Merge branch 'feature/dctor_all_readers' into feature/combine_open_files_and_double_buffer

paddle/fluid/framework/reader.cc

@@ -67,7 +67,8 @@ void ReaderBase::Start() {
   }
 }
 
-ReaderBase::~ReaderBase() { Shutdown(); }
+ReaderBase::~ReaderBase() {}
 
+DecoratedReader::~DecoratedReader() { reader_->Shutdown(); }
 }  // namespace framework
 }  // namespace paddle

paddle/fluid/framework/reader.h

@@ -25,8 +25,6 @@
 namespace paddle {
 namespace framework {
 
-enum ReaderStatus { kRunning, kStopped };
-
 class ReaderBase {
  public:
   virtual void ReadNext(std::vector<LoDTensor>* out);
@@ -48,6 +46,8 @@ class ReaderBase {
 
   virtual void StartImpl() {}
 
+  enum ReaderStatus { kRunning, kStopped };
+
   ReaderStatus status_{kRunning};
 
   mutable std::mutex mu_;
@@ -74,6 +74,8 @@ class DecoratedReader : public ReaderBase,
     reader_->InsertDecoratedReader(shared_from_this());
   }
 
+  ~DecoratedReader();
+
  protected:
   void ShutdownImpl() override { reader_->Shutdown(); }
 

paddle/fluid/operators/reader/create_double_buffer_reader_op.cc

@@ -14,79 +14,79 @@
 
 #include <thread>  // NOLINT
 
+#include "ThreadPool.h"
 #include "paddle/fluid/operators/reader/blocking_queue.h"
 #include "paddle/fluid/operators/reader/reader_op_registry.h"
 
 namespace paddle {
 namespace operators {
 namespace reader {
+class BufferedReader : public framework::DecoratedReader {
+  using TensorVec = std::vector<framework::LoDTensor>;
+  using VecFuture = std::future<TensorVec>;
 
-// 'Double buffer' means we shall maintain two batches of input data at the same
-// time. So the kCacheSize shoul be at least 2.
-static constexpr size_t kCacheSize = 3;
-// There will be two bacthes out of the channel during training:
-// 1. the one waiting to be sent to the channel
-// 2. the one just be received from the channel, which is also being used by
-// subsequent operators.
-// So the channel size should be kChacheSize - 2
-static constexpr size_t kChannelSize = 1;  // kCacheSize - 2
-
-class DoubleBufferReader : public framework::DecoratedReader {
  public:
-  explicit DoubleBufferReader(
-      const std::shared_ptr<ReaderBase>& reader,
-      platform::Place target_place = platform::CPUPlace())
-      : DecoratedReader(reader), place_(target_place) {
-    cpu_tensor_cache_.resize(kCacheSize);
-    gpu_tensor_cache_.resize(kCacheSize);
-#ifdef PADDLE_WITH_CUDA
-    if (platform::is_gpu_place(place_)) {
-      for (size_t i = 0; i < kCacheSize; ++i) {
-        ctxs_.emplace_back(new platform::CUDADeviceContext(
-            boost::get<platform::CUDAPlace>(place_)));
-      }
+  BufferedReader(const std::shared_ptr<framework::ReaderBase>& reader,
+                 const platform::Place& place, size_t buffer_size)
+      : framework::DecoratedReader(reader),
+        thread_pool_(1),
+        place_(place),
+        buffer_size_(buffer_size) {
+    AppendFutureToBatchSize();
+  }
+
+  ~BufferedReader() override {
+    reader_->Shutdown();
+    buffer_.clear();
+  }
+
+ private:
+  void AppendFutureToBatchSize() {
+    while (buffer_.size() < buffer_size_) {
+      AppendFuture();
     }
-#endif
-    StartPrefetcher();
   }
 
-  void ReadNextImpl(std::vector<framework::LoDTensor>* out) override;
+  void AppendFuture() {
+    buffer_.emplace_back(thread_pool_.enqueue([this] {
+      TensorVec cpu_buffer;
+      reader_->ReadNext(&cpu_buffer);
+      if (platform::is_gpu_place(place_)) {
+        TensorVec gpu_buffer;
 
-  ~DoubleBufferReader() { EndPrefetcher(); }
+        for (size_t i = 0; i < cpu_buffer.size(); ++i) {
+          gpu_buffer.emplace_back();
+          framework::TensorCopySync(cpu_buffer[i], place_, &gpu_buffer.back());
+        }
 
- private:
+        cpu_buffer = gpu_buffer;
+      }
+      return cpu_buffer;
+    }));
+  }
+
+ protected:
   void ShutdownImpl() override {
-    EndPrefetcher();
     reader_->Shutdown();
+    buffer_.clear();
   }
-
   void StartImpl() override {
     reader_->Start();
-    StartPrefetcher();
-  }
-
-  void StartPrefetcher() {
-    channel_ = new reader::BlockingQueue<size_t>(kChannelSize);
-    prefetcher_ = std::thread([this] { PrefetchThreadFunc(); });
+    AppendFutureToBatchSize();
   }
-
-  void EndPrefetcher() {
-    channel_->Close();
-    if (prefetcher_.joinable()) {
-      prefetcher_.join();
-    }
-    delete channel_;
-    channel_ = nullptr;
+  void ReadNextImpl(std::vector<framework::LoDTensor>* out) override {
+    std::cerr << "Read" << std::endl;
+    PADDLE_ENFORCE_EQ(buffer_.size(), buffer_size_);
+    *out = buffer_.front().get();
+    buffer_.pop_front();
+    AppendFuture();
   }
 
-  void PrefetchThreadFunc();
-
-  std::thread prefetcher_;
-  reader::BlockingQueue<size_t>* channel_;
+ private:
+  ThreadPool thread_pool_;
   platform::Place place_;
-  std::vector<std::vector<framework::LoDTensor>> cpu_tensor_cache_;
-  std::vector<std::vector<framework::LoDTensor>> gpu_tensor_cache_;
-  std::vector<std::unique_ptr<platform::DeviceContext>> ctxs_;
+  const size_t buffer_size_;
+  std::list<VecFuture> buffer_;
 };
 
 class CreateDoubleBufferReaderOp : public framework::OperatorBase {
@@ -118,8 +118,8 @@ class CreateDoubleBufferReaderOp : public framework::OperatorBase {
       place = platform::CUDAPlace(static_cast<int>(num));
     }
 
-    out->Reset(framework::MakeDecoratedReader<DoubleBufferReader>(
-        underlying_reader, place));
+    out->Reset(framework::MakeDecoratedReader<BufferedReader>(underlying_reader,
+                                                              place, 2));
   }
 };
 
@@ -146,51 +146,6 @@ class CreateDoubleBufferReaderOpMaker : public DecoratedReaderMakerBase {
   }
 };
 
-void DoubleBufferReader::ReadNextImpl(std::vector<framework::LoDTensor>* out) {
-  size_t cached_tensor_id;
-  if (channel_->Receive(&cached_tensor_id)) {
-    if (platform::is_gpu_place(place_)) {
-      *out = gpu_tensor_cache_[cached_tensor_id];
-    } else {
-      // CPU place
-      *out = cpu_tensor_cache_[cached_tensor_id];
-    }
-  } else {
-    out->clear();
-  }
-}
-
-void DoubleBufferReader::PrefetchThreadFunc() {
-  VLOG(5) << "A new prefetch thread starts.";
-  size_t cached_tensor_id = 0;
-  while (true) {
-    auto& cpu_batch = cpu_tensor_cache_[cached_tensor_id];
-    reader_->ReadNext(&cpu_batch);
-    if (cpu_batch.empty()) {
-      // The underlying reader have no next data.
-      break;
-    }
-    if (platform::is_gpu_place(place_)) {
-      auto& gpu_batch = gpu_tensor_cache_[cached_tensor_id];
-      gpu_batch.resize(cpu_batch.size());
-      for (size_t i = 0; i < cpu_batch.size(); ++i) {
-        // TODO(fengjiayi): Use asynchronous TensorCopy instead
-        framework::TensorCopySync(cpu_batch[i], place_, &gpu_batch[i]);
-        gpu_batch[i].set_lod(cpu_batch[i].lod());
-      }
-    }
-    if (!channel_->Send(cached_tensor_id)) {
-      VLOG(5) << "WARNING: The double buffer channel has been closed. The "
-                 "prefetch thread will terminate.";
-      break;
-    }
-    ++cached_tensor_id;
-    cached_tensor_id %= kCacheSize;
-  }
-  channel_->Close();
-  VLOG(5) << "Prefetch thread terminates.";
-}
-
 }  // namespace reader
 }  // namespace operators
 }  // namespace paddle

python/paddle/fluid/tests/unittests/test_data_balance.py

@@ -190,3 +190,7 @@ class TestDataBalance(unittest.TestCase):
     def test_all(self):
         self.main()
         self.main_lod()
+
+
+if __name__ == '__main__':
+    unittest.main()