From 3b3981565eec50aeb101b31916f568ac1bc94683 Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Tue, 27 Mar 2018 22:07:15 +0800 Subject: [PATCH 01/69] mpi enabled design doc --- .../design/dist_train/mpi_enabled_design.md | 56 +++++++++++++++++++ paddle/fluid/operators/detail/mpi_utils.cpp | 4 ++ paddle/fluid/operators/detail/mpi_utils.h | 8 +++ 3 files changed, 68 insertions(+) create mode 100644 doc/fluid/design/dist_train/mpi_enabled_design.md create mode 100644 paddle/fluid/operators/detail/mpi_utils.cpp create mode 100644 paddle/fluid/operators/detail/mpi_utils.h diff --git a/doc/fluid/design/dist_train/mpi_enabled_design.md b/doc/fluid/design/dist_train/mpi_enabled_design.md new file mode 100644 index 0000000000..19f4298d71 --- /dev/null +++ b/doc/fluid/design/dist_train/mpi_enabled_design.md @@ -0,0 +1,56 @@ +#MPI-enabled PaddlePaddle Design doc +## Overview +We will introduce Open MPI API to PaddlePaddle, which can bring two benefits to PaddlePaddle: +1. Enable RDMA with PaddlePaddle, which bring high performance low latency networks. +2. Enable GPUDriect with PaddlePaddle, which bring highest throughput and lowest latency GPU read and write. + +## Global Config +Launch the script using the 'mpirun' launcher, For example: ```mpirun -np 3 -hosts node1,node2,node3 python train.py```. By doing this, We can number the actors (trainer/pserver/master) whith o .. (n-1). The actor's number is the Rank of the calling process in group of comm (integer), The MPI processes identify each other using an Rank ID. We have to create a mapping between PaddlePaddle's actors and there Rank ID, so that we can communicate with the correct destinations when using MPI operations. + **We have to store the Rank ID and the mapping in global variables.** + +#Utils +We will build mpi_send_recv_utils Class to unify package interface about MPI Send and Receive. +```c++ +#mpi send and receive utils +class Mpi_ISend { + +} +class Mpi_IRecv { + +} + +class MPIUtils { + public: + const int GetRankID(const std::string& task_id); + void InitMPI(); + private: + std::map name_to_id_; +} + +``` +```c++ +class MPIServer { + public: + SetCond(); + ShutDown(); + WaitClientGet(); + reset(); + Push(); + SetScope(); + SetDevCtx(); + get(); +} +``` + +## New OP +We won't replace all the gRPC requests to MPI requests, the standard gRPC library is used for all administrative operations and the MPI API will used to transfer tensor or selectRows to Pservers. Base of this idea, we create two new operators to handle requests and receives, the two operators are send_mpi_op and listenandserve_mpi_op. They are a little similar with [send_op](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/fluid/operators/send_op.cc) and [listen_and_serv_op](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/fluid/operators/listen_and_serv_op.cc). + +### send_mpi_op +vary similar with send_op, we will replace grpc with mpi send service. +### listenandserve_mpi_op +vary similar with listen_and_serv_op, we will replace grpc with mpi receive service. +## Build args +Beause MPI or CUDA need hardware supported, so we will add some build args to control compiling. +**The specific arguments is under design** +## Execute args +Launch the script using the 'mpirun' launcher, For example: ```mpirun -np 3 -hosts node1,node2,node3 python train.py```. \ No newline at end of file diff --git a/paddle/fluid/operators/detail/mpi_utils.cpp b/paddle/fluid/operators/detail/mpi_utils.cpp new file mode 100644 index 0000000000..adf4a3b925 --- /dev/null +++ b/paddle/fluid/operators/detail/mpi_utils.cpp @@ -0,0 +1,4 @@ +// +// Created by tangwei12 on 2018/3/27. +// + diff --git a/paddle/fluid/operators/detail/mpi_utils.h b/paddle/fluid/operators/detail/mpi_utils.h new file mode 100644 index 0000000000..fb2f141246 --- /dev/null +++ b/paddle/fluid/operators/detail/mpi_utils.h @@ -0,0 +1,8 @@ +// +// Created by tangwei12 on 2018/3/27. +// + +#ifndef PADDLE_MPI_UTILS_H +#define PADDLE_MPI_UTILS_H + +#endif //PADDLE_MPI_UTILS_H From b1adcd4641831f6f8e2d52ba439490487b8da5aa Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Tue, 27 Mar 2018 22:07:59 +0800 Subject: [PATCH 02/69] mpi sever code --- paddle/fluid/operators/detail/mpi_client.h | 53 +++++++++++++++++++ paddle/fluid/operators/detail/mpi_server.h | 23 ++++++++ paddle/fluid/operators/detail/mpi_utils.cpp | 44 ++++++++++++++++ paddle/fluid/operators/detail/mpi_utils.h | 58 ++++++++++++++++++--- 4 files changed, 172 insertions(+), 6 deletions(-) create mode 100644 paddle/fluid/operators/detail/mpi_client.h create mode 100644 paddle/fluid/operators/detail/mpi_server.h diff --git a/paddle/fluid/operators/detail/mpi_client.h b/paddle/fluid/operators/detail/mpi_client.h new file mode 100644 index 0000000000..14dcd678a0 --- /dev/null +++ b/paddle/fluid/operators/detail/mpi_client.h @@ -0,0 +1,53 @@ + +/* 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 "paddle/fluid/framework/data_type.h" +#include "paddle/fluid/framework/lod_tensor.h" +#include "paddle/fluid/framework/scope.h" +#include "paddle/fluid/framework/selected_rows.h" + +namespace paddle { +namespace operators { +namespace detail { +class MPIClient { + public: + bool AsyncSendVariable(const std::string& ep, + const platform::DeviceContext& ctx, + const framework::Scope& scope, + const std::string& var_name, + int64_t time_out = 600 * 1000); + + bool AsyncGetVariable(const std::string& ep, + const platform::DeviceContext& ctx, + const framework::Scope& scope, + const std::string& var_name, + int64_t time_out = 600 * 1000); + + void AsyncSendBatchBarrier(const std::string& ep, + int64_t time_out = 600 * 1000); + + void AsyncSendFetchBarrier(const std::string& ep, + int64_t time_out = 600 * 1000); + bool Wait(); + + private: + int64_t req_count_ = 0; +}; +} // namespace detail +} // namespace operators +} // namespace paddle diff --git a/paddle/fluid/operators/detail/mpi_server.h b/paddle/fluid/operators/detail/mpi_server.h new file mode 100644 index 0000000000..dda99318af --- /dev/null +++ b/paddle/fluid/operators/detail/mpi_server.h @@ -0,0 +1,23 @@ + +/* 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 +namespace paddle { +namespace operators { +namespace detail { +class MPIServer { + public: + private: +}; +} // namespace detail +} // namespace operators +} // namespace paddle diff --git a/paddle/fluid/operators/detail/mpi_utils.cpp b/paddle/fluid/operators/detail/mpi_utils.cpp index adf4a3b925..6560761e6b 100644 --- a/paddle/fluid/operators/detail/mpi_utils.cpp +++ b/paddle/fluid/operators/detail/mpi_utils.cpp @@ -2,3 +2,47 @@ // Created by tangwei12 on 2018/3/27. // +#include + +#include "paddle/fluid/operators/detail/mpi_utils.h" + +#define max_worker_name_length 128 + +namespace paddle { +namespace operators { +namespace detail { +MPIUtils::MPIUtils(const std::string& worker_name) { + InitMPI(); + + int rank = 0, size = 1; + char my_name[max_work_group_size]; + MPI_Comm_rank(MPI_COMM_WORLD, &rank); + MPI_Comm_size(MPI_COMM_WORLD, &size); + snprintf(my_name, max_worker_name_length, worker_name.c_str()); + + std::vector worker_names(size * max_worker_name_length); + MPI_Allgather(my_name, max_worker_name_length, MPI_CHAR, &worker_names[0], + max_worker_name_length, MPI_CHAR, MPI_COMM_WORLD); + for (int i = 0; i < number_of_procs; i++) { + name_to_id_[std::string(&worker_names[i * 128])] = i; + } +} + +void MPIUtils::InitMPI() { + int flag = 0; + MPI_CHECK(MPI_Initialized(&flag)); + + if (!flag) { + int rank = 0, size = 1, len = -1; + char host_name[max_worker_name_length]; + + MPI_Init(0, 0); + MPI_Comm_rank(MPI_COMM_WORLD, &rank); + MPI_Comm_size(MPI_COMM_WORLD, &size); + MPI_Get_processor_name(host_name, &len) + } +}; +} // namespace detail + +} // namespace operators +} // namespace paddle \ No newline at end of file diff --git a/paddle/fluid/operators/detail/mpi_utils.h b/paddle/fluid/operators/detail/mpi_utils.h index fb2f141246..1f5ffdb18c 100644 --- a/paddle/fluid/operators/detail/mpi_utils.h +++ b/paddle/fluid/operators/detail/mpi_utils.h @@ -1,8 +1,54 @@ -// -// Created by tangwei12 on 2018/3/27. -// +/* 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. */ -#ifndef PADDLE_MPI_UTILS_H -#define PADDLE_MPI_UTILS_H +#pragma once +#include +#include +#include +#include -#endif //PADDLE_MPI_UTILS_H +namespace paddle { +namespace operators { +namespace detail { +class MPIUtils { + public: + MPIUtils(const std::string& worker_name); + const int GetRankID(const std::string& task_id); + + private: + void InitMPI(); + std::map name_id_map; +}; + +class MPIIsend { + public: + void init(); + int isFinished(); + void send(); + ~MPIIsend(); + + private: + int done1; + int done2; + sendrecv::VariableMessage req; +}; + +class MPIIrecv { + public: + void init(); + int isFinished(); + void recv(); + ~MPIIrecv(); +}; + +} // namespace detail +} // namespace operators +} // namespace paddle From 94ce020241cbc081a95089e677a79e340f3a4e0a Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Wed, 28 Mar 2018 15:50:59 +0800 Subject: [PATCH 03/69] mpi tools --- paddle/fluid/operators/detail/mpi_client.cpp | 29 ++++++++++++ paddle/fluid/operators/detail/mpi_client.h | 37 ++++++++-------- paddle/fluid/operators/detail/mpi_utils.cpp | 46 +++++++++++++++++++- paddle/fluid/operators/detail/mpi_utils.h | 21 ++++----- 4 files changed, 105 insertions(+), 28 deletions(-) create mode 100644 paddle/fluid/operators/detail/mpi_client.cpp diff --git a/paddle/fluid/operators/detail/mpi_client.cpp b/paddle/fluid/operators/detail/mpi_client.cpp new file mode 100644 index 0000000000..6890e437ef --- /dev/null +++ b/paddle/fluid/operators/detail/mpi_client.cpp @@ -0,0 +1,29 @@ + +/* 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 "mpi_client.h" +#include "mpi_utils.h" + +namespace paddle { +namespace operators { +namespace detail { +bool MPIClient::AsyncSendVariable() { + char* msg = "123456787654"; + int dst = 1; + MPIIsend send = MPIIsend(dst, msg); +} + +bool MPIClient::Wait() {} + +} // namespace detail +} // namespace operators +} // namespace paddle \ No newline at end of file diff --git a/paddle/fluid/operators/detail/mpi_client.h b/paddle/fluid/operators/detail/mpi_client.h index 14dcd678a0..a01e5b2d11 100644 --- a/paddle/fluid/operators/detail/mpi_client.h +++ b/paddle/fluid/operators/detail/mpi_client.h @@ -26,23 +26,26 @@ namespace operators { namespace detail { class MPIClient { public: - bool AsyncSendVariable(const std::string& ep, - const platform::DeviceContext& ctx, - const framework::Scope& scope, - const std::string& var_name, - int64_t time_out = 600 * 1000); - - bool AsyncGetVariable(const std::string& ep, - const platform::DeviceContext& ctx, - const framework::Scope& scope, - const std::string& var_name, - int64_t time_out = 600 * 1000); - - void AsyncSendBatchBarrier(const std::string& ep, - int64_t time_out = 600 * 1000); - - void AsyncSendFetchBarrier(const std::string& ep, - int64_t time_out = 600 * 1000); + // bool AsyncSendVariable(const std::string& ep, + // const platform::DeviceContext& ctx, + // const framework::Scope& scope, + // const std::string& var_name, + // int64_t time_out = 600 * 1000); + + // bool AsyncGetVariable(const std::string& ep, + // const platform::DeviceContext& ctx, + // const framework::Scope& scope, + // const std::string& var_name, + // int64_t time_out = 600 * 1000); + + // void AsyncSendBatchBarrier(const std::string& ep, + // int64_t time_out = 600 * 1000); + + // void AsyncSendFetchBarrier(const std::string& ep, + // int64_t time_out = 600 * 1000); + + bool AsyncSendVariable(); + bool Wait(); private: diff --git a/paddle/fluid/operators/detail/mpi_utils.cpp b/paddle/fluid/operators/detail/mpi_utils.cpp index 6560761e6b..370294fe21 100644 --- a/paddle/fluid/operators/detail/mpi_utils.cpp +++ b/paddle/fluid/operators/detail/mpi_utils.cpp @@ -3,10 +3,13 @@ // #include +#include -#include "paddle/fluid/operators/detail/mpi_utils.h" +#include +#include "mpi_utils.h" #define max_worker_name_length 128 +#define mpi_tag = 2008 namespace paddle { namespace operators { @@ -42,6 +45,47 @@ void MPIUtils::InitMPI() { MPI_Get_processor_name(host_name, &len) } }; + +MPIIsend::MPIIsend(int dst, const char* req) { + done1 = 0; + done2 = 0; + length = strlen(req); + req = req; +} + +MPIIsend::Send() { + MPI_Isend(&req, length, MPI_CHAR, dst, mpi_tag, MPI_COMM_WORLD, + &msg1_); + MPI_Test(&msg1_, &done1_, MPI_STATUS_IGNORE) +} + + bool MPIIsend::IsFinished() { + MPI_Status status; + if (!done1_) MPI_Test(&msg1_, &done1_, &status); + return done1; + } + +MPIIsend::~MPIIsend(){ + MPI_Wait(&msg1_, MPI_STATUS_IGNORE); + MPI_Free_mem(req); +} + +MPIIrecv::MPIIrecv(){ + +} + +MPIIrecv::Recv(){ + +} + +MPIIrecv::IsFinished(){ + +} + +MPIIrecv::~MPIIrecv(){ + +} + } // namespace detail } // namespace operators diff --git a/paddle/fluid/operators/detail/mpi_utils.h b/paddle/fluid/operators/detail/mpi_utils.h index 1f5ffdb18c..a754439c26 100644 --- a/paddle/fluid/operators/detail/mpi_utils.h +++ b/paddle/fluid/operators/detail/mpi_utils.h @@ -10,7 +10,7 @@ See the License for the specific language governing permissions and limitations under the License. */ #pragma once -#include +#include #include #include #include @@ -30,22 +30,23 @@ class MPIUtils { class MPIIsend { public: - void init(); - int isFinished(); - void send(); + MPIIsend(int dst, const char* buf); + bool IsFinished(); + void Send(); ~MPIIsend(); private: - int done1; - int done2; - sendrecv::VariableMessage req; + int done1; + int length; + char* req; + MPI_Request msg1_; }; class MPIIrecv { public: - void init(); - int isFinished(); - void recv(); +MPIIrecv(); +bool IsFinished(); + void Recv(); ~MPIIrecv(); }; From 9d256dd10ac3822e56e7962dede03fa01cceb451 Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Thu, 29 Mar 2018 18:14:25 +0800 Subject: [PATCH 04/69] mpi enabled design doc --- .../design/dist_train/mpi_enabled_design.md | 77 ++++++------------ .../design/dist_train/src/mpi_module.png | Bin 0 -> 106872 bytes 2 files changed, 27 insertions(+), 50 deletions(-) create mode 100644 doc/fluid/design/dist_train/src/mpi_module.png diff --git a/doc/fluid/design/dist_train/mpi_enabled_design.md b/doc/fluid/design/dist_train/mpi_enabled_design.md index 19f4298d71..2548c6cdf5 100644 --- a/doc/fluid/design/dist_train/mpi_enabled_design.md +++ b/doc/fluid/design/dist_train/mpi_enabled_design.md @@ -1,56 +1,33 @@ #MPI-enabled PaddlePaddle Design doc -## Overview + +# Background +Now, PaddlePaddle Fluid with Distribution has relatively large network bottleneck, We want to use RDMA and GPUDriect to improve and solve it, so we enabled the features to PaddlePaddle with the help of MPI. + We will introduce Open MPI API to PaddlePaddle, which can bring two benefits to PaddlePaddle: -1. Enable RDMA with PaddlePaddle, which bring high performance low latency networks. -2. Enable GPUDriect with PaddlePaddle, which bring highest throughput and lowest latency GPU read and write. +1. Enable RDMA with PaddlePaddle, which bring high-performance low latency networks. +2. Enable GPUDriect with PaddlePaddle, which bring the highest throughput and lowest latency GPU read and write. -## Global Config -Launch the script using the 'mpirun' launcher, For example: ```mpirun -np 3 -hosts node1,node2,node3 python train.py```. By doing this, We can number the actors (trainer/pserver/master) whith o .. (n-1). The actor's number is the Rank of the calling process in group of comm (integer), The MPI processes identify each other using an Rank ID. We have to create a mapping between PaddlePaddle's actors and there Rank ID, so that we can communicate with the correct destinations when using MPI operations. +## Execute args +Launch the script using the ```mpirun``` launcher, For example: ```mpirun -np 3 -hosts node1,node2,node3 python train.py```. By doing this, We can number the actors (trainer/pserver/master) with o .. (n-1). The node's number is the Rank of the calling process in a group of comm (integer), The MPI processes identify each other using a Rank ID. We have to create a mapping between PaddlePaddle's actors and their Rank ID so that we can communicate with the correct destinations when using MPI operations. **We have to store the Rank ID and the mapping in global variables.** -#Utils -We will build mpi_send_recv_utils Class to unify package interface about MPI Send and Receive. -```c++ -#mpi send and receive utils -class Mpi_ISend { - -} -class Mpi_IRecv { - -} - -class MPIUtils { - public: - const int GetRankID(const std::string& task_id); - void InitMPI(); - private: - std::map name_to_id_; -} - -``` -```c++ -class MPIServer { - public: - SetCond(); - ShutDown(); - WaitClientGet(); - reset(); - Push(); - SetScope(); - SetDevCtx(); - get(); -} -``` - -## New OP -We won't replace all the gRPC requests to MPI requests, the standard gRPC library is used for all administrative operations and the MPI API will used to transfer tensor or selectRows to Pservers. Base of this idea, we create two new operators to handle requests and receives, the two operators are send_mpi_op and listenandserve_mpi_op. They are a little similar with [send_op](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/fluid/operators/send_op.cc) and [listen_and_serv_op](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/fluid/operators/listen_and_serv_op.cc). - -### send_mpi_op -vary similar with send_op, we will replace grpc with mpi send service. -### listenandserve_mpi_op -vary similar with listen_and_serv_op, we will replace grpc with mpi receive service. +## New OP/MODULE +We won't replace all the gRPC requests to MPI requests, the standard gRPC library is used for all administrative operations and the MPI API will be used to transfer tensor or selectRows to Pservers. The base of this idea, we create two new operators to handle requests and receives, the two operators are send_mpi_op and listenandserve_mpi_op. They are a little similar with [send_op](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/fluid/operators/send_op.cc) and [listen_and_serv_op](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/fluid/operators/listen_and_serv_op.cc), also, We will build a new module to package MPI send and receive process. + +### mpi_module +We will build a new module to package MPI send and receive process. MPI send and recvice are defferent to gRPC, the MPI [recvice](https://www.open-mpi.org/doc/v1.8/man3/MPI_Irecv.3.php) must know receive buffer size and receive buffer element. For this reason, We have to make conmunications twice, the first one is to send metadata about gradient through gRPC, the second one is the real conmunications through MPI which send gradient data to mpi_listenandserve_op. +The detail flow is below: +![](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/fluid/design/dist_train/src/mpi_module.png) + +### mpi_send_op +Very similar with ```send_op```, we will replace gRPC code which used to send gradient with ```mpi_module```, at the same time , we will wrap it with ```framework::Async```. + +### mpi_listenandserve_op +Very similar with ```listen_and_serv_op```, we will replace gRPC code which used to receive gradient with ```mpi_module```, at the same time , we will wrap it with ```framework::Async```. + +### modify distribute_transpiler.py +Need to add args to distinguish use MPI or not. if confirm to use MPI, we will modify ```send_op``` to ```mpi_send_op``` in distribute_transpiler, and modify ```listenandserve_op``` to ```mpi_listenandserve_op``` also. + ## Build args -Beause MPI or CUDA need hardware supported, so we will add some build args to control compiling. -**The specific arguments is under design** -## Execute args -Launch the script using the 'mpirun' launcher, For example: ```mpirun -np 3 -hosts node1,node2,node3 python train.py```. \ No newline at end of file +Because MPI or CUDA need hardware supported, so we will add some build args to control compiling. +**The specific arguments are under design** \ No newline at end of file diff --git a/doc/fluid/design/dist_train/src/mpi_module.png b/doc/fluid/design/dist_train/src/mpi_module.png new file mode 100644 index 0000000000000000000000000000000000000000..e6b6a3e5d6f68baeeb67d7f71154bd8d85f32b6f GIT binary patch literal 106872 zcmeEuXH-+$7A_!&O0|K~Q4ytjlwO0VAV`tki}a3k2rVL@B1I5Tdhb2-P(`H~I)Q|a z6d{BFfrQT6oN|xncy+w@^Nn$Th$JL?uRZHGzd6@>sj4hTb%x;#5fKs9L-~7ZL_{as 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z=`gR{BhjzV{`U-4f%8ed(g$aMJC^&sTF-pJs{QTnfaL@~LqrSBS^v~rck@32@c#pc r;5&!_?OkVm`uh!k`}9nB`T{{Xdd+z^wTAW@@b^MU;#uw!P0#-a&W%-7 literal 0 HcmV?d00001 From 900b3e97de99c7a2fb493f577d554032fd6331d4 Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Tue, 3 Apr 2018 13:05:49 +0800 Subject: [PATCH 05/69] send mpi and rpc framework --- paddle/fluid/operators/detail/mpi_utils.cpp | 114 ++++++++++---------- paddle/fluid/operators/detail/mpi_utils.h | 100 ++++++++++------- 2 files changed, 120 insertions(+), 94 deletions(-) diff --git a/paddle/fluid/operators/detail/mpi_utils.cpp b/paddle/fluid/operators/detail/mpi_utils.cpp index 370294fe21..d3191c1563 100644 --- a/paddle/fluid/operators/detail/mpi_utils.cpp +++ b/paddle/fluid/operators/detail/mpi_utils.cpp @@ -12,81 +12,79 @@ #define mpi_tag = 2008 namespace paddle { -namespace operators { -namespace detail { -MPIUtils::MPIUtils(const std::string& worker_name) { - InitMPI(); + namespace operators { + namespace detail { + MPIUtils::MPIUtils(const std::string &worker_name) { + InitMPI(); - int rank = 0, size = 1; - char my_name[max_work_group_size]; - MPI_Comm_rank(MPI_COMM_WORLD, &rank); - MPI_Comm_size(MPI_COMM_WORLD, &size); - snprintf(my_name, max_worker_name_length, worker_name.c_str()); + int rank = 0, size = 1; + char my_name[max_work_group_size]; + MPI_Comm_rank(MPI_COMM_WORLD, &rank); + MPI_Comm_size(MPI_COMM_WORLD, &size); + snprintf(my_name, max_worker_name_length, worker_name.c_str()); - std::vector worker_names(size * max_worker_name_length); - MPI_Allgather(my_name, max_worker_name_length, MPI_CHAR, &worker_names[0], - max_worker_name_length, MPI_CHAR, MPI_COMM_WORLD); - for (int i = 0; i < number_of_procs; i++) { - name_to_id_[std::string(&worker_names[i * 128])] = i; - } -} + std::vector worker_names(size * max_worker_name_length); + MPI_Allgather(my_name, max_worker_name_length, MPI_CHAR, &worker_names[0], + max_worker_name_length, MPI_CHAR, MPI_COMM_WORLD); + for (int i = 0; i < number_of_procs; i++) { + name_to_id_[std::string(&worker_names[i * 128])] = i; + } + } -void MPIUtils::InitMPI() { - int flag = 0; - MPI_CHECK(MPI_Initialized(&flag)); + void MPIUtils::InitMPI() { + int flag = 0; + MPI_CHECK(MPI_Initialized(&flag)); - if (!flag) { - int rank = 0, size = 1, len = -1; - char host_name[max_worker_name_length]; + if (!flag) { + int rank = 0, size = 1, len = -1; + char host_name[max_worker_name_length]; - MPI_Init(0, 0); - MPI_Comm_rank(MPI_COMM_WORLD, &rank); - MPI_Comm_size(MPI_COMM_WORLD, &size); - MPI_Get_processor_name(host_name, &len) - } -}; + MPI_Init(0, 0); + MPI_Comm_rank(MPI_COMM_WORLD, &rank); + MPI_Comm_size(MPI_COMM_WORLD, &size); + MPI_Get_processor_name(host_name, &len); + } + }; -MPIIsend::MPIIsend(int dst, const char* req) { - done1 = 0; - done2 = 0; - length = strlen(req); - req = req; -} -MPIIsend::Send() { - MPI_Isend(&req, length, MPI_CHAR, dst, mpi_tag, MPI_COMM_WORLD, - &msg1_); - MPI_Test(&msg1_, &done1_, MPI_STATUS_IGNORE) -} + MPISend::MPISend(const Meta &meta) { + done1_ = 1; + done2_ = 0; + this->meta = meta; + } - bool MPIIsend::IsFinished() { - MPI_Status status; - if (!done1_) MPI_Test(&msg1_, &done1_, &status); - return done1; - } + MPISend::Send() { + MPI_Send(&meta.request, meta.count, meta.datatype, meta.dst, meta.tag, + MPI_COMM_WORLD); + done2_ = 1; + } -MPIIsend::~MPIIsend(){ - MPI_Wait(&msg1_, MPI_STATUS_IGNORE); - MPI_Free_mem(req); -} + bool MPISend::IsReady() { + return true; + } -MPIIrecv::MPIIrecv(){ + bool MPISend::IsFinished() { return done1_ && done2_; } -} + MPISend::~MPISend() { MPI_Free_mem(meta); } -MPIIrecv::Recv(){ -} + MPIRecv::MPIRecv(const Meta &meta) { + this->meta = meta; + } -MPIIrecv::IsFinished(){ + MPIRecv::Recv() {} -} + bool MPIRecv::IsReady() { + return true; + } -MPIIrecv::~MPIIrecv(){ + MPIRecv::IsFinished() {} -} + MPIRecv::~MPIRecv() { + MPI_Free_mem(meta); + } -} // namespace detail + } // namespace detail -} // namespace operators + } // namespace operators } // namespace paddle \ No newline at end of file diff --git a/paddle/fluid/operators/detail/mpi_utils.h b/paddle/fluid/operators/detail/mpi_utils.h index a754439c26..05801020bf 100644 --- a/paddle/fluid/operators/detail/mpi_utils.h +++ b/paddle/fluid/operators/detail/mpi_utils.h @@ -10,46 +10,74 @@ See the License for the specific language governing permissions and limitations under the License. */ #pragma once + #include #include #include #include namespace paddle { -namespace operators { -namespace detail { -class MPIUtils { - public: - MPIUtils(const std::string& worker_name); - const int GetRankID(const std::string& task_id); - - private: - void InitMPI(); - std::map name_id_map; -}; - -class MPIIsend { - public: - MPIIsend(int dst, const char* buf); - bool IsFinished(); - void Send(); - ~MPIIsend(); - - private: - int done1; - int length; - char* req; - MPI_Request msg1_; -}; - -class MPIIrecv { - public: -MPIIrecv(); -bool IsFinished(); - void Recv(); - ~MPIIrecv(); -}; - -} // namespace detail -} // namespace operators + namespace operators { + namespace detail { + class MPIUtils { + public: + MPIUtils(const std::string &worker_name); + + const int GetRankID(const std::string &task_id); + + private: + void InitMPI(); + + std::map name_id_map; + }; + + class Meta { + public: + int src; + int dst; + MPI_Datatype datatype; + char *request; + int count; + int tag; + int device; + }; + + class MPISend { + public: + MPISend(const Meta &meta); + + bool IsFinished(); + + bool IsReady(); + + void Send(); + + ~MPISend(); + + private: + int done1_; + int done2_; + Meta *meta; + }; + + class MPIRecv { + public: + MPIRecv(const Meta &meta); + + bool IsReady(); + + bool IsFinished(); + + void Recv(); + + ~MPIRecv(); + + private: + int done1_; + int done2_; + Meta *meta; + }; + + } // namespace detail + } // namespace operators } // namespace paddle From 17833d30e3c4eedf72839becec7aa0c144929261 Mon Sep 17 00:00:00 2001 From: Luo Tao Date: Mon, 9 Apr 2018 16:48:07 +0800 Subject: [PATCH 06/69] fuse batch norm for conv operator without bias --- python/paddle/fluid/__init__.py | 1 + python/paddle/fluid/framework.py | 9 + python/paddle/fluid/inference_transpiler.py | 174 ++++++++++++++++++ .../tests/book/test_image_classification.py | 15 ++ 4 files changed, 199 insertions(+) create mode 100644 python/paddle/fluid/inference_transpiler.py diff --git a/python/paddle/fluid/__init__.py b/python/paddle/fluid/__init__.py index f01d638efd..445204b2fd 100644 --- a/python/paddle/fluid/__init__.py +++ b/python/paddle/fluid/__init__.py @@ -36,6 +36,7 @@ from distribute_transpiler import DistributeTranspiler from distribute_transpiler_simple import SimpleDistributeTranspiler from concurrency import (Go, make_channel, channel_send, channel_recv, channel_close, Select) +from inference_transpiler import InferenceTranspiler import clip from memory_optimization_transpiler import memory_optimize, release_memory import profiler diff --git a/python/paddle/fluid/framework.py b/python/paddle/fluid/framework.py index 33cf691817..0ca853d3c6 100644 --- a/python/paddle/fluid/framework.py +++ b/python/paddle/fluid/framework.py @@ -920,6 +920,15 @@ class Block(object): ops_in_cpp_index += 1 ops_in_python_index += 1 + # sync ops inserted from c++ end + if len(self.ops) != len(ops_in_cpp) and start_index == 0 and len( + self.ops) == end_index: + del self.ops[:] + for index in range(len(ops_in_cpp)): + op_desc = ops_in_cpp[index] + op = Operator(self, op_desc) + self.ops.append(op) + assert len(self.ops) == len(ops_in_cpp) for index in range(len(self.ops)): assert self.ops[index].desc == ops_in_cpp[index] diff --git a/python/paddle/fluid/inference_transpiler.py b/python/paddle/fluid/inference_transpiler.py new file mode 100644 index 0000000000..6a45de5741 --- /dev/null +++ b/python/paddle/fluid/inference_transpiler.py @@ -0,0 +1,174 @@ +# 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 os +import shutil +from . import core + + +class InferenceTranspiler: + def transpile(self, program, scope, place): + ''' + Transpile the program to a inference program by fused batch normalization. + + The batch normalization followed the convolution or fully connected layer + can be integrated with them. Doing so will give us a forward acceleration, + especially in environments like mobile or embedded. + + For input X: + - Conv process: X = input * W + bias + - Batch norm process: X' = (X - mean) / std + - Scale Process: Y = a * X' + b + + After fuse into one operation: + + Y = (input * W + bias - mean) / std * a + b + = input * a * W / std + ((bias - mean) / std * a + b) + + The operator transformation is: + - before: + - conv->batch_norm->any_other_op (bias == 0) + - conv->elementwise_add->batch_norm->any_other_op (bias != 0) + - after: + - conv->elementwise_add->any_other_op + + The transpile stages are: + 1. insert elementwise_add op when bias == 0, and adjust its input and output. + 2. fuse the batch_norm's parameters to conv and elementwise_add operators. + 3. remove batch_norm ops and its variables which are not used in any other ops. + 4. remove unused variables. + + :param program: program to transpile + :type program: Program + :param scope: inference scope + :type scope: Scope + :param place: inference place + :type place: Place + :return: program by fused batch normalization + :rtype: Program + ''' + self.scope = scope + self.place = place + self.block_desc = program.get_desc().block(0) + i = 0 + while i < self.block_desc.op_size(): + current_op = self.block_desc.op(i) + # TODO(luotao1): consider only conv2d now. fc would be delt later. + if current_op.type() in ['conv2d']: + next_op = self.block_desc.op(i + 1) + # TODO(luotao1): consider only conv2d without bias now. + # If conv2d with bias, the next_op.type is elementwise_add. + if (next_op.type() == 'batch_norm'): + # insert bias op + bias_op = self._insert_bias_op(i + 1, current_op, next_op) + program.sync_with_cpp() + # fuse batch_norm + self._fuse_param(current_op, next_op, bias_op) + # remove batch_norm_op + self.block_desc.remove_op(i + 2, i + 3) + program.sync_with_cpp() + i = i + 1 + i = i + 1 + + self._remove_unused_var() + program.sync_with_cpp() + + return program + + # ====================== private transpiler functions ===================== + def _insert_bias_op(self, index, current_op, bn_op): + ''' + Construct elementwise_add operator for adding bias + and insert it into program. + + :param index: insert location of bias_op + :type index: Int + :param current_op: current operator (conv or fc) + :type current_op: Operator + :param bn_op: batch norm operator + :type bn_op: Operator + :return: bias_op + :rtype: Operator + ''' + bias_op = self.block_desc.insert_op(index) + bias_op.set_type("elementwise_add") + # The input of bias_op is current_op's output and Bias of bn_op + # The output of bias_op is bn_op's output + bias_op.set_input("X", current_op.output("Output")) + bias_op.set_input("Y", bn_op.input("Bias")) + bias_op.set_output("Out", bn_op.output("Y")) + bias_op.set_attr('axis', 1) # dim_start=1 + return bias_op + + def _fuse_param(self, current_op, bn_op, bias_op): + ''' + fuse the batch_norm_op' parameters to current_op (conv or fc) + + :param current_op: current operator (conv or fc) + :type current_op: Operator + :param bn_op: batch norm operator + :type bn_op: Operator + :param bias_op: elementwise_add operator for adding bias + :type bias_op: Operator + ''' + + def _load_tensor(param_name): + return self.scope.find_var(param_name[0]).get_tensor() + + def _load_param(param_name): + return np.array(_load_tensor(param_name)) + + bias_bn = _load_param(bn_op.input("Bias")) #Bias + scale_bn = _load_param(bn_op.input("Scale")) #Scale + mean_bn = _load_param(bn_op.input("Mean")) #Mean + var_bn = _load_param(bn_op.input("Variance")) #Variance + + # TODO(luotao1): consider only conv2d now. fc would be delt later. + current_param = _load_param(current_op.input("Filter")) + current_tensor = _load_tensor(current_op.input("Filter")) + + std_bn = np.float32(np.sqrt(np.add(var_bn, 1e-5))) + tmp = np.float32(np.divide(scale_bn, std_bn)) + + # add bias of batch_norm_op to conv2d + bias = np.zeros(bias_bn.shape) + bias = np.float32( + np.add(np.multiply(np.subtract(bias, mean_bn), tmp), bias_bn)) + bias_tensor = _load_tensor(bias_op.input("Y")) + bias_tensor.set(bias, self.place) + + # re-compute weight of conv2d + tmp = tmp.reshape(tmp.shape[0], -1) + dst_param = current_param.reshape((tmp.shape[0], -1)) + dst_param = np.float32(np.multiply(dst_param, tmp)) + dst_param = dst_param.reshape(current_param.shape) + + # set the updated parameters + current_tensor.set(np.array(dst_param), self.place) + + def _remove_unused_var(self): + ''' + remove unused varibles in program desc + ''' + args = [] + for i in xrange(0, self.block_desc.op_size()): + current_op = self.block_desc.op(i) + args += current_op.input_arg_names() + args += current_op.output_arg_names() + args = list(set(args)) # unique the input and output arguments + + for var in self.block_desc.all_vars(): + if var.name() not in args: + self.block_desc.remove_var(var.name()) diff --git a/python/paddle/fluid/tests/book/test_image_classification.py b/python/paddle/fluid/tests/book/test_image_classification.py index e8bb082be1..87cbe98c9b 100644 --- a/python/paddle/fluid/tests/book/test_image_classification.py +++ b/python/paddle/fluid/tests/book/test_image_classification.py @@ -22,6 +22,7 @@ import sys import numpy import unittest import os +import numpy as np def resnet_cifar10(input, depth=32): @@ -224,6 +225,20 @@ def infer(use_cuda, save_dirname=None): results = exe.run(inference_program, feed={feed_target_names[0]: tensor_img}, fetch_list=fetch_targets) + + # Use inference_transpiler to speedup + t = fluid.InferenceTranspiler() + inference_transpiler_program = t.transpile(inference_program, + inference_scope, place) + transpiler_results = exe.run(inference_transpiler_program, + feed={feed_target_names[0]: tensor_img}, + fetch_list=fetch_targets) + + assert len(results[0]) == len(transpiler_results[0]) + for i in range(len(results[0])): + np.testing.assert_almost_equal(results[0][i], + transpiler_results[0][i]) + print("infer results: ", results[0]) From ea0cf6f3829ddce01b2e5a2c0dea36e3ff7fce40 Mon Sep 17 00:00:00 2001 From: Luo Tao Date: Tue, 10 Apr 2018 13:00:28 +0800 Subject: [PATCH 07/69] rewrite inference_transpiler in Python end --- paddle/fluid/framework/block_desc.cc | 50 +----------------- python/paddle/fluid/framework.py | 20 ++++---- python/paddle/fluid/inference_transpiler.py | 51 ++++++++++--------- .../tests/book/test_image_classification.py | 4 +- .../tests/unittests/test_protobuf_descs.py | 20 -------- 5 files changed, 41 insertions(+), 104 deletions(-) diff --git a/paddle/fluid/framework/block_desc.cc b/paddle/fluid/framework/block_desc.cc index fbe08349c3..b8847e4b90 100644 --- a/paddle/fluid/framework/block_desc.cc +++ b/paddle/fluid/framework/block_desc.cc @@ -13,11 +13,10 @@ See the License for the specific language governing permissions and limitations under the License. */ #include "paddle/fluid/framework/block_desc.h" +#include #include "paddle/fluid/framework/operator.h" #include "paddle/fluid/framework/program_desc.h" -#include - namespace paddle { namespace framework { @@ -147,52 +146,7 @@ void BlockDesc::RemoveOp(size_t s, size_t e) { if (ops_.begin() + s == ops_.end() || ops_.begin() + e == ops_.end()) { return; } - auto get_vars = [](std::deque>::iterator &op, - std::vector &v) { - auto in_names = (*op)->InputArgumentNames(); - v.insert(v.end(), in_names.begin(), in_names.end()); - auto out_names = (*op)->OutputArgumentNames(); - v.insert(v.end(), out_names.begin(), out_names.end()); - std::sort(v.begin(), v.end()); - auto last = std::unique(v.begin(), v.end()); - v.erase(last, v.end()); - }; - need_update_ = true; - - for (size_t i = s; i < e; i++) { - // since remove op one by one, every time remove the first op. - auto op = ops_.begin() + s; - - // collect input and output variables from current delete op - std::vector cur_vars; - get_vars(op, cur_vars); - - // remove current op - ops_.erase(ops_.begin() + s); - - // collect input and output variables from other ops - std::vector other_vars; - for (auto it = ops_.begin(); it != ops_.end(); it++) { - get_vars(it, other_vars); - } - - // variables should be deleted - std::vector delete_vars; - // delete_vars = cur_vars - cur_vars ^ other_input_vars - std::set_difference(cur_vars.begin(), cur_vars.end(), other_vars.begin(), - other_vars.end(), - std::inserter(delete_vars, delete_vars.end())); - // remove variables - for (size_t i = 0; i < delete_vars.size(); i++) { - auto name = delete_vars[i]; - auto it = vars_.find(name); - PADDLE_ENFORCE(it != vars_.end(), - "%s is not in variable list, it should not be deleted", - name); - vars_.erase(it); - VLOG(3) << "deleting variable " << name; - } - } + ops_.erase(ops_.begin() + s, ops_.begin() + e); } std::vector BlockDesc::AllOps() const { diff --git a/python/paddle/fluid/framework.py b/python/paddle/fluid/framework.py index 0ca853d3c6..793421a22f 100644 --- a/python/paddle/fluid/framework.py +++ b/python/paddle/fluid/framework.py @@ -818,6 +818,11 @@ class Block(object): del self.vars[name] self.sync_with_cpp() + def remove_var(self, name): + self.sync_with_cpp() + self.desc.remove_var(name) + del self.vars[name] + def create_parameter(self, *args, **kwargs): global_block = self.program.global_block() param = Parameter(global_block, *args, **kwargs) @@ -838,6 +843,11 @@ class Block(object): self.ops.insert(index, op) return op + def remove_op(self, index): + self.sync_with_cpp() + self.desc.remove_op(index, index + 1) + del self.ops[index] + def delete_ops(self, ops): # remove from cpp # FIXME(typhoonzero): remove only the first occurrence. @@ -846,6 +856,7 @@ class Block(object): end = list(self.ops).index(ops[-1]) except Exception, e: raise e + self.desc.remove_op(start, end + 1) def slice_ops(self, start, end): @@ -920,15 +931,6 @@ class Block(object): ops_in_cpp_index += 1 ops_in_python_index += 1 - # sync ops inserted from c++ end - if len(self.ops) != len(ops_in_cpp) and start_index == 0 and len( - self.ops) == end_index: - del self.ops[:] - for index in range(len(ops_in_cpp)): - op_desc = ops_in_cpp[index] - op = Operator(self, op_desc) - self.ops.append(op) - assert len(self.ops) == len(ops_in_cpp) for index in range(len(self.ops)): assert self.ops[index].desc == ops_in_cpp[index] diff --git a/python/paddle/fluid/inference_transpiler.py b/python/paddle/fluid/inference_transpiler.py index 6a45de5741..3791e93576 100644 --- a/python/paddle/fluid/inference_transpiler.py +++ b/python/paddle/fluid/inference_transpiler.py @@ -61,30 +61,26 @@ class InferenceTranspiler: ''' self.scope = scope self.place = place - self.block_desc = program.get_desc().block(0) + self.block = program.block(0) i = 0 - while i < self.block_desc.op_size(): - current_op = self.block_desc.op(i) + while i < len(self.block.ops): + current_op = self.block.ops[i] # TODO(luotao1): consider only conv2d now. fc would be delt later. - if current_op.type() in ['conv2d']: - next_op = self.block_desc.op(i + 1) + if current_op.type in ['conv2d']: + next_op = self.block.ops[i + 1] # TODO(luotao1): consider only conv2d without bias now. # If conv2d with bias, the next_op.type is elementwise_add. - if (next_op.type() == 'batch_norm'): + if (next_op.type == 'batch_norm'): # insert bias op bias_op = self._insert_bias_op(i + 1, current_op, next_op) - program.sync_with_cpp() # fuse batch_norm self._fuse_param(current_op, next_op, bias_op) # remove batch_norm_op - self.block_desc.remove_op(i + 2, i + 3) - program.sync_with_cpp() + self.block.remove_op(i + 2) i = i + 1 i = i + 1 self._remove_unused_var() - program.sync_with_cpp() - return program # ====================== private transpiler functions ===================== @@ -102,14 +98,19 @@ class InferenceTranspiler: :return: bias_op :rtype: Operator ''' - bias_op = self.block_desc.insert_op(index) - bias_op.set_type("elementwise_add") # The input of bias_op is current_op's output and Bias of bn_op # The output of bias_op is bn_op's output - bias_op.set_input("X", current_op.output("Output")) - bias_op.set_input("Y", bn_op.input("Bias")) - bias_op.set_output("Out", bn_op.output("Y")) - bias_op.set_attr('axis', 1) # dim_start=1 + x_var = self.block.var(current_op.output("Output")[0]) + y_var = self.block.var(bn_op.input("Bias")[0]) + out_var = self.block.var(bn_op.output("Y")[0]) + + bias_op = self.block.insert_op( + index, + type="elementwise_add", + inputs={"X": x_var, + "Y": y_var}, + outputs={"Out": out_var}, + attrs={"axis": 1}) # dim_start=1 return bias_op def _fuse_param(self, current_op, bn_op, bias_op): @@ -160,15 +161,15 @@ class InferenceTranspiler: def _remove_unused_var(self): ''' - remove unused varibles in program desc + remove unused varibles in program ''' args = [] - for i in xrange(0, self.block_desc.op_size()): - current_op = self.block_desc.op(i) - args += current_op.input_arg_names() - args += current_op.output_arg_names() + for i in range(len(self.block.ops)): + current_op = self.block.ops[i] + args += current_op.input_arg_names + args += current_op.output_arg_names args = list(set(args)) # unique the input and output arguments - for var in self.block_desc.all_vars(): - if var.name() not in args: - self.block_desc.remove_var(var.name()) + for var in self.block.vars.keys(): + if var not in args: + self.block.remove_var(var) diff --git a/python/paddle/fluid/tests/book/test_image_classification.py b/python/paddle/fluid/tests/book/test_image_classification.py index 87cbe98c9b..bca42a89cd 100644 --- a/python/paddle/fluid/tests/book/test_image_classification.py +++ b/python/paddle/fluid/tests/book/test_image_classification.py @@ -236,8 +236,8 @@ def infer(use_cuda, save_dirname=None): assert len(results[0]) == len(transpiler_results[0]) for i in range(len(results[0])): - np.testing.assert_almost_equal(results[0][i], - transpiler_results[0][i]) + np.testing.assert_almost_equal( + results[0][i], transpiler_results[0][i], decimal=6) print("infer results: ", results[0]) diff --git a/python/paddle/fluid/tests/unittests/test_protobuf_descs.py b/python/paddle/fluid/tests/unittests/test_protobuf_descs.py index f98a8bbc68..3f9059fb5b 100644 --- a/python/paddle/fluid/tests/unittests/test_protobuf_descs.py +++ b/python/paddle/fluid/tests/unittests/test_protobuf_descs.py @@ -201,24 +201,6 @@ class TestBlockDesc(unittest.TestCase): op1.set_type("test") op2.set_type("test") - var0 = block.var("var0") - var1 = block.var("var1") - var2 = block.var("var2") - var3 = block.var("var3") - var4 = block.var("var4") - var5 = block.var("var5") - - op0.set_input("X", ["var0"]) - op0.set_output("Y", ["var0"]) - op1.set_input("X", ["var1", "var2"]) - op1.set_output("Y", ["var3", "var4"]) - op2.set_input("X", ["var1"]) - op2.set_output("Y", ["var4", "var5"]) - - program.sync_with_cpp() - - # remove op1, its input var2 and output var3 will be removed at the same time, - # but its input var1 and output var4 will not be removed since they are used for op2. block.remove_op(1, 2) program.sync_with_cpp() @@ -226,8 +208,6 @@ class TestBlockDesc(unittest.TestCase): for idx in xrange(0, block.op_size()): all_ops.append(block.op(idx)) self.assertEqual(all_ops, [op0, op2]) - all_vars = block.all_vars() - self.assertEqual(set(all_vars), {var0, var1, var4, var5}) if __name__ == '__main__': From 5483258b7e8c6e56968b1d63091539ed34609b1c Mon Sep 17 00:00:00 2001 From: Luo Tao Date: Tue, 10 Apr 2018 19:01:18 +0800 Subject: [PATCH 08/69] fuse batch norm for conv operator with bias --- python/paddle/fluid/inference_transpiler.py | 44 +++++++++++++++---- .../tests/book/test_image_classification.py | 12 +++-- 2 files changed, 45 insertions(+), 11 deletions(-) diff --git a/python/paddle/fluid/inference_transpiler.py b/python/paddle/fluid/inference_transpiler.py index 3791e93576..194f7adf46 100644 --- a/python/paddle/fluid/inference_transpiler.py +++ b/python/paddle/fluid/inference_transpiler.py @@ -45,10 +45,11 @@ class InferenceTranspiler: - conv->elementwise_add->any_other_op The transpile stages are: - 1. insert elementwise_add op when bias == 0, and adjust its input and output. + 1. insert elementwise_add op when bias == 0. 2. fuse the batch_norm's parameters to conv and elementwise_add operators. - 3. remove batch_norm ops and its variables which are not used in any other ops. - 4. remove unused variables. + 3. remove batch_norm ops which are not used in any other ops. + 4. adjust the input of any_other_op to be the output of elementwise_add operator. + 5. remove unused variables. :param program: program to transpile :type program: Program @@ -62,24 +63,35 @@ class InferenceTranspiler: self.scope = scope self.place = place self.block = program.block(0) + self.input_map = {} # store the input names should be adjusted + i = 0 while i < len(self.block.ops): current_op = self.block.ops[i] # TODO(luotao1): consider only conv2d now. fc would be delt later. if current_op.type in ['conv2d']: next_op = self.block.ops[i + 1] - # TODO(luotao1): consider only conv2d without bias now. - # If conv2d with bias, the next_op.type is elementwise_add. + # conv2d without bias if (next_op.type == 'batch_norm'): # insert bias op bias_op = self._insert_bias_op(i + 1, current_op, next_op) # fuse batch_norm - self._fuse_param(current_op, next_op, bias_op) + self._fuse_param(current_op, next_op, bias_op, 0) # remove batch_norm_op self.block.remove_op(i + 2) i = i + 1 + # conv2d with bias, the next_op.type is elementwise_add + elif (next_op.type == 'elementwise_add'): + next_next_op = self.block.ops[i + 2] + if (next_next_op.type == 'batch_norm'): + # fuse batch_norm + self._fuse_param(current_op, next_next_op, next_op, 1) + # remove batch_norm_op + self.block.remove_op(i + 2) + i = i + 1 i = i + 1 + self._adjust_input() self._remove_unused_var() return program @@ -113,7 +125,7 @@ class InferenceTranspiler: attrs={"axis": 1}) # dim_start=1 return bias_op - def _fuse_param(self, current_op, bn_op, bias_op): + def _fuse_param(self, current_op, bn_op, bias_op, with_bias): ''' fuse the batch_norm_op' parameters to current_op (conv or fc) @@ -123,6 +135,8 @@ class InferenceTranspiler: :type bn_op: Operator :param bias_op: elementwise_add operator for adding bias :type bias_op: Operator + :param with_bias: If current operator has bias, with_bias = 1; otherwise 0. + :type with_bias: Int ''' def _load_tensor(param_name): @@ -144,7 +158,10 @@ class InferenceTranspiler: tmp = np.float32(np.divide(scale_bn, std_bn)) # add bias of batch_norm_op to conv2d - bias = np.zeros(bias_bn.shape) + if with_bias: + bias = _load_param(bias_op.input("Y")) + else: + bias = np.zeros(bias_bn.shape) bias = np.float32( np.add(np.multiply(np.subtract(bias, mean_bn), tmp), bias_bn)) bias_tensor = _load_tensor(bias_op.input("Y")) @@ -159,6 +176,17 @@ class InferenceTranspiler: # set the updated parameters current_tensor.set(np.array(dst_param), self.place) + # collect the renamed input + self.input_map[bn_op.output("Y")[0]] = bias_op.output("Out")[0] + + def _adjust_input(self): + for i in range(len(self.block.ops)): + current_op = self.block.ops[i] + for input_arg in current_op.input_arg_names: + if input_arg in self.input_map: + current_op.rename_input(input_arg, + self.input_map[input_arg]) + def _remove_unused_var(self): ''' remove unused varibles in program diff --git a/python/paddle/fluid/tests/book/test_image_classification.py b/python/paddle/fluid/tests/book/test_image_classification.py index bca42a89cd..5e47bcb2cb 100644 --- a/python/paddle/fluid/tests/book/test_image_classification.py +++ b/python/paddle/fluid/tests/book/test_image_classification.py @@ -26,7 +26,13 @@ import numpy as np def resnet_cifar10(input, depth=32): - def conv_bn_layer(input, ch_out, filter_size, stride, padding, act='relu'): + def conv_bn_layer(input, + ch_out, + filter_size, + stride, + padding, + act='relu', + bias_attr=False): tmp = fluid.layers.conv2d( input=input, filter_size=filter_size, @@ -34,7 +40,7 @@ def resnet_cifar10(input, depth=32): stride=stride, padding=padding, act=None, - bias_attr=False) + bias_attr=bias_attr) return fluid.layers.batch_norm(input=tmp, act=act) def shortcut(input, ch_in, ch_out, stride): @@ -45,7 +51,7 @@ def resnet_cifar10(input, depth=32): def basicblock(input, ch_in, ch_out, stride): tmp = conv_bn_layer(input, ch_out, 3, stride, 1) - tmp = conv_bn_layer(tmp, ch_out, 3, 1, 1, act=None) + tmp = conv_bn_layer(tmp, ch_out, 3, 1, 1, act=None, bias_attr=True) short = shortcut(input, ch_in, ch_out, stride) return fluid.layers.elementwise_add(x=tmp, y=short, act='relu') From 7815cdffbaacd49f8ba875f5d53a8972b9c3b060 Mon Sep 17 00:00:00 2001 From: Luo Tao Date: Wed, 11 Apr 2018 15:22:17 +0800 Subject: [PATCH 09/69] use clone method to flush in forth --- python/paddle/fluid/inference_transpiler.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/python/paddle/fluid/inference_transpiler.py b/python/paddle/fluid/inference_transpiler.py index 194f7adf46..a215b98c61 100644 --- a/python/paddle/fluid/inference_transpiler.py +++ b/python/paddle/fluid/inference_transpiler.py @@ -93,7 +93,10 @@ class InferenceTranspiler: self._adjust_input() self._remove_unused_var() - return program + # TODO(luotao): use clone() method to flush the program.desc in force, + # since some large program.desc will not be flushed immediately. + # And a better solution will be considered later. + return program.clone() # ====================== private transpiler functions ===================== def _insert_bias_op(self, index, current_op, bn_op): From c97003df57aa776a3a02d19d3119452b7694eedb Mon Sep 17 00:00:00 2001 From: weixing02 <564445201@qq.com> Date: Thu, 12 Apr 2018 13:06:21 +0800 Subject: [PATCH 10/69] Regenerate initializer.rst and add MSRAInitializer to initializer.__all__ --- doc/fluid/api/initializer.rst | 42 ++++++++++++++++++++++++++++++ python/paddle/fluid/initializer.py | 4 +-- 2 files changed, 44 insertions(+), 2 deletions(-) diff --git a/doc/fluid/api/initializer.rst b/doc/fluid/api/initializer.rst index ee69925fda..f186c9c85a 100644 --- a/doc/fluid/api/initializer.rst +++ b/doc/fluid/api/initializer.rst @@ -33,3 +33,45 @@ Xavier :members: :noindex: +MSRA +------ + +.. autoclass:: paddle.fluid.initializer.MSRA + :members: + :noindex: + +ConstantInitializer +------------------- + +.. autoclass:: paddle.fluid.initializer.ConstantInitializer + :members: + :noindex: + +UniformInitializer +------------------ + +.. autoclass:: paddle.fluid.initializer.UniformInitializer + :members: + :noindex: + +NormalInitializer +----------------- + +.. autoclass:: paddle.fluid.initializer.NormalInitializer + :members: + :noindex: + +XavierInitializer +----------------- + +.. autoclass:: paddle.fluid.initializer.XavierInitializer + :members: + :noindex: + MSRA + ------ + +MSRAInitializer +----------------- +.. autoclass:: paddle.fluid.initializer.MSRAInitializer + :members: + :noindex: diff --git a/python/paddle/fluid/initializer.py b/python/paddle/fluid/initializer.py index 4e132ed261..6b74eaba8d 100644 --- a/python/paddle/fluid/initializer.py +++ b/python/paddle/fluid/initializer.py @@ -17,9 +17,9 @@ import numpy as np import contextlib __all__ = [ - 'Constant', 'Uniform', 'Normal', 'Xavier', 'force_init_on_cpu', + 'Constant', 'Uniform', 'Normal', 'Xavier', 'MSRA', 'force_init_on_cpu', 'init_on_cpu', 'ConstantInitializer', 'UniformInitializer', - 'NormalInitializer', 'XavierInitializer' + 'NormalInitializer', 'XavierInitializer', 'MSRAInitializer' ] _force_init_on_cpu_ = False From 3836cf32879e5f54e02553adff8d82f9866e4542 Mon Sep 17 00:00:00 2001 From: weixing02 <564445201@qq.com> Date: Fri, 13 Apr 2018 12:25:01 +0800 Subject: [PATCH 11/69] Delete MSRAInitializer --- python/paddle/fluid/initializer.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/python/paddle/fluid/initializer.py b/python/paddle/fluid/initializer.py index 6b74eaba8d..4e132ed261 100644 --- a/python/paddle/fluid/initializer.py +++ b/python/paddle/fluid/initializer.py @@ -17,9 +17,9 @@ import numpy as np import contextlib __all__ = [ - 'Constant', 'Uniform', 'Normal', 'Xavier', 'MSRA', 'force_init_on_cpu', + 'Constant', 'Uniform', 'Normal', 'Xavier', 'force_init_on_cpu', 'init_on_cpu', 'ConstantInitializer', 'UniformInitializer', - 'NormalInitializer', 'XavierInitializer', 'MSRAInitializer' + 'NormalInitializer', 'XavierInitializer' ] _force_init_on_cpu_ = False From 11b6fabee128e7b129b6892f3e4b37ec5fc82ab7 Mon Sep 17 00:00:00 2001 From: weixing02 Date: Fri, 13 Apr 2018 15:27:41 +0800 Subject: [PATCH 12/69] Remove dense_vector api from documents --- doc/v2/api/data/data_reader.rst | 38 ++++++++++++++++++++++++++++++++- 1 file changed, 37 insertions(+), 1 deletion(-) diff --git a/doc/v2/api/data/data_reader.rst b/doc/v2/api/data/data_reader.rst index 2ccfec9c28..d7c896a627 100644 --- a/doc/v2/api/data/data_reader.rst +++ b/doc/v2/api/data/data_reader.rst @@ -6,7 +6,43 @@ Data Reader Interface DataTypes ========= -.. automodule:: paddle.v2.data_type +.. autofunction:: paddle.v2.data_type.dense_array + :noindex: + +.. autofunction:: paddle.v2.data_type.integer_value + :noindex: + +.. autofunction:: paddle.v2.data_type.integer_value_sequence + :noindex: + +.. autofunction:: paddle.v2.data_type.integer_value_sub_sequence + :noindex: + +.. autofunction:: paddle.v2.data_type.sparse_binary_vector + :noindex: + +.. autofunction:: paddle.v2.data_type.sparse_binary_vector_sequence + :noindex: + +.. autofunction:: paddle.v2.data_type.sparse_binary_vector_sub_sequence + :noindex: + +.. autofunction:: paddle.v2.data_type.sparse_float_vector + :noindex: + +.. autofunction:: paddle.v2.data_type.sparse_float_vector_sequence + :noindex: + +.. autofunction:: paddle.v2.data_type.sparse_float_vector_sub_sequence + :noindex: + +.. autofunction:: paddle.v2.data_type.sparse_non_value_slot + :noindex: + +.. autofunction:: paddle.v2.data_type.sparse_value_slot + :noindex: + +.. autoclass:: paddle.v2.data_type.InputType :members: :noindex: From f45818e7f9291322a13fd9e137c151282e0bd1a9 Mon Sep 17 00:00:00 2001 From: Luo Tao Date: Fri, 13 Apr 2018 16:55:02 +0800 Subject: [PATCH 13/69] create new varible in scope --- python/paddle/fluid/__init__.py | 1 + python/paddle/fluid/inference_transpiler.py | 48 ++++++++++++++----- .../tests/book/test_image_classification.py | 9 ++-- 3 files changed, 41 insertions(+), 17 deletions(-) diff --git a/python/paddle/fluid/__init__.py b/python/paddle/fluid/__init__.py index bb4b6d5fc4..e9ca0d45f9 100644 --- a/python/paddle/fluid/__init__.py +++ b/python/paddle/fluid/__init__.py @@ -67,6 +67,7 @@ __all__ = framework.__all__ + executor.__all__ + concurrency.__all__ + [ 'clip', 'SimpleDistributeTranspiler', 'DistributeTranspiler', + 'InferenceTranspiler', 'memory_optimize', 'release_memory', 'profiler', diff --git a/python/paddle/fluid/inference_transpiler.py b/python/paddle/fluid/inference_transpiler.py index a215b98c61..7b7bd899ea 100644 --- a/python/paddle/fluid/inference_transpiler.py +++ b/python/paddle/fluid/inference_transpiler.py @@ -21,7 +21,20 @@ from . import core class InferenceTranspiler: def transpile(self, program, scope, place): ''' - Transpile the program to a inference program by fused batch normalization. + Transpile the program. Support only fuse batch normalization now. + + :param program: program to transpile + :type program: Program + :param scope: inference scope + :type scope: Scope + :param place: inference place + :type place: Place + ''' + self.fuse_batch_norm(program, scope, place) + + def fuse_batch_norm(self, program, scope, place): + ''' + Transpile the program by fused batch normalization. The batch normalization followed the convolution or fully connected layer can be integrated with them. Doing so will give us a forward acceleration, @@ -57,8 +70,6 @@ class InferenceTranspiler: :type scope: Scope :param place: inference place :type place: Place - :return: program by fused batch normalization - :rtype: Program ''' self.scope = scope self.place = place @@ -96,7 +107,7 @@ class InferenceTranspiler: # TODO(luotao): use clone() method to flush the program.desc in force, # since some large program.desc will not be flushed immediately. # And a better solution will be considered later. - return program.clone() + program = program.clone() # ====================== private transpiler functions ===================== def _insert_bias_op(self, index, current_op, bn_op): @@ -142,11 +153,25 @@ class InferenceTranspiler: :type with_bias: Int ''' - def _load_tensor(param_name): - return self.scope.find_var(param_name[0]).get_tensor() + def _update_param(op, old_param_name, new_param): + # For the sake of remaining the original variables the same as before, + # create new variables in scope to store the new parameters. + old_param_name = old_param_name[0] + old_var = self.block.vars[old_param_name] + new_param_name = old_param_name + '_fuse_bn' + new_var = self.block.create_parameter( + name=new_param_name.encode('ascii'), + type=old_var.type, + dtype=old_var.dtype, + shape=old_var.shape) + op.rename_input(old_param_name, new_param_name) + self.scope.var(new_param_name) + + tensor = self.scope.find_var(new_param_name).get_tensor() + tensor.set(np.array(new_param), self.place) def _load_param(param_name): - return np.array(_load_tensor(param_name)) + return np.array(self.scope.find_var(param_name[0]).get_tensor()) bias_bn = _load_param(bn_op.input("Bias")) #Bias scale_bn = _load_param(bn_op.input("Scale")) #Scale @@ -155,8 +180,6 @@ class InferenceTranspiler: # TODO(luotao1): consider only conv2d now. fc would be delt later. current_param = _load_param(current_op.input("Filter")) - current_tensor = _load_tensor(current_op.input("Filter")) - std_bn = np.float32(np.sqrt(np.add(var_bn, 1e-5))) tmp = np.float32(np.divide(scale_bn, std_bn)) @@ -167,8 +190,6 @@ class InferenceTranspiler: bias = np.zeros(bias_bn.shape) bias = np.float32( np.add(np.multiply(np.subtract(bias, mean_bn), tmp), bias_bn)) - bias_tensor = _load_tensor(bias_op.input("Y")) - bias_tensor.set(bias, self.place) # re-compute weight of conv2d tmp = tmp.reshape(tmp.shape[0], -1) @@ -176,8 +197,9 @@ class InferenceTranspiler: dst_param = np.float32(np.multiply(dst_param, tmp)) dst_param = dst_param.reshape(current_param.shape) - # set the updated parameters - current_tensor.set(np.array(dst_param), self.place) + # update parameters + _update_param(current_op, current_op.input("Filter"), dst_param) + _update_param(bias_op, bias_op.input("Y"), bias) # collect the renamed input self.input_map[bn_op.output("Y")[0]] = bias_op.output("Out")[0] diff --git a/python/paddle/fluid/tests/book/test_image_classification.py b/python/paddle/fluid/tests/book/test_image_classification.py index 5e47bcb2cb..aeacca5753 100644 --- a/python/paddle/fluid/tests/book/test_image_classification.py +++ b/python/paddle/fluid/tests/book/test_image_classification.py @@ -226,16 +226,17 @@ def infer(use_cuda, save_dirname=None): batch_size = 1 tensor_img = numpy.random.rand(batch_size, 3, 32, 32).astype("float32") + # Use inference_transpiler to speedup + inference_transpiler_program = inference_program.clone() + t = fluid.InferenceTranspiler() + t.transpile(inference_transpiler_program, inference_scope, place) + # Construct feed as a dictionary of {feed_target_name: feed_target_data} # and results will contain a list of data corresponding to fetch_targets. results = exe.run(inference_program, feed={feed_target_names[0]: tensor_img}, fetch_list=fetch_targets) - # Use inference_transpiler to speedup - t = fluid.InferenceTranspiler() - inference_transpiler_program = t.transpile(inference_program, - inference_scope, place) transpiler_results = exe.run(inference_transpiler_program, feed={feed_target_names[0]: tensor_img}, fetch_list=fetch_targets) From ec512cdcce5cf6e5952c7184db222f3d293d218d Mon Sep 17 00:00:00 2001 From: Luo Tao Date: Fri, 13 Apr 2018 18:45:09 +0800 Subject: [PATCH 14/69] add comment for branch network --- python/paddle/fluid/inference_transpiler.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/python/paddle/fluid/inference_transpiler.py b/python/paddle/fluid/inference_transpiler.py index 7b7bd899ea..be8a627953 100644 --- a/python/paddle/fluid/inference_transpiler.py +++ b/python/paddle/fluid/inference_transpiler.py @@ -81,6 +81,9 @@ class InferenceTranspiler: current_op = self.block.ops[i] # TODO(luotao1): consider only conv2d now. fc would be delt later. if current_op.type in ['conv2d']: + # TODO(luotao1): consider single chain network now. + # For branch network, we counldn't use block.ops[i + 1] as + # the judgment condition. next_op = self.block.ops[i + 1] # conv2d without bias if (next_op.type == 'batch_norm'): From 093d227a7796e50dc2f7a04094b4725c6f40f399 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Mon, 16 Apr 2018 10:33:01 +0800 Subject: [PATCH 15/69] Use mutex to stablize ncclCtxMap --- paddle/fluid/platform/nccl_helper.h | 50 +++++++++-------------------- 1 file changed, 16 insertions(+), 34 deletions(-) diff --git a/paddle/fluid/platform/nccl_helper.h b/paddle/fluid/platform/nccl_helper.h index ca9ab2c7ae..0013597fd5 100644 --- a/paddle/fluid/platform/nccl_helper.h +++ b/paddle/fluid/platform/nccl_helper.h @@ -39,20 +39,19 @@ inline ncclDataType_t ToNCCLDataType(std::type_index type) { class NCCLGroupGuard { public: + static std::mutex &NCCLMutex() { + static std::mutex mtx; + return mtx; + } + inline NCCLGroupGuard() { - mutex().lock(); + NCCLMutex().lock(); PADDLE_ENFORCE(dynload::ncclGroupStart()); } inline ~NCCLGroupGuard() { PADDLE_ENFORCE(dynload::ncclGroupEnd()); - mutex().unlock(); - } - - private: - static std::mutex &mutex() { - static std::mutex mtx; - return mtx; + NCCLMutex().unlock(); } }; @@ -68,26 +67,6 @@ struct NCCLContext { int device_id() const { return boost::get(ctx_->GetPlace()).device; } - - static void InitNCCLContext(std::unordered_map *contexts, - const std::vector &places) { - std::vector comms; - std::vector devs; - comms.resize(contexts->size()); - devs.reserve(contexts->size()); - - for (auto &p : places) { - devs.push_back(boost::get(p).device); - } - - PADDLE_ENFORCE(platform::dynload::ncclCommInitAll( - &comms[0], static_cast(contexts->size()), &devs[0])); - - int i = 0; - for (auto &dev_id : devs) { - contexts->at(dev_id).comm_ = comms[i++]; - } - } }; struct NCCLContextMap { @@ -107,12 +86,12 @@ struct NCCLContextMap { "NCCL Context Map does not support contain two or more same device"); if (places.size() > 1) { - std::vector comms; - comms.resize(order_.size()); - - PADDLE_ENFORCE(platform::dynload::ncclCommInitAll( - &comms[0], static_cast(order_.size()), &order_[0])); - + std::unique_ptr comms(new ncclComm_t[order_.size()]); + { + std::lock_guard guard(NCCLGroupGuard::NCCLMutex()); + PADDLE_ENFORCE(platform::dynload::ncclCommInitAll( + comms.get(), static_cast(order_.size()), order_.data())); + } int i = 0; for (auto &dev_id : order_) { contexts_.at(dev_id).comm_ = comms[i++]; @@ -120,6 +99,9 @@ struct NCCLContextMap { } } + NCCLContextMap(const NCCLContextMap &other) = delete; + NCCLContextMap &operator=(const NCCLContextMap &other) = delete; + CUDADeviceContext *DevCtx(int dev_id) const { return at(dev_id).ctx_.get(); } CUDADeviceContext *DevCtx(platform::Place p) const { From d0342f12aabd51979e86249f5450fb099393c449 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Mon, 16 Apr 2018 11:33:15 +0800 Subject: [PATCH 16/69] Simplify DelayOps Logic --- .../details/threaded_ssa_graph_executor.cc | 43 +++++++------------ .../tests/unittests/test_parallel_executor.py | 5 ++- 2 files changed, 18 insertions(+), 30 deletions(-) diff --git a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc index a371ee10fe..927078bc64 100644 --- a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc +++ b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc @@ -51,8 +51,6 @@ FeedFetchList ThreadedSSAGraphExecutor::Run( // together since we currently cannot overlap computation and memcpy streams. // Should revisit it if overlapping is available. std::unordered_set delayed_ops; - std::unordered_set blocked_by_delayed_ops; - std::unordered_set delayed_vars; auto InsertPendingVar = [&pending_vars, &ready_vars](VarHandleBase &var) { pending_vars.insert(&var); @@ -122,24 +120,26 @@ FeedFetchList ThreadedSSAGraphExecutor::Run( InsertPendingOp(*op); } - auto run_all_ready_ops = [&] { - for (auto *op : ready_ops) { - if (op->IsMultiDeviceTransfer() && allow_op_delay_) { - delayed_ops.insert(op); - delayed_vars.insert(op->outputs_.begin(), op->outputs_.end()); - ready_vars.Extend(op->outputs_); - continue; - } + auto run_all_ops = [&](std::unordered_set &set) { + for (auto *op : set) { running_ops_++; RunOp(&ready_vars, op); } - ready_ops.clear(); + set.clear(); }; // Step 3. Execution - while (!pending_vars.empty() || !ready_ops.empty() || !delayed_ops.empty()) { + while (!pending_vars.empty()) { // 1. Run All Ready ops - run_all_ready_ops(); + // Keep loop until all vars are ready. + // + // NOTE: DelayedOps have a lower priority. It will be scheduled after all + // ready_ops have been performed. + if (ready_ops.empty() && allow_op_delay_) { + run_all_ops(delayed_ops); + } else { + run_all_ops(ready_ops); + } // 2. Find ready variable bool timeout; @@ -160,29 +160,16 @@ FeedFetchList ThreadedSSAGraphExecutor::Run( auto &deps = pending_ops[op]; --deps; if (deps == 0) { - if (delayed_vars.find(ready_var) != delayed_vars.end()) { - blocked_by_delayed_ops.insert(op); + if (op->IsMultiDeviceTransfer() && allow_op_delay_) { + delayed_ops.insert(op); } else { ready_ops.insert(op); } } } } - // When there are no other ops to schedule, schedule buffered delayed - // ops and unblock other ops. - if (ready_ops.empty() && !delayed_ops.empty() && running_ops_ == 0) { - RunDelayedOps(delayed_ops); - delayed_ops.clear(); - for (auto *op : blocked_by_delayed_ops) { - ready_ops.insert(op); - } - blocked_by_delayed_ops.clear(); - } - // Keep loop until all vars are ready. } PADDLE_ENFORCE(ready_ops.empty()); - PADDLE_ENFORCE(delayed_ops.empty()); - PADDLE_ENFORCE(blocked_by_delayed_ops.empty()); // Wait FetchOps. if (!fetch_ops.empty()) { diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor.py b/python/paddle/fluid/tests/unittests/test_parallel_executor.py index 83d22fd799..0cd88d61e1 100644 --- a/python/paddle/fluid/tests/unittests/test_parallel_executor.py +++ b/python/paddle/fluid/tests/unittests/test_parallel_executor.py @@ -206,18 +206,19 @@ class TestParallelExecutorBase(unittest.TestCase): feed_dict={}): main = fluid.Program() startup = fluid.Program() + startup.random_seed = 1 # Fix random seed with fluid.program_guard(main, startup): loss = method(use_feed=len(feed_dict) > 0) adam = fluid.optimizer.Adam() adam.minimize(loss) if memory_opt: fluid.memory_optimize(main) - place = fluid.CUDAPlace(0) startup_exe = fluid.Executor(place) startup_exe.run(startup) - exe = fluid.ParallelExecutor(True, loss_name=loss.name) + exe = fluid.ParallelExecutor( + True, loss_name=loss.name, allow_op_delay=allow_op_delay) if batch_size is not None: batch_size *= fluid.core.get_cuda_device_count() begin = time.time() From 8d73752c737d29eb00d5b3ea6bcd754c4c7f93c8 Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Mon, 16 Apr 2018 12:00:09 +0800 Subject: [PATCH 17/69] add async update design doc --- doc/fluid/design/dist_train/async_update.md | 52 ++++++++++++++++++ .../dist_train/src/async_pserver.graffle | Bin 0 -> 10621 bytes .../design/dist_train/src/async_pserver.png | Bin 0 -> 164416 bytes .../dist_train/src/async_update.graffle | Bin 0 -> 8121 bytes .../design/dist_train/src/async_update.png | Bin 0 -> 192539 bytes 5 files changed, 52 insertions(+) create mode 100644 doc/fluid/design/dist_train/async_update.md create mode 100644 doc/fluid/design/dist_train/src/async_pserver.graffle create mode 100644 doc/fluid/design/dist_train/src/async_pserver.png create mode 100644 doc/fluid/design/dist_train/src/async_update.graffle create mode 100644 doc/fluid/design/dist_train/src/async_update.png diff --git a/doc/fluid/design/dist_train/async_update.md b/doc/fluid/design/dist_train/async_update.md new file mode 100644 index 0000000000..05175596f7 --- /dev/null +++ b/doc/fluid/design/dist_train/async_update.md @@ -0,0 +1,52 @@ +# Design Doc: Asynchronous Update With Distributed Training + +## Background + +For the typical synchronous distributed training, some significant steps are as follows: + +1. A Trainer will compute the gradients and SEND them to the Parameter +Server(PServer) nodes. +1. After the PServer node received gradients came from all the Trainers, it would apply the gradient to the respective variables, and using an optimize algorithms(SGD, + Momentment...) to update the parameters. +1. The Trainer would wait for the PServers finished the optimize stage, and GET the parameters from PServer, so all the Trainers would get the same parameters. + +In the synchronously distributed training, there should be a `Barrier` to synchronise the +parameters after the optimizing stage. The performance of a distributed training job +depends on the lowest node, if there were hundreds or thousand training nodes in a Job, +the performance of synchronously distributed training might be very slow because of +the slow node. So this design doc would introduce an approach to implement +*asynchronously* distributed training in PaddlePaddle Fluid. + +## Design + + + +As the figure above, we describe a global view of asynchronously update process and use +the parameter `w1` as an example to introduce the steps: +1. For each gradient variables, they may distribute on different GPU card and aggregate +them while they are all calculated. +1. Split the gradient variable into multiple blocks according to the number of PServer +instances and sent them. +1. PServer would run an `Optimize Block` to use a specified optimize algorithm to update +the specified parameter, such as `w1`. +1. The trainer will fetch the latest parameter after PServer finished the optimize stage. +1. Broadcast the received variable into multiple GPU cards and continue to run the next +mini-batch. + +### Trainer + +- We need a new Operator named `RemoteOptimize` to send gradients to multiple PServer +instances and fetch the latest parameter. +- There could be a large number of gradient variables to be sent, so we need to use another +thread pool(IO Threadpool) which number of the schedulable threads is larger than the +computing thread pool to avoid competitive the thread resources with computing. + +### Parameter Server + + + +- There should be multiple trainer instances want to optimize the same parameter at +the same time, to avoid the pollution, we need one `BlockingQueue` for each gradient +variable to process them one by one. +- We need a `Map` structure to map a gradient variable name to the `OptimizeBlock` which +can optimize the respective parameter. diff --git a/doc/fluid/design/dist_train/src/async_pserver.graffle b/doc/fluid/design/dist_train/src/async_pserver.graffle new file mode 100644 index 0000000000000000000000000000000000000000..110eec7f9b3f26034cd90feb188b558c11f7ce02 GIT binary patch literal 10621 zcmaLc^H(Mgqb=}kYjRDtZA>-Ut|x1T@IT{t#;VLwuwP&=*)> zd-c_M{oH-~!_eY?@l;vyYRIWZlFeWR7yT&!Yz6>wOPXp)tiw?4PW=qNIVXO~<-Ar9 z@EroTKMqSr`9C(WzVT^jZ!a^O3O{6l9&G7>)kizb!q{d2(3i9RMmU4CxG?Z>9kt;# zVygOq?=ejHfj^1hmj{%8?=SU)8#JOgI~u<;1IiZs1nulYSLh|9b8LI8EvvUQ#3t*M zrIfNZ?Yw3wFfirfcwK(HL>FIU0-l3G2C2-!dzwCcf(CwAn3M{3&P6T9$Jmv5Qx!sN z1YHpYyUxnRzpR!RW6h}!4>#;xm$P}a@M5_{E0daog4G9>0f?1|z!a+XQLVabzeU2P z2kMGf0UiAZhD>XUs}iq`IgwbTB-dmfx2yq2T{}}}FDuS)-!C2EDX#n8ax1u*RD!mu z?z&8jvSz*6NNjbxOVue~1Dj`!>pSZs#7rHSrKOf`<3gxQ3dgl;?d)?!EyoE}4k6v= z?(ws-sj~#xey7cmwl*xX+*FjuB)Id&8lK8Q+aB^g6WAH6^<%&Jueq?{;#lpd?`}S` zioYgcTev7`G9x0Q;S$A8I5uZ`ina~>)7$;~LGX)frBusPD>{*k_;NNk_G|!~_htca zB~=xIR&*@EWZ4kuO#{l3#c%?UhIu7*IhWIs=tn8T@a!*I+uSH^&WA@vg+M|&emUiD zu8Pmi7sBEjS)+*V9^s!dZ$lTik&iz2DH9gkuPkQ77KoS`OwV0q8295^&^3-B_(Hi> zZ}ukSBf%X9zOa-Kn6vNYGTBX|lm=Lf8o);gDM#co^P=wPp@`(+9FO3n`oNDvvc`po#O#0+q<;ZxZ>V3r#v(&C)nR9FE)+LuyX@m-et(u+v~(Qq$h?UdSRi zs-|+tC|DKfFys_6OiYn@9ic8R<6gtwstBZ7GzT9DXg&1-rZI@_vi#o*feC?)WaKQ7 zBA3aw!U5%wC;?;vmO-i#VfDH9-+I!{U=|DGX$oLNWixqrhP|q7!UO?{;-ZTif9cm> zl@(K0*KjO}M=3?I8xgQ_3?g_PX23k}4FzAz4Ut#2U@F6EA(zUV}cC%p6`D_NL)m_Pl(5+u8zbC5O(CNY!lzFQ( za}SE{M~rKumj-1`TxN?{PD2AGq;}BLApa`Hc%q~&#NMeL_G{C zr_P}hfxp(q`KS=A`RUchEV(8b(MFR3bW zEr{^2oo=tGYDU7($WLlLN2#Yjta2u9g!zShK!-)gcqvoUYjq>pWNh@qqAasN*<_!k zmP5Wkyp^=205b;$Q9EG)PMcw4zv{vrd7IhE9p$91wzrtKB3Nx7*AsQVssvL8!a1_p zXn~Xcu(7aFtG_{?ApBl4ld#fRpY8#^aG;$W7pv3hUf(9hC~e8nD3bNFZ^!TsN-EW8 z@Z#MFXsYLHX}eFzMYsU7lJMP@z zqE2vFw#KR8wozW9KX6wAC`i4mATMH}FrlX!UZ=zEu1h93&AE{uGCN^-6)EMDL=|-0 z21&Wubd#Y;D~>6cV4Z~bGT~gilR9NaT;u%G56KC7g8h-Po(Cwpb1I%;5CRxb({)-oC@{c1%San78|gD)CO? 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zwsC-M^lvn&_I(kxqZgpimmi2K<)(ZSkncWkiv>cD11m6e8WWage(5dhz%-@es(J4G zfCgBL-IJ%hB3h1gI)N&N9rCy6n?%BOuF;0cXA$ASulyCF6ae`gR~I|C`$M;wx)s1* ztI8hKyq`yRVN~{Zr zGGv4+X5Sn`Bmk;rBt;9q2+lQAF*SZSgfxZ!Y!najmWb(&VXuM{e4&>UP@nxRz&9kl zfxyk%VOG^Qu2GcWJ2u%W#Wq<;4gzO|;ZOom`pi~Qs#vjo3VrMX)|h^LD86CV{Ww#e zM2D3#%s(x;&Vp4}?ycF3qUR0r+lS5af}p0W}d zK}ROx;Vm6rKa0t&i?SPg?GYK|N)VENOmMD&$F|d9-?vXRDr$6-i0Z6yUvP^4&ZlhM54MEbpa7z{IWDn!SLZRhi~Cp%w9w@ z6GJDm=l{pn(Baa5O^3P1&f_3$t;Tu(fiPWvZ%eckwE%S$rP;eO3$RfoW=#8?M4=c<@z2G{{ZTM$7uin literal 0 HcmV?d00001 From 8c1b257596ecdd10b170af75a0d033f671aa519e Mon Sep 17 00:00:00 2001 From: typhoonzero Date: Mon, 16 Apr 2018 12:54:58 +0800 Subject: [PATCH 18/69] add dist unitest data compare --- paddle/fluid/operators/listen_and_serv_op.cc | 15 ++-- paddle/fluid/operators/listen_and_serv_op.h | 2 +- paddle/fluid/operators/send_recv_op_test.cc | 6 -- python/paddle/fluid/layers/io.py | 15 ++-- .../fluid/tests/unittests/test_recv_op.py | 71 ------------------- 5 files changed, 22 insertions(+), 87 deletions(-) delete mode 100644 python/paddle/fluid/tests/unittests/test_recv_op.py diff --git a/paddle/fluid/operators/listen_and_serv_op.cc b/paddle/fluid/operators/listen_and_serv_op.cc index 5d293665f0..a4c925b538 100644 --- a/paddle/fluid/operators/listen_and_serv_op.cc +++ b/paddle/fluid/operators/listen_and_serv_op.cc @@ -12,6 +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. */ +#include #include #include // NOLINT #include @@ -67,7 +68,7 @@ ListenAndServOp::ListenAndServOp(const std::string &type, const framework::AttributeMap &attrs) : OperatorBase(type, inputs, outputs, attrs) {} -int ListenAndServOp::GetSelectedPort() { +int ListenAndServOp::GetSelectedPort() const { return rpc_service_->GetSelectedPort(); } @@ -99,7 +100,7 @@ void ListenAndServOp::RunImpl(const framework::Scope &scope, framework::Executor executor(dev_place); std::vector block_list; for (size_t blkid = 1; blkid < num_blocks; ++blkid) { - if (blkid != prefetch_block->ID()) { + if (blkid != static_cast(prefetch_block->ID())) { block_list.push_back(blkid); } } @@ -121,10 +122,14 @@ void ListenAndServOp::RunImpl(const framework::Scope &scope, rpc_service_->SetProgram(program); // start the server listening after all member initialized. server_thread_.reset(new std::thread(RunServer, rpc_service_)); - // FIXME(typhoonzero): do we need to wait until the server port is ready? + VLOG(3) << "wait server thread to become ready..."; sleep(5); + // Write to a file of server selected port for python use. + std::ofstream port_file; + port_file.open("/tmp/paddle.selected_port"); + port_file << rpc_service_->GetSelectedPort(); + port_file.close(); - // TODO(typhoonzero): change this to a while_op for every cluster-batch. bool exit_flag = false; // Record received sparse variables, so that // we could reset those after execute optimize program @@ -175,7 +180,7 @@ void ListenAndServOp::RunImpl(const framework::Scope &scope, parallel_blkids.push_back(1); double ts = detail::GetTimestamp(); for (size_t blkid = 2; blkid < num_blocks; ++blkid) { - if (blkid != prefetch_block->ID()) { + if (blkid != static_cast(prefetch_block->ID())) { if (program->Block(blkid).Parent() != last_parent_blkid) { ParallelExecuteBlocks(parallel_blkids, &executor, optimize_prepared, program, &recv_scope); diff --git a/paddle/fluid/operators/listen_and_serv_op.h b/paddle/fluid/operators/listen_and_serv_op.h index 759b2a462b..9744921cef 100644 --- a/paddle/fluid/operators/listen_and_serv_op.h +++ b/paddle/fluid/operators/listen_and_serv_op.h @@ -39,7 +39,7 @@ class ListenAndServOp : public framework::OperatorBase { const framework::VariableNameMap &outputs, const framework::AttributeMap &attrs); - int GetSelectedPort(); + int GetSelectedPort() const; void Stop() override; diff --git a/paddle/fluid/operators/send_recv_op_test.cc b/paddle/fluid/operators/send_recv_op_test.cc index 3bf5d57809..a342874f97 100644 --- a/paddle/fluid/operators/send_recv_op_test.cc +++ b/paddle/fluid/operators/send_recv_op_test.cc @@ -139,7 +139,6 @@ void StartServerNet(bool is_sparse) { attrs.insert({"PrefetchBlock", prefetch_block}); listen_and_serv_op = f::OpRegistry::CreateOp("listen_and_serv", {{"X", {"x1"}}}, {}, attrs); - LOG(INFO) << "selected port before run " << selected_port; listen_and_serv_op->Run(scope, place); LOG(INFO) << "server exit"; } @@ -158,16 +157,13 @@ TEST(SendRecvOp, CPUDense) { selected_port = static_cast( listen_and_serv_op.get()) ->GetSelectedPort(); - LOG(INFO) << "selected port " << selected_port; std::string endpoint = paddle::string::Sprintf("127.0.0.1:%d", selected_port); attrs.insert({"endpoints", std::vector({endpoint})}); attrs.insert({"epmap", std::vector({endpoint})}); auto send_op = f::OpRegistry::CreateOp( "send", {{"X", {"x1"}}}, {{"Out", {"Out"}}, {"RPCClient", {"RPC_CLIENT_VAR"}}}, attrs); - LOG(INFO) << "before run " << endpoint; send_op->Run(scope, place); - LOG(INFO) << "end run"; auto in_var = scope.Var("x1"); auto tensor = in_var->GetMutable(); @@ -180,7 +176,6 @@ TEST(SendRecvOp, CPUDense) { for (int64_t i = 0; i < target->numel(); ++i) { EXPECT_EQ(expected[i] * 2, actual[i]); } - LOG(INFO) << "before stop"; listen_and_serv_op->Stop(); server_thread.join(); listen_and_serv_op.reset(nullptr); @@ -199,7 +194,6 @@ TEST(SendRecvOp, CPUSparse) { selected_port = static_cast( listen_and_serv_op.get()) ->GetSelectedPort(); - LOG(INFO) << "selected port " << selected_port; std::string endpoint = paddle::string::Sprintf("127.0.0.1:%d", selected_port); attrs.insert({"endpoints", std::vector({endpoint})}); attrs.insert({"epmap", std::vector({endpoint})}); diff --git a/python/paddle/fluid/layers/io.py b/python/paddle/fluid/layers/io.py index e7d6c4e252..ead57ac370 100644 --- a/python/paddle/fluid/layers/io.py +++ b/python/paddle/fluid/layers/io.py @@ -13,7 +13,7 @@ # limitations under the License. from .. import core -from ..framework import convert_np_dtype_to_dtype_, default_main_program, default_startup_program +from ..framework import convert_np_dtype_to_dtype_, default_main_program, default_startup_program, Program from ..unique_name import generate as unique_name from control_flow import BlockGuard from ..layer_helper import LayerHelper @@ -158,6 +158,7 @@ class ListenAndServ(object): main_program = self.helper.main_program current_block = main_program.current_block() parent_block = self.parent_block() + empty_block = Program().global_block() parent_block.append_op( type='listen_and_serv', @@ -166,11 +167,12 @@ class ListenAndServ(object): attrs={ 'endpoint': self.endpoint, 'Fanin': self.fan_in, - 'OptimizeBlock': current_block + 'OptimizeBlock': current_block, + 'PrefetchBlock': empty_block }) -def Send(endpoints, send_vars, get_vars): +def Send(endpoints, send_vars, get_vars=None): """ Send layer @@ -184,7 +186,6 @@ def Send(endpoints, send_vars, get_vars): side when server have finished running server side program. """ assert (type(send_vars) == list) - assert (type(get_vars) == list) epmap = endpoints.split(",") endpoints = list(set(epmap)) @@ -192,6 +193,11 @@ def Send(endpoints, send_vars, get_vars): helper = LayerHelper("Send", **locals()) rpc_client_var = default_main_program().global_block().create_var( name="RPC_CLIENT_VAR", persistable=True, type=core.VarDesc.VarType.RAW) + if not get_vars: + get_vars = [] + for s in send_vars: + v = helper.create_tmp_variable(dtype=s.dtype, stop_gradient=True) + get_vars.append(v) helper.append_op( type="send", @@ -200,6 +206,7 @@ def Send(endpoints, send_vars, get_vars): "RPCClient": rpc_client_var}, attrs={"endpoints": endpoints, "epmap": epmap}) + return get_vars def Recv(endpoints, get_vars): diff --git a/python/paddle/fluid/tests/unittests/test_recv_op.py b/python/paddle/fluid/tests/unittests/test_recv_op.py deleted file mode 100644 index 2ebceca7e4..0000000000 --- a/python/paddle/fluid/tests/unittests/test_recv_op.py +++ /dev/null @@ -1,71 +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. - -import unittest - -import paddle.fluid as fluid -import paddle.fluid.layers as layers -import numpy -from multiprocessing import Process -import os, sys -import time - - -class TestRecvOp(unittest.TestCase): - def no_test_send(self): - # Run init_serv in a thread - place = fluid.CPUPlace() - p = Process(target=self.init_serv, args=(place, )) - p.daemon = True - p.start() - time.sleep(1) - self.init_client(place) - # FIXME(typhoonzero): find a way to gracefully shutdown the server. - os.system("kill -9 %d" % p.pid) - p.join() - - def init_serv(self, place): - main = fluid.Program() - with fluid.program_guard(main): - serv = layers.ListenAndServ( - "127.0.0.1:6174", ["X"], optimizer_mode=False) - with serv.do(): - x = layers.data( - shape=[32, 32], - dtype='float32', - name="X", - append_batch_size=False) - fluid.initializer.Constant(value=1.0)(x, main.global_block()) - o = layers.scale(x=x, scale=10.0) - main.global_block().create_var( - name=o.name, psersistable=False, dtype=o.dtype, shape=o.shape) - exe = fluid.Executor(place) - exe.run(main) - - def init_client(self, place): - main = fluid.Program() - with fluid.program_guard(main): - x = layers.data( - shape=[32, 32], - dtype='float32', - name='X', - append_batch_size=False) - fluid.initializer.Constant(value=1.0)(x, main.global_block()) - layers.Send("127.0.0.1:6174", [x], [x]) - exe = fluid.Executor(place) - exe.run(main) - - -if __name__ == "__main__": - unittest.main() From 34cffe916968f998770d5a876650e888bfbcb0f6 Mon Sep 17 00:00:00 2001 From: typhoonzero Date: Mon, 16 Apr 2018 13:04:30 +0800 Subject: [PATCH 19/69] add unitest file --- .../tests/unittests/test_dist_train_op.py | 100 ++++++++++++++++++ 1 file changed, 100 insertions(+) create mode 100644 python/paddle/fluid/tests/unittests/test_dist_train_op.py diff --git a/python/paddle/fluid/tests/unittests/test_dist_train_op.py b/python/paddle/fluid/tests/unittests/test_dist_train_op.py new file mode 100644 index 0000000000..d3f4f74fe7 --- /dev/null +++ b/python/paddle/fluid/tests/unittests/test_dist_train_op.py @@ -0,0 +1,100 @@ +# 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 +import numpy +from multiprocessing import Process +from threading import Thread +import os, sys +import time + + +class TestSendOp(unittest.TestCase): + def test_send(self): + # Run init_serv in a thread + place = fluid.CPUPlace() + # NOTE: python thread will not work here due to GIL. + p = Process(target=self.init_serv, args=(place, )) + p.daemon = True + p.start() + + time.sleep(8) + with open("/tmp/paddle.selected_port", "r") as fn: + selected_port = int(fn.readlines()[0]) + self.init_client(place, selected_port) + # FIXME(typhoonzero): find a way to gracefully shutdown the server. + os.system("kill -9 %d" % p.pid) + p.join() + + self.run_local(place) + self.assertTrue(numpy.allclose(self.local_out, self.dist_out)) + + def init_serv(self, place): + main = fluid.Program() + + with fluid.program_guard(main): + serv = layers.ListenAndServ( + "127.0.0.1:0", ["X"], optimizer_mode=False) + with serv.do(): + x = layers.data( + shape=[32, 32], + dtype='float32', + name="X", + append_batch_size=False) + fluid.initializer.Constant(value=1.0)(x, main.global_block()) + o = layers.scale(x=x, scale=10.0) + main.global_block().create_var( + name=o.name, psersistable=False, dtype=o.dtype, shape=o.shape) + + self.server_exe = fluid.Executor(place) + self.server_exe.run(main) + + def init_client(self, place, port): + main = fluid.Program() + with fluid.program_guard(main): + x = layers.data( + shape=[32, 32], + dtype='float32', + name='X', + append_batch_size=False) + fluid.initializer.Constant(value=2.3)(x, main.global_block()) + get_var = main.global_block().create_var( + name="scale_0.tmp_0", # server side var + dtype="float32", + persistable=False, + shape=[32, 32]) + o = layers.Send("127.0.0.1:%d" % port, [x], [get_var]) + exe = fluid.Executor(place) + self.dist_out = exe.run(main, fetch_list=o) # o is a list + + def run_local(self, place): + main = fluid.Program() + with fluid.program_guard(main): + x = layers.data( + shape=[32, 32], + dtype='float32', + name='X', + append_batch_size=False) + fluid.initializer.Constant(value=2.3)(x, main.global_block()) + o = layers.scale(x=x, scale=10.0) + exe = fluid.Executor(place) + self.local_out = exe.run(main, fetch_list=[o]) + + +if __name__ == "__main__": + unittest.main() From 5bf671b4aa22950d4d83e333792dfc1670639e82 Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Mon, 16 Apr 2018 15:14:22 +0800 Subject: [PATCH 20/69] structure optimized, more detail --- .../design/dist_train/mpi_enabled_design.md | 55 ++++++++++++------- 1 file changed, 34 insertions(+), 21 deletions(-) diff --git a/doc/fluid/design/dist_train/mpi_enabled_design.md b/doc/fluid/design/dist_train/mpi_enabled_design.md index 2548c6cdf5..4ad3afc7b7 100644 --- a/doc/fluid/design/dist_train/mpi_enabled_design.md +++ b/doc/fluid/design/dist_train/mpi_enabled_design.md @@ -1,33 +1,46 @@ -#MPI-enabled PaddlePaddle Design doc +# MPI-enabled PaddlePaddle Design doc # Background -Now, PaddlePaddle Fluid with Distribution has relatively large network bottleneck, We want to use RDMA and GPUDriect to improve and solve it, so we enabled the features to PaddlePaddle with the help of MPI. +When we do distribute multi GPU training, the communication overhead between servers become the major bottleneck, because of the following reasons: +1. Must copy at least once from GPU to CPU memory so that the data can be ready to transfer. And for the pserver side, copy data from CPU to GPU introduce more overhead. +2. GPU->CPU data transfer is 10 times slower than data transfer between GPUs or between PCIe devices. +3. TCP connections can not make full use of RDMA 100Gb devices. -We will introduce Open MPI API to PaddlePaddle, which can bring two benefits to PaddlePaddle: +We will use OpenMPI API to PaddlePaddle, which can bring two benefits to PaddlePaddle: 1. Enable RDMA with PaddlePaddle, which bring high-performance low latency networks. 2. Enable GPUDriect with PaddlePaddle, which bring the highest throughput and lowest latency GPU read and write. -## Execute args -Launch the script using the ```mpirun``` launcher, For example: ```mpirun -np 3 -hosts node1,node2,node3 python train.py```. By doing this, We can number the actors (trainer/pserver/master) with o .. (n-1). The node's number is the Rank of the calling process in a group of comm (integer), The MPI processes identify each other using a Rank ID. We have to create a mapping between PaddlePaddle's actors and their Rank ID so that we can communicate with the correct destinations when using MPI operations. - **We have to store the Rank ID and the mapping in global variables.** +# Change list +* Compile args: Need add compile args to enable MPI support. +* Execute args: Need add execute args to assign when and how to use MPI operations. +* New ops: Need new op ```mpi_send_op``` and ```mpi_listenandserve_op``` to support MPI send and receive. +* Transpiler optimized: Which can add ```mpi_send_op``` and ```mpi_listenandserve_op``` to the running graph. +* MPI utils package: Need MPI utils package as the low-level API supported. + +## Compile args +Because MPI or CUDA need hardware supported, so we will add compile args to enable MPI support and control compiling.Add ```WITH_MPI``` compile args to control MPI to use or not. If the ```WITH_MPI``` is ```ON```, compile system will find openMPI codes in configuration. We should prepare openMPI environment before compiling. -## New OP/MODULE -We won't replace all the gRPC requests to MPI requests, the standard gRPC library is used for all administrative operations and the MPI API will be used to transfer tensor or selectRows to Pservers. The base of this idea, we create two new operators to handle requests and receives, the two operators are send_mpi_op and listenandserve_mpi_op. They are a little similar with [send_op](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/fluid/operators/send_op.cc) and [listen_and_serv_op](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/fluid/operators/listen_and_serv_op.cc), also, We will build a new module to package MPI send and receive process. +## Execute args +Launch the script using the ```mpirun``` launcher, For example: ```mpirun -np 3 -hosts node1,node2,node3 python train.py```. By doing this, We can number the actors (trainer/pserver/master) with o .. (n-1). The node's number is the Rank of the calling process in a group of comm (integer), The MPI processes identify each other using a Rank ID. We have to create a mapping between PaddlePaddle's nodes and their Rank ID so that we can communicate with the correct destinations when using MPI operations. -### mpi_module -We will build a new module to package MPI send and receive process. MPI send and recvice are defferent to gRPC, the MPI [recvice](https://www.open-mpi.org/doc/v1.8/man3/MPI_Irecv.3.php) must know receive buffer size and receive buffer element. For this reason, We have to make conmunications twice, the first one is to send metadata about gradient through gRPC, the second one is the real conmunications through MPI which send gradient data to mpi_listenandserve_op. -The detail flow is below: -![](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/fluid/design/dist_train/src/mpi_module.png) +## New ops +We won't replace all the gRPC requests to MPI requests, the standard gRPC library is used for all administrative operations and the MPI API will be used to transfer tensor or selectRows to Pservers. The base of this idea, we create two new operators to handle requests and receives, the two operators are ```mpi_send_op``` and ```mpi_listenandserve_op```. They are a little similar to [send_op](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/fluid/operators/send_op.cc) and [listen_and_serv_op](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/fluid/operators/listen_and_serv_op.cc), also, We will build a new module to package MPI send and receive process. ### mpi_send_op -Very similar with ```send_op```, we will replace gRPC code which used to send gradient with ```mpi_module```, at the same time , we will wrap it with ```framework::Async```. +Very similar with ```send_op```, we will replace gRPC code which used to send gradient with ```mpi_module```, at the same time, we will wrap it with ```framework::Async```. ### mpi_listenandserve_op -Very similar with ```listen_and_serv_op```, we will replace gRPC code which used to receive gradient with ```mpi_module```, at the same time , we will wrap it with ```framework::Async```. - -### modify distribute_transpiler.py -Need to add args to distinguish use MPI or not. if confirm to use MPI, we will modify ```send_op``` to ```mpi_send_op``` in distribute_transpiler, and modify ```listenandserve_op``` to ```mpi_listenandserve_op``` also. - -## Build args -Because MPI or CUDA need hardware supported, so we will add some build args to control compiling. -**The specific arguments are under design** \ No newline at end of file +Very similar with ```listen_and_serv_op```, we will replace gRPC code which used to receive gradient with ```mpi_module```, at the same time, we will wrap it with ```framework::Async```. + +## Transpiler optimized +**We can get env ```OMPI_COMM_WORLD_SIZE``` and ```OMPI_COMM_WORLD_RANK``` to distinguish use MPI or not, If we use openMPI, the variable in env must exist.** + if confirm to use MPI, we will modify ```send_op``` to ```mpi_send_op``` in distribute_transpiler, and modify ```listenandserve_op``` to ```mpi_listenandserve_op``` also. + +## MPI utils package +In this package, We will write openMPI low-level API to use MPI. +The API included in this package are: +* MPI send and receive module, We will build a new module to package MPI send and receive process. MPI send and receive are different to gRPC, the MPI [recvice](https://www.open-mpi.org/doc/v1.8/man3/MPI_Irecv.3.php) must know receive buffer size and receive buffer element. For this reason, We have to make communications twice, the first one is to send metadata about gradient through gRPC, the second one is the real communication through MPI which send gradient data to mpi_listenandserve_op. +The detailed flow is below: +![](https://github.com/seiriosPlus/Paddle/blob/mpi_enabled/doc/fluid/design/dist_train/src/mpi_module.png) +* MPI global configurations, which store the Rank ID and the mapping in global variables, for example: +gRPC client : MPI nodes :``` 127.0.0.1:32004 : 3 ``` From 5fc8326732bcd5a40fd96190ba0fbc9a1fc135d1 Mon Sep 17 00:00:00 2001 From: fengjiayi Date: Mon, 16 Apr 2018 17:05:01 +0800 Subject: [PATCH 21/69] Add parallel accuracy test --- .../tests/unittests/test_parallel_executor.py | 24 +++++++++++++++++-- 1 file changed, 22 insertions(+), 2 deletions(-) diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor.py b/python/paddle/fluid/tests/unittests/test_parallel_executor.py index 83d22fd799..fda8651032 100644 --- a/python/paddle/fluid/tests/unittests/test_parallel_executor.py +++ b/python/paddle/fluid/tests/unittests/test_parallel_executor.py @@ -203,10 +203,14 @@ class TestParallelExecutorBase(unittest.TestCase): iter=10, batch_size=None, allow_op_delay=False, - feed_dict={}): + feed_dict={}, + random_seed=None, + use_parallel_executor=True): main = fluid.Program() startup = fluid.Program() with fluid.program_guard(main, startup): + if seed is not None: + startup.random_seed(random_seed) loss = method(use_feed=len(feed_dict) > 0) adam = fluid.optimizer.Adam() adam.minimize(loss) @@ -217,7 +221,11 @@ class TestParallelExecutorBase(unittest.TestCase): startup_exe = fluid.Executor(place) startup_exe.run(startup) - exe = fluid.ParallelExecutor(True, loss_name=loss.name) + if use_parallel_executor: + exe = fluid.ParallelExecutor(True, loss_name=loss.name) + else: + exe = fluid.Executor(place=place) + if batch_size is not None: batch_size *= fluid.core.get_cuda_device_count() begin = time.time() @@ -238,6 +246,7 @@ class TestParallelExecutorBase(unittest.TestCase): print first_loss, last_loss # self.assertGreater(first_loss[0], last_loss[0]) + return first_loss, last_loss class TestMNIST(TestParallelExecutorBase): @@ -267,6 +276,17 @@ class TestMNIST(TestParallelExecutorBase): simple_fc_net, feed_dict={"image": img, "label": label}) + def test_simple_fc_parallel_accuracy(self): + single_first_loss, single_last_loss = self.check_network_convergence( + simple_fc_net, random_seed=0, use_parallel_executor=False) + parallel_first_loss, parallel_last_loss = self.check_network_convergence( + simple_fc_net, random_seed=0, use_parallel_executor=True) + print("FUCK") + print('single_first_loss=', single_first_loss) + print('single_last_loss=', single_last_loss) + print('parallel_first_loss=', parallel_first_loss) + print('parallel_last_loss=', parallel_last_loss) + def test_batchnorm_fc(self): self.check_network_convergence(fc_with_batchnorm) img = numpy.zeros(shape=[32, 784], dtype='float32') From fbd5cf604faf9ac2ad6140b503f312bbff10c7c7 Mon Sep 17 00:00:00 2001 From: JiayiFeng Date: Mon, 16 Apr 2018 09:38:44 +0000 Subject: [PATCH 22/69] stash --- .../fluid/tests/unittests/test_parallel_executor.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor.py b/python/paddle/fluid/tests/unittests/test_parallel_executor.py index fda8651032..e311ebec36 100644 --- a/python/paddle/fluid/tests/unittests/test_parallel_executor.py +++ b/python/paddle/fluid/tests/unittests/test_parallel_executor.py @@ -204,13 +204,13 @@ class TestParallelExecutorBase(unittest.TestCase): batch_size=None, allow_op_delay=False, feed_dict={}, - random_seed=None, + seed=None, use_parallel_executor=True): main = fluid.Program() startup = fluid.Program() with fluid.program_guard(main, startup): if seed is not None: - startup.random_seed(random_seed) + startup.random_seed = seed loss = method(use_feed=len(feed_dict) > 0) adam = fluid.optimizer.Adam() adam.minimize(loss) @@ -278,9 +278,9 @@ class TestMNIST(TestParallelExecutorBase): def test_simple_fc_parallel_accuracy(self): single_first_loss, single_last_loss = self.check_network_convergence( - simple_fc_net, random_seed=0, use_parallel_executor=False) + simple_fc_net, seed=0, use_parallel_executor=False) parallel_first_loss, parallel_last_loss = self.check_network_convergence( - simple_fc_net, random_seed=0, use_parallel_executor=True) + simple_fc_net, seed=0, use_parallel_executor=True) print("FUCK") print('single_first_loss=', single_first_loss) print('single_last_loss=', single_last_loss) From 22df230ee49bef4662e062c7ae05e51d2183c08a Mon Sep 17 00:00:00 2001 From: JiayiFeng Date: Mon, 16 Apr 2018 09:45:31 +0000 Subject: [PATCH 23/69] rename 'feed_dict' in ParallelExecutor.run() to 'feed' --- python/paddle/fluid/parallel_executor.py | 19 ++++++++++--------- 1 file changed, 10 insertions(+), 9 deletions(-) diff --git a/python/paddle/fluid/parallel_executor.py b/python/paddle/fluid/parallel_executor.py index 5ce2aa1fc4..8d9f8c3489 100644 --- a/python/paddle/fluid/parallel_executor.py +++ b/python/paddle/fluid/parallel_executor.py @@ -61,8 +61,8 @@ class ParallelExecutor(object): main_program=test_program, share_vars_from=train_exe) - train_loss, = train_exe.run([loss.name], feed_dict=feed_dict) - test_loss, = test_exe.run([loss.name], feed_dict=feed_dict) + train_loss, = train_exe.run([loss.name], feed=feed_dict) + test_loss, = test_exe.run([loss.name], feed=feed_dict) """ self._places = [] @@ -123,22 +123,23 @@ class ParallelExecutor(object): allow_op_delay) self.scope = scope - def run(self, fetch_list, feed_dict={}): + def run(self, fetch_list, feed={}, feed_dict={}): """ :param fetch_list: A list of variable names that will be fetched. - :param feed_dict: A dict mapping for feed variable name to LoDTensor + :param feed: A dict mapping for feed variable name to LoDTensor or numpy array. :return: fetched value list. """ - if not isinstance(feed_dict, dict): - raise TypeError("feed_dict should be a dict") + feed = feed_dict + if not isinstance(feed, dict): + raise TypeError("feed should be a dict") feed_tensor_dict = {} - for i, feed_name in enumerate(feed_dict): - feed_tensor = feed_dict[feed_name] + for i, feed_name in enumerate(feed): + feed_tensor = feed[feed_name] if not isinstance(feed_tensor, core.LoDTensor): feed_tensor = core.LoDTensor() - feed_tensor.set(feed_dict[feed_name], self._act_places[0]) + feed_tensor.set(feed[feed_name], self._act_places[0]) feed_tensor_dict[feed_name] = feed_tensor fetch_var_name = '@FETCHED_VAR_NAME@' From 415460b557126e90a31eb6c848abddfdf3abacc1 Mon Sep 17 00:00:00 2001 From: JiayiFeng Date: Mon, 16 Apr 2018 10:54:37 +0000 Subject: [PATCH 24/69] stash --- .../tests/unittests/test_parallel_executor.py | 21 +++++++++---------- 1 file changed, 10 insertions(+), 11 deletions(-) diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor.py b/python/paddle/fluid/tests/unittests/test_parallel_executor.py index e311ebec36..42df00c3ee 100644 --- a/python/paddle/fluid/tests/unittests/test_parallel_executor.py +++ b/python/paddle/fluid/tests/unittests/test_parallel_executor.py @@ -229,13 +229,13 @@ class TestParallelExecutorBase(unittest.TestCase): if batch_size is not None: batch_size *= fluid.core.get_cuda_device_count() begin = time.time() - first_loss, = exe.run([loss.name], feed_dict=feed_dict) + first_loss, = exe.run([loss.name], feed=feed_dict) first_loss = numpy.array(first_loss) for i in xrange(iter): - exe.run([], feed_dict=feed_dict) + exe.run([], feed=feed_dict) - last_loss, = exe.run([loss.name], feed_dict=feed_dict) + last_loss, = exe.run([loss.name], feed=feed_dict) end = time.time() if batch_size is not None: @@ -277,11 +277,10 @@ class TestMNIST(TestParallelExecutorBase): "label": label}) def test_simple_fc_parallel_accuracy(self): - single_first_loss, single_last_loss = self.check_network_convergence( - simple_fc_net, seed=0, use_parallel_executor=False) - parallel_first_loss, parallel_last_loss = self.check_network_convergence( - simple_fc_net, seed=0, use_parallel_executor=True) - print("FUCK") + #single_first_loss, single_last_loss = self.check_network_convergence( + # simple_fc_net, seed=0, use_parallel_executor=False) + #parallel_first_loss, parallel_last_loss = self.check_network_convergence( + # simple_fc_net, seed=0, use_parallel_executor=True) print('single_first_loss=', single_first_loss) print('single_last_loss=', single_last_loss) print('parallel_first_loss=', parallel_first_loss) @@ -515,10 +514,10 @@ class ParallelExecutorTestingDuringTraining(unittest.TestCase): share_vars_from=train_exe) for i in xrange(5): - test_loss, = test_exe.run([loss.name], feed_dict=feed_dict) + test_loss, = test_exe.run([loss.name], feed=feed_dict) test_loss = numpy.array(test_loss) - train_loss, = train_exe.run([loss.name], feed_dict=feed_dict) + train_loss, = train_exe.run([loss.name], feed=feed_dict) train_loss = numpy.array(train_loss) self.assertTrue( numpy.allclose( @@ -668,5 +667,5 @@ class TestCRFModel(unittest.TestCase): for i in xrange(10): cur_batch = next(data) print map(numpy.array, - pe.run(feed_dict=feeder.feed(cur_batch), + pe.run(feed=feeder.feed(cur_batch), fetch_list=[avg_cost.name]))[0] From d78cab15190aa02599cd98a189b8808ea1300bbe Mon Sep 17 00:00:00 2001 From: typhoonzero Date: Mon, 16 Apr 2018 17:36:03 +0800 Subject: [PATCH 25/69] update --- .../paddle/fluid/tests/unittests/test_dist_train_op.py | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/python/paddle/fluid/tests/unittests/test_dist_train_op.py b/python/paddle/fluid/tests/unittests/test_dist_train_op.py index d3f4f74fe7..c7fdd06f10 100644 --- a/python/paddle/fluid/tests/unittests/test_dist_train_op.py +++ b/python/paddle/fluid/tests/unittests/test_dist_train_op.py @@ -33,17 +33,18 @@ class TestSendOp(unittest.TestCase): p.daemon = True p.start() - time.sleep(8) + time.sleep(10) with open("/tmp/paddle.selected_port", "r") as fn: selected_port = int(fn.readlines()[0]) self.init_client(place, selected_port) - # FIXME(typhoonzero): find a way to gracefully shutdown the server. - os.system("kill -9 %d" % p.pid) - p.join() self.run_local(place) self.assertTrue(numpy.allclose(self.local_out, self.dist_out)) + # FIXME(typhoonzero): find a way to gracefully shutdown the server. + os.system("kill -9 %d" % p.pid) + p.join() + def init_serv(self, place): main = fluid.Program() From 15c3a8e106f341dd8c277bfee55c6646ff9383d3 Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Mon, 16 Apr 2018 19:37:14 +0800 Subject: [PATCH 26/69] update by comment --- doc/fluid/design/dist_train/async_update.md | 39 ++++++++++-------- .../dist_train/src/async_pserver.graffle | Bin 10621 -> 11035 bytes .../design/dist_train/src/async_pserver.png | Bin 164416 -> 169986 bytes .../dist_train/src/async_update.graffle | Bin 8121 -> 8266 bytes .../design/dist_train/src/async_update.png | Bin 192539 -> 183948 bytes 5 files changed, 22 insertions(+), 17 deletions(-) diff --git a/doc/fluid/design/dist_train/async_update.md b/doc/fluid/design/dist_train/async_update.md index 05175596f7..be8783a7e7 100644 --- a/doc/fluid/design/dist_train/async_update.md +++ b/doc/fluid/design/dist_train/async_update.md @@ -4,41 +4,46 @@ For the typical synchronous distributed training, some significant steps are as follows: -1. A Trainer will compute the gradients and SEND them to the Parameter -Server(PServer) nodes. -1. After the PServer node received gradients came from all the Trainers, it would apply the gradient to the respective variables, and using an optimize algorithms(SGD, - Momentment...) to update the parameters. -1. The Trainer would wait for the PServers finished the optimize stage, and GET the parameters from PServer, so all the Trainers would get the same parameters. +1. A Trainer will compute the gradients and SEND them to the Parameter Server(PServer) nodes. +1. After the PServer node received gradients came from all the Trainers, +it would apply the gradient to the respective variables, and using an optimize algorithms(SGD, +Momentment...) to update the parameters. +1. The Trainer would wait for the PServers finished the optimize stage, and GET the parameters from PServer, +so all the Trainers would get the same parameters. In the synchronously distributed training, there should be a `Barrier` to synchronise the -parameters after the optimizing stage. The performance of a distributed training job -depends on the lowest node, if there were hundreds or thousand training nodes in a Job, -the performance of synchronously distributed training might be very slow because of -the slow node. So this design doc would introduce an approach to implement +parameters after the optimizing stage. The performance of a distributed training job would +depend on the slowest node if there were hundreds or thousands of training nodes in a +Job, the performance of synchronously distributed training might be very poor because of +the slow node. So this design doc would introduce an approach to implement *asynchronously* distributed training in PaddlePaddle Fluid. ## Design - + As the figure above, we describe a global view of asynchronously update process and use the parameter `w1` as an example to introduce the steps: 1. For each gradient variables, they may distribute on different GPU card and aggregate them while they are all calculated. 1. Split the gradient variable into multiple blocks according to the number of PServer -instances and sent them. -1. PServer would run an `Optimize Block` to use a specified optimize algorithm to update -the specified parameter, such as `w1`. -1. The trainer will fetch the latest parameter after PServer finished the optimize stage. +instances and then sent them. +1. PServer would run an `Optimize Block` using a specified optimize algorithm to update +the specified parameter. +1. The trainer will fetch the parameter before running forward Op depends on the specified +parameter. 1. Broadcast the received variable into multiple GPU cards and continue to run the next mini-batch. ### Trainer -- We need a new Operator named `RemoteOptimize` to send gradients to multiple PServer -instances and fetch the latest parameter. +- For the multiple devices distributed training, we need to aggregate the gradient +variables which placed on different devices firstly, and then schedule a `SendVars` Operator to +send the gradient variables to the multiple PServer instances. +- Schedule `FetchVars` operator to fetch the latest parameter from PServer before running +the forward ops. - There could be a large number of gradient variables to be sent, so we need to use another -thread pool(IO Threadpool) which number of the schedulable threads is larger than the +thread pool(IO Threadpool) which a number of the schedulable threads is larger than the computing thread pool to avoid competitive the thread resources with computing. ### Parameter Server diff --git 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zwsC-M^lvn&_I(kxqZgpimmi2K<)(ZSkncWkiv>cD11m6e8WWage(5dhz%-@es(J4G zfCgBL-IJ%hB3h1gI)N&N9rCy6n?%BOuF;0cXA$ASulyCF6ae`gR~I|C`$M;wx)s1* ztI8hKyq`yRVN~{Zr zGGv4+X5Sn`Bmk;rBt;9q2+lQAF*SZSgfxZ!Y!najmWb(&VXuM{e4&>UP@nxRz&9kl zfxyk%VOG^Qu2GcWJ2u%W#Wq<;4gzO|;ZOom`pi~Qs#vjo3VrMX)|h^LD86CV{Ww#e zM2D3#%s(x;&Vp4}?ycF3qUR0r+lS5af}p0W}d zK}ROx;Vm6rKa0t&i?SPg?GYK|N)VENOmMD&$F|d9-?vXRDr$6-i0Z6yUvP^4&ZlhM54MEbpa7z{IWDn!SLZRhi~Cp%w9w@ z6GJDm=l{pn(Baa5O^3P1&f_3$t;Tu(fiPWvZ%eckwE%S$rP;eO3$RfoW=#8?M4=c<@z2G{{ZTM$7uin From 49e885b6eaf969c07413889f12f12241fefbe4f6 Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Mon, 16 Apr 2018 19:43:36 +0800 Subject: [PATCH 27/69] update --- doc/fluid/design/dist_train/async_update.md | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/doc/fluid/design/dist_train/async_update.md b/doc/fluid/design/dist_train/async_update.md index be8783a7e7..344a44bde8 100644 --- a/doc/fluid/design/dist_train/async_update.md +++ b/doc/fluid/design/dist_train/async_update.md @@ -5,9 +5,10 @@ For the typical synchronous distributed training, some significant steps are as follows: 1. A Trainer will compute the gradients and SEND them to the Parameter Server(PServer) nodes. -1. After the PServer node received gradients came from all the Trainers, -it would apply the gradient to the respective variables, and using an optimize algorithms(SGD, -Momentment...) to update the parameters. +1. After the PServer node received gradients came from all the Trainers, It will aggregate the +gradient variables for the same parameter into one gradient variable and then apply the aggregated +gradient to the respective parameter, finally using an optimize algorithms(SGD, Monument...) +to update the parameters. 1. The Trainer would wait for the PServers finished the optimize stage, and GET the parameters from PServer, so all the Trainers would get the same parameters. @@ -38,7 +39,7 @@ mini-batch. ### Trainer - For the multiple devices distributed training, we need to aggregate the gradient -variables which placed on different devices firstly, and then schedule a `SendVars` Operator to +variables which placed on different devices firstly and then schedule a `SendVars` Operator to send the gradient variables to the multiple PServer instances. - Schedule `FetchVars` operator to fetch the latest parameter from PServer before running the forward ops. From d4682247e183beed0c176e0e3b051dfab9e20069 Mon Sep 17 00:00:00 2001 From: Luo Tao Date: Mon, 16 Apr 2018 23:04:42 +0800 Subject: [PATCH 28/69] auto find tensorrt library --- CMakeLists.txt | 7 +---- Dockerfile | 2 +- cmake/configure.cmake | 10 ++++++ cmake/tensorrt.cmake | 33 ++++++++++++++++++++ paddle/fluid/inference/CMakeLists.txt | 2 +- paddle/fluid/platform/dynload/CMakeLists.txt | 2 +- 6 files changed, 47 insertions(+), 9 deletions(-) create mode 100644 cmake/tensorrt.cmake diff --git a/CMakeLists.txt b/CMakeLists.txt index de47086dbd..23bbe829ac 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -39,7 +39,6 @@ option(WITH_GPU "Compile PaddlePaddle with NVIDIA GPU" ${CUDA_F option(WITH_AMD_GPU "Compile PaddlePaddle with AMD GPU" OFF) option(WITH_AVX "Compile PaddlePaddle with AVX intrinsics" ${AVX_FOUND}) option(WITH_MKL "Compile PaddlePaddle with MKL support." ${AVX_FOUND}) -option(WITH_TENSORRT "Compile PaddlePaddle with TensorRT support." OFF) option(WITH_DSO "Compile PaddlePaddle with dynamic linked CUDA" ON) option(WITH_TESTING "Compile PaddlePaddle with unit testing" OFF) option(WITH_SWIG_PY "Compile PaddlePaddle with inference api" ON) @@ -180,13 +179,9 @@ set(EXTERNAL_LIBS if(WITH_GPU) include(cuda) + include(tensorrt) endif(WITH_GPU) -# TensorRT depends on GPU. -if (NOT WITH_GPU) - set(WITH_TENSORRT OFF) -endif() - if(WITH_AMD_GPU) find_package(HIP) include(hip) diff --git a/Dockerfile b/Dockerfile index 9097bb657d..870304a6ac 100644 --- a/Dockerfile +++ b/Dockerfile @@ -46,7 +46,7 @@ ENV PATH=${PATH}:${GOROOT}/bin:${GOPATH}/bin RUN curl -s -q https://glide.sh/get | sh # Install TensorRT -# The unnecessary files has been removed to make the library small. +# The unnecessary files has been removed to make the library small. It only contains include and lib now. RUN wget -qO- http://paddlepaddledeps.bj.bcebos.com/TensorRT-4.0.0.3.Ubuntu-16.04.4.x86_64-gnu.cuda-8.0.cudnn7.0.tar.gz | \ tar -xz -C /usr/local && \ cp -rf /usr/local/TensorRT/include /usr && \ diff --git a/cmake/configure.cmake b/cmake/configure.cmake index f726405c47..e490397cc0 100644 --- a/cmake/configure.cmake +++ b/cmake/configure.cmake @@ -80,6 +80,16 @@ if(WITH_GPU) # Include cuda and cudnn include_directories(${CUDNN_INCLUDE_DIR}) include_directories(${CUDA_TOOLKIT_INCLUDE}) + + if(TENSORRT_FOUND) + if(${CUDA_VERSION_MAJOR} VERSION_LESS 8) + message(FATAL_ERROR "TensorRT needs CUDA >= 8.0 to compile") + endif() + if(${CUDNN_MAJOR_VERSION} VERSION_LESS 7) + message(FATAL_ERROR "TensorRT needs CUDNN >= 7.0 to compile") + endif() + include_directories(${TENSORRT_INCLUDE_DIR}) + endif() elseif(WITH_AMD_GPU) add_definitions(-DPADDLE_WITH_HIP) set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -D__HIP_PLATFORM_HCC__") diff --git a/cmake/tensorrt.cmake b/cmake/tensorrt.cmake new file mode 100644 index 0000000000..0c07d36bed --- /dev/null +++ b/cmake/tensorrt.cmake @@ -0,0 +1,33 @@ +if(NOT WITH_GPU) + return() +endif() + +set(TENSORRT_ROOT "/usr" CACHE PATH "TENSORRT ROOT") +find_path(TENSORRT_INCLUDE_DIR NvInfer.h + PATHS ${TENSORRT_ROOT} ${TENSORRT_ROOT}/include + $ENV{TENSORRT_ROOT} $ENV{TENSORRT_ROOT}/include + NO_DEFAULT_PATH +) + +find_library(TENSORRT_LIBRARY NAMES libnvinfer.so libnvinfer.a + PATHS ${TENSORRT_ROOT} ${TENSORRT_ROOT}/lib + $ENV{TENSORRT_ROOT} $ENV{TENSORRT_ROOT}/lib + NO_DEFAULT_PATH + DOC "Path to TensorRT library.") + +if(TENSORRT_INCLUDE_DIR AND TENSORRT_LIBRARY) + set(TENSORRT_FOUND ON) +else() + set(TENSORRT_FOUND OFF) +endif() + +if(TENSORRT_FOUND) + file(READ ${TENSORRT_INCLUDE_DIR}/NvInfer.h TENSORRT_VERSION_FILE_CONTENTS) + string(REGEX MATCH "define NV_TENSORRT_MAJOR +([0-9]+)" TENSORRT_MAJOR_VERSION + "${TENSORRT_VERSION_FILE_CONTENTS}") + string(REGEX REPLACE "define NV_TENSORRT_MAJOR +([0-9]+)" "\\1" + TENSORRT_MAJOR_VERSION "${TENSORRT_MAJOR_VERSION}") + + message(STATUS "Current TensorRT header is ${TENSORRT_INCLUDE_DIR}/NvInfer.h. " + "Current TensorRT version is v${TENSORRT_MAJOR_VERSION}. ") +endif() diff --git a/paddle/fluid/inference/CMakeLists.txt b/paddle/fluid/inference/CMakeLists.txt index 8494edee6c..cc45bfe9b1 100644 --- a/paddle/fluid/inference/CMakeLists.txt +++ b/paddle/fluid/inference/CMakeLists.txt @@ -21,7 +21,7 @@ endif() if(WITH_TESTING) add_subdirectory(tests/book) - if (WITH_TENSORRT) + if (TENSORRT_FOUND) add_subdirectory(tensorrt) endif() endif() diff --git a/paddle/fluid/platform/dynload/CMakeLists.txt b/paddle/fluid/platform/dynload/CMakeLists.txt index b93b925a72..364c4901b2 100644 --- a/paddle/fluid/platform/dynload/CMakeLists.txt +++ b/paddle/fluid/platform/dynload/CMakeLists.txt @@ -1,7 +1,7 @@ cc_library(dynamic_loader SRCS dynamic_loader.cc DEPS glog gflags enforce) list(APPEND CUDA_SRCS cublas.cc cudnn.cc curand.cc nccl.cc) -if (WITH_TENSORRT) +if (TENSORRT_FOUND) list(APPEND CUDA_SRCS tensorrt.cc) endif() From a54962d36c5bd4e880ea37ead2826583509168ec Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Tue, 17 Apr 2018 10:27:34 +0800 Subject: [PATCH 29/69] update by comment --- doc/fluid/design/dist_train/async_update.md | 8 ++++---- .../dist_train/src/async_pserver.graffle | Bin 11035 -> 10525 bytes .../design/dist_train/src/async_pserver.png | Bin 169986 -> 169996 bytes 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/doc/fluid/design/dist_train/async_update.md b/doc/fluid/design/dist_train/async_update.md index 344a44bde8..0318ef33c2 100644 --- a/doc/fluid/design/dist_train/async_update.md +++ b/doc/fluid/design/dist_train/async_update.md @@ -28,10 +28,10 @@ the parameter `w1` as an example to introduce the steps: 1. For each gradient variables, they may distribute on different GPU card and aggregate them while they are all calculated. 1. Split the gradient variable into multiple blocks according to the number of PServer -instances and then sent them. +instances and then send them. 1. PServer would run an `Optimize Block` using a specified optimize algorithm to update the specified parameter. -1. The trainer will fetch the parameter before running forward Op depends on the specified +1. The trainer will fetch the parameter before running forward Op which depends on the specified parameter. 1. Broadcast the received variable into multiple GPU cards and continue to run the next mini-batch. @@ -44,7 +44,7 @@ send the gradient variables to the multiple PServer instances. - Schedule `FetchVars` operator to fetch the latest parameter from PServer before running the forward ops. - There could be a large number of gradient variables to be sent, so we need to use another -thread pool(IO Threadpool) which a number of the schedulable threads is larger than the +thread pool(IO Threadpool) whose a number of the schedulable threads is larger than the computing thread pool to avoid competitive the thread resources with computing. ### Parameter Server @@ -52,7 +52,7 @@ computing thread pool to avoid competitive the thread resources with computing. - There should be multiple trainer instances want to optimize the same parameter at -the same time, to avoid the pollution, we need one `BlockingQueue` for each gradient +the same time, to avoid the racing, we need one `BlockingQueue` for each gradient variable to process them one by one. - We need a `Map` structure to map a gradient variable name to the `OptimizeBlock` which can optimize the respective parameter. diff --git a/doc/fluid/design/dist_train/src/async_pserver.graffle b/doc/fluid/design/dist_train/src/async_pserver.graffle index ea6dcfa2a9e4daac1500d98743a7a5a4234470f9..d2301611774fcb3866473e3e6470568d1e1312cf 100644 GIT binary patch literal 10525 zcmaLcQ*b8iwkPn|=-9Sx+fF*RJJuUp9Xsh*9ox2T+jia<^X)xnPEAeiIqPCwtgC-L zt7=_5KcXlYkbf08$d&I|OM!Ir%}I3+siAM%vtUJRbfj;^dzXzA0IX?@XZ^8H-I&scVphv z##dkK4t`ZBzCM!1pd~Cz3V%?VEtoJOdbHv5 z$sVjGWYeGuwdY&+S=L!BM)i~cRHF~dw^M0L`D3{&ZPTjPOeS>zp|W6*$w20#{K}AV zF-L#>SsW(K698$3@x_tiGIip7 z>XX_FeOq`2MHdmtDMo&~&*ml%(t2EfET&lcmrZ#e%ct5)@OzRzOVAUTGPjwV7Ua}S z>tVj+H77B3ve!_aug$^U-bBOnEK=BUO}RH;*#wK1@<@TpXw!YHt*-BJZM`2AT@-Mg z2GmIMZx4FDyEm9A@Eevk_(hJ0s5)T;;gCdb;LBq*A44!lef3t4w|S!EE>Gr4f{2*m zYO2J%49EuC_)FI@Ca-q!Z2Kt~Z_`cj_LvTgh8ic%_~@rXQcSw0l(7-iRS!-ecA!Wl 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+0800 Subject: [PATCH 30/69] update --- doc/fluid/design/dist_train/async_update.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/doc/fluid/design/dist_train/async_update.md b/doc/fluid/design/dist_train/async_update.md index 0318ef33c2..6a0835b761 100644 --- a/doc/fluid/design/dist_train/async_update.md +++ b/doc/fluid/design/dist_train/async_update.md @@ -31,8 +31,8 @@ them while they are all calculated. instances and then send them. 1. PServer would run an `Optimize Block` using a specified optimize algorithm to update the specified parameter. -1. The trainer will fetch the parameter before running forward Op which depends on the specified -parameter. +1. The trainer will fetch latest parameter from PServer before running forward Op which depends +on the specified parameter. 1. Broadcast the received variable into multiple GPU cards and continue to run the next mini-batch. From 4999f85f6a7cfd9869c1bf3f656d2cb54f5a1c6b Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Tue, 17 Apr 2018 10:43:34 +0800 Subject: [PATCH 31/69] Clean RunDelayedOp method --- .../fluid/framework/details/threaded_ssa_graph_executor.cc | 7 ------- .../fluid/framework/details/threaded_ssa_graph_executor.h | 2 -- 2 files changed, 9 deletions(-) diff --git a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc index 927078bc64..3d2bd633af 100644 --- a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc +++ b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc @@ -33,13 +33,6 @@ ThreadedSSAGraphExecutor::ThreadedSSAGraphExecutor( running_ops_(0), allow_op_delay_(allow_op_delay) {} -void ThreadedSSAGraphExecutor::RunDelayedOps( - const std::unordered_set &delayed_ops) { - for (auto op : delayed_ops) { - op->Run(use_event_); - } -} - FeedFetchList ThreadedSSAGraphExecutor::Run( const std::vector &fetch_tensors) { std::unordered_map pending_ops; diff --git a/paddle/fluid/framework/details/threaded_ssa_graph_executor.h b/paddle/fluid/framework/details/threaded_ssa_graph_executor.h index bb5e837b13..d70bbd4ef0 100644 --- a/paddle/fluid/framework/details/threaded_ssa_graph_executor.h +++ b/paddle/fluid/framework/details/threaded_ssa_graph_executor.h @@ -88,8 +88,6 @@ class ThreadedSSAGraphExecutor : public SSAGraphExecutor { void RunOp(BlockingQueue *ready_var_q, details::OpHandleBase *op); - void RunDelayedOps(const std::unordered_set &delayed_ops); - private: std::unique_ptr<::ThreadPool> pool_; std::vector local_scopes_; From b821a7efc1246dd41e88800f0f045b5f2e0398eb Mon Sep 17 00:00:00 2001 From: Yancey1989 Date: Tue, 17 Apr 2018 10:48:18 +0800 Subject: [PATCH 32/69] specified pip version in production image --- paddle/scripts/docker/build.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/paddle/scripts/docker/build.sh b/paddle/scripts/docker/build.sh index be1565ab53..2b2a904974 100755 --- a/paddle/scripts/docker/build.sh +++ b/paddle/scripts/docker/build.sh @@ -198,7 +198,7 @@ EOF # run paddle version to install python packages first RUN apt-get update &&\ ${NCCL_DEPS}\ - apt-get install -y wget python-pip dmidecode python-tk && pip install -U pip && \ + apt-get install -y wget python-pip dmidecode python-tk && pip install -U pip==9.0.3 && \ pip install /*.whl; apt-get install -f -y && \ apt-get clean -y && \ rm -f /*.whl && \ From 91f0e3f887f0294d468f4d067b52754639a2a002 Mon Sep 17 00:00:00 2001 From: Qiao Longfei Date: Tue, 17 Apr 2018 11:54:50 +0800 Subject: [PATCH 33/69] Add distributed training overview doc (#9937) * add asynchronous design doc * update distributed_training.png * add distributed_training.graffle * add async_distributed_training.png * update design doc * change name to distributed_training_overview * follow comment * change distributed_training_overview.md to README.md * update sync_distributed_training.png * follow comment * fix typo --- doc/fluid/design/dist_train/README.md | 57 ++++++++++++++++++ .../src/async_distributed_training.png | Bin 0 -> 184568 bytes .../src/distributed_training.graffle | Bin 0 -> 8709 bytes .../src/sync_distributed_training.png | Bin 0 -> 188676 bytes 4 files changed, 57 insertions(+) create mode 100644 doc/fluid/design/dist_train/README.md create mode 100644 doc/fluid/design/dist_train/src/async_distributed_training.png create mode 100644 doc/fluid/design/dist_train/src/distributed_training.graffle create mode 100644 doc/fluid/design/dist_train/src/sync_distributed_training.png diff --git a/doc/fluid/design/dist_train/README.md b/doc/fluid/design/dist_train/README.md new file mode 100644 index 0000000000..2dd652d8bd --- /dev/null +++ b/doc/fluid/design/dist_train/README.md @@ -0,0 +1,57 @@ +## Distributed training overview doc + +Currently Paddle Fluid use parameter server architecture to support distributed training. + +For synchronous and asynchronous training, the differences are mostly in the logic of parameter server. Now we have already support synchronous training. + +### Synchronous training + +The training process of synchronous training is: + +![synchronous distributed training](./src/sync_distributed_training.png) + +1. Pserver + 1. set `barrier_condition_` to 0 and waits for trainers to send gradient. +1. Trainer + 1. Trainer read minibatch of data, run forward-backward with local parameter copy and get the gradients for parameters. + 1. Trainer use split op to split all the gradient into blocks. The split method is determined at compile time. + 1. Trainer use send_op to send all the split gradients to corresponding parameter server. + 1. After trainer send all the gradients, it will send a `BATCH_BARRIER_MESSAGE` to all pservers. + 1. Trainer call GetVariable to pserver and wait for `barrier_condition_` on pserver to be 1. +1. Pserver + 1. Pserver will count the number of `BATCH_BARRIER_MESSAGE`. + 1. When the count of `BATCH_BARRIER_MESSAGE` is equal to the number of Trainer. Pserver thinks it received all gradient from all trainers. + 1. Pserver will run the optimization block to optimize the parameters. + 1. After optimization, pserver set `barrier_condition_` to 1. + 1. Pserver wait for `FETCH_BARRIER_MESSAGE`. +1. Trainer. + 1. The trainer uses GetVariable to get all the parameters from pserver. + 1. Trainer sends a `FETCH_BARRIER_MESSAGE` to each pserver. +1. Pserver. + 1. when the number of `FETCH_BARRIER_MESSAGE` reach the number of all trainers. Pserver think all the parameters have been got. it will go back to 1. to set `barrier_condition_` to 0. + +### Asynchronous training +In the above process. There are two barriers for all trainers to synchronize with each other. In asynchronous training, these two barriers are not needed. The trainer can just send gradients to pserver and then get parameters back. + +The training process of asynchronous training can be: + +![asynchronous distributed training](./src/async_distributed_training.png) + +1. Pserver: + 1. Each parameter has a queue to receive its gradient from trainers. + 1. Each parameter has a thread to read data from the queue and run optimize block, using the gradient to optimize the parameter. + 1. Using an independent thread to handle RPC call `GetVariable` for trainers to get parameters back.(Maybe here we should use a thread pool to speed up fetching the parameters.) + +1. Trainer: + 1. Trainer read a batch of data. Run forward and backward with local parameter copy and get the gradients for parameters. + 1. Trainer split all gradients to blocks and then send these gradient blocks to pservers(pserver will put them into the queue). + 2. Trainer gets all parameters back from pserver. + +### Note: +There are also some conditions that need to consider. For exmaple: + +1. If trainer needs to wait for the pserver to apply it's gradient and then get back the parameters back. +1. If we need a lock between parameter update and parameter fetch. +1. 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zGss%4#5JbdAZN`E`R5!y_MZhCu_=4W(XB_5ENEi0^mx5~G7?OGi{_0F^W z0q=I>+x#kJ4-GE41v{M(lgXmq5OMwH4QKO;m%wlBqFzVp;k}(QL!=fLWNU`|ED{1zts-hp>k^Jz@mVWpCK{>l;Ob%5V zo@6pzO4!JIVlkFGQ3s@(D^b`v%ggEV5jAmaCWZt@#{{x!=9jQHL(k?Rb?g z?ic>t>o;Y-2($13a$^^D_Gwer#s&N#YDkj36gjYPR|JVg`Ef0K!94h3bqgRBj2q7$ z`wSdG3NOx7Ye3slZ)%bCvF3i`ab%$GSe%bU@z^DwCDfGG-Zbr6t9qb*P6F%$7f(3Q#(w<0eg;&$51_ievV){_b?{v!{!`?gS;_f@ic# ziT}A+wXsKz0v9X*H6u-SUd7-XY@=79d;b<-%8x8HR7Zp9vq7t1lt$(z&M(!wC*YEYj7y>^?vU$!!m~O)Jk)Q|%;Z|w^S%+~zvHeo&1639Znc7bmL{`#n8tJs zy$D*Kwq17-`gzqjqm~~giqNqQ(7Bmm@|>8Qyy&nGT=pF$t+(y=sZGSsTcHGg-84q_ zjub-3ih_E)Q!_^%*I{ZtW``&V@X^|ET%3?SEUZZ6Bat0TaV0Am@35 zavU7=UrXCHl7y6fCW3H@9?iq@8#G(_jEEWk)T Date: Mon, 16 Apr 2018 15:30:56 +0800 Subject: [PATCH 34/69] Sync Copy --- paddle/fluid/pybind/tensor_py.h | 1 + 1 file changed, 1 insertion(+) diff --git a/paddle/fluid/pybind/tensor_py.h b/paddle/fluid/pybind/tensor_py.h index 4a9dbd324c..c9cad15a74 100644 --- a/paddle/fluid/pybind/tensor_py.h +++ b/paddle/fluid/pybind/tensor_py.h @@ -190,6 +190,7 @@ void PyCUDATensorSetFromArray( static_cast(pool.Get(place)); paddle::platform::GpuMemcpyAsync(dst, array.data(), sizeof(T) * array.size(), cudaMemcpyHostToDevice, dev_ctx->stream()); + dev_ctx->Wait(); } template <> From e6bc7bb09ac8ce339626eef2514405e76701b976 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Mon, 16 Apr 2018 15:46:31 +0800 Subject: [PATCH 35/69] Tuning code --- paddle/fluid/pybind/pybind.cc | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/paddle/fluid/pybind/pybind.cc b/paddle/fluid/pybind/pybind.cc index a1e8ff6399..254c4a5942 100644 --- a/paddle/fluid/pybind/pybind.cc +++ b/paddle/fluid/pybind/pybind.cc @@ -510,6 +510,11 @@ All parameter, weight, gradient are variables in Paddle. return &self.GetLocalScopes(); }, py::return_value_policy::reference) + .def("local_scopes_len", + [](ParallelExecutor &self) { return self.GetLocalScopes().size(); }) + .def("local_scope", [](ParallelExecutor &self, + size_t i) { return self.GetLocalScopes()[i]; }, + py::return_value_policy::reference) .def("run", &ParallelExecutor::Run); BindRecordIOWriter(&m); From 7289e75836bc2728d3d9aff2d08166cce5383645 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Mon, 16 Apr 2018 16:00:53 +0800 Subject: [PATCH 36/69] Udpate --- paddle/fluid/framework/details/threaded_ssa_graph_executor.cc | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc index a371ee10fe..43b520b543 100644 --- a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc +++ b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc @@ -204,8 +204,8 @@ void ThreadedSSAGraphExecutor::RunOp( VLOG(10) << op << " " << op->Name() << "Signal posted"; } catch (platform::EnforceNotMet ex) { exception_.reset(new platform::EnforceNotMet(ex)); - } catch (...) { - LOG(FATAL) << "Unknown exception catched"; + } catch (std::exception &exp) { + LOG(FATAL) << exp.what(); } }; if (pool_) { From e9e27e0f3227a64c029abb93f784e03599839d35 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Mon, 16 Apr 2018 16:16:27 +0800 Subject: [PATCH 37/69] Revert --- paddle/fluid/framework/details/threaded_ssa_graph_executor.cc | 4 ++-- paddle/fluid/pybind/tensor_py.h | 1 - 2 files changed, 2 insertions(+), 3 deletions(-) diff --git a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc index 43b520b543..a371ee10fe 100644 --- a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc +++ b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc @@ -204,8 +204,8 @@ void ThreadedSSAGraphExecutor::RunOp( VLOG(10) << op << " " << op->Name() << "Signal posted"; } catch (platform::EnforceNotMet ex) { exception_.reset(new platform::EnforceNotMet(ex)); - } catch (std::exception &exp) { - LOG(FATAL) << exp.what(); + } catch (...) { + LOG(FATAL) << "Unknown exception catched"; } }; if (pool_) { diff --git a/paddle/fluid/pybind/tensor_py.h b/paddle/fluid/pybind/tensor_py.h index c9cad15a74..4a9dbd324c 100644 --- a/paddle/fluid/pybind/tensor_py.h +++ b/paddle/fluid/pybind/tensor_py.h @@ -190,7 +190,6 @@ void PyCUDATensorSetFromArray( static_cast(pool.Get(place)); paddle::platform::GpuMemcpyAsync(dst, array.data(), sizeof(T) * array.size(), cudaMemcpyHostToDevice, dev_ctx->stream()); - dev_ctx->Wait(); } template <> From a822f8ddbbf8e48d133ed78048dc4c17d863af74 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Mon, 16 Apr 2018 16:23:22 +0800 Subject: [PATCH 38/69] Add wait --- paddle/fluid/pybind/tensor_py.h | 1 + 1 file changed, 1 insertion(+) diff --git a/paddle/fluid/pybind/tensor_py.h b/paddle/fluid/pybind/tensor_py.h index 4a9dbd324c..c9cad15a74 100644 --- a/paddle/fluid/pybind/tensor_py.h +++ b/paddle/fluid/pybind/tensor_py.h @@ -190,6 +190,7 @@ void PyCUDATensorSetFromArray( static_cast(pool.Get(place)); paddle::platform::GpuMemcpyAsync(dst, array.data(), sizeof(T) * array.size(), cudaMemcpyHostToDevice, dev_ctx->stream()); + dev_ctx->Wait(); } template <> From 2ab12ca2480979ba4d651adff7fef6daf3a86ce7 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Tue, 17 Apr 2018 10:26:04 +0800 Subject: [PATCH 39/69] Add comments and clean code --- paddle/fluid/pybind/pybind.cc | 6 ++++-- paddle/fluid/pybind/tensor_py.h | 9 +++++++++ 2 files changed, 13 insertions(+), 2 deletions(-) diff --git a/paddle/fluid/pybind/pybind.cc b/paddle/fluid/pybind/pybind.cc index 254c4a5942..5121987f92 100644 --- a/paddle/fluid/pybind/pybind.cc +++ b/paddle/fluid/pybind/pybind.cc @@ -505,13 +505,15 @@ All parameter, weight, gradient are variables in Paddle. scope, local_scopes, allow_op_delay); }) .def("bcast_params", &ParallelExecutor::BCastParamsToGPUs) + // NOTE: even we return a vec* to Python use reference policy. + // We still cannot get local_scope from this vector, since the element + // of vec will be freed by Python GC. We can only return Scope* + // one by one and mark them as reference. .def("local_scopes", [](ParallelExecutor &self) -> std::vector * { return &self.GetLocalScopes(); }, py::return_value_policy::reference) - .def("local_scopes_len", - [](ParallelExecutor &self) { return self.GetLocalScopes().size(); }) .def("local_scope", [](ParallelExecutor &self, size_t i) { return self.GetLocalScopes()[i]; }, py::return_value_policy::reference) diff --git a/paddle/fluid/pybind/tensor_py.h b/paddle/fluid/pybind/tensor_py.h index c9cad15a74..159d1d5f4e 100644 --- a/paddle/fluid/pybind/tensor_py.h +++ b/paddle/fluid/pybind/tensor_py.h @@ -190,6 +190,10 @@ void PyCUDATensorSetFromArray( static_cast(pool.Get(place)); paddle::platform::GpuMemcpyAsync(dst, array.data(), sizeof(T) * array.size(), cudaMemcpyHostToDevice, dev_ctx->stream()); + // NOTE: For safety, here wait the copy complete. + // It because the CPU array.data() could be destroyed after this method. + // If we make this method async, it could be copied data from a memory buffer + // that has been freed. dev_ctx->Wait(); } @@ -217,6 +221,11 @@ void PyCUDATensorSetFromArray( paddle::platform::GpuMemcpyAsync(dst, array.data(), sizeof(uint16_t) * array.size(), cudaMemcpyHostToDevice, dev_ctx->stream()); + // NOTE: For safety, here wait the copy complete. + // It because the CPU array.data() could be destroyed after this method. + // If we make this method async, it could be copied data from a memory buffer + // that has been freed. + dev_ctx->Wait(); } template From b4aaa00a8a71c106172da84ce3f81ba16df76227 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Tue, 17 Apr 2018 13:57:07 +0800 Subject: [PATCH 40/69] Polish logic of ParallelExecutor --- paddle/fluid/framework/parallel_executor.cc | 34 +++++---- paddle/fluid/framework/parallel_executor.h | 16 +++-- paddle/fluid/pybind/pybind.cc | 7 +- python/paddle/fluid/parallel_executor.py | 69 ++++++++++++++----- .../tests/unittests/test_parallel_executor.py | 12 ++-- 5 files changed, 96 insertions(+), 42 deletions(-) diff --git a/paddle/fluid/framework/parallel_executor.cc b/paddle/fluid/framework/parallel_executor.cc index c1486b527d..0962f40c4a 100644 --- a/paddle/fluid/framework/parallel_executor.cc +++ b/paddle/fluid/framework/parallel_executor.cc @@ -155,13 +155,9 @@ void ParallelExecutor::BCastParamsToGPUs( #endif } -void ParallelExecutor::Run( - const std::vector &fetch_tensors, - const std::string &fetched_var_name, - const std::unordered_map &feed_tensors) { +void ParallelExecutor::Run(const std::vector &fetch_tensors, + const std::string &fetched_var_name) { platform::RecordBlock b(0); - SplitTensorToPlaces(feed_tensors); - // Create local scopes. for (auto &scope : member_->local_scopes_) { Scope &local_scope = scope->NewScope(); @@ -195,14 +191,28 @@ void ParallelExecutor::Run( auto &local_scope = *scope->Var(details::kLocalExecScopeName)->GetMutable(); scope->DeleteScope(local_scope); - local_scope = nullptr; } } -void ParallelExecutor::SplitTensorToPlaces( - const std::unordered_map &feed_tensors) { - for (auto it : feed_tensors) { - auto lod_tensors = it.second.SplitLoDTensor(member_->places_); +void ParallelExecutor::FeedTensorsIntoLocalScopes( + const std::vector> &tensors) { + PADDLE_ENFORCE_EQ(member_->local_scopes_.size(), tensors.size()); + + for (size_t i = 0; i < tensors.size(); ++i) { + auto &map = tensors[i]; + auto *scope = member_->local_scopes_[i]; + for (auto &pair : map) { + auto *trg = scope->Var(pair.first)->GetMutable(); + trg->ShareDataWith(pair.second); + trg->set_lod(pair.second.lod()); + } + } +} + +void ParallelExecutor::FeedAndSplitTensorIntoLocalScopes( + const std::unordered_map &tensors) { + for (auto pair : tensors) { + auto lod_tensors = pair.second.SplitLoDTensor(member_->places_); PADDLE_ENFORCE_EQ( member_->places_.size(), lod_tensors.size(), "The number of samples of current batch is less than the count of " @@ -211,7 +221,7 @@ void ParallelExecutor::SplitTensorToPlaces( for (size_t j = 0; j < member_->places_.size(); ++j) { // TODO(panxy0718): Do I need to delete this var? auto t = - member_->local_scopes_[j]->Var(it.first)->GetMutable(); + member_->local_scopes_[j]->Var(pair.first)->GetMutable(); t->ShareDataWith(lod_tensors[j]); t->set_lod(lod_tensors[j].lod()); } diff --git a/paddle/fluid/framework/parallel_executor.h b/paddle/fluid/framework/parallel_executor.h index b4f16dba85..303ac3bc55 100644 --- a/paddle/fluid/framework/parallel_executor.h +++ b/paddle/fluid/framework/parallel_executor.h @@ -44,16 +44,22 @@ class ParallelExecutor { std::vector& GetLocalScopes(); + /** + * Feed tensors to local scopes. The size of tensors should be equal to the + * size of local scopes. + */ + void FeedTensorsIntoLocalScopes( + const std::vector>& tensors); + + void FeedAndSplitTensorIntoLocalScopes( + const std::unordered_map& tensors); + void Run(const std::vector& fetch_tensors, - const std::string& fetched_var_name, - const std::unordered_map& feed_tensors); + const std::string& fetched_var_name); void BCastParamsToGPUs(const std::unordered_set& vars) const; private: - void SplitTensorToPlaces( - const std::unordered_map& feed_tensors); - ParallelExecutorPrivate* member_; }; diff --git a/paddle/fluid/pybind/pybind.cc b/paddle/fluid/pybind/pybind.cc index 5121987f92..19bd30d966 100644 --- a/paddle/fluid/pybind/pybind.cc +++ b/paddle/fluid/pybind/pybind.cc @@ -514,9 +514,10 @@ All parameter, weight, gradient are variables in Paddle. return &self.GetLocalScopes(); }, py::return_value_policy::reference) - .def("local_scope", [](ParallelExecutor &self, - size_t i) { return self.GetLocalScopes()[i]; }, - py::return_value_policy::reference) + .def("feed_tensors_into_local_scopes", + &ParallelExecutor::FeedTensorsIntoLocalScopes) + .def("feed_and_split_tensor_into_local_scopes", + &ParallelExecutor::FeedAndSplitTensorIntoLocalScopes) .def("run", &ParallelExecutor::Run); BindRecordIOWriter(&m); diff --git a/python/paddle/fluid/parallel_executor.py b/python/paddle/fluid/parallel_executor.py index 5ce2aa1fc4..f9741fbed6 100644 --- a/python/paddle/fluid/parallel_executor.py +++ b/python/paddle/fluid/parallel_executor.py @@ -123,28 +123,65 @@ class ParallelExecutor(object): allow_op_delay) self.scope = scope - def run(self, fetch_list, feed_dict={}): + def run(self, fetch_list, feed=None, feed_dict=None): """ - :param fetch_list: A list of variable names that will be fetched. - :param feed_dict: A dict mapping for feed variable name to LoDTensor - or numpy array. - :return: fetched value list. - """ - if not isinstance(feed_dict, dict): - raise TypeError("feed_dict should be a dict") - feed_tensor_dict = {} - for i, feed_name in enumerate(feed_dict): - feed_tensor = feed_dict[feed_name] - if not isinstance(feed_tensor, core.LoDTensor): - feed_tensor = core.LoDTensor() - feed_tensor.set(feed_dict[feed_name], self._act_places[0]) - feed_tensor_dict[feed_name] = feed_tensor + Args: + fetch_list(list): The fetched variable names + feed(list|dict|None): The feed variables. If the feed is a dict, tensors in that dict will be splitted + into each devices. If the feed is a list, each element of the list will be copied to each device. + feed_dict: Alias for feed parameter, for backward compatibility. + + Returns: fetched result list. + + """ + if feed is None: + feed = feed_dict + + if isinstance(feed, dict): + feed_tensor_dict = dict() + for feed_name in feed: + feed_tensor = feed[feed_name] + if not isinstance(feed_tensor, core.LoDTensor): + feed_tensor = core.LoDTensor() + # always set to CPU place, since the tensor need to be splitted + # it is fast in CPU + feed_tensor.set(feed[feed_name], core.CPUPlace()) + feed_tensor_dict[feed_name] = feed_tensor + + self.executor.feed_and_split_tensor_into_local_scopes( + feed_tensor_dict) + elif isinstance(feed, list) or isinstance(feed, tuple): + if len(feed) != len(self._act_places): + raise ValueError( + "Feed a list of tensor, the list should be the same size as places" + ) + + res = list() + + for i, each in enumerate(feed): + if not isinstance(each, dict): + raise TypeError( + "Each element of feed list should be a dict") + res_dict = dict() + for feed_name in each: + tensor = each[feed_name] + if not isinstance(tensor, core.LoDTensor): + tmp = core.LoDTensor() + tmp.set(tensor, self._act_places[i]) + tensor = tmp + res_dict[feed_name] = tensor + res.append(res_dict) + self.executor.feed_tensors_into_local_scopes(res) fetch_var_name = '@FETCHED_VAR_NAME@' - self.executor.run(fetch_list, fetch_var_name, feed_tensor_dict) + self.executor.run(fetch_list, fetch_var_name) arr = self.scope.find_var(fetch_var_name).get_lod_tensor_array() return [arr[i] for i in range(len(arr))] def bcast_params(self): self.executor.bcast_params(set(self.persistable_vars)) + + @property + def device_count(self): + return len(self._act_places) diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor.py b/python/paddle/fluid/tests/unittests/test_parallel_executor.py index 83d22fd799..2f8c10fc1c 100644 --- a/python/paddle/fluid/tests/unittests/test_parallel_executor.py +++ b/python/paddle/fluid/tests/unittests/test_parallel_executor.py @@ -203,11 +203,11 @@ class TestParallelExecutorBase(unittest.TestCase): iter=10, batch_size=None, allow_op_delay=False, - feed_dict={}): + feed_dict=None): main = fluid.Program() startup = fluid.Program() with fluid.program_guard(main, startup): - loss = method(use_feed=len(feed_dict) > 0) + loss = method(use_feed=feed_dict is not None) adam = fluid.optimizer.Adam() adam.minimize(loss) if memory_opt: @@ -221,13 +221,13 @@ class TestParallelExecutorBase(unittest.TestCase): if batch_size is not None: batch_size *= fluid.core.get_cuda_device_count() begin = time.time() - first_loss, = exe.run([loss.name], feed_dict=feed_dict) + first_loss, = exe.run([loss.name], feed=feed_dict) first_loss = numpy.array(first_loss) for i in xrange(iter): - exe.run([], feed_dict=feed_dict) + exe.run([], feed=feed_dict) - last_loss, = exe.run([loss.name], feed_dict=feed_dict) + last_loss, = exe.run([loss.name], feed=feed_dict) end = time.time() if batch_size is not None: @@ -648,5 +648,5 @@ class TestCRFModel(unittest.TestCase): for i in xrange(10): cur_batch = next(data) print map(numpy.array, - pe.run(feed_dict=feeder.feed(cur_batch), + pe.run(feed=feeder.feed(cur_batch), fetch_list=[avg_cost.name]))[0] From 10669f1fe7fd13eaa8049fc3b37bb590978d6ac8 Mon Sep 17 00:00:00 2001 From: tangwei12 Date: Tue, 17 Apr 2018 14:11:53 +0800 Subject: [PATCH 41/69] Separate the implement to another PR later --- paddle/fluid/operators/detail/mpi_client.cpp | 29 ------- paddle/fluid/operators/detail/mpi_client.h | 56 ------------ paddle/fluid/operators/detail/mpi_server.h | 23 ----- paddle/fluid/operators/detail/mpi_utils.cpp | 90 -------------------- paddle/fluid/operators/detail/mpi_utils.h | 83 ------------------ 5 files changed, 281 deletions(-) delete mode 100644 paddle/fluid/operators/detail/mpi_client.cpp delete mode 100644 paddle/fluid/operators/detail/mpi_client.h delete mode 100644 paddle/fluid/operators/detail/mpi_server.h delete mode 100644 paddle/fluid/operators/detail/mpi_utils.cpp delete mode 100644 paddle/fluid/operators/detail/mpi_utils.h diff --git a/paddle/fluid/operators/detail/mpi_client.cpp b/paddle/fluid/operators/detail/mpi_client.cpp deleted file mode 100644 index 6890e437ef..0000000000 --- a/paddle/fluid/operators/detail/mpi_client.cpp +++ /dev/null @@ -1,29 +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 "mpi_client.h" -#include "mpi_utils.h" - -namespace paddle { -namespace operators { -namespace detail { -bool MPIClient::AsyncSendVariable() { - char* msg = "123456787654"; - int dst = 1; - MPIIsend send = MPIIsend(dst, msg); -} - -bool MPIClient::Wait() {} - -} // namespace detail -} // namespace operators -} // namespace paddle \ No newline at end of file diff --git a/paddle/fluid/operators/detail/mpi_client.h b/paddle/fluid/operators/detail/mpi_client.h deleted file mode 100644 index a01e5b2d11..0000000000 --- a/paddle/fluid/operators/detail/mpi_client.h +++ /dev/null @@ -1,56 +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 - -#include "paddle/fluid/framework/data_type.h" -#include "paddle/fluid/framework/lod_tensor.h" -#include "paddle/fluid/framework/scope.h" -#include "paddle/fluid/framework/selected_rows.h" - -namespace paddle { -namespace operators { -namespace detail { -class MPIClient { - public: - // bool AsyncSendVariable(const std::string& ep, - // const platform::DeviceContext& ctx, - // const framework::Scope& scope, - // const std::string& var_name, - // int64_t time_out = 600 * 1000); - - // bool AsyncGetVariable(const std::string& ep, - // const platform::DeviceContext& ctx, - // const framework::Scope& scope, - // const std::string& var_name, - // int64_t time_out = 600 * 1000); - - // void AsyncSendBatchBarrier(const std::string& ep, - // int64_t time_out = 600 * 1000); - - // void AsyncSendFetchBarrier(const std::string& ep, - // int64_t time_out = 600 * 1000); - - bool AsyncSendVariable(); - - bool Wait(); - - private: - int64_t req_count_ = 0; -}; -} // namespace detail -} // namespace operators -} // namespace paddle diff --git a/paddle/fluid/operators/detail/mpi_server.h b/paddle/fluid/operators/detail/mpi_server.h deleted file mode 100644 index dda99318af..0000000000 --- a/paddle/fluid/operators/detail/mpi_server.h +++ /dev/null @@ -1,23 +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 -namespace paddle { -namespace operators { -namespace detail { -class MPIServer { - public: - private: -}; -} // namespace detail -} // namespace operators -} // namespace paddle diff --git a/paddle/fluid/operators/detail/mpi_utils.cpp b/paddle/fluid/operators/detail/mpi_utils.cpp deleted file mode 100644 index d3191c1563..0000000000 --- a/paddle/fluid/operators/detail/mpi_utils.cpp +++ /dev/null @@ -1,90 +0,0 @@ -// -// Created by tangwei12 on 2018/3/27. -// - -#include -#include - -#include -#include "mpi_utils.h" - -#define max_worker_name_length 128 -#define mpi_tag = 2008 - -namespace paddle { - namespace operators { - namespace detail { - MPIUtils::MPIUtils(const std::string &worker_name) { - InitMPI(); - - int rank = 0, size = 1; - char my_name[max_work_group_size]; - MPI_Comm_rank(MPI_COMM_WORLD, &rank); - MPI_Comm_size(MPI_COMM_WORLD, &size); - snprintf(my_name, max_worker_name_length, worker_name.c_str()); - - std::vector worker_names(size * max_worker_name_length); - MPI_Allgather(my_name, max_worker_name_length, MPI_CHAR, &worker_names[0], - max_worker_name_length, MPI_CHAR, MPI_COMM_WORLD); - for (int i = 0; i < number_of_procs; i++) { - name_to_id_[std::string(&worker_names[i * 128])] = i; - } - } - - void MPIUtils::InitMPI() { - int flag = 0; - MPI_CHECK(MPI_Initialized(&flag)); - - if (!flag) { - int rank = 0, size = 1, len = -1; - char host_name[max_worker_name_length]; - - MPI_Init(0, 0); - MPI_Comm_rank(MPI_COMM_WORLD, &rank); - MPI_Comm_size(MPI_COMM_WORLD, &size); - MPI_Get_processor_name(host_name, &len); - } - }; - - - MPISend::MPISend(const Meta &meta) { - done1_ = 1; - done2_ = 0; - this->meta = meta; - } - - MPISend::Send() { - MPI_Send(&meta.request, meta.count, meta.datatype, meta.dst, meta.tag, - MPI_COMM_WORLD); - done2_ = 1; - } - - bool MPISend::IsReady() { - return true; - } - - bool MPISend::IsFinished() { return done1_ && done2_; } - - MPISend::~MPISend() { MPI_Free_mem(meta); } - - - MPIRecv::MPIRecv(const Meta &meta) { - this->meta = meta; - } - - MPIRecv::Recv() {} - - bool MPIRecv::IsReady() { - return true; - } - - MPIRecv::IsFinished() {} - - MPIRecv::~MPIRecv() { - MPI_Free_mem(meta); - } - - } // namespace detail - - } // namespace operators -} // namespace paddle \ No newline at end of file diff --git a/paddle/fluid/operators/detail/mpi_utils.h b/paddle/fluid/operators/detail/mpi_utils.h deleted file mode 100644 index 05801020bf..0000000000 --- a/paddle/fluid/operators/detail/mpi_utils.h +++ /dev/null @@ -1,83 +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 -#include - -namespace paddle { - namespace operators { - namespace detail { - class MPIUtils { - public: - MPIUtils(const std::string &worker_name); - - const int GetRankID(const std::string &task_id); - - private: - void InitMPI(); - - std::map name_id_map; - }; - - class Meta { - public: - int src; - int dst; - MPI_Datatype datatype; - char *request; - int count; - int tag; - int device; - }; - - class MPISend { - public: - MPISend(const Meta &meta); - - bool IsFinished(); - - bool IsReady(); - - void Send(); - - ~MPISend(); - - private: - int done1_; - int done2_; - Meta *meta; - }; - - class MPIRecv { - public: - MPIRecv(const Meta &meta); - - bool IsReady(); - - bool IsFinished(); - - void Recv(); - - ~MPIRecv(); - - private: - int done1_; - int done2_; - Meta *meta; - }; - - } // namespace detail - } // namespace operators -} // namespace paddle From 64c139e8546cbc444d61fc2104ed897476e718b8 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Tue, 17 Apr 2018 14:21:33 +0800 Subject: [PATCH 42/69] Using constructor for VarHandle --- .../details/broadcast_op_handle_test.cc | 19 +++++-------------- .../details/gather_op_handle_test.cc | 18 +++++------------- .../details/multi_devices_graph_builder.cc | 10 +++------- .../framework/details/ssa_graph_builder.cc | 18 +++++------------- paddle/fluid/framework/details/var_handle.h | 12 ++++++++++-- 5 files changed, 28 insertions(+), 49 deletions(-) diff --git a/paddle/fluid/framework/details/broadcast_op_handle_test.cc b/paddle/fluid/framework/details/broadcast_op_handle_test.cc index dfc52b012f..bcd61335be 100644 --- a/paddle/fluid/framework/details/broadcast_op_handle_test.cc +++ b/paddle/fluid/framework/details/broadcast_op_handle_test.cc @@ -77,14 +77,9 @@ struct TestBroadcastOpHandle { local_scopes_[input_scope_idx]->Var("input"); op_handle_.reset(new BroadcastOpHandle(local_scopes_, gpu_list_)); - - vars_.emplace_back(new VarHandle()); - VarHandle* in_var_handle = static_cast(vars_.back().get()); - in_var_handle->place_ = gpu_list_[input_scope_idx]; - in_var_handle->name_ = "input"; - in_var_handle->version_ = 1; - in_var_handle->scope_idx_ = input_scope_idx; - in_var_handle->generated_op_ = nullptr; + auto* in_var_handle = + new VarHandle(1, input_scope_idx, "input", gpu_list_[input_scope_idx]); + vars_.emplace_back(in_var_handle); op_handle_->AddInput(in_var_handle); // add dummy var @@ -96,12 +91,8 @@ struct TestBroadcastOpHandle { for (size_t j = 0; j < gpu_list_.size(); ++j) { op_handle_->dev_ctxes_[gpu_list_[j]] = ctxs_[j].get(); - vars_.emplace_back(new VarHandle()); - VarHandle* out_var_handle = static_cast(vars_.back().get()); - out_var_handle->place_ = gpu_list_[j]; - out_var_handle->name_ = "out"; - out_var_handle->version_ = 2; - out_var_handle->scope_idx_ = j; + VarHandle* out_var_handle = new VarHandle(2, j, "out", gpu_list_[j]); + vars_.emplace_back(out_var_handle); op_handle_->AddOutput(out_var_handle); } diff --git a/paddle/fluid/framework/details/gather_op_handle_test.cc b/paddle/fluid/framework/details/gather_op_handle_test.cc index 10839f239d..2da8c89d2d 100644 --- a/paddle/fluid/framework/details/gather_op_handle_test.cc +++ b/paddle/fluid/framework/details/gather_op_handle_test.cc @@ -79,13 +79,8 @@ struct TestGatherOpHandle { // add input for (size_t j = 0; j < gpu_list_.size(); ++j) { op_handle_->dev_ctxes_[gpu_list_[j]] = ctxs_[j].get(); - vars_.emplace_back(new VarHandle()); - VarHandle* in_var_handle = static_cast(vars_.back().get()); - in_var_handle->place_ = gpu_list_[j]; - in_var_handle->name_ = "input"; - in_var_handle->version_ = 1; - in_var_handle->scope_idx_ = j; - in_var_handle->generated_op_ = nullptr; + auto* in_var_handle = new VarHandle(1, j, "input", gpu_list_[j]); + vars_.emplace_back(in_var_handle); op_handle_->AddInput(in_var_handle); } @@ -97,12 +92,9 @@ struct TestGatherOpHandle { op_handle_->AddInput(in_dummy_var_handle); // add output - vars_.emplace_back(new VarHandle()); - VarHandle* out_var_handle = static_cast(vars_.back().get()); - out_var_handle->place_ = gpu_list_[input_scope_idx]; - out_var_handle->name_ = "out"; - out_var_handle->version_ = 2; - out_var_handle->scope_idx_ = input_scope_idx; + auto* out_var_handle = + new VarHandle(2, input_scope_idx, "out", gpu_list_[input_scope_idx]); + vars_.emplace_back(out_var_handle); op_handle_->AddOutput(out_var_handle); // add dummy var diff --git a/paddle/fluid/framework/details/multi_devices_graph_builder.cc b/paddle/fluid/framework/details/multi_devices_graph_builder.cc index 5a95cbc536..4d76dbf7f6 100644 --- a/paddle/fluid/framework/details/multi_devices_graph_builder.cc +++ b/paddle/fluid/framework/details/multi_devices_graph_builder.cc @@ -177,13 +177,9 @@ std::unique_ptr MultiDevSSAGraphBuilder::Build( auto &prev_grad = vars[vars.size() - 1]; op_handle->AddInput(prev_grad.get()); - vars.emplace_back(new VarHandle); - auto &var = vars.back(); - var->place_ = p; - var->name_ = og; - var->version_ = vars.size() - 1; - - op_handle->AddOutput(var.get()); + auto var = new VarHandle(vars.size() - 1, i, og, p); + vars.emplace_back(var); + op_handle->AddOutput(var); } #else PADDLE_ENFORCE("Not implemented"); diff --git a/paddle/fluid/framework/details/ssa_graph_builder.cc b/paddle/fluid/framework/details/ssa_graph_builder.cc index be5fb75775..25e8c77bb4 100644 --- a/paddle/fluid/framework/details/ssa_graph_builder.cc +++ b/paddle/fluid/framework/details/ssa_graph_builder.cc @@ -54,13 +54,8 @@ VarHandle *SSAGraphBuilder::CreateOrGetLatestVarHandle( auto &var_holder = var_holders[each_var_name]; VarHandle *var = nullptr; if (var_holder.empty()) { - var_holder.emplace_back(new VarHandle); - auto &init_var = var_holder[0]; - init_var->place_ = place; - init_var->name_ = each_var_name; - init_var->generated_op_ = nullptr; - init_var->version_ = 0; - var = init_var.get(); + var = new VarHandle(0, place_offset, each_var_name, place); + var_holder.emplace_back(var); } else { var = var_holder.rbegin()->get(); } @@ -73,12 +68,9 @@ void SSAGraphBuilder::CreateOpOutput(SSAGraph *graph, OpHandleBase *op_handle, size_t place_offset) { auto &vars = graph->vars_[place_offset][each_var_name]; size_t version = vars.size(); - vars.emplace_back(new VarHandle()); - auto &var = vars.back(); - var->version_ = version; - var->name_ = each_var_name; - var->place_ = place; - op_handle->AddOutput(var.get()); + auto var = new VarHandle(version, place_offset, each_var_name, place); + vars.emplace_back(var); + op_handle->AddOutput(var); } template diff --git a/paddle/fluid/framework/details/var_handle.h b/paddle/fluid/framework/details/var_handle.h index 871e41343f..2b887c67e6 100644 --- a/paddle/fluid/framework/details/var_handle.h +++ b/paddle/fluid/framework/details/var_handle.h @@ -16,6 +16,7 @@ #include #include #include +#include #include "paddle/fluid/platform/place.h" @@ -33,10 +34,10 @@ struct VarHandleBase { // The operator who generate this variable. nullptr if the variable // is a root node. - OpHandleBase *generated_op_; + OpHandleBase* generated_op_{nullptr}; // Operators which depend on this variable ready. - std::unordered_set pending_ops_; + std::unordered_set pending_ops_; }; // VarHandle is actually a single version of Runtime Variable. @@ -47,6 +48,13 @@ struct VarHandleBase { struct VarHandle : public VarHandleBase { std::string DebugString() const override; + VarHandle(size_t version, size_t scope_index, std::string name, + platform::Place place) + : version_(version), + scope_idx_(scope_index), + name_(std::move(name)), + place_(std::move(place)) {} + // version field currently is not used, however, just store the version to // debug easily. size_t version_; From a1d910b1440af8e648f0be556633a3784e2efc04 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Tue, 17 Apr 2018 14:23:29 +0800 Subject: [PATCH 43/69] Fix line witdth --- python/paddle/fluid/parallel_executor.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/python/paddle/fluid/parallel_executor.py b/python/paddle/fluid/parallel_executor.py index f9741fbed6..190efe6c1b 100644 --- a/python/paddle/fluid/parallel_executor.py +++ b/python/paddle/fluid/parallel_executor.py @@ -128,8 +128,10 @@ class ParallelExecutor(object): Args: fetch_list(list): The fetched variable names - feed(list|dict|None): The feed variables. If the feed is a dict, tensors in that dict will be splitted - into each devices. If the feed is a list, each element of the list will be copied to each device. + feed(list|dict|None): The feed variables. If the feed is a dict, + tensors in that dict will be splitted into each devices. If + the feed is a list, each element of the list will be copied + to each device. feed_dict: Alias for feed parameter, for backward compatibility. Returns: fetched result list. From 6708546305ad8cd7cd444cbdaed2607087d7a368 Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Tue, 17 Apr 2018 14:33:37 +0800 Subject: [PATCH 44/69] specify version for pip --- Dockerfile.android | 2 +- tools/manylinux1/Dockerfile.android | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/Dockerfile.android b/Dockerfile.android index cc022d596b..848a7eba6f 100644 --- a/Dockerfile.android +++ b/Dockerfile.android @@ -27,7 +27,7 @@ RUN git config --global credential.helper store # Fix locales to en_US.UTF-8 RUN localedef -i en_US -f UTF-8 en_US.UTF-8 -RUN pip install --upgrade pip && \ +RUN pip install --upgrade pip==9.0.3 && \ pip install -U 'protobuf==3.1.0' && \ pip install -U wheel sphinx && \ pip install pre-commit diff --git a/tools/manylinux1/Dockerfile.android b/tools/manylinux1/Dockerfile.android index b6cae228a0..7eb040902b 100644 --- a/tools/manylinux1/Dockerfile.android +++ b/tools/manylinux1/Dockerfile.android @@ -37,7 +37,7 @@ RUN git config --global credential.helper store # Fix locales to en_US.UTF-8 RUN localedef -i en_US -f UTF-8 en_US.UTF-8 -RUN pip install --upgrade pip && \ +RUN pip install --upgrade pip==9.0.3 && \ pip install -U 'protobuf==3.1.0' && \ pip install -U wheel sphinx && \ pip install pre-commit From a79676e8bfd5782d2e00e0d73ef71ec69b56253a Mon Sep 17 00:00:00 2001 From: dzhwinter Date: Tue, 17 Apr 2018 14:42:59 +0800 Subject: [PATCH 45/69] Update parallel_executor.md (#9959) --- doc/fluid/design/concepts/parallel_executor.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/fluid/design/concepts/parallel_executor.md b/doc/fluid/design/concepts/parallel_executor.md index 9aed3b059a..4f88e27bed 100644 --- a/doc/fluid/design/concepts/parallel_executor.md +++ b/doc/fluid/design/concepts/parallel_executor.md @@ -84,7 +84,7 @@ Running an operator can be asynchronized. There is a thread pool to execute an ` ## Synchronize GPU Kernels -The GPU is a non-blocking device. The different streams need be synchronized when switing streams. In current implementation, the synchronization based on the following algorithm: +The GPU is a non-blocking device. The different streams need be synchronized when switching streams. In current implementation, the synchronization based on the following algorithm: 1. `OpHandle` will record `DeviceContext` that it is used. 2. In `OpHandle::Run`, if the `DeviceContext` of current operator is different from `DeviceContext` of any input variable, just wait the generate operator of this input variable. From 7286954337416d4ec023d86ad5533e5baa47c717 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Tue, 17 Apr 2018 14:59:25 +0800 Subject: [PATCH 46/69] Add more comments --- python/paddle/fluid/parallel_executor.py | 27 ++++++++++++++++++++++++ 1 file changed, 27 insertions(+) diff --git a/python/paddle/fluid/parallel_executor.py b/python/paddle/fluid/parallel_executor.py index 190efe6c1b..07cc1e2934 100644 --- a/python/paddle/fluid/parallel_executor.py +++ b/python/paddle/fluid/parallel_executor.py @@ -16,6 +16,7 @@ import core import multiprocessing import framework import executor +import sys __all__ = ['ParallelExecutor'] @@ -125,6 +126,30 @@ class ParallelExecutor(object): def run(self, fetch_list, feed=None, feed_dict=None): """ + Run a parallel executor with fetch_list. + + The feed parameter can be a dict or a list. If feed is a dict, the + feed data will be split into multiple devices. If feed is a list, we + assume the data has been splitted into multiple devices, the each + element in the list will be copied to each device directly. + + For example, if the feed is a dict: + >>> exe = ParallelExecutor() + >>> # the image will be splitted into devices. If there is two devices + >>> # each device will process an image with shape (24, 1, 28, 28) + >>> exe.run(feed={'image': numpy.random.random(size=(48, 1, 28, 28))}) + + For example, if the feed is a list: + >>> exe = ParallelExecutor() + >>> # each device will process each element in the list. + >>> # the 1st device will process an image with shape (48, 1, 28, 28) + >>> # the 2nd device will process an image with shape (32, 1, 28, 28) + >>> # + >>> # you can use exe.device_count to get the device number. + >>> exe.run(feed=[{"image": numpy.random.random(size=(48, 1, 28, 28))}, + >>> {"image": numpy.random.random(size=(32, 1, 28, 28))}, + >>> ]) + Args: fetch_list(list): The fetched variable names @@ -133,12 +158,14 @@ class ParallelExecutor(object): the feed is a list, each element of the list will be copied to each device. feed_dict: Alias for feed parameter, for backward compatibility. + This parameter is deprecated. Returns: fetched result list. """ if feed is None: feed = feed_dict + print >> sys.stderr, "`feed_dict` is deprecated. Please use `feed=`" if isinstance(feed, dict): feed_tensor_dict = dict() From 5e13314dc1a505ec4a7b2f36e826e1aaf4b2b540 Mon Sep 17 00:00:00 2001 From: mozga-intel Date: Tue, 17 Apr 2018 00:59:41 +0200 Subject: [PATCH 47/69] Commit --- .../fluid/tests/unittests/CMakeLists.txt | 9 +- .../unittests/test_activation_mkldnn_op.py | 99 +++++++++++++++++++ .../tests/unittests/test_activation_op.py | 77 --------------- .../tests/unittests/test_conv2d_mkldnn_op.py | 36 +++++++ .../fluid/tests/unittests/test_conv2d_op.py | 17 ---- .../{test_fc_op.py => test_fc_mkldnn_op.py} | 0 .../tests/unittests/test_lrn_mkldnn_op.py | 49 +++++++++ .../fluid/tests/unittests/test_lrn_op.py | 29 ------ .../tests/unittests/test_pool2d_mkldnn_op.py | 50 ++++++++++ .../fluid/tests/unittests/test_pool2d_op.py | 31 ------ 10 files changed, 240 insertions(+), 157 deletions(-) create mode 100644 python/paddle/fluid/tests/unittests/test_activation_mkldnn_op.py create mode 100644 python/paddle/fluid/tests/unittests/test_conv2d_mkldnn_op.py rename python/paddle/fluid/tests/unittests/{test_fc_op.py => test_fc_mkldnn_op.py} (100%) create mode 100644 python/paddle/fluid/tests/unittests/test_lrn_mkldnn_op.py create mode 100644 python/paddle/fluid/tests/unittests/test_pool2d_mkldnn_op.py diff --git a/python/paddle/fluid/tests/unittests/CMakeLists.txt b/python/paddle/fluid/tests/unittests/CMakeLists.txt index 356c3e64b3..8f17eeea13 100644 --- a/python/paddle/fluid/tests/unittests/CMakeLists.txt +++ b/python/paddle/fluid/tests/unittests/CMakeLists.txt @@ -1,10 +1,13 @@ file(GLOB TEST_OPS RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "test_*.py") string(REPLACE ".py" "" TEST_OPS "${TEST_OPS}") -# The fully connected test is removed whe the WITH_MKLDNN flag is OFF -# Because the fully connected layer has only one kernel (MKLDNN) +# The MKLDNN tests are skiped when the MKLDNN flag is OFF if(NOT WITH_MKLDNN) - list(REMOVE_ITEM TEST_OPS test_fc_op) + foreach(src ${TEST_OPS}) + if(${src} MATCHES ".*_mkldnn_op$") + list(REMOVE_ITEM TEST_OPS ${src}) + endif() + endforeach() endif(NOT WITH_MKLDNN) if(NOT WITH_DISTRIBUTE) diff --git a/python/paddle/fluid/tests/unittests/test_activation_mkldnn_op.py b/python/paddle/fluid/tests/unittests/test_activation_mkldnn_op.py new file mode 100644 index 0000000000..7d554c2276 --- /dev/null +++ b/python/paddle/fluid/tests/unittests/test_activation_mkldnn_op.py @@ -0,0 +1,99 @@ +# 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.core as core +from op_test import OpTest +from scipy.special import expit +from test_activation_op import TestRelu, TestTanh, TestSqrt, TestAbs + + +class TestMKLDNNReluDim2(TestRelu): + def setUp(self): + super(TestMKLDNNReluDim2, self).setUp() + + self.attrs = {"use_mkldnn": True} + + +class TestMKLDNNTanhDim2(TestTanh): + def setUp(self): + super(TestMKLDNNTanhDim2, self).setUp() + + self.attrs = {"use_mkldnn": True} + + +class TestMKLDNNSqrtDim2(TestSqrt): + def setUp(self): + super(TestMKLDNNSqrtDim2, self).setUp() + + self.attrs = {"use_mkldnn": True} + + +class TestMKLDNNAbsDim2(TestAbs): + def setUp(self): + super(TestMKLDNNAbsDim2, self).setUp() + self.attrs = {"use_mkldnn": True} + + +class TestMKLDNNReluDim4(TestRelu): + def setUp(self): + super(TestMKLDNNReluDim4, self).setUp() + + x = np.random.uniform(-1, 1, [2, 4, 3, 5]).astype("float32") + # The same reason with TestAbs + x[np.abs(x) < 0.005] = 0.02 + out = np.maximum(x, 0) + + self.inputs = {'X': OpTest.np_dtype_to_fluid_dtype(x)} + self.outputs = {'Out': out} + self.attrs = {"use_mkldnn": True} + + +class TestMKLDNNTanhDim4(TestTanh): + def setUp(self): + super(TestMKLDNNTanhDim4, self).setUp() + + self.inputs = { + 'X': np.random.uniform(0.1, 1, [2, 4, 3, 5]).astype("float32") + } + self.outputs = {'Out': np.tanh(self.inputs['X'])} + self.attrs = {"use_mkldnn": True} + + +class TestMKLDNNSqrtDim4(TestSqrt): + def setUp(self): + super(TestMKLDNNSqrtDim4, self).setUp() + + self.inputs = { + 'X': np.random.uniform(0.1, 1, [2, 4, 3, 5]).astype("float32") + } + self.outputs = {'Out': np.sqrt(self.inputs['X'])} + self.attrs = {"use_mkldnn": True} + + +class TestMKLDNNAbsDim4(TestAbs): + def setUp(self): + super(TestMKLDNNAbsDim4, self).setUp() + + x = np.random.uniform(-1, 1, [2, 4, 3, 5]).astype("float32") + # The same reason with TestAbs + x[np.abs(x) < 0.005] = 0.02 + self.inputs = {'X': x} + self.outputs = {'Out': np.abs(self.inputs['X'])} + self.attrs = {"use_mkldnn": True} + + +if __name__ == '__main__': + unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_activation_op.py b/python/paddle/fluid/tests/unittests/test_activation_op.py index 57d4a50e91..c9069777fa 100644 --- a/python/paddle/fluid/tests/unittests/test_activation_op.py +++ b/python/paddle/fluid/tests/unittests/test_activation_op.py @@ -1098,82 +1098,5 @@ class TestFP16Swish(TestSwish): self.check_output_with_place(place, atol=1e-3) -#--------------------test MKLDNN-------------------- -class TestMKLDNNReluDim2(TestRelu): - def setUp(self): - super(TestMKLDNNReluDim2, self).setUp() - - self.attrs = {"use_mkldnn": True} - - -class TestMKLDNNTanhDim2(TestTanh): - def setUp(self): - super(TestMKLDNNTanhDim2, self).setUp() - - self.attrs = {"use_mkldnn": True} - - -class TestMKLDNNSqrtDim2(TestSqrt): - def setUp(self): - super(TestMKLDNNSqrtDim2, self).setUp() - - self.attrs = {"use_mkldnn": True} - - -class TestMKLDNNAbsDim2(TestAbs): - def setUp(self): - super(TestMKLDNNAbsDim2, self).setUp() - - self.attrs = {"use_mkldnn": True} - - -class TestMKLDNNReluDim4(TestRelu): - def setUp(self): - super(TestMKLDNNReluDim4, self).setUp() - - x = np.random.uniform(-1, 1, [2, 4, 3, 5]).astype("float32") - # The same reason with TestAbs - x[np.abs(x) < 0.005] = 0.02 - out = np.maximum(x, 0) - - self.inputs = {'X': OpTest.np_dtype_to_fluid_dtype(x)} - self.outputs = {'Out': out} - self.attrs = {"use_mkldnn": True} - - -class TestMKLDNNTanhDim4(TestTanh): - def setUp(self): - super(TestMKLDNNTanhDim4, self).setUp() - - self.inputs = { - 'X': np.random.uniform(0.1, 1, [2, 4, 3, 5]).astype("float32") - } - self.outputs = {'Out': np.tanh(self.inputs['X'])} - self.attrs = {"use_mkldnn": True} - - -class TestMKLDNNSqrtDim4(TestSqrt): - def setUp(self): - super(TestMKLDNNSqrtDim4, self).setUp() - - self.inputs = { - 'X': np.random.uniform(0.1, 1, [2, 4, 3, 5]).astype("float32") - } - self.outputs = {'Out': np.sqrt(self.inputs['X'])} - self.attrs = {"use_mkldnn": True} - - -class TestMKLDNNAbsDim4(TestAbs): - def setUp(self): - super(TestMKLDNNAbsDim4, self).setUp() - - x = np.random.uniform(-1, 1, [2, 4, 3, 5]).astype("float32") - # The same reason with TestAbs - x[np.abs(x) < 0.005] = 0.02 - self.inputs = {'X': x} - self.outputs = {'Out': np.abs(self.inputs['X'])} - self.attrs = {"use_mkldnn": True} - - if __name__ == "__main__": unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_conv2d_mkldnn_op.py b/python/paddle/fluid/tests/unittests/test_conv2d_mkldnn_op.py new file mode 100644 index 0000000000..db6be21baa --- /dev/null +++ b/python/paddle/fluid/tests/unittests/test_conv2d_mkldnn_op.py @@ -0,0 +1,36 @@ +# 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 + +from test_conv2d_op import TestConv2dOp, TestWithPad, TestWithStride + + +class TestMKLDNN(TestConv2dOp): + def init_kernel_type(self): + self.use_mkldnn = True + + +class TestMKLDNNWithPad(TestWithPad): + def init_kernel_type(self): + self.use_mkldnn = True + + +class TestMKLDNNWithStride(TestWithStride): + def init_kernel_type(self): + self.use_mkldnn = True + + +if __name__ == '__main__': + unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_conv2d_op.py b/python/paddle/fluid/tests/unittests/test_conv2d_op.py index 65606a0b43..a478649541 100644 --- a/python/paddle/fluid/tests/unittests/test_conv2d_op.py +++ b/python/paddle/fluid/tests/unittests/test_conv2d_op.py @@ -373,22 +373,5 @@ class TestDepthwiseConv2(TestConv2dOp): # def init_op_type(self): # self.op_type = "conv_cudnn" - -#----------------Conv2dMKLDNN---------------- -class TestMKLDNN(TestConv2dOp): - def init_kernel_type(self): - self.use_mkldnn = True - - -class TestMKLDNNWithPad(TestWithPad): - def init_kernel_type(self): - self.use_mkldnn = True - - -class TestMKLDNNWithStride(TestWithStride): - def init_kernel_type(self): - self.use_mkldnn = True - - if __name__ == '__main__': unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_fc_op.py b/python/paddle/fluid/tests/unittests/test_fc_mkldnn_op.py similarity index 100% rename from python/paddle/fluid/tests/unittests/test_fc_op.py rename to python/paddle/fluid/tests/unittests/test_fc_mkldnn_op.py diff --git a/python/paddle/fluid/tests/unittests/test_lrn_mkldnn_op.py b/python/paddle/fluid/tests/unittests/test_lrn_mkldnn_op.py new file mode 100644 index 0000000000..966a16dc87 --- /dev/null +++ b/python/paddle/fluid/tests/unittests/test_lrn_mkldnn_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 +from test_lrn_op import TestLRNOp + + +class TestLRNMKLDNNOp(TestLRNOp): + def get_attrs(self): + attrs = TestLRNOp.get_attrs(self) + attrs['use_mkldnn'] = True + return attrs + + def test_check_output(self): + self.check_output(atol=0.002) + + +class TestLRNMKLDNNOpWithIsTest(TestLRNMKLDNNOp): + def get_attrs(self): + attrs = TestLRNMKLDNNOp.get_attrs(self) + attrs['is_test'] = True + return attrs + + def test_check_grad_normal(self): + def check_raise_is_test(): + try: + self.check_grad(['X'], 'Out', max_relative_error=0.01) + except Exception as e: + t = \ + "is_test attribute should be set to False in training phase." + if t in str(e): + raise AttributeError + + self.assertRaises(AttributeError, check_raise_is_test) + + +if __name__ == "__main__": + unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_lrn_op.py b/python/paddle/fluid/tests/unittests/test_lrn_op.py index 8fa480b9bc..eaff45cbb2 100644 --- a/python/paddle/fluid/tests/unittests/test_lrn_op.py +++ b/python/paddle/fluid/tests/unittests/test_lrn_op.py @@ -87,34 +87,5 @@ class TestLRNOp(OpTest): self.check_grad(['X'], 'Out', max_relative_error=0.01) -class TestLRNMKLDNNOp(TestLRNOp): - def get_attrs(self): - attrs = TestLRNOp.get_attrs(self) - attrs['use_mkldnn'] = True - return attrs - - def test_check_output(self): - self.check_output(atol=0.002) - - -class TestLRNMKLDNNOpWithIsTest(TestLRNMKLDNNOp): - def get_attrs(self): - attrs = TestLRNMKLDNNOp.get_attrs(self) - attrs['is_test'] = True - return attrs - - def test_check_grad_normal(self): - def check_raise_is_test(): - try: - self.check_grad(['X'], 'Out', max_relative_error=0.01) - except Exception as e: - t = \ - "is_test attribute should be set to False in training phase." - if t in str(e): - raise AttributeError - - self.assertRaises(AttributeError, check_raise_is_test) - - if __name__ == "__main__": unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_pool2d_mkldnn_op.py b/python/paddle/fluid/tests/unittests/test_pool2d_mkldnn_op.py new file mode 100644 index 0000000000..003ebba18b --- /dev/null +++ b/python/paddle/fluid/tests/unittests/test_pool2d_mkldnn_op.py @@ -0,0 +1,50 @@ +# 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 +from test_pool2d_op import TestPool2d_Op, TestCase1, TestCase2, TestCase3, TestCase4, TestCase5 + + +class TestMKLDNNCase1(TestPool2d_Op): + def init_kernel_type(self): + self.use_mkldnn = True + + +class TestMKLDNNCase2(TestCase1): + def init_kernel_type(self): + self.use_mkldnn = True + + +class TestMKLDNNCase3(TestCase2): + def init_kernel_type(self): + self.use_mkldnn = True + + +class TestMKLDNNCase4(TestCase3): + def init_kernel_type(self): + self.use_mkldnn = True + + +class TestMKLDNNCase5(TestCase4): + def init_kernel_type(self): + self.use_mkldnn = True + + +class TestMKLDNNCase6(TestCase5): + def init_kernel_type(self): + self.use_mkldnn = True + + +if __name__ == '__main__': + unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_pool2d_op.py b/python/paddle/fluid/tests/unittests/test_pool2d_op.py index 764fa575fb..328a9ffd25 100644 --- a/python/paddle/fluid/tests/unittests/test_pool2d_op.py +++ b/python/paddle/fluid/tests/unittests/test_pool2d_op.py @@ -317,36 +317,5 @@ class TestCeilModeCase4(TestCase2): self.ceil_mode = True -#--------------------test pool2d MKLDNN-------------------- -class TestMKLDNNCase1(TestPool2d_Op): - def init_kernel_type(self): - self.use_mkldnn = True - - -class TestMKLDNNCase2(TestCase1): - def init_kernel_type(self): - self.use_mkldnn = True - - -class TestMKLDNNCase3(TestCase2): - def init_kernel_type(self): - self.use_mkldnn = True - - -class TestMKLDNNCase4(TestCase3): - def init_kernel_type(self): - self.use_mkldnn = True - - -class TestMKLDNNCase5(TestCase4): - def init_kernel_type(self): - self.use_mkldnn = True - - -class TestMKLDNNCase6(TestCase5): - def init_kernel_type(self): - self.use_mkldnn = True - - if __name__ == '__main__': unittest.main() From ab86fb11c4492a06a6899a40c696aca6b4234586 Mon Sep 17 00:00:00 2001 From: JiayiFeng Date: Tue, 17 Apr 2018 07:42:45 +0000 Subject: [PATCH 48/69] complete parallel accuracy test --- python/paddle/fluid/parallel_executor.py | 3 +- .../tests/unittests/test_parallel_executor.py | 49 ++++++++++++++----- 2 files changed, 39 insertions(+), 13 deletions(-) diff --git a/python/paddle/fluid/parallel_executor.py b/python/paddle/fluid/parallel_executor.py index 8d9f8c3489..9527a887a3 100644 --- a/python/paddle/fluid/parallel_executor.py +++ b/python/paddle/fluid/parallel_executor.py @@ -130,7 +130,8 @@ class ParallelExecutor(object): or numpy array. :return: fetched value list. """ - feed = feed_dict + if feed == {}: + feed = feed_dict if not isinstance(feed, dict): raise TypeError("feed should be a dict") diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor.py b/python/paddle/fluid/tests/unittests/test_parallel_executor.py index 42df00c3ee..f819025f10 100644 --- a/python/paddle/fluid/tests/unittests/test_parallel_executor.py +++ b/python/paddle/fluid/tests/unittests/test_parallel_executor.py @@ -200,17 +200,29 @@ class TestParallelExecutorBase(unittest.TestCase): def check_network_convergence(self, method, memory_opt=True, - iter=10, + iter=50, batch_size=None, allow_op_delay=False, feed_dict={}, seed=None, use_parallel_executor=True): + def run_executor(exe, feed, fetch_list, program=None): + if isinstance(exe, fluid.ParallelExecutor): + res = exe.run(fetch_list=fetch_list, feed=feed) + elif isinstance(exe, fluid.Executor): + if program is None: + program = fluid.default_main_program() + res = exe.run(program=program, feed=feed, fetch_list=fetch_list) + else: + raise ValueError('Unkown type exe') + return res + main = fluid.Program() startup = fluid.Program() with fluid.program_guard(main, startup): if seed is not None: startup.random_seed = seed + main.random_seed = seed loss = method(use_feed=len(feed_dict) > 0) adam = fluid.optimizer.Adam() adam.minimize(loss) @@ -229,13 +241,15 @@ class TestParallelExecutorBase(unittest.TestCase): if batch_size is not None: batch_size *= fluid.core.get_cuda_device_count() begin = time.time() - first_loss, = exe.run([loss.name], feed=feed_dict) + first_loss, = run_executor( + exe=exe, feed=feed_dict, fetch_list=[loss.name]) first_loss = numpy.array(first_loss) for i in xrange(iter): - exe.run([], feed=feed_dict) + run_executor(exe=exe, feed=feed_dict, fetch_list=[]) - last_loss, = exe.run([loss.name], feed=feed_dict) + last_loss, = run_executor( + exe=exe, feed=feed_dict, fetch_list=[loss.name]) end = time.time() if batch_size is not None: @@ -277,14 +291,25 @@ class TestMNIST(TestParallelExecutorBase): "label": label}) def test_simple_fc_parallel_accuracy(self): - #single_first_loss, single_last_loss = self.check_network_convergence( - # simple_fc_net, seed=0, use_parallel_executor=False) - #parallel_first_loss, parallel_last_loss = self.check_network_convergence( - # simple_fc_net, seed=0, use_parallel_executor=True) - print('single_first_loss=', single_first_loss) - print('single_last_loss=', single_last_loss) - print('parallel_first_loss=', parallel_first_loss) - print('parallel_last_loss=', parallel_last_loss) + img = numpy.zeros(shape=[32, 784], dtype='float32') + label = numpy.ones(shape=[32, 1], dtype='int64') + single_first_loss, single_last_loss = self.check_network_convergence( + method=simple_fc_net, + seed=1000, + feed_dict={"image": img, + "label": label}, + use_parallel_executor=False) + parallel_first_loss, parallel_last_loss = self.check_network_convergence( + method=simple_fc_net, + seed=1000, + feed_dict={"image": img, + "label": label}, + use_parallel_executor=True) + + for p_f in parallel_first_loss: + self.assertAlmostEquals(p_f, single_first_loss[0], delta=1e-6) + for p_l in parallel_last_loss: + self.assertAlmostEquals(p_l, single_last_loss[0], delta=1e-6) def test_batchnorm_fc(self): self.check_network_convergence(fc_with_batchnorm) From 7d19b65e65360bcb9a3ad9f2bfe678995bf70c60 Mon Sep 17 00:00:00 2001 From: Luo Tao Date: Tue, 17 Apr 2018 16:20:17 +0800 Subject: [PATCH 49/69] move paddle/scripts/check_env.sh to benchmark/ --- {paddle/scripts => benchmark/paddle/image}/check_env.sh | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename {paddle/scripts => benchmark/paddle/image}/check_env.sh (100%) diff --git a/paddle/scripts/check_env.sh b/benchmark/paddle/image/check_env.sh similarity index 100% rename from paddle/scripts/check_env.sh rename to benchmark/paddle/image/check_env.sh From 1de9edee514e6ddc98e2372384395bfff78d82e0 Mon Sep 17 00:00:00 2001 From: JiayiFeng Date: Tue, 17 Apr 2018 08:20:34 +0000 Subject: [PATCH 50/69] Follow comments --- python/paddle/fluid/parallel_executor.py | 5 +++++ .../paddle/fluid/tests/unittests/test_parallel_executor.py | 1 - 2 files changed, 5 insertions(+), 1 deletion(-) diff --git a/python/paddle/fluid/parallel_executor.py b/python/paddle/fluid/parallel_executor.py index 9527a887a3..7ad5f0d740 100644 --- a/python/paddle/fluid/parallel_executor.py +++ b/python/paddle/fluid/parallel_executor.py @@ -16,6 +16,7 @@ import core import multiprocessing import framework import executor +import warnings __all__ = ['ParallelExecutor'] @@ -130,6 +131,10 @@ class ParallelExecutor(object): or numpy array. :return: fetched value list. """ + if not feed_dict == {}: + warnings.warn( + "The 'feed_dict' of ParallelExecutor.run() is deprecated. Please use 'feed' instead." + ) if feed == {}: feed = feed_dict if not isinstance(feed, dict): diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor.py b/python/paddle/fluid/tests/unittests/test_parallel_executor.py index c376810ad5..b653f2c11f 100644 --- a/python/paddle/fluid/tests/unittests/test_parallel_executor.py +++ b/python/paddle/fluid/tests/unittests/test_parallel_executor.py @@ -223,7 +223,6 @@ class TestParallelExecutorBase(unittest.TestCase): with fluid.program_guard(main, startup): if seed is not None: startup.random_seed = seed - main.random_seed = seed loss = method(use_feed=len(feed_dict) > 0) adam = fluid.optimizer.Adam() adam.minimize(loss) From eb2e4eeadeaced1716da76aea6b4014f80bad301 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Tue, 17 Apr 2018 16:37:15 +0800 Subject: [PATCH 51/69] Debug --- paddle/fluid/framework/parallel_executor.cc | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/paddle/fluid/framework/parallel_executor.cc b/paddle/fluid/framework/parallel_executor.cc index c1486b527d..186ddbe369 100644 --- a/paddle/fluid/framework/parallel_executor.cc +++ b/paddle/fluid/framework/parallel_executor.cc @@ -64,12 +64,12 @@ ParallelExecutor::ParallelExecutor( // Create local scopes if (local_scopes.empty()) { for (size_t i = 0; i < member_->places_.size(); ++i) { - member_->local_scopes_.push_back(&scope->NewScope()); + member_->local_scopes_.emplace_back(&scope->NewScope()); } } else { PADDLE_ENFORCE_EQ(member_->places_.size(), local_scopes.size()); for (size_t i = 0; i < member_->places_.size(); ++i) { - member_->local_scopes_.push_back(local_scopes[i]); + member_->local_scopes_.emplace_back(local_scopes[i]); } } From 89728f8e66d078ecc6cae24a93b8931de8250b16 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Tue, 17 Apr 2018 16:42:40 +0800 Subject: [PATCH 52/69] update --- paddle/fluid/framework/parallel_executor.cc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/paddle/fluid/framework/parallel_executor.cc b/paddle/fluid/framework/parallel_executor.cc index 186ddbe369..c63162d2ff 100644 --- a/paddle/fluid/framework/parallel_executor.cc +++ b/paddle/fluid/framework/parallel_executor.cc @@ -177,7 +177,7 @@ void ParallelExecutor::Run( InitializeVariable(scope->Var(std::get<0>(name_type_pair)), std::get<1>(name_type_pair)); } else { - InitializeVariable(scope->Var(std::get<0>(name_type_pair)), + InitializeVariable(local_scope.Var(std::get<0>(name_type_pair)), std::get<1>(name_type_pair)); } } From d7527681c619296634ceb061e0b013bb2bf22fff Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Tue, 17 Apr 2018 16:47:35 +0800 Subject: [PATCH 53/69] Fix scale grad --- .../fluid/framework/details/scale_loss_grad_op_handle.cc | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/paddle/fluid/framework/details/scale_loss_grad_op_handle.cc b/paddle/fluid/framework/details/scale_loss_grad_op_handle.cc index 7fb9f99a8a..7a65ee62c9 100644 --- a/paddle/fluid/framework/details/scale_loss_grad_op_handle.cc +++ b/paddle/fluid/framework/details/scale_loss_grad_op_handle.cc @@ -30,10 +30,11 @@ ScaleLossGradOpHandle::~ScaleLossGradOpHandle() {} void ScaleLossGradOpHandle::RunImpl() { std::string var_name = static_cast(this->outputs_[0])->name_; + auto &local_scope = *scope_->FindVar(kLocalExecScopeName)->Get(); - float *tmp = - scope_->FindVar(var_name)->GetMutable()->mutable_data( - make_ddim({1}), place_); + float *tmp = local_scope.FindVar(var_name) + ->GetMutable() + ->mutable_data(make_ddim({1}), place_); if (platform::is_cpu_place(place_)) { *tmp = coeff_; From 2e8459be71c796b73a603c8adf87b0d811ddecd3 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Tue, 17 Apr 2018 16:52:58 +0800 Subject: [PATCH 54/69] DebugCode --- .../details/nccl_all_reduce_op_handle.cc | 15 ++++++++++----- 1 file changed, 10 insertions(+), 5 deletions(-) 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 1e48f75958..e587210b35 100644 --- a/paddle/fluid/framework/details/nccl_all_reduce_op_handle.cc +++ b/paddle/fluid/framework/details/nccl_all_reduce_op_handle.cc @@ -73,8 +73,9 @@ void NCCLAllReduceOpHandle::RunImpl() { for (size_t i = 0; i < local_scopes_.size(); ++i) { auto *s = local_scopes_[i]; + auto &local_scope = *s->FindVar(kLocalExecScopeName)->Get(); - auto &lod_tensor = s->FindVar(var_name)->Get(); + auto &lod_tensor = local_scope.FindVar(var_name)->Get(); lod_tensors.emplace_back(lod_tensor); } @@ -110,17 +111,21 @@ void NCCLAllReduceOpHandle::RunImpl() { } }); } else { // Special handle CPU only Operator's gradient. Like CRF - auto &trg = - *this->local_scopes_[0]->Var()->GetMutable(); + auto &trg = *this->local_scopes_[0] + ->FindVar(kLocalExecScopeName) + ->Get() + ->Var() + ->GetMutable(); // Reduce All Tensor to trg in CPU ReduceLoDTensor func(lod_tensors, &trg); VisitDataType(ToDataType(lod_tensors[0].type()), func); for (size_t i = 0; i < local_scopes_.size(); ++i) { - auto &scope = local_scopes_[i]; + auto &scope = + *local_scopes_[i]->FindVar(kLocalExecScopeName)->Get(); auto &p = places_[i]; - auto *var = scope->FindVar(var_name); + auto *var = scope.FindVar(var_name); auto *dev_ctx = dev_ctxes_[p]; RunAndRecordEvent(p, [&trg, var, dev_ctx, p] { From 71a2e6b73ccc71fa76e8b12f494cc13ead990669 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Tue, 17 Apr 2018 16:57:02 +0800 Subject: [PATCH 55/69] Reverse create var --- paddle/fluid/framework/parallel_executor.cc | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/paddle/fluid/framework/parallel_executor.cc b/paddle/fluid/framework/parallel_executor.cc index c63162d2ff..aceb2a9def 100644 --- a/paddle/fluid/framework/parallel_executor.cc +++ b/paddle/fluid/framework/parallel_executor.cc @@ -163,7 +163,9 @@ void ParallelExecutor::Run( SplitTensorToPlaces(feed_tensors); // Create local scopes. - for (auto &scope : member_->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; From 22f58382bce8cb13775b6e41da8cee69c925196a Mon Sep 17 00:00:00 2001 From: typhoonzero Date: Tue, 17 Apr 2018 17:03:00 +0800 Subject: [PATCH 56/69] run dist train test single process --- python/paddle/fluid/tests/unittests/CMakeLists.txt | 2 ++ .../unittests/{test_dist_train_op.py => test_dist_train.py} | 0 2 files changed, 2 insertions(+) rename python/paddle/fluid/tests/unittests/{test_dist_train_op.py => test_dist_train.py} (100%) diff --git a/python/paddle/fluid/tests/unittests/CMakeLists.txt b/python/paddle/fluid/tests/unittests/CMakeLists.txt index 356c3e64b3..435652547f 100644 --- a/python/paddle/fluid/tests/unittests/CMakeLists.txt +++ b/python/paddle/fluid/tests/unittests/CMakeLists.txt @@ -62,6 +62,7 @@ list(REMOVE_ITEM TEST_OPS test_registry) list(REMOVE_ITEM TEST_OPS test_fetch_var) list(REMOVE_ITEM TEST_OPS test_parallel_op) list(REMOVE_ITEM TEST_OPS test_dynrnn_static_input) +list(REMOVE_ITEM TEST_OPS test_dist_train) # tests that can be bundled together in one python process for speed. if(WITH_FAST_BUNDLE_TEST) @@ -100,3 +101,4 @@ py_test_modules(test_registry MODULES test_registry) py_test_modules(test_fetch_var MODULES test_fetch_var) py_test_modules(test_dynrnn_static_input MODULES test_dynrnn_static_input) py_test_modules(test_parallel_op MODULES test_parallel_op) +py_test_modules(test_dist_train MODULES test_dist_train) diff --git a/python/paddle/fluid/tests/unittests/test_dist_train_op.py b/python/paddle/fluid/tests/unittests/test_dist_train.py similarity index 100% rename from python/paddle/fluid/tests/unittests/test_dist_train_op.py rename to python/paddle/fluid/tests/unittests/test_dist_train.py From 06fb055a2f3572d8fe5233c0f150f55ca74de66f Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Tue, 17 Apr 2018 19:53:51 +0800 Subject: [PATCH 57/69] New group --- paddle/fluid/framework/parallel_executor.cc | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/paddle/fluid/framework/parallel_executor.cc b/paddle/fluid/framework/parallel_executor.cc index aceb2a9def..53306f1219 100644 --- a/paddle/fluid/framework/parallel_executor.cc +++ b/paddle/fluid/framework/parallel_executor.cc @@ -63,7 +63,8 @@ ParallelExecutor::ParallelExecutor( // Step 1. Bcast the params to devs. // Create local scopes if (local_scopes.empty()) { - for (size_t i = 0; i < member_->places_.size(); ++i) { + member_->local_scopes_.emplace_back(member_->global_scope_); + for (size_t i = 1; i < member_->places_.size(); ++i) { member_->local_scopes_.emplace_back(&scope->NewScope()); } } else { From 81c47b21ef742dca9a7bfad16059575ce57f20aa Mon Sep 17 00:00:00 2001 From: Luo Tao Date: Tue, 17 Apr 2018 19:38:20 +0800 Subject: [PATCH 58/69] add type check and default scope --- python/paddle/fluid/inference_transpiler.py | 29 ++++++++++++------- .../tests/book/test_image_classification.py | 2 +- 2 files changed, 20 insertions(+), 11 deletions(-) diff --git a/python/paddle/fluid/inference_transpiler.py b/python/paddle/fluid/inference_transpiler.py index be8a627953..39b01610f9 100644 --- a/python/paddle/fluid/inference_transpiler.py +++ b/python/paddle/fluid/inference_transpiler.py @@ -13,26 +13,35 @@ # limitations under the License. import numpy as np -import os -import shutil +from framework import Program +from executor import global_scope from . import core class InferenceTranspiler: - def transpile(self, program, scope, place): + def transpile(self, program, place, scope=None): ''' Transpile the program. Support only fuse batch normalization now. :param program: program to transpile :type program: Program - :param scope: inference scope - :type scope: Scope :param place: inference place :type place: Place + :param scope: inference scope + :type scope: Scope or None ''' - self.fuse_batch_norm(program, scope, place) - - def fuse_batch_norm(self, program, scope, place): + if not isinstance(program, Program): + raise TypeError("program should be as Program type") + if not isinstance(place, core.CPUPlace) and not isinstance( + place, core.CUDAPlace): + raise TypeError("place should be as CPUPlace/CUDAPlace type") + if scope is None: + scope = global_scope() + if not isinstance(scope, core.Scope): + raise TypeError("scope should be as Scope type or None") + self.fuse_batch_norm(program, place, scope) + + def fuse_batch_norm(self, program, place, scope): ''' Transpile the program by fused batch normalization. @@ -66,10 +75,10 @@ class InferenceTranspiler: :param program: program to transpile :type program: Program - :param scope: inference scope - :type scope: Scope :param place: inference place :type place: Place + :param scope: inference scope + :type scope: Scope ''' self.scope = scope self.place = place diff --git a/python/paddle/fluid/tests/book/test_image_classification.py b/python/paddle/fluid/tests/book/test_image_classification.py index aeacca5753..0027b651e8 100644 --- a/python/paddle/fluid/tests/book/test_image_classification.py +++ b/python/paddle/fluid/tests/book/test_image_classification.py @@ -229,7 +229,7 @@ def infer(use_cuda, save_dirname=None): # Use inference_transpiler to speedup inference_transpiler_program = inference_program.clone() t = fluid.InferenceTranspiler() - t.transpile(inference_transpiler_program, inference_scope, place) + t.transpile(inference_transpiler_program, place) # Construct feed as a dictionary of {feed_target_name: feed_target_data} # and results will contain a list of data corresponding to fetch_targets. From acdf7cbd19c105cc20a7e32a57512bbc3b8dc844 Mon Sep 17 00:00:00 2001 From: Jacek Czaja Date: Mon, 16 Apr 2018 08:24:51 -0700 Subject: [PATCH 59/69] - Added EPS for softmax MKLDNN op - EPS added to softmax mkldnn primitive outcome is limited to training phase Fixes after review clang format fixes clang format fixes --- paddle/fluid/operators/softmax_mkldnn_op.cc | 9 +++++++++ paddle/fluid/operators/softmax_op.cc | 3 +++ python/paddle/fluid/layers/nn.py | 6 +++++- 3 files changed, 17 insertions(+), 1 deletion(-) diff --git a/paddle/fluid/operators/softmax_mkldnn_op.cc b/paddle/fluid/operators/softmax_mkldnn_op.cc index dc2f176344..d00bd1447e 100644 --- a/paddle/fluid/operators/softmax_mkldnn_op.cc +++ b/paddle/fluid/operators/softmax_mkldnn_op.cc @@ -73,6 +73,15 @@ class SoftmaxMKLDNNKernel : public paddle::framework::OpKernel { softmax_dst_memory); std::vector pipeline{softmax}; stream(stream::kind::eager).submit(pipeline).wait(); + + const bool is_test = ctx.Attr("is_test"); + if (!is_test) { + T threshold = exp(-64); + for (size_t i = 0; i < dst_tz[0] * dst_tz[1]; ++i) { + output_data[i] = + output_data[i] < threshold ? threshold : output_data[i]; + } + } } }; diff --git a/paddle/fluid/operators/softmax_op.cc b/paddle/fluid/operators/softmax_op.cc index 6bdefc0f23..e1f286f9ba 100644 --- a/paddle/fluid/operators/softmax_op.cc +++ b/paddle/fluid/operators/softmax_op.cc @@ -97,6 +97,9 @@ class SoftmaxOpMaker : public framework::OpProtoAndCheckerMaker { AddAttr("use_mkldnn", "(bool, default false) Only used in mkldnn kernel") .SetDefault(false); + AddAttr("is_test", + "Disable epsilon adding to softmax results. Used by MKLDNN.") + .SetDefault(false); AddComment(R"DOC( Softmax Operator. diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index 5c2c2dd7ab..fb41cc6009 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -87,6 +87,7 @@ def fc(input, bias_attr=None, use_mkldnn=False, act=None, + is_test=False, name=None): """ **Fully Connected Layer** @@ -133,6 +134,7 @@ def fc(input, bias_attr (ParamAttr|list of ParamAttr, default None): The parameter attribute for the bias of this layer. If it is set to None, no bias will be added to the output units. act (str, default None): Activation to be applied to the output of this layer. + is_test(bool): A flag indicating whether execution is in test phase. use_mkldnn(bool): Use mkldnn kernel or not, it is valid only when the mkldnn library is installed. Default: False name (str, default None): The name of this layer. @@ -177,7 +179,9 @@ def fc(input, "W": w}, outputs={"Out": tmp}, attrs={"use_mkldnn": use_mkldnn, - "bias_attr": bias_attr}) + "is_test": is_test, + "bias_attr": bias_attr + }) return helper.append_activation(tmp) else: for input_var, param_attr in helper.iter_inputs_and_params(): From de8094f57eee01abc62724ed8aa7becdc0474314 Mon Sep 17 00:00:00 2001 From: Jacek Czaja Date: Tue, 17 Apr 2018 06:31:56 -0700 Subject: [PATCH 60/69] Cosmetic fixes --- python/paddle/fluid/layers/nn.py | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index fb41cc6009..e25400c68e 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -178,10 +178,11 @@ def fc(input, inputs={"Input": input, "W": w}, outputs={"Out": tmp}, - attrs={"use_mkldnn": use_mkldnn, - "is_test": is_test, - "bias_attr": bias_attr - }) + attrs={ + "use_mkldnn": use_mkldnn, + "is_test": is_test, + "bias_attr": bias_attr + }) return helper.append_activation(tmp) else: for input_var, param_attr in helper.iter_inputs_and_params(): From d08791d11ab6a4be26f4bda40ea89601ad7de690 Mon Sep 17 00:00:00 2001 From: Abhinav Arora Date: Tue, 17 Apr 2018 10:59:58 -0700 Subject: [PATCH 61/69] Fix CPPLint issues with Chunk_eval_op (#9964) --- paddle/fluid/operators/chunk_eval_op.cc | 2 + paddle/fluid/operators/chunk_eval_op.h | 49 ++++++++++++++----------- 2 files changed, 30 insertions(+), 21 deletions(-) diff --git a/paddle/fluid/operators/chunk_eval_op.cc b/paddle/fluid/operators/chunk_eval_op.cc index 77d3cffe7c..95440ff89e 100644 --- a/paddle/fluid/operators/chunk_eval_op.cc +++ b/paddle/fluid/operators/chunk_eval_op.cc @@ -13,6 +13,8 @@ See the License for the specific language governing permissions and limitations under the License. */ #include "paddle/fluid/operators/chunk_eval_op.h" +#include +#include namespace paddle { namespace operators { diff --git a/paddle/fluid/operators/chunk_eval_op.h b/paddle/fluid/operators/chunk_eval_op.h index 9e97f7c776..8631415062 100644 --- a/paddle/fluid/operators/chunk_eval_op.h +++ b/paddle/fluid/operators/chunk_eval_op.h @@ -14,6 +14,9 @@ limitations under the License. */ #pragma once #include +#include +#include + #include "paddle/fluid/framework/eigen.h" #include "paddle/fluid/framework/op_registry.h" @@ -36,11 +39,11 @@ class ChunkEvalKernel : public framework::OpKernel { }; void GetSegments(const int64_t* label, int length, - std::vector& segments, int num_chunk_types, + std::vector* segments, int num_chunk_types, int num_tag_types, int other_chunk_type, int tag_begin, int tag_inside, int tag_end, int tag_single) const { - segments.clear(); - segments.reserve(length); + segments->clear(); + segments->reserve(length); int chunk_start = 0; bool in_chunk = false; int tag = -1; @@ -58,7 +61,7 @@ class ChunkEvalKernel : public framework::OpKernel { i - 1, // end prev_type, }; - segments.push_back(segment); + segments->push_back(segment); in_chunk = false; } if (ChunkBegin(prev_tag, prev_type, tag, type, other_chunk_type, @@ -73,7 +76,7 @@ class ChunkEvalKernel : public framework::OpKernel { length - 1, // end type, }; - segments.push_back(segment); + segments->push_back(segment); } } @@ -177,8 +180,8 @@ class ChunkEvalKernel : public framework::OpKernel { for (int i = 0; i < num_sequences; ++i) { int seq_length = lod[0][i + 1] - lod[0][i]; EvalOneSeq(inference_data + lod[0][i], label_data + lod[0][i], seq_length, - output_segments, label_segments, *num_infer_chunks_data, - *num_label_chunks_data, *num_correct_chunks_data, + &output_segments, &label_segments, num_infer_chunks_data, + num_label_chunks_data, num_correct_chunks_data, num_chunk_types, num_tag_types, other_chunk_type, tag_begin, tag_inside, tag_end, tag_single, excluded_chunk_types); } @@ -197,10 +200,10 @@ class ChunkEvalKernel : public framework::OpKernel { } void EvalOneSeq(const int64_t* output, const int64_t* label, int length, - std::vector& output_segments, - std::vector& label_segments, - int64_t& num_output_segments, int64_t& num_label_segments, - int64_t& num_correct, int num_chunk_types, int num_tag_types, + std::vector* output_segments, + std::vector* label_segments, + int64_t* num_output_segments, int64_t* num_label_segments, + int64_t* num_correct, int num_chunk_types, int num_tag_types, int other_chunk_type, int tag_begin, int tag_inside, int tag_end, int tag_single, const std::set& excluded_chunk_types) const { @@ -209,25 +212,29 @@ class ChunkEvalKernel : public framework::OpKernel { GetSegments(label, length, label_segments, num_chunk_types, num_tag_types, other_chunk_type, tag_begin, tag_inside, tag_end, tag_single); size_t i = 0, j = 0; - while (i < output_segments.size() && j < label_segments.size()) { - if (output_segments[i] == label_segments[j] && - excluded_chunk_types.count(output_segments[i].type) != 1) { - ++num_correct; + while (i < output_segments->size() && j < label_segments->size()) { + if (output_segments->at(i) == label_segments->at(j) && + excluded_chunk_types.count(output_segments->at(i).type) != 1) { + ++(*num_correct); } - if (output_segments[i].end < label_segments[j].end) { + if (output_segments->at(i).end < label_segments->at(j).end) { ++i; - } else if (output_segments[i].end > label_segments[j].end) { + } else if (output_segments->at(i).end > label_segments->at(j).end) { ++j; } else { ++i; ++j; } } - for (auto& segment : label_segments) { - if (excluded_chunk_types.count(segment.type) != 1) ++num_label_segments; + for (auto& segment : (*label_segments)) { + if (excluded_chunk_types.count(segment.type) != 1) { + ++(*num_label_segments); + } } - for (auto& segment : output_segments) { - if (excluded_chunk_types.count(segment.type) != 1) ++num_output_segments; + for (auto& segment : (*output_segments)) { + if (excluded_chunk_types.count(segment.type) != 1) { + ++(*num_output_segments); + } } } }; From 2d1a6f8d4a5b278bec270826cf0274a13ba6349b Mon Sep 17 00:00:00 2001 From: Abhinav Arora Date: Tue, 17 Apr 2018 11:00:19 -0700 Subject: [PATCH 62/69] Fix cpplint issues in Detection_map_op (#9969) * Fix conv_op.h * Fix conv_mkldnn_op * Fix cpplint issues in detection_map_op --- paddle/fluid/operators/conv_mkldnn_op.cc | 29 ++++---- paddle/fluid/operators/conv_op.h | 8 ++- paddle/fluid/operators/detection_map_op.cc | 1 + paddle/fluid/operators/detection_map_op.h | 83 ++++++++++++---------- paddle/fluid/operators/edit_distance_op.cu | 1 + 5 files changed, 67 insertions(+), 55 deletions(-) diff --git a/paddle/fluid/operators/conv_mkldnn_op.cc b/paddle/fluid/operators/conv_mkldnn_op.cc index 0a8a5d4c71..d7a8f918ed 100644 --- a/paddle/fluid/operators/conv_mkldnn_op.cc +++ b/paddle/fluid/operators/conv_mkldnn_op.cc @@ -72,10 +72,10 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel { auto dst_md = platform::MKLDNNMemDesc( dst_tz, mkldnn::memory::data_type::f32, mkldnn::memory::format::nchw); - auto src_memory = - mkldnn::memory({src_md, mkldnn_engine}, (void*)input_data); - auto weights_memory = - mkldnn::memory({weights_md, mkldnn_engine}, (void*)filter_data); + auto src_memory = mkldnn::memory({src_md, mkldnn_engine}, + reinterpret_cast(input_data)); + auto weights_memory = mkldnn::memory({weights_md, mkldnn_engine}, + reinterpret_cast(filter_data)); auto dst_memory = mkldnn::memory({dst_md, mkldnn_engine}, output_data); std::shared_ptr conv_pd = @@ -180,8 +180,9 @@ class ConvMKLDNNGradOpKernel : public paddle::framework::OpKernel { dst_tz, mkldnn::memory::data_type::f32, mkldnn::memory::format::nchw); // create memory - auto diff_dst_memory = mkldnn::memory({diff_weights_md, mkldnn_engine}, - (void*)output_grad_data); + auto diff_dst_memory = + mkldnn::memory({diff_weights_md, mkldnn_engine}, + reinterpret_cast(output_grad_data)); // Retrieve conv_pd from device context auto conv_pd = std::static_pointer_cast( @@ -198,10 +199,11 @@ class ConvMKLDNNGradOpKernel : public paddle::framework::OpKernel { mkldnn_engine); // create memory - auto diff_weights_memory = mkldnn::memory( - {diff_weights_md, mkldnn_engine}, (void*)filter_grad_data); - auto src_memory = - mkldnn::memory({src_md, mkldnn_engine}, (void*)input_data); + auto diff_weights_memory = + mkldnn::memory({diff_weights_md, mkldnn_engine}, + reinterpret_cast(filter_grad_data)); + auto src_memory = mkldnn::memory({src_md, mkldnn_engine}, + reinterpret_cast(input_data)); // create backward conv primitive for weights auto conv_bwd_weights_prim = mkldnn::convolution_backward_weights( @@ -221,9 +223,10 @@ class ConvMKLDNNGradOpKernel : public paddle::framework::OpKernel { // create memory auto diff_src_memory = - mkldnn::memory({diff_src_md, mkldnn_engine}, (void*)input_grad_data); - auto weights_memory = - mkldnn::memory({weights_md, mkldnn_engine}, (void*)filter_data); + mkldnn::memory({diff_src_md, mkldnn_engine}, + reinterpret_cast(input_grad_data)); + auto weights_memory = mkldnn::memory( + {weights_md, mkldnn_engine}, reinterpret_cast(filter_data)); // create backward conv primitive for data auto conv_bwd_data_prim = mkldnn::convolution_backward_data( diff --git a/paddle/fluid/operators/conv_op.h b/paddle/fluid/operators/conv_op.h index 12b45f1d65..d6f86a5c88 100644 --- a/paddle/fluid/operators/conv_op.h +++ b/paddle/fluid/operators/conv_op.h @@ -14,6 +14,7 @@ limitations under the License. */ #pragma once +#include #include "paddle/fluid/framework/eigen.h" #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/operators/math/depthwise_conv.h" @@ -41,9 +42,10 @@ inline int ConvOutputSize(int input_size, int filter_size, int dilation, return output_size; } -inline bool IsExpand(std::vector& filter_dim, - std::vector& strides, std::vector& paddings, - std::vector& dilations) { +inline bool IsExpand(const std::vector& filter_dim, + const std::vector& strides, + const std::vector& paddings, + const std::vector& dilations) { bool filter_1 = true, strides_1 = true, padding_0 = true, dilation_1 = true; for (size_t j = 0; j < strides.size(); ++j) { filter_1 = filter_1 && (static_cast(filter_dim[j + 2]) == 1); diff --git a/paddle/fluid/operators/detection_map_op.cc b/paddle/fluid/operators/detection_map_op.cc index 93ef15b933..38f43b6d03 100644 --- a/paddle/fluid/operators/detection_map_op.cc +++ b/paddle/fluid/operators/detection_map_op.cc @@ -13,6 +13,7 @@ See the License for the specific language governing permissions and limitations under the License. */ #include "paddle/fluid/operators/detection_map_op.h" +#include namespace paddle { namespace operators { diff --git a/paddle/fluid/operators/detection_map_op.h b/paddle/fluid/operators/detection_map_op.h index 8c15bfa36b..431812e2bf 100644 --- a/paddle/fluid/operators/detection_map_op.h +++ b/paddle/fluid/operators/detection_map_op.h @@ -13,6 +13,11 @@ See the License for the specific language governing permissions and limitations under the License. */ #pragma once +#include +#include +#include +#include +#include #include "paddle/fluid/framework/eigen.h" #include "paddle/fluid/framework/op_registry.h" @@ -82,7 +87,7 @@ class DetectionMAPOpKernel : public framework::OpKernel { std::vector>> gt_boxes; std::vector>>> detect_boxes; - GetBoxes(*in_label, *in_detect, gt_boxes, detect_boxes); + GetBoxes(*in_label, *in_detect, >_boxes, detect_boxes); std::map label_pos_count; std::map>> true_pos; @@ -95,20 +100,20 @@ class DetectionMAPOpKernel : public framework::OpKernel { } if (in_pos_count != nullptr && state) { - GetInputPos(*in_pos_count, *in_true_pos, *in_false_pos, label_pos_count, - true_pos, false_pos, class_num); + GetInputPos(*in_pos_count, *in_true_pos, *in_false_pos, &label_pos_count, + &true_pos, &false_pos, class_num); } CalcTrueAndFalsePositive(gt_boxes, detect_boxes, evaluate_difficult, - overlap_threshold, label_pos_count, true_pos, - false_pos); + overlap_threshold, &label_pos_count, &true_pos, + &false_pos); int background_label = ctx.Attr("background_label"); T map = CalcMAP(ap_type, label_pos_count, true_pos, false_pos, background_label); - GetOutputPos(ctx, label_pos_count, true_pos, false_pos, *out_pos_count, - *out_true_pos, *out_false_pos, class_num); + GetOutputPos(ctx, label_pos_count, true_pos, false_pos, out_pos_count, + out_true_pos, out_false_pos, class_num); T* map_data = out_map->mutable_data(ctx.GetPlace()); map_data[0] = map; @@ -155,7 +160,7 @@ class DetectionMAPOpKernel : public framework::OpKernel { void GetBoxes(const framework::LoDTensor& input_label, const framework::LoDTensor& input_detect, - std::vector>>& gt_boxes, + std::vector>>* gt_boxes, std::vector>>>& detect_boxes) const { auto labels = framework::EigenTensor::From(input_label); @@ -179,7 +184,7 @@ class DetectionMAPOpKernel : public framework::OpKernel { box.is_difficult = true; boxes[label].push_back(box); } - gt_boxes.push_back(boxes); + gt_boxes->push_back(boxes); } auto detect_index = detect_lod[0]; @@ -200,9 +205,9 @@ class DetectionMAPOpKernel : public framework::OpKernel { const std::map& label_pos_count, const std::map>>& true_pos, const std::map>>& false_pos, - framework::Tensor& output_pos_count, - framework::LoDTensor& output_true_pos, - framework::LoDTensor& output_false_pos, const int class_num) const { + framework::Tensor* output_pos_count, + framework::LoDTensor* output_true_pos, + framework::LoDTensor* output_false_pos, const int class_num) const { int true_pos_count = 0; int false_pos_count = 0; for (auto it = true_pos.begin(); it != true_pos.end(); ++it) { @@ -214,12 +219,12 @@ class DetectionMAPOpKernel : public framework::OpKernel { false_pos_count += fp.size(); } - int* pos_count_data = output_pos_count.mutable_data( + int* pos_count_data = output_pos_count->mutable_data( framework::make_ddim({class_num, 1}), ctx.GetPlace()); - T* true_pos_data = output_true_pos.mutable_data( + T* true_pos_data = output_true_pos->mutable_data( framework::make_ddim({true_pos_count, 2}), ctx.GetPlace()); - T* false_pos_data = output_false_pos.mutable_data( + T* false_pos_data = output_false_pos->mutable_data( framework::make_ddim({false_pos_count, 2}), ctx.GetPlace()); true_pos_count = 0; false_pos_count = 0; @@ -261,21 +266,21 @@ class DetectionMAPOpKernel : public framework::OpKernel { framework::LoD false_pos_lod; false_pos_lod.emplace_back(false_pos_starts); - output_true_pos.set_lod(true_pos_lod); - output_false_pos.set_lod(false_pos_lod); + output_true_pos->set_lod(true_pos_lod); + output_false_pos->set_lod(false_pos_lod); return; } void GetInputPos(const framework::Tensor& input_pos_count, const framework::LoDTensor& input_true_pos, const framework::LoDTensor& input_false_pos, - std::map& label_pos_count, - std::map>>& true_pos, - std::map>>& false_pos, + std::map* label_pos_count, + std::map>>* true_pos, + std::map>>* false_pos, const int class_num) const { const int* pos_count_data = input_pos_count.data(); for (int i = 0; i < class_num; ++i) { - label_pos_count[i] = pos_count_data[i]; + (*label_pos_count)[i] = pos_count_data[i]; } auto SetData = [](const framework::LoDTensor& pos_tensor, @@ -291,8 +296,8 @@ class DetectionMAPOpKernel : public framework::OpKernel { } }; - SetData(input_true_pos, true_pos); - SetData(input_false_pos, false_pos); + SetData(input_true_pos, *true_pos); + SetData(input_false_pos, *false_pos); return; } @@ -301,9 +306,9 @@ class DetectionMAPOpKernel : public framework::OpKernel { const std::vector>>>& detect_boxes, bool evaluate_difficult, float overlap_threshold, - std::map& label_pos_count, - std::map>>& true_pos, - std::map>>& false_pos) const { + std::map* label_pos_count, + std::map>>* true_pos, + std::map>>* false_pos) const { int batch_size = gt_boxes.size(); for (int n = 0; n < batch_size; ++n) { auto image_gt_boxes = gt_boxes[n]; @@ -320,10 +325,10 @@ class DetectionMAPOpKernel : public framework::OpKernel { continue; } int label = it->first; - if (label_pos_count.find(label) == label_pos_count.end()) { - label_pos_count[label] = count; + if (label_pos_count->find(label) == label_pos_count->end()) { + (*label_pos_count)[label] = count; } else { - label_pos_count[label] += count; + (*label_pos_count)[label] += count; } } } @@ -338,8 +343,8 @@ class DetectionMAPOpKernel : public framework::OpKernel { int label = it->first; for (size_t i = 0; i < pred_boxes.size(); ++i) { auto score = pred_boxes[i].first; - true_pos[label].push_back(std::make_pair(score, 0)); - false_pos[label].push_back(std::make_pair(score, 1)); + (*true_pos)[label].push_back(std::make_pair(score, 0)); + (*false_pos)[label].push_back(std::make_pair(score, 1)); } } continue; @@ -351,8 +356,8 @@ class DetectionMAPOpKernel : public framework::OpKernel { if (image_gt_boxes.find(label) == image_gt_boxes.end()) { for (size_t i = 0; i < pred_boxes.size(); ++i) { auto score = pred_boxes[i].first; - true_pos[label].push_back(std::make_pair(score, 0)); - false_pos[label].push_back(std::make_pair(score, 1)); + (*true_pos)[label].push_back(std::make_pair(score, 0)); + (*false_pos)[label].push_back(std::make_pair(score, 1)); } continue; } @@ -381,17 +386,17 @@ class DetectionMAPOpKernel : public framework::OpKernel { (!evaluate_difficult && !matched_bboxes[max_idx].is_difficult); if (match_evaluate_difficult) { if (!visited[max_idx]) { - true_pos[label].push_back(std::make_pair(score, 1)); - false_pos[label].push_back(std::make_pair(score, 0)); + (*true_pos)[label].push_back(std::make_pair(score, 1)); + (*false_pos)[label].push_back(std::make_pair(score, 0)); visited[max_idx] = true; } else { - true_pos[label].push_back(std::make_pair(score, 0)); - false_pos[label].push_back(std::make_pair(score, 1)); + (*true_pos)[label].push_back(std::make_pair(score, 0)); + (*false_pos)[label].push_back(std::make_pair(score, 1)); } } } else { - true_pos[label].push_back(std::make_pair(score, 0)); - false_pos[label].push_back(std::make_pair(score, 1)); + (*true_pos)[label].push_back(std::make_pair(score, 0)); + (*false_pos)[label].push_back(std::make_pair(score, 1)); } } } diff --git a/paddle/fluid/operators/edit_distance_op.cu b/paddle/fluid/operators/edit_distance_op.cu index 3b89ad5d49..913a914542 100644 --- a/paddle/fluid/operators/edit_distance_op.cu +++ b/paddle/fluid/operators/edit_distance_op.cu @@ -14,6 +14,7 @@ limitations under the License. */ #include #include "paddle/fluid/framework/op_registry.h" +#include "paddle/fluid/operators/edit_distance_op.h" #include "paddle/fluid/operators/math/math_function.h" #include "paddle/fluid/platform/cuda_helper.h" #include "paddle/fluid/platform/gpu_info.h" From 6f8314235327848906bd7800743be376b01cdd74 Mon Sep 17 00:00:00 2001 From: Abhinav Arora Date: Tue, 17 Apr 2018 12:57:03 -0700 Subject: [PATCH 63/69] Fix cpplint issues with beam_search_op and beam_search_decode_op (#9962) * Fix cpplint warnings in beam_search_decode_op * Fix cpplint warnings in beam_search_op * Fix test * fix --- paddle/fluid/operators/beam_search_decode_op.cc | 1 + paddle/fluid/operators/beam_search_decode_op.h | 11 ++++++----- paddle/fluid/operators/beam_search_decode_op_test.cc | 4 ++-- paddle/fluid/operators/beam_search_op.cc | 3 +++ paddle/fluid/operators/beam_search_op.h | 2 ++ 5 files changed, 14 insertions(+), 7 deletions(-) diff --git a/paddle/fluid/operators/beam_search_decode_op.cc b/paddle/fluid/operators/beam_search_decode_op.cc index 718f469d38..4a8dfd4b54 100644 --- a/paddle/fluid/operators/beam_search_decode_op.cc +++ b/paddle/fluid/operators/beam_search_decode_op.cc @@ -13,6 +13,7 @@ See the License for the specific language governing permissions and limitations under the License. */ #include "paddle/fluid/operators/beam_search_decode_op.h" +#include #include "paddle/fluid/platform/device_context.h" namespace paddle { diff --git a/paddle/fluid/operators/beam_search_decode_op.h b/paddle/fluid/operators/beam_search_decode_op.h index 3cc6ed3105..4cb0457d92 100644 --- a/paddle/fluid/operators/beam_search_decode_op.h +++ b/paddle/fluid/operators/beam_search_decode_op.h @@ -14,6 +14,7 @@ limitations under the License. */ #pragma once +#include #include "paddle/fluid/framework/lod_tensor_array.h" #include "paddle/fluid/framework/op_registry.h" @@ -87,7 +88,7 @@ struct BeamSearchDecoder { */ std::vector> PackTwoSteps( const LoDTensor& cur_ids, const LoDTensor& cur_scores, - std::vector>& prefixes_list, + std::vector>* prefixes_list, std::vector>* sentence_vector_list) const; /** @@ -140,7 +141,7 @@ Sentence BeamSearchDecoder::MakeSentence(const BeamNode* node) const { template std::vector> BeamSearchDecoder::PackTwoSteps( const LoDTensor& cur_ids, const LoDTensor& cur_scores, - std::vector>& prefixes_list, + std::vector>* prefixes_list, std::vector>* sentence_vector_list) const { std::vector> result; @@ -153,7 +154,7 @@ std::vector> BeamSearchDecoder::PackTwoSteps( // if prefixes size is 0, it means this is the first step. In this step, // all candidate id is the start of candidate sentences. - if (prefixes_list.empty()) { + if (prefixes_list->empty()) { PADDLE_ENFORCE_EQ(cur_ids.lod().at(kSourceLevel).back(), cur_ids.lod().at(kSentenceLevel).back(), "in the first step"); @@ -162,7 +163,7 @@ std::vector> BeamSearchDecoder::PackTwoSteps( cur_ids.data()[id_idx], cur_scores.data()[id_idx]))); } } else { - BeamNodeVector& prefixes = prefixes_list[src_idx]; + BeamNodeVector& prefixes = prefixes_list->at(src_idx); SentenceVector& sentence_vector = (*sentence_vector_list)[src_idx]; PADDLE_ENFORCE_EQ(src_end - src_start, prefixes.size(), @@ -262,7 +263,7 @@ void BeamSearchDecoder::PackAllSteps(const LoDTensorArray& step_ids, for (size_t step_id = 0; step_id < step_num; ++step_id) { beamnode_vector_list = PackTwoSteps(step_ids.at(step_id), step_scores.at(step_id), - beamnode_vector_list, &sentence_vector_list); + &beamnode_vector_list, &sentence_vector_list); } // append last beam_node to result for (size_t src_idx = 0; src_idx < src_num; ++src_idx) { diff --git a/paddle/fluid/operators/beam_search_decode_op_test.cc b/paddle/fluid/operators/beam_search_decode_op_test.cc index c3faf46e09..36f9594969 100644 --- a/paddle/fluid/operators/beam_search_decode_op_test.cc +++ b/paddle/fluid/operators/beam_search_decode_op_test.cc @@ -125,7 +125,7 @@ TEST(BeamSearchDecodeOp, PackTwoStepsFistStep) { BeamSearchDecoder helper; beamnode_vector_list = helper.PackTwoSteps( - ids[0], scores[0], beamnode_vector_list, &sentence_vector_list); + ids[0], scores[0], &beamnode_vector_list, &sentence_vector_list); ASSERT_EQ(beamnode_vector_list.size(), 2UL); ASSERT_EQ(beamnode_vector_list[0].size(), 2UL); ASSERT_EQ(beamnode_vector_list[1].size(), 4UL); @@ -167,7 +167,7 @@ TEST(BeamSearchDecodeOp, PackTwoSteps) { BeamSearchDecoder helper1; beamnode_vector_list = helper1.PackTwoSteps( - ids[0], scores[0], beamnode_vector_list, &sentence_vector_list); + ids[0], scores[0], &beamnode_vector_list, &sentence_vector_list); ASSERT_EQ(sentence_vector_list[0].size(), 1UL); ASSERT_EQ(sentence_vector_list[1].size(), 0UL); diff --git a/paddle/fluid/operators/beam_search_op.cc b/paddle/fluid/operators/beam_search_op.cc index e848b1f12c..fdab4e92f4 100644 --- a/paddle/fluid/operators/beam_search_op.cc +++ b/paddle/fluid/operators/beam_search_op.cc @@ -14,7 +14,10 @@ limitations under the License. */ #include "paddle/fluid/operators/beam_search_op.h" +#include #include +#include +#include #include "paddle/fluid/framework/lod_tensor.h" #include "paddle/fluid/framework/op_registry.h" diff --git a/paddle/fluid/operators/beam_search_op.h b/paddle/fluid/operators/beam_search_op.h index b333ef4e6c..0a481a85ce 100644 --- a/paddle/fluid/operators/beam_search_op.h +++ b/paddle/fluid/operators/beam_search_op.h @@ -18,6 +18,8 @@ limitations under the License. */ #include "gtest/gtest.h" #endif +#include +#include #include "paddle/fluid/framework/lod_tensor.h" #include "paddle/fluid/framework/operator.h" From 1b5c1bcb57cd765da3fc5c4e7a84933bf4f9cfdd Mon Sep 17 00:00:00 2001 From: Abhinav Arora Date: Tue, 17 Apr 2018 15:35:45 -0700 Subject: [PATCH 64/69] Disabling Channel Test to fix CI --- paddle/fluid/framework/CMakeLists.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/paddle/fluid/framework/CMakeLists.txt b/paddle/fluid/framework/CMakeLists.txt index 1f3ca24df1..340b891e41 100644 --- a/paddle/fluid/framework/CMakeLists.txt +++ b/paddle/fluid/framework/CMakeLists.txt @@ -102,7 +102,7 @@ cc_test(init_test SRCS init_test.cc DEPS init) cc_test(op_kernel_type_test SRCS op_kernel_type_test.cc DEPS place device_context framework_proto) cc_test(cow_ptr_tests SRCS details/cow_ptr_test.cc) -cc_test(channel_test SRCS channel_test.cc) +# cc_test(channel_test SRCS channel_test.cc) cc_test(tuple_test SRCS tuple_test.cc ) cc_test(concurrency_test SRCS concurrency_test.cc DEPS go_op channel_close_op channel_create_op channel_send_op channel_recv_op sum_op select_op elementwise_add_op compare_op From ed681d5235fca44ba985c2380168afe8e09a1e7b Mon Sep 17 00:00:00 2001 From: Abhinav Arora Date: Tue, 17 Apr 2018 17:02:44 -0700 Subject: [PATCH 65/69] Fix conv_mkldnn_op.cc which is causing CI failure --- paddle/fluid/operators/conv_mkldnn_op.cc | 32 +++++++++++++----------- 1 file changed, 18 insertions(+), 14 deletions(-) diff --git a/paddle/fluid/operators/conv_mkldnn_op.cc b/paddle/fluid/operators/conv_mkldnn_op.cc index d7a8f918ed..63d371310d 100644 --- a/paddle/fluid/operators/conv_mkldnn_op.cc +++ b/paddle/fluid/operators/conv_mkldnn_op.cc @@ -72,10 +72,12 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel { auto dst_md = platform::MKLDNNMemDesc( dst_tz, mkldnn::memory::data_type::f32, mkldnn::memory::format::nchw); - auto src_memory = mkldnn::memory({src_md, mkldnn_engine}, - reinterpret_cast(input_data)); - auto weights_memory = mkldnn::memory({weights_md, mkldnn_engine}, - reinterpret_cast(filter_data)); + auto src_memory = + mkldnn::memory({src_md, mkldnn_engine}, + reinterpret_cast(const_cast(input_data))); + auto weights_memory = + mkldnn::memory({weights_md, mkldnn_engine}, + reinterpret_cast(const_cast(filter_data))); auto dst_memory = mkldnn::memory({dst_md, mkldnn_engine}, output_data); std::shared_ptr conv_pd = @@ -180,9 +182,9 @@ class ConvMKLDNNGradOpKernel : public paddle::framework::OpKernel { dst_tz, mkldnn::memory::data_type::f32, mkldnn::memory::format::nchw); // create memory - auto diff_dst_memory = - mkldnn::memory({diff_weights_md, mkldnn_engine}, - reinterpret_cast(output_grad_data)); + auto diff_dst_memory = mkldnn::memory( + {diff_weights_md, mkldnn_engine}, + reinterpret_cast(const_cast(output_grad_data))); // Retrieve conv_pd from device context auto conv_pd = std::static_pointer_cast( @@ -202,8 +204,9 @@ class ConvMKLDNNGradOpKernel : public paddle::framework::OpKernel { auto diff_weights_memory = mkldnn::memory({diff_weights_md, mkldnn_engine}, reinterpret_cast(filter_grad_data)); - auto src_memory = mkldnn::memory({src_md, mkldnn_engine}, - reinterpret_cast(input_data)); + auto src_memory = + mkldnn::memory({src_md, mkldnn_engine}, + reinterpret_cast(const_cast(input_data))); // create backward conv primitive for weights auto conv_bwd_weights_prim = mkldnn::convolution_backward_weights( @@ -222,11 +225,12 @@ class ConvMKLDNNGradOpKernel : public paddle::framework::OpKernel { strides, paddings, *conv_pd, mkldnn_engine); // create memory - auto diff_src_memory = - mkldnn::memory({diff_src_md, mkldnn_engine}, - reinterpret_cast(input_grad_data)); - auto weights_memory = mkldnn::memory( - {weights_md, mkldnn_engine}, reinterpret_cast(filter_data)); + auto diff_src_memory = mkldnn::memory( + {diff_src_md, mkldnn_engine}, + reinterpret_cast(const_cast(input_grad_data))); + auto weights_memory = + mkldnn::memory({weights_md, mkldnn_engine}, + reinterpret_cast(const_cast(filter_data))); // create backward conv primitive for data auto conv_bwd_data_prim = mkldnn::convolution_backward_data( From ee9832a7a9fc314995e529f715656ba4b3b0e2b3 Mon Sep 17 00:00:00 2001 From: qingqing01 Date: Wed, 18 Apr 2018 11:27:58 +0800 Subject: [PATCH 66/69] Add Top-k Python API. (#9973) * Add topk Python API. * Add unit test. * Remove the repeated API. --- doc/fluid/api/layers.rst | 5 ++ paddle/fluid/operators/top_k_op.h | 7 +-- python/paddle/fluid/layers/control_flow.py | 38 ------------ python/paddle/fluid/layers/metric.py | 19 ++---- python/paddle/fluid/layers/nn.py | 58 ++++++++++++++++--- .../fluid/tests/unittests/test_layers.py | 9 +++ 6 files changed, 70 insertions(+), 66 deletions(-) diff --git a/doc/fluid/api/layers.rst b/doc/fluid/api/layers.rst index 5c02886efd..3790f09c84 100644 --- a/doc/fluid/api/layers.rst +++ b/doc/fluid/api/layers.rst @@ -815,3 +815,8 @@ zeros .. autofunction:: paddle.fluid.layers.zeros :noindex: +topk +---- + +.. autofunction:: paddle.fluid.layers.topk + :noindex: diff --git a/paddle/fluid/operators/top_k_op.h b/paddle/fluid/operators/top_k_op.h index 9f8482aded..d44eeae8e6 100644 --- a/paddle/fluid/operators/top_k_op.h +++ b/paddle/fluid/operators/top_k_op.h @@ -24,7 +24,6 @@ namespace paddle { namespace operators { using Tensor = framework::Tensor; -using LoDTensor = framework::LoDTensor; template @@ -36,9 +35,9 @@ class TopkKernel : public framework::OpKernel { void Compute(const framework::ExecutionContext& ctx) const override { // Get the top k elements of each row of input tensor // FIXME: only deal with matrix(2d tensor). - 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"); // k is determined by Attr const size_t k = static_cast(ctx.Attr("k")); diff --git a/python/paddle/fluid/layers/control_flow.py b/python/paddle/fluid/layers/control_flow.py index b9a53eda91..4b707973e2 100644 --- a/python/paddle/fluid/layers/control_flow.py +++ b/python/paddle/fluid/layers/control_flow.py @@ -32,7 +32,6 @@ __all__ = [ 'Switch', 'lod_rank_table', 'max_sequence_len', - 'topk', 'lod_tensor_to_array', 'array_to_lod_tensor', 'increment', @@ -751,43 +750,6 @@ def max_sequence_len(rank_table): return res -def topk(input, k): - """ - **topk** - - This function performs the operation that selects the k entries in the input - vector and outputs their values and indices as vectors. Thus topk_out[j] is - the j-th largest entry in input, and its index is topk_indices[j] - - Args: - input (Variable|list): The input tensor that has all the data. - k (int): The number of top elements that the function will pick. - - Returns: - Variable: The variable of type array that contains the k largest entries - from input. - Variable: The variable of type array that contains the indices of k - largest entries from input. - - Examples: - .. code-block:: python - - x = fluid.layers.data(name='x', shape=[10]) - k = 5 - array = fluid.layers.topk(x, k) - """ - helper = LayerHelper('topk', **locals()) - topk_out = helper.create_tmp_variable(dtype=input.dtype) - topk_indices = helper.create_tmp_variable(dtype='int64') - helper.append_op( - type='top_k', - inputs={'X': [input]}, - outputs={'Out': [topk_out], - 'Indices': [topk_indices]}, - attrs={'k': k}) - return topk_out, topk_indices - - def lod_tensor_to_array(x, table): """ Convert a LOD_TENSOR to an LOD_TENSOR_ARRAY. diff --git a/python/paddle/fluid/layers/metric.py b/python/paddle/fluid/layers/metric.py index f66dccfa2d..cab2eb5551 100644 --- a/python/paddle/fluid/layers/metric.py +++ b/python/paddle/fluid/layers/metric.py @@ -20,6 +20,7 @@ from ..layer_helper import LayerHelper from ..initializer import Normal, Constant from ..framework import Variable from ..param_attr import ParamAttr +import nn __all__ = ['accuracy', 'auc'] @@ -27,17 +28,10 @@ __all__ = ['accuracy', 'auc'] def accuracy(input, label, k=1, correct=None, total=None): """ This function computes the accuracy using the input and label. - The output is the top_k inputs and their indices. + The output is the top k inputs and their indices. """ helper = LayerHelper("accuracy", **locals()) - topk_out = helper.create_tmp_variable(dtype=input.dtype) - topk_indices = helper.create_tmp_variable(dtype="int64") - helper.append_op( - type="top_k", - inputs={"X": [input]}, - outputs={"Out": [topk_out], - "Indices": [topk_indices]}, - attrs={"k": k}) + topk_out, topk_indices = nn.topk(input, k=k) acc_out = helper.create_tmp_variable(dtype="float32") if correct is None: correct = helper.create_tmp_variable(dtype="int64") @@ -68,12 +62,7 @@ def auc(input, label, curve='ROC', num_thresholds=200): helper = LayerHelper("auc", **locals()) topk_out = helper.create_tmp_variable(dtype=input.dtype) topk_indices = helper.create_tmp_variable(dtype="int64") - helper.append_op( - type="top_k", - inputs={"X": [input]}, - outputs={"Out": [topk_out], - "Indices": [topk_indices]}, - attrs={"k": k}) + topk_out, topk_indices = nn.topk(input, k=k) auc_out = helper.create_tmp_variable(dtype="float32") if correct is None: correct = helper.create_tmp_variable(dtype="int64") diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index 2993cb9734..752f4689be 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -60,6 +60,7 @@ __all__ = [ 'edit_distance', 'l2_normalize', 'matmul', + 'topk', 'warpctc', 'sequence_reshape', 'transpose', @@ -2576,6 +2577,53 @@ def matmul(x, y, transpose_x=False, transpose_y=False, name=None): return out +def topk(input, k): + """ + This operator is used to find values and indices of the k largest entries + for the last dimension. + + If the input is a vector (rank=1), finds the k largest entries in the vector + and outputs their values and indices as vectors. Thus values[j] is the j-th + largest entry in input, and its index is indices[j]. + + If the input is a Tensor with higher rank, this operator computes the top k + entries along the last dimension. + + Args: + input(Variable): The input variable which can be a vector or Tensor with + higher rank. + k(int): An integer value to specify the top k largest elements. + + Returns: + values(Variable): The k largest elements along each last dimensional + slice. + indices(Variable): The indices of values within the last dimension of + input. + + Examples: + .. code-block:: python + + top5_values, top5_indices = layers.topk(input, k=5) + """ + shape = input.shape + if k < 1 and k >= shape[-1]: + raise ValueError("k must be greater than 0 and less than %d." % + (shape[-1])) + + helper = LayerHelper("top_k", **locals()) + values = helper.create_tmp_variable(dtype=input.dtype) + indices = helper.create_tmp_variable(dtype="int64") + helper.append_op( + type="top_k", + inputs={"X": [input]}, + outputs={"Out": [values], + "Indices": [indices]}, + attrs={"k": k}) + values.stop_gradient = True + indices.stop_gradient = True + return values, indices + + def edit_distance(input, label, normalized=True, ignored_tokens=None, name=None): """ @@ -2717,15 +2765,7 @@ def ctc_greedy_decoder(input, blank, name=None): cost = fluid.layers.ctc_greedy_decoder(input=x, blank=0) """ helper = LayerHelper("ctc_greedy_decoder", **locals()) - # top 1 op - topk_out = helper.create_tmp_variable(dtype=input.dtype) - topk_indices = helper.create_tmp_variable(dtype="int64") - helper.append_op( - type="top_k", - inputs={"X": [input]}, - outputs={"Out": [topk_out], - "Indices": [topk_indices]}, - attrs={"k": 1}) + _, topk_indices = topk(input, k=1) # ctc align op ctc_out = helper.create_tmp_variable(dtype="int64") diff --git a/python/paddle/fluid/tests/unittests/test_layers.py b/python/paddle/fluid/tests/unittests/test_layers.py index a1be2d671d..17d6afdee1 100644 --- a/python/paddle/fluid/tests/unittests/test_layers.py +++ b/python/paddle/fluid/tests/unittests/test_layers.py @@ -350,6 +350,15 @@ class TestBook(unittest.TestCase): self.assertIsNotNone(smooth_label) print(str(program)) + def test_topk(self): + program = Program() + with program_guard(program): + data = layers.data(name="label", shape=[200], dtype="float32") + values, indices = layers.topk(data, k=5) + self.assertIsNotNone(values) + self.assertIsNotNone(indices) + print(str(program)) + if __name__ == '__main__': unittest.main() From 35483a209480094c3ca8c72285a1249ada5db6c4 Mon Sep 17 00:00:00 2001 From: gongweibao Date: Wed, 18 Apr 2018 13:20:35 +0800 Subject: [PATCH 67/69] Add neural transformer leanring rate decay function. (#9951) Add neural transformer leanring rate decay function --- .../fluid/layers/learning_rate_scheduler.py | 33 +++++++++++++++++-- 1 file changed, 30 insertions(+), 3 deletions(-) diff --git a/python/paddle/fluid/layers/learning_rate_scheduler.py b/python/paddle/fluid/layers/learning_rate_scheduler.py index 65b95a58d6..d13c54daa5 100644 --- a/python/paddle/fluid/layers/learning_rate_scheduler.py +++ b/python/paddle/fluid/layers/learning_rate_scheduler.py @@ -20,7 +20,7 @@ from ..initializer import init_on_cpu __all__ = [ 'exponential_decay', 'natural_exp_decay', 'inverse_time_decay', - 'polynomial_decay', 'piecewise_decay' + 'polynomial_decay', 'piecewise_decay', 'noam_decay' ] """ When training a model, it's often useful to decay the @@ -32,14 +32,41 @@ strategy according to this module. """ -def _decay_step_counter(): +def _decay_step_counter(begin=0): # the first global step is zero in learning rate decay global_step = nn.autoincreased_step_counter( - counter_name='@LR_DECAY_COUNTER@', begin=0, step=1) + counter_name='@LR_DECAY_COUNTER@', begin=begin, step=1) global_step = tensor.cast(global_step, 'float32') return global_step +def noam_decay(d_model, warmup_steps): + """Apply decay to learning rate. + ```python + lr_value = np.power(d_model, -0.5) * np.min([ + np.power(current_steps, -0.5), + np.power(warmup_steps, -1.5) * current_steps + ]) + ``` + + Args: + d_model(Variable): The dimensionality of input and output of model. + Reference: attention is all you need + https://arxiv.org/pdf/1706.03762.pdf + warmup_steps(Variable): A super parameter. + + Returns: + The decayed learning rate. + """ + global_step = _decay_step_counter(1) + with init_on_cpu(): + a = global_step**-0.5 + b = (warmup_steps**-1.5) * global_step + lr_value = (d_model**-0.5) * ops.elementwise_min(a, b) + + return lr_value + + def exponential_decay(learning_rate, decay_steps, decay_rate, staircase=False): """Applies exponential decay to the learning rate. From 35ebe2eca705da5a301d2dcb3e086ba5b826d3c6 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Wed, 18 Apr 2018 16:15:49 +0800 Subject: [PATCH 68/69] Clean MultiDevicesGraphBuilder --- .../details/multi_devices_graph_builder.cc | 202 ++++++++++-------- .../details/multi_devices_graph_builder.h | 14 ++ 2 files changed, 122 insertions(+), 94 deletions(-) diff --git a/paddle/fluid/framework/details/multi_devices_graph_builder.cc b/paddle/fluid/framework/details/multi_devices_graph_builder.cc index 4d76dbf7f6..882d438934 100644 --- a/paddle/fluid/framework/details/multi_devices_graph_builder.cc +++ b/paddle/fluid/framework/details/multi_devices_graph_builder.cc @@ -89,101 +89,25 @@ std::unique_ptr MultiDevSSAGraphBuilder::Build( bool is_forwarding = true; for (auto *op : program.Block(0).AllOps()) { - bool change_forward = false; - if (!is_forwarding) { - // FIXME(yy): Do not hard code like this - if (op->OutputArgumentNames().size() == 1 && - op->OutputArgumentNames()[0] == GradVarName(loss_var_name_)) { - continue; // Drop fill 1. for backward coeff; - } - } - - // append send op if program is distributed trainer main program. - // always use the first device - if (!is_forwarding && op->Type() == "send") { - auto &p = places_[0]; - auto *s = local_scopes_[0]; - // FIXME(wuyi): send op always copy from GPU 0 - result.ops_.emplace_back(new SendOpHandle(*op, s, p)); - // Create inputs for output on original place and no ssa output - // is created for send op. - CreateOpHandleIOs(&result, *op, p, 0); - continue; - } - - for (size_t i = 0; i < places_.size(); ++i) { - auto &p = places_[i]; - auto *s = local_scopes_[i]; - - result.ops_.emplace_back(new ComputationOpHandle(*op, s, p)); - auto *op_handle = result.ops_.back().get(); - CreateOpHandleIOs(&result, *op, p, i); - - auto var_names = op->OutputArgumentNames(); - - if (is_forwarding) { - if (var_names.size() == 1 && var_names[0] == loss_var_name_) { -// Insert ScaleCost OpHandle -#ifdef PADDLE_WITH_CUDA - auto *communication_dev_ctx = nccl_ctxs_->DevCtx(p); -#else - auto *communication_dev_ctx = - platform::DeviceContextPool::Instance().Get(platform::CPUPlace()); -#endif - - op_handle = new ScaleLossGradOpHandle(local_scopes_.size(), s, p, - communication_dev_ctx); - result.ops_.emplace_back(op_handle); - - // FIXME: Currently ScaleLossGradOp only use device_count as scale - // factor. So it does not depend on any other operators. - // VarHandle *loss = GetVarHandle(loss_var_name, place); - // loss->pending_ops_.emplace_back(op_handle); - // op_handle->inputs_.emplace_back(loss); - - CreateOpOutput(&result, op_handle, GradVarName(loss_var_name_), p, i); - change_forward = true; - } - } - } - - if (change_forward) { + if (op->Type() == "send") { + // append send op if program is distributed trainer main program. + // always use the first device + CreateSendOp(&result, *op); + } else if (IsScaleLossOp(*op)) { + CreateScaleLossGradOp(&result); is_forwarding = false; - } - - if (!is_forwarding) { - auto var_names = op->OutputArgumentNames(); - // Currently, we assume that once gradient is generated, it can be - // broadcast, and each gradient is only broadcast once. But there are no - // other cases, for example, we need to adjust the gradient according to - // the input when we get the gradient, which is not considered at present. - for (auto &og : var_names) { - if (grad_names_.count(og) != 0 && - og_has_been_broadcast.count(og) == 0) { // is param grad - // Insert NCCL AllReduce Op - og_has_been_broadcast.insert(og); -#ifdef PADDLE_WITH_CUDA - result.ops_.emplace_back( - new NCCLAllReduceOpHandle(local_scopes_, places_, *nccl_ctxs_)); - auto *op_handle = result.ops_.back().get(); - - for (size_t i = 0; i < places_.size(); ++i) { - auto &p = places_[i]; - auto &vars = result.vars_[i][og]; - - if (vars.empty()) { // This device has no data. continue. - continue; - } - auto &prev_grad = vars[vars.size() - 1]; - op_handle->AddInput(prev_grad.get()); - - auto var = new VarHandle(vars.size() - 1, i, og, p); - vars.emplace_back(var); - op_handle->AddOutput(var); + } else { + CreateComputationalOps(&result, *op); + if (!is_forwarding) { + // Currently, we assume that once gradient is generated, it can be + // broadcast, and each gradient is only broadcast once. But there are no + // other cases, for example, we need to adjust the gradient according to + // the input when we get the gradient, which is not considered at + // present. + for (auto &og : op->OutputArgumentNames()) { + if (IsParameterGradientOnce(og, &og_has_been_broadcast)) { + InsertNCCLAllReduceOp(&result, og); } -#else - PADDLE_ENFORCE("Not implemented"); -#endif } } } @@ -207,7 +131,97 @@ std::unique_ptr MultiDevSSAGraphBuilder::Build( } return std::unique_ptr(graph); -} // namespace details +} + +void MultiDevSSAGraphBuilder::InsertNCCLAllReduceOp( + SSAGraph *result, const std::string &og) const { +#ifdef PADDLE_WITH_CUDA + result->ops_.emplace_back( + new NCCLAllReduceOpHandle(local_scopes_, places_, *nccl_ctxs_)); + auto *op_handle = result->ops_.back().get(); + + for (size_t i = 0; i < places_.size(); ++i) { + auto &p = places_[i]; + auto &vars = result->vars_[i][og]; + if (vars.empty()) { // This device has no data. continue. + continue; + } + auto &prev_grad = vars[vars.size() - 1]; + op_handle->AddInput(prev_grad.get()); + + auto var = new VarHandle(vars.size() - 1, i, og, p); + vars.emplace_back(var); + op_handle->AddOutput(var); + } +#else + PADDLE_ENFORCE("Not implemented"); +#endif +} + +bool MultiDevSSAGraphBuilder::IsParameterGradientOnce( + const std::string &og, + std::unordered_set *og_has_been_broadcast) const { + bool is_pg_once = + grad_names_.count(og) != 0 && og_has_been_broadcast->count(og) == 0; + if (is_pg_once) { + // Insert NCCL AllReduce Op + og_has_been_broadcast->insert(og); + } + return is_pg_once; +} + +void MultiDevSSAGraphBuilder::CreateScaleLossGradOp(SSAGraph *result) const { + for (size_t i = 0; i < places_.size(); ++i) { +// Insert ScaleCost OpHandle +#ifdef PADDLE_WITH_CUDA + auto *communication_dev_ctx = nccl_ctxs_->DevCtx(places_[i]); +#else + auto *communication_dev_ctx = + platform::DeviceContextPool::Instance().Get(platform::CPUPlace()); +#endif + + auto *op_handle = + new ScaleLossGradOpHandle(local_scopes_.size(), local_scopes_[i], + places_[i], communication_dev_ctx); + result->ops_.emplace_back(op_handle); + + // FIXME: Currently ScaleLossGradOp only use device_count as scale + // factor. So it does not depend on any other operators. + // VarHandle *loss = GetVarHandle(loss_var_name, place); + // loss->pending_ops_.emplace_back(op_handle); + // op_handle->inputs_.emplace_back(loss); + + CreateOpOutput(result, op_handle, GradVarName(loss_var_name_), places_[i], + i); + } +} + +void MultiDevSSAGraphBuilder::CreateComputationalOps(SSAGraph *result, + const OpDesc &op) const { + for (size_t scope_idx = 0; scope_idx < places_.size(); ++scope_idx) { + auto p = places_[scope_idx]; + auto s = local_scopes_[scope_idx]; + result->ops_.emplace_back(new ComputationOpHandle(op, s, p)); + CreateOpHandleIOs(result, op, p, scope_idx); + } +} + +void MultiDevSSAGraphBuilder::CreateSendOp(SSAGraph *result, + const OpDesc &op) const { + auto &p = places_[0]; + auto *s = local_scopes_[0]; + // FIXME(wuyi): send op always copy from GPU 0 + result->ops_.emplace_back(new SendOpHandle(op, s, p)); + // Create inputs for output on original place and no ssa output + // is created for send op. + CreateOpHandleIOs(result, op, p, 0); +} + +bool MultiDevSSAGraphBuilder::IsScaleLossOp(const OpDesc &op) const { + // FIXME(yy): Do not hard code like this + return op.OutputArgumentNames().size() == 1 && + op.OutputArgumentNames()[0] == GradVarName(loss_var_name_); +} } // namespace details } // namespace framework } // namespace paddle diff --git a/paddle/fluid/framework/details/multi_devices_graph_builder.h b/paddle/fluid/framework/details/multi_devices_graph_builder.h index f1518d75b4..b5ba2dbd3c 100644 --- a/paddle/fluid/framework/details/multi_devices_graph_builder.h +++ b/paddle/fluid/framework/details/multi_devices_graph_builder.h @@ -57,6 +57,20 @@ class MultiDevSSAGraphBuilder : public SSAGraphBuilder { #ifdef PADDLE_WITH_CUDA platform::NCCLContextMap *nccl_ctxs_; #endif + + bool IsScaleLossOp(const OpDesc &op) const; + + void CreateSendOp(SSAGraph *result, const OpDesc &op) const; + + void CreateComputationalOps(SSAGraph *result, const OpDesc &op) const; + + void CreateScaleLossGradOp(SSAGraph *result) const; + + bool IsParameterGradientOnce( + const std::string &og, + std::unordered_set *og_has_been_broadcast) const; + + void InsertNCCLAllReduceOp(SSAGraph *result, const std::string &og) const; }; } // namespace details } // namespace framework From 38d75c912cf7ca3e64bedc1446334a1a33d8e776 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Wed, 18 Apr 2018 17:23:33 +0800 Subject: [PATCH 69/69] Follow comments --- .../fluid/framework/details/multi_devices_graph_builder.cc | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/paddle/fluid/framework/details/multi_devices_graph_builder.cc b/paddle/fluid/framework/details/multi_devices_graph_builder.cc index 882d438934..d2b6a35a5d 100644 --- a/paddle/fluid/framework/details/multi_devices_graph_builder.cc +++ b/paddle/fluid/framework/details/multi_devices_graph_builder.cc @@ -143,10 +143,8 @@ void MultiDevSSAGraphBuilder::InsertNCCLAllReduceOp( for (size_t i = 0; i < places_.size(); ++i) { auto &p = places_[i]; auto &vars = result->vars_[i][og]; - if (vars.empty()) { // This device has no data. continue. - continue; - } - auto &prev_grad = vars[vars.size() - 1]; + PADDLE_ENFORCE(!vars.empty()); + auto &prev_grad = vars.back(); op_handle->AddInput(prev_grad.get()); auto var = new VarHandle(vars.size() - 1, i, og, p);

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