Replace Channel in DoubleBufferReader with BlockingQueue

paddle/fluid/operators/reader/create_double_buffer_reader_op.cc

@@ -14,7 +14,7 @@
 
 #include <thread>  // NOLINT
 
-#include "paddle/fluid/framework/channel.h"
+#include "paddle/fluid/operators/reader/blocking_queue.h"
 #include "paddle/fluid/operators/reader/reader_op_registry.h"
 
 namespace paddle {
@@ -23,13 +23,13 @@ namespace reader {
 
 // '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 = 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 = 0;  // kCacheSize - 2
+static constexpr size_t kChannelSize = 1;  // kCacheSize - 2
 
 class DoubleBufferReader : public framework::DecoratedReader {
  public:
@@ -58,7 +58,7 @@ class DoubleBufferReader : public framework::DecoratedReader {
   bool HasNext() const;
 
   void StartPrefetcher() {
-    channel_ = framework::MakeChannel<size_t>(kChannelSize);
+    channel_ = new reader::BlockingQueue<size_t>(kChannelSize);
     prefetcher_ = std::thread([this] { PrefetchThreadFunc(); });
   }
 
@@ -74,7 +74,7 @@ class DoubleBufferReader : public framework::DecoratedReader {
   void PrefetchThreadFunc();
 
   std::thread prefetcher_;
-  framework::Channel<size_t>* channel_;
+  reader::BlockingQueue<size_t>* channel_;
   platform::Place place_;
   std::vector<std::vector<framework::LoDTensor>> cpu_tensor_cache_;
   std::vector<std::vector<framework::LoDTensor>> gpu_tensor_cache_;
@@ -185,10 +185,7 @@ void DoubleBufferReader::PrefetchThreadFunc() {
         gpu_batch[i].set_lod(cpu_batch[i].lod());
       }
     }
-    try {
-      size_t tmp = cached_tensor_id;
-      channel_->Send(&tmp);
-    } catch (paddle::platform::EnforceNotMet e) {
+    if (!channel_->Send(cached_tensor_id)) {
       VLOG(5) << "WARNING: The double buffer channel has been closed. The "
                  "prefetch thread will terminate.";
       break;