtype.py b/python/paddle/fluid/tests/unittests/test_network_with_dtype.py new file mode 100644 index 0000000000000000000000000000000000000000..baafcdbb80238385752183ee0a8ff96a5da4659c --- /dev/null +++ b/python/paddle/fluid/tests/unittests/test_network_with_dtype.py @@ -0,0 +1,74 @@ +# 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 +import paddle.fluid as fluid +import paddle.fluid.core as core +from paddle.fluid.executor import Executor + +BATCH_SIZE = 20 + + +class TestNetWithDtype(unittest.TestCase): + def setUp(self): + self.dtype = "float64" + self.init_dtype() + self.x = fluid.layers.data(name='x', shape=[13], dtype=self.dtype) + self.y = fluid.layers.data(name='y', shape=[1], dtype=self.dtype) + y_predict = fluid.layers.fc(input=self.x, size=1, act=None) + + cost = fluid.layers.square_error_cost(input=y_predict, label=self.y) + avg_cost = fluid.layers.mean(cost) + self.fetch_list = [avg_cost] + + sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.001) + sgd_optimizer.minimize(avg_cost) + + def run_net_on_place(self, place): + train_reader = paddle.batch( + paddle.dataset.uci_housing.train(), batch_size=BATCH_SIZE) + feeder = fluid.DataFeeder(place=place, feed_list=[self.x, self.y]) + exe = fluid.Executor(place) + exe.run(fluid.default_startup_program()) + for data in train_reader(): + exe.run(fluid.default_main_program(), + feed=feeder.feed(data), + fetch_list=self.fetch_list) + # the main program is runable, the datatype is fully supported + break + + def init_dtype(self): + pass + + def test_cpu(self): + place = fluid.CPUPlace() + self.run_net_on_place(place) + + def test_gpu(self): + if not core.is_compiled_with_cuda(): + return + place = fluid.CUDAPlace(0) + self.run_net_on_place(place) + + +# TODO(dzhwinter): make sure the fp16 is runable +# class TestFloat16(SimpleNet): +# def init_dtype(self): +# self.dtype = "float16" + +if __name__ == '__main__': + unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor.py b/python/paddle/fluid/tests/unittests/test_parallel_executor.py index 9056f5e66fceb42397c9a923d802320dd772725b..4eb25a6e00b7564ac17db568ec78c1c84933af43 100644 --- a/python/paddle/fluid/tests/unittests/test_parallel_executor.py +++ b/python/paddle/fluid/tests/unittests/test_parallel_executor.py @@ -12,7 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. -import numpy +import numpy as np import unittest import paddle.fluid as fluid @@ -243,7 +243,7 @@ class TestParallelExecutorBase(unittest.TestCase): begin = time.time() first_loss, = run_executor( exe=exe, feed=feed_dict, fetch_list=[loss.name]) - first_loss = numpy.array(first_loss) + first_loss = np.array(first_loss) for i in xrange(iter): run_executor(exe=exe, feed=feed_dict, fetch_list=[]) @@ -256,7 +256,7 @@ class TestParallelExecutorBase(unittest.TestCase): print "%.4f Instance per second" % ( (batch_size * iter + 2) / (end - begin)) - last_loss = numpy.array(last_loss) + last_loss = np.array(last_loss) print first_loss, last_loss # self.assertGreater(first_loss[0], last_loss[0]) @@ -284,8 +284,8 @@ class TestMNIST(TestParallelExecutorBase): self.check_network_convergence(simple_fc_net) self.check_network_convergence(simple_fc_net, allow_op_delay=True) - img = numpy.zeros(shape=[32, 784], dtype='float32') - label = numpy.ones(shape=[32, 1], dtype='int64') + img = np.zeros(shape=[32, 784], dtype='float32') + label = np.ones(shape=[32, 1], dtype='int64') self.check_network_convergence( simple_fc_net, feed_dict={"image": img, "label": label}) @@ -294,8 +294,8 @@ class TestMNIST(TestParallelExecutorBase): self.check_simple_fc_convergence() def check_simple_fc_parallel_accuracy(self): - img = numpy.zeros(shape=[32, 784], dtype='float32') - label = numpy.ones(shape=[32, 1], dtype='int64') + img = np.zeros(shape=[32, 784], dtype='float32') + label = np.ones(shape=[32, 1], dtype='int64') single_first_loss, single_last_loss = self.check_network_convergence( method=simple_fc_net, seed=1000, @@ -319,8 +319,8 @@ class TestMNIST(TestParallelExecutorBase): def check_batchnorm_fc_convergence(self): self.check_network_convergence(fc_with_batchnorm) - img = numpy.zeros(shape=[32, 784], dtype='float32') - label = numpy.ones(shape=[32, 1], dtype='int64') + img = np.zeros(shape=[32, 784], dtype='float32') + label = np.ones(shape=[32, 1], dtype='int64') self.check_network_convergence( fc_with_batchnorm, feed_dict={"image": img, "label": label}) @@ -404,9 +404,6 @@ class ModelHyperParams(object): dropout = 0.1 -import numpy as np - - def prepare_batch_input(insts, src_pad_idx, trg_pad_idx, n_head): """ Pad the instances to the max sequence length in batch, and generate the @@ -533,9 +530,8 @@ class ParallelExecutorTestingDuringTraining(unittest.TestCase): opt.minimize(loss) batch_size = 32 - image = numpy.random.normal(size=(batch_size, - 784)).astype('float32') - label = numpy.random.randint(0, 10, (batch_size, 1), dtype="int64") + image = np.random.normal(size=(batch_size, 784)).astype('float32') + label = np.random.randint(0, 10, (batch_size, 1), dtype="int64") place = fluid.CUDAPlace(0) exe = fluid.Executor(place) @@ -552,12 +548,12 @@ class ParallelExecutorTestingDuringTraining(unittest.TestCase): for i in xrange(5): test_loss, = test_exe.run([loss.name], feed=feed_dict) - test_loss = numpy.array(test_loss) + test_loss = np.array(test_loss) train_loss, = train_exe.run([loss.name], feed=feed_dict) - train_loss = numpy.array(train_loss) + train_loss = np.array(train_loss) self.assertTrue( - numpy.allclose( + np.allclose( train_loss, test_loss, atol=1e-8), "Train loss: " + str(train_loss) + "\n Test loss:" + str(test_loss)) @@ -712,7 +708,7 @@ class TestCRFModel(unittest.TestCase): data = train_data() for i in xrange(10): cur_batch = next(data) - print map(numpy.array, + print map(np.array, pe.run(feed=feeder.feed(cur_batch), fetch_list=[avg_cost.name]))[0] @@ -721,3 +717,84 @@ class TestCRFModel(unittest.TestCase): def test_update_dense_parameter(self): self.check_network_convergence(is_sparse=False) + + +# test fetch all the variables of global_block + +import paddle.dataset.flowers as flowers +import math + + +def Lenet(data, class_dim): + conv1 = fluid.layers.conv2d(data, 32, 5, 1, act=None) + bn1 = fluid.layers.batch_norm(conv1, act='relu') + pool1 = fluid.layers.pool2d(bn1, 2, 'max', 2) + conv2 = fluid.layers.conv2d(pool1, 50, 5, 1, act=None) + bn2 = fluid.layers.batch_norm(conv2, act='relu') + pool2 = fluid.layers.pool2d(bn2, 2, 'max', 2) + + fc1 = fluid.layers.fc(pool2, size=500, act='relu') + fc2 = fluid.layers.fc(fc1, size=class_dim, act='softmax') + + return fc2 + + +class TestFetchOp(unittest.TestCase): + def parallel_exe(self, train_inputs, seed): + main = fluid.Program() + startup = fluid.Program() + startup.random_seed = seed + with fluid.program_guard(main, startup): + data = fluid.layers.data( + name='image', shape=[3, 224, 224], dtype='float32') + label = fluid.layers.data(name='label', shape=[1], dtype='int64') + out = Lenet(data, class_dim=102) + loss = fluid.layers.cross_entropy(input=out, label=label) + loss = fluid.layers.mean(loss) + + opt = fluid.optimizer.Momentum( + learning_rate=0.1, + momentum=0.9, + regularization=fluid.regularizer.L2Decay(1e-4)) + + opt.minimize(loss) + + # TODO(zcd): I found that onece the memory optimizer is open, + # parallel_exe doesn't fetch some variable, such as conv2d_0.b_0@GRAD, + # conv2d_1.b_0@GRAD. Those variables should not be pruned. + # fluid.memory_optimize(main) + + place = fluid.CUDAPlace(0) + exe = fluid.Executor(place) + exe.run(startup) + + feeder = fluid.DataFeeder(place=place, feed_list=[data, label]) + pe = fluid.ParallelExecutor( + use_cuda=True, loss_name=loss.name, main_program=main) + + fetch_list = [] + all_vars = main.global_block().vars + for k, v in all_vars.iteritems(): + if 'tmp' not in k and k[0] is not '_' or v.persistable: + fetch_list.append(k) + + for data in train_inputs: + ret = pe.run(fetch_list, feed=feeder.feed(data)) + for i in range(len(fetch_list)): + assert not math.isnan(np.sum(ret[i])) and \ + not math.isinf(np.sum(ret[i])) + + def test_update_sparse_parameter(self): + tst_reader = paddle.batch(flowers.test(use_xmap=False), batch_size=16) + tst_reader_iter = tst_reader() + + iters = 3 + train_inputs = [] + for i in range(iters): + train_inputs.append(tst_reader_iter.next()) + + self.parallel_exe(train_inputs, seed=1) + + +if __name__ == '__main__': + unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_split_var.py b/python/paddle/fluid/tests/unittests/test_split_var.py index 104ceb4fe7beb70b9016f57cef0ef895a3eb8ba6..79d387f0066672058d1640f4e5fd28ed8913fe4c 100644 --- a/python/paddle/fluid/tests/unittests/test_split_var.py +++ b/python/paddle/fluid/tests/unittests/test_split_var.py @@ -14,7 +14,7 @@ import math import unittest -from paddle.fluid.distribute_transpiler import split_dense_variable +from paddle.fluid.transpiler.distribute_transpiler import split_dense_variable import paddle.fluid as fluid import paddle.fluid.core as core import random diff --git a/tools/aws_benchmarking/server/cluster_master.py b/tools/aws_benchmarking/server/cluster_master.py index 1333a942bf013a8182585b56e5843803c56945b1..a9b24846544d8aca5e4c7bd5709e70564c088431 100644 --- a/tools/aws_benchmarking/server/cluster_master.py +++ b/tools/aws_benchmarking/server/cluster_master.py @@ -20,6 +20,7 @@ import time import threading import logging import copy +import csv import netaddr import boto3 @@ -136,6 +137,12 @@ parser.add_argument( parser.add_argument( '--master_server_ip', type=str, default="", help="master server private ip") +parser.add_argument( + '--metric_data_identifier', + type=str, + default="**metrics_data: ", + help="key string to identify metrics data") + parser.add_argument( '--no_clean_up', type=str2bool, @@ -155,6 +162,11 @@ logging.basicConfig( log_files = ["master.log"] +metrics = {} + +metrics_csv_file_name = "metrics.csv" +is_metrics_file_created = False + def create_subnet(): # if no vpc id provided, list vpcs @@ -329,12 +341,42 @@ def create_pservers(): cleanup(args.task_name) +def save_metrics_data(str_msg): + #parse msg + logging.info("found metrics data, saving it to csv file") + global is_metrics_file_created + metrics_raw = str_msg.split(",") + with open(args.log_path + metrics_csv_file_name, 'a') as csvfile: + csv_fieldnames = [] + csv_write_data = {} + for metric in metrics_raw: + metric_data = metric.split("=") + metric_key = metric_data[0].strip() + metric_val = float(metric_data[1].strip()) + if not metric_key in metrics: + metrics[metric_key] = [] + metric_repo = metrics[metric_key] + metric_repo.append(metric_val) + csv_fieldnames.append(metric_key) + csv_write_data[metric_key] = metric_val + writer = csv.DictWriter(csvfile, fieldnames=csv_fieldnames) + if not is_metrics_file_created: + writer.writeheader() + is_metrics_file_created = True + writer.writerow(csv_write_data) + logging.info("csv file appended") + + def log_to_file(source, filename): if not filename in log_files: log_files.append(filename) with open(args.log_path + filename, "a") as log_file: for line in iter(source.readline, ""): log_file.write(line) + if (line.startswith(args.metric_data_identifier)): + #found key data, trying to add to csv + line = line.replace(args.metric_data_identifier, "") + save_metrics_data(line) def parse_command(command_raw, defaults={}):