Merge pull request #9302 from Xreki/core_inference_multi_thread

Add multi-thread inference example which shares the inference_program and parameters

paddle/fluid/framework/program_desc.cc

@@ -85,9 +85,9 @@ ProgramDesc::ProgramDesc(const std::string &binary_str) {
 }
 
 const std::vector<std::string> ProgramDesc::GetFeedTargetNames() {
-  BlockDesc *global_block = blocks_[0].get();
+  auto &global_block = Block(0);
   std::vector<std::string> feed_target_names;
-  for (auto *op : global_block->AllOps()) {
+  for (auto *op : global_block.AllOps()) {
     if (op->Type() == kFeedOpType) {
       feed_target_names.insert(feed_target_names.begin(), op->Output("Out")[0]);
     }
@@ -96,9 +96,9 @@ const std::vector<std::string> ProgramDesc::GetFeedTargetNames() {
 }
 
 const std::vector<std::string> ProgramDesc::GetFetchTargetNames() {
-  BlockDesc *global_block = blocks_[0].get();
+  auto &global_block = Block(0);
   std::vector<std::string> fetch_target_names;
-  for (auto *op : global_block->AllOps()) {
+  for (auto *op : global_block.AllOps()) {
     if (op->Type() == kFetchOpType) {
       fetch_target_names.push_back(op->Input("X")[0]);
     }
@@ -106,5 +106,43 @@ const std::vector<std::string> ProgramDesc::GetFetchTargetNames() {
   return fetch_target_names;
 }
 
+void ProgramDesc::SetFeedHolderName(const std::string &feed_holder_name) {
+  auto *global_block = MutableBlock(0);
+  int index = 0;
+  for (auto *op : global_block->AllOps()) {
+    if (op->Type() == kFeedOpType) {
+      // Unify the input's name of all feed_ops to feed_holder_name
+      global_block->RemoveVar(op->Input("X")[0]);
+      op->SetInput("X", {feed_holder_name});
+      op->SetAttr("col", {index});
+      op->CheckAttrs();
+      index++;
+    }
+  }
+
+  auto *feed_holder = global_block->Var(feed_holder_name);
+  feed_holder->SetType(proto::VarType::FEED_MINIBATCH);
+  feed_holder->SetPersistable(true);
+}
+
+void ProgramDesc::SetFetchHolderName(const std::string &fetch_holder_name) {
+  auto *global_block = MutableBlock(0);
+  int index = 0;
+  for (auto *op : global_block->AllOps()) {
+    if (op->Type() == kFetchOpType) {
+      // Unify the output's name of all fetch_ops to fetch_holder_name
+      global_block->RemoveVar(op->Output("Out")[0]);
+      op->SetOutput("Out", {fetch_holder_name});
+      op->SetAttr("col", {index});
+      op->CheckAttrs();
+      index++;
+    }
+  }
+
+  auto *fetch_holder = global_block->Var(fetch_holder_name);
+  fetch_holder->SetType(proto::VarType::FETCH_LIST);
+  fetch_holder->SetPersistable(true);
+}
+
 }  // namespace framework
 }  // namespace paddle

paddle/fluid/framework/program_desc.h

@@ -15,6 +15,7 @@ limitations under the License. */
 #pragma once
 
 #include <memory>
+#include <string>
 #include <vector>
 #include "paddle/fluid/framework/block_desc.h"
 #include "paddle/fluid/framework/framework.pb.h"
@@ -52,9 +53,26 @@ class ProgramDesc {
 
   proto::ProgramDesc *Proto();
 
+  // The output variable of feed_op is referenced as feed_target.
+  // This function is used to collect the output variable's name of all
+  // feed_ops.
   const std::vector<std::string> GetFeedTargetNames();
+
+  // The input variable of fetch_op is referenced as fetch_target.
+  // This function is used to collect the input variable's name of all
+  // fetch_ops.
   const std::vector<std::string> GetFetchTargetNames();
 
+  // The input variable of feed_op that holds input Tensor provided by users is
+  // referenced as feed_holder.
+  // This function is used to change or unify the feed_holder variables' name.
+  void SetFeedHolderName(const std::string &feed_holder_name);
+
+  // The output variable of fetch_op that holds output Tensor needed by users is
+  // referenced as fetch_holder.
+  // This function is used to change or unify the fetch_holder variables' name.
+  void SetFetchHolderName(const std::string &fetch_holder_name);
+
  private:
   proto::ProgramDesc desc_;
 

paddle/fluid/inference/tests/book/test_inference_fit_a_line.cc

@@ -12,6 +12,7 @@ limitations under the License. */
 #include "gflags/gflags.h"
 #include "gtest/gtest.h"
 #include "paddle/fluid/inference/tests/test_helper.h"
+#include "paddle/fluid/inference/tests/test_multi_thread_helper.h"
 
 DEFINE_string(dirname, "", "Directory of the inference model.");
 
@@ -26,32 +27,63 @@ TEST(inference, fit_a_line) {
   // 0. Call `paddle::framework::InitDevices()` initialize all the devices
   // In unittests, this is done in paddle/testing/paddle_gtest_main.cc
 
-  paddle::framework::LoDTensor input;
+  for (int num_threads : {1, 2}) {
+    std::vector<std::vector<paddle::framework::LoDTensor*>> cpu_feeds;
+    cpu_feeds.resize(num_threads);
+    for (int i = 0; i < num_threads; ++i) {
+      auto* input = new paddle::framework::LoDTensor();
       // The second dim of the input tensor should be 13
       // The input data should be >= 0
       int64_t batch_size = 10;
-  SetupTensor<float>(&input, {batch_size, 13}, static_cast<float>(0),
+      SetupTensor<float>(input, {batch_size, 13}, static_cast<float>(0),
                          static_cast<float>(10));
-  std::vector<paddle::framework::LoDTensor*> cpu_feeds;
-  cpu_feeds.push_back(&input);
+      cpu_feeds[i].push_back(input);
+    }
 
-  paddle::framework::LoDTensor output1;
-  std::vector<paddle::framework::LoDTensor*> cpu_fetchs1;
-  cpu_fetchs1.push_back(&output1);
+    std::vector<std::vector<paddle::framework::LoDTensor*>> cpu_fetchs1;
+    cpu_fetchs1.resize(num_threads);
+    for (int i = 0; i < num_threads; ++i) {
+      auto* output = new paddle::framework::LoDTensor();
+      cpu_fetchs1[i].push_back(output);
+    }
 
     // Run inference on CPU
-  TestInference<paddle::platform::CPUPlace>(dirname, cpu_feeds, cpu_fetchs1);
-  LOG(INFO) << output1.dims();
+    LOG(INFO) << "--- CPU Runs (num_threads: " << num_threads << "): ---";
+    if (num_threads == 1) {
+      TestInference<paddle::platform::CPUPlace>(dirname, cpu_feeds[0],
+                                                cpu_fetchs1[0]);
+    } else {
+      TestMultiThreadInference<paddle::platform::CPUPlace>(
+          dirname, cpu_feeds, cpu_fetchs1, num_threads);
+    }
 
 #ifdef PADDLE_WITH_CUDA
-  paddle::framework::LoDTensor output2;
-  std::vector<paddle::framework::LoDTensor*> cpu_fetchs2;
-  cpu_fetchs2.push_back(&output2);
+    std::vector<std::vector<paddle::framework::LoDTensor*>> cpu_fetchs2;
+    cpu_fetchs2.resize(num_threads);
+    for (int i = 0; i < num_threads; ++i) {
+      auto* output = new paddle::framework::LoDTensor();
+      cpu_fetchs2[i].push_back(output);
+    }
 
     // Run inference on CUDA GPU
-  TestInference<paddle::platform::CUDAPlace>(dirname, cpu_feeds, cpu_fetchs2);
-  LOG(INFO) << output2.dims();
+    LOG(INFO) << "--- GPU Runs (num_threads: " << num_threads << "): ---";
+    if (num_threads == 1) {
+      TestInference<paddle::platform::CUDAPlace>(dirname, cpu_feeds[0],
+                                                 cpu_fetchs2[0]);
+    } else {
+      TestMultiThreadInference<paddle::platform::CUDAPlace>(
+          dirname, cpu_feeds, cpu_fetchs2, num_threads);
+    }
 
-  CheckError<float>(output1, output2);
+    for (int i = 0; i < num_threads; ++i) {
+      CheckError<float>(*cpu_fetchs1[i][0], *cpu_fetchs2[i][0]);
+      delete cpu_fetchs2[i][0];
+    }
 #endif
+
+    for (int i = 0; i < num_threads; ++i) {
+      delete cpu_feeds[i][0];
+      delete cpu_fetchs1[i][0];
+    }
+  }  // num_threads-loop
 }

paddle/fluid/inference/tests/test_helper.h

@@ -25,7 +25,8 @@ limitations under the License. */
 template <typename T>
 void SetupTensor(paddle::framework::LoDTensor* input,
                  paddle::framework::DDim dims, T lower, T upper) {
-  std::mt19937 rng(100);  // An arbitrarily chosen but fixed seed.
+  static unsigned int seed = 100;
+  std::mt19937 rng(seed++);
   std::uniform_real_distribution<double> uniform_dist(0, 1);
 
   T* input_ptr = input->mutable_data<T>(dims, paddle::platform::CPUPlace());

paddle/fluid/inference/tests/test_multi_thread_helper.h

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#pragma once
+
+#include <map>
+#include <string>
+#include <thread>  // NOLINT
+#include <vector>
+#include "paddle/fluid/framework/lod_tensor.h"
+#include "paddle/fluid/inference/io.h"
+
+void ThreadedRunInference(
+    const std::unique_ptr<paddle::framework::ProgramDesc>& inference_program,
+    paddle::framework::Executor* executor, paddle::framework::Scope* scope,
+    const int thread_id,
+    const std::vector<paddle::framework::LoDTensor*>& cpu_feeds,
+    const std::vector<paddle::framework::LoDTensor*>& cpu_fetchs) {
+  auto copy_program = std::unique_ptr<paddle::framework::ProgramDesc>(
+      new paddle::framework::ProgramDesc(*inference_program));
+
+  std::string feed_holder_name = "feed_" + paddle::string::to_string(thread_id);
+  std::string fetch_holder_name =
+      "fetch_" + paddle::string::to_string(thread_id);
+  copy_program->SetFeedHolderName(feed_holder_name);
+  copy_program->SetFetchHolderName(fetch_holder_name);
+
+  // 3. Get the feed_target_names and fetch_target_names
+  const std::vector<std::string>& feed_target_names =
+      copy_program->GetFeedTargetNames();
+  const std::vector<std::string>& fetch_target_names =
+      copy_program->GetFetchTargetNames();
+
+  // 4. Prepare inputs: set up maps for feed targets
+  std::map<std::string, const paddle::framework::LoDTensor*> feed_targets;
+  for (size_t i = 0; i < feed_target_names.size(); ++i) {
+    // Please make sure that cpu_feeds[i] is right for feed_target_names[i]
+    feed_targets[feed_target_names[i]] = cpu_feeds[i];
+  }
+
+  // 5. Define Tensor to get the outputs: set up maps for fetch targets
+  std::map<std::string, paddle::framework::LoDTensor*> fetch_targets;
+  for (size_t i = 0; i < fetch_target_names.size(); ++i) {
+    fetch_targets[fetch_target_names[i]] = cpu_fetchs[i];
+  }
+
+  // 6. Run the inference program
+  executor->Run(*copy_program, scope, feed_targets, fetch_targets, true,
+                feed_holder_name, fetch_holder_name);
+}
+
+template <typename Place>
+void TestMultiThreadInference(
+    const std::string& dirname,
+    const std::vector<std::vector<paddle::framework::LoDTensor*>>& cpu_feeds,
+    const std::vector<std::vector<paddle::framework::LoDTensor*>>& cpu_fetchs,
+    const int num_threads) {
+  // 1. Define place, executor, scope
+  auto place = Place();
+  auto executor = paddle::framework::Executor(place);
+  auto* scope = new paddle::framework::Scope();
+
+  // 2. Initialize the inference_program and load parameters
+  std::unique_ptr<paddle::framework::ProgramDesc> inference_program =
+      paddle::inference::Load(executor, *scope, dirname);
+
+  std::vector<std::thread*> threads;
+  for (int i = 0; i < num_threads; ++i) {
+    threads.push_back(new std::thread(
+        ThreadedRunInference, std::ref(inference_program), &executor, scope, i,
+        std::ref(cpu_feeds[i]), std::ref(cpu_fetchs[i])));
+  }
+  for (int i = 0; i < num_threads; ++i) {
+    threads[i]->join();
+    delete threads[i];
+  }
+
+  delete scope;
+}