fix hang bug

paddle/fluid/pybind/pybind.cc

@@ -546,19 +546,39 @@ All parameter, weight, gradient are variables in Paddle.
       ::paddle::operators::reader::LoDTensorBlockingQueue;
   using LoDTensorBlockingQueueHolder =
       ::paddle::operators::reader::LoDTensorBlockingQueueHolder;
+
+  using LockFreeLoDTensorBlockingQueue =
+      ::paddle::operators::reader::LockFreeLoDTensorBlockingQueue;
+  using LockFreeLoDTensorBlockingQueueHolder =
+      ::paddle::operators::reader::LockFreeLoDTensorBlockingQueueHolder;
+
   py::class_<LoDTensorBlockingQueue, std::shared_ptr<LoDTensorBlockingQueue>>(
       m, "LoDTensorBlockingQueue", "")
       .def("push",
            [](LoDTensorBlockingQueue &self,
-              const std::vector<framework::LoDTensor> &lod_tensor_vec) {
+              std::vector<framework::LoDTensor> &lod_tensor_vec) {
              pybind11::gil_scoped_release release;
-             return self.Push(lod_tensor_vec);
+             return self.Push(std::move(lod_tensor_vec));
            })
       .def("size", &LoDTensorBlockingQueue::Size)
       .def("capacity", &LoDTensorBlockingQueue::Cap)
       .def("close", &LoDTensorBlockingQueue::Close)
       .def("is_closed", &LoDTensorBlockingQueue::IsClosed);
 
+  py::class_<LockFreeLoDTensorBlockingQueue,
+             std::shared_ptr<LockFreeLoDTensorBlockingQueue>>(
+      m, "LockFreeLoDTensorBlockingQueue", "")
+      .def("push",
+           [](LockFreeLoDTensorBlockingQueue &self,
+              std::vector<framework::LoDTensor> &lod_tensor_vec) {
+             pybind11::gil_scoped_release release;
+             return self.Push(std::move(lod_tensor_vec));
+           })
+      .def("size", &LockFreeLoDTensorBlockingQueue::Size)
+      .def("capacity", &LockFreeLoDTensorBlockingQueue::Cap)
+      .def("close", &LockFreeLoDTensorBlockingQueue::Close)
+      .def("is_closed", &LockFreeLoDTensorBlockingQueue::IsClosed);
+
   m.def("init_lod_tensor_blocking_queue",
         [](Variable &var,
            size_t capacity) -> std::shared_ptr<LoDTensorBlockingQueue> {
@@ -568,6 +588,15 @@ All parameter, weight, gradient are variables in Paddle.
         },
         py::return_value_policy::copy);
 
+  m.def("init_lock_free_lod_tensor_blocking_queue",
+        [](Variable &var,
+           size_t capacity) -> std::shared_ptr<LockFreeLoDTensorBlockingQueue> {
+          auto *holder = var.GetMutable<LockFreeLoDTensorBlockingQueueHolder>();
+          holder->InitOnce(capacity);
+          return holder->GetQueue();
+        },
+        py::return_value_policy::copy);
+
   py::class_<Scope>(m, "_Scope", R"DOC(
     Scope is an association of a name to Variable. All variables belong to Scope.
 

paddle/fluid/pybind/reader_py.cc

@@ -25,77 +25,107 @@
 namespace paddle {
 namespace pybind {
 
-class FeedReader {
+class MultiDeviceFeedReader {
+ public:
   using ResultDictList =
       std::vector<std::unordered_map<std::string, framework::LoDTensor>>;
 
- public:
-  FeedReader(std::unique_ptr<framework::ReaderHolder> reader,
-             const std::vector<std::string> &names, size_t num_places,
-             bool drop_last = true)
-      : reader_(std::move(reader)),
+  MultiDeviceFeedReader(
+      const std::shared_ptr<operators::reader::LoDTensorBlockingQueue> &queue,
+      const std::vector<std::string> &names,
+      const std::vector<platform::Place> &dst_places, bool use_double_buffer)
+      : queue_(queue),
         names_(names),
-        num_places_(num_places),
-        drop_last_(drop_last) {}
-
-  ResultDictList ReadNext() {
-    std::vector<framework::LoDTensor> tensors;
-    reader_->ReadNext(&tensors);
-    if (tensors.empty()) return ResultDictList();
+        pool_(new ::ThreadPool(dst_places.size())) {
+    std::shared_ptr<framework::ReaderBase> reader(
+        new operators::reader::PyReader(queue));
+
+    readers_.reserve(dst_places.size());
+    for (auto &p : dst_places) {
+      auto *holder = new framework::ReaderHolder();
+      if (use_double_buffer) {
+        holder->Reset(
+            framework::MakeDecoratedReader<operators::reader::BufferedReader>(
+                reader, p, 2));
+      } else {
+        if (platform::is_gpu_place(p)) {
+          PADDLE_THROW(
+              "Place cannot be CUDAPlace when use_double_buffer is False");
+        }
+        holder->Reset(reader);
+      }
+      readers_.emplace_back(holder);
+    }
 
-    PADDLE_ENFORCE(tensors.size() % names_.size() == 0,
-                   "Tensor size: %d, names size: %d", tensors.size(),
-                   names_.size());
+    futures_.resize(dst_places.size());
+    ret_.resize(dst_places.size());
+    ReadAsync();
+  }
 
-    size_t read_place_num = tensors.size() / names_.size();
+  ResultDictList ReadNext() {
+    bool success = WaitFutures();
 
-    if (drop_last_ && read_place_num != num_places_) {
-      return ResultDictList();
+    if (!success) {
+      return {};
     }
 
-    ResultDictList ret(read_place_num);
-    for (size_t i = 0; i < tensors.size(); ++i) {
-      ret[i / names_.size()].emplace(names_[i % names_.size()],
-                                     std::move(tensors[i]));
+    ResultDictList result(ret_.size());
+    for (size_t i = 0; i < ret_.size(); ++i) {
+      for (size_t j = 0; j < names_.size(); ++j) {
+        result[i].emplace(names_[j], std::move(ret_[i][j]));
+      }
     }
-    return ret;
+    ReadAsync();
+    return result;
   }
 
-  void Start() { reader_->Start(); }
+  void Reset() {
+    Shutdown();
+    Start();
 
-  void Reset() { reader_->ResetAll(); }
+    ReadAsync();
+  }
+
+  ~MultiDeviceFeedReader() {
+    queue_->Close();
+    pool_.reset();
+  }
 
  private:
-  std::unique_ptr<framework::ReaderHolder> reader_;
-  std::vector<std::string> names_;
-  size_t num_places_;
-  bool drop_last_;
-};
+  bool WaitFutures() {
+    bool success = true;
+    for (auto &f : futures_) {
+      success &= f.get();
+    }
+    return success;
+  }
 
-static std::unique_ptr<framework::ReaderHolder> CreatePyReader(
-    const std::vector<
-        std::shared_ptr<operators::reader::LoDTensorBlockingQueue>> &queues,
-    const std::vector<platform::Place> &dst_places) {
-  std::shared_ptr<framework::ReaderBase> reader;
-  if (queues.size() == 1) {
-    reader.reset(new operators::reader::PyReader(queues[0]));
-  } else {
-    reader.reset(new operators::reader::MultiQueuePyReader(queues));
+  void Shutdown() {
+    for (auto &r : readers_) r->Shutdown();
   }
-  std::vector<std::shared_ptr<framework::ReaderBase>> buffered_reader;
-  buffered_reader.reserve(dst_places.size());
-  for (auto &p : dst_places) {
-    buffered_reader.emplace_back(
-        framework::MakeDecoratedReader<operators::reader::BufferedReader>(
-            reader, p, 2));
+
+  void Start() {
+    for (auto &r : readers_) r->Start();
   }
-  reader = framework::MakeDecoratedReader<operators::reader::ComposeReader>(
-      buffered_reader);
 
-  auto *holder = new framework::ReaderHolder();
-  holder->Reset(reader);
-  return std::unique_ptr<framework::ReaderHolder>(holder);
-}
+  void ReadAsync() {
+    for (size_t i = 0; i < readers_.size(); ++i) {
+      futures_[i] = pool_->enqueue([this, i] {
+        readers_[i]->ReadNext(&ret_[i]);
+        return !ret_[i].empty();
+      });
+    }
+  }
+
+  std::vector<std::string> names_;
+  std::unique_ptr<::ThreadPool> pool_;
+
+  std::shared_ptr<operators::reader::LoDTensorBlockingQueue> queue_;
+  std::vector<std::unique_ptr<framework::ReaderHolder>> readers_;
+  std::vector<std::future<bool>> futures_;
+  std::vector<std::vector<framework::LoDTensor>> ret_;
+  bool drop_last_;
+};
 
 namespace py = pybind11;
 
@@ -108,22 +138,20 @@ void BindReader(py::module *module) {
       .def("start", &framework::ReaderHolder::Start)
       .def("reset", &framework::ReaderHolder::ResetAll);
 
-  py::class_<FeedReader>(m, "FeedReader", "")
-      .def("read_next", &FeedReader::ReadNext,
-           py::call_guard<py::gil_scoped_release>())
-      .def("start", &FeedReader::Start,
+  py::class_<MultiDeviceFeedReader>(m, "MultiDeviceFeedReader", "")
+      .def("read_next", &MultiDeviceFeedReader::ReadNext,
            py::call_guard<py::gil_scoped_release>())
-      .def("reset", &FeedReader::Reset,
+      .def("reset", &MultiDeviceFeedReader::Reset,
            py::call_guard<py::gil_scoped_release>());
 
   m.def("create_py_reader",
-        [](const std::vector<
-               std::shared_ptr<operators::reader::LoDTensorBlockingQueue>>
-               queues,
+        [](const std::shared_ptr<operators::reader::LoDTensorBlockingQueue>
+               &queue,
            const std::vector<std::string> &names,
-           const std::vector<platform::Place> &dst_places, bool drop_last) {
-          return new FeedReader(CreatePyReader(queues, dst_places), names,
-                                dst_places.size(), drop_last);
+           const std::vector<platform::Place> &dst_places,
+           bool use_double_buffer) {
+          return new MultiDeviceFeedReader(queues, names, dst_places,
+                                           use_double_buffer);
         },
         py::return_value_policy::take_ownership);
 }

python/paddle/fluid/layers/io.py

@@ -486,7 +486,8 @@ def _py_reader(capacity,
                lod_levels=None,
                name=None,
                use_double_buffer=True,
-               feed_list=None):
+               feed_list=None,
+               lock_free=False):
 
     if feed_list is not None:
         if not isinstance(feed_list, list):
@@ -526,12 +527,17 @@ def _py_reader(capacity,
         double_buffer_name = "_".join([name, "double_buffer"])
 
     var = global_scope().var(queue_name)
-    feed_queue = core.init_lod_tensor_blocking_queue(var, capacity)
+    if not lock_free:
+        feed_queue = core.init_lod_tensor_blocking_queue(var, capacity)
+    else:
+        feed_queue = core.init_lock_free_lod_tensor_blocking_queue(var,
+                                                                   capacity)
 
     startup_blk = default_startup_program().current_block()
     startup_var = startup_blk.create_var(name=reader_name)
     startup_blk.append_op(
-        type='create_py_reader',
+        type='create_py_reader'
+        if not lock_free else 'create_lock_free_py_reader',
         inputs={'blocking_queue': [queue_name]},
         outputs={'Out': [startup_var]},
         attrs={
@@ -638,7 +644,8 @@ def py_reader(capacity,
               dtypes,
               lod_levels=None,
               name=None,
-              use_double_buffer=True):
+              use_double_buffer=True,
+              lock_free=False):
     """
     Create a Python reader for data feeding in Python
 
@@ -763,7 +770,8 @@ def py_reader(capacity,
         dtypes=dtypes,
         lod_levels=lod_levels,
         name=name,
-        use_double_buffer=use_double_buffer)
+        use_double_buffer=use_double_buffer,
+        lock_free=lock_free)
 
 
 def create_py_reader_by_data(capacity,

python/paddle/fluid/reader.py

@@ -17,6 +17,7 @@ import six
 import threading
 from .framework import Program, Variable, program_guard
 from .data_feeder import DataFeeder
+import paddle.reader.decorator as decorator
 
 __all__ = ['PyReader']
 
@@ -36,8 +37,8 @@ def _convert_places(places):
     return ret
 
 
-class PyReader(object):
-    def __init__(self, feed_list, places, capacity, multi_queue=True):
+class PyReader(Reader):
+    def __init__(self, feed_list, places, capacity):
         self._tensor_reader = None
         self._thread = None
 
@@ -53,15 +54,11 @@ class PyReader(object):
 
         self._queue_capacity = capacity
 
-        queue_num = len(self._places) if multi_queue else 1
-        for _ in six.moves.range(queue_num):
-            self._queues.append(
-                core.init_lod_tensor_blocking_queue(core.Variable(),
-                                                    self._queue_capacity))
+        self.queue = core.init_lod_tensor_blocking_queue(core.Variable(),
+                                                         self._queue_capacity)
 
-        self._reader = core.create_py_reader(self._queues, self._var_names,
+        self._reader = core.create_py_reader(self._queue, self._var_names,
                                              self._places, self._drop_last)
-        self._exited = True
 
     def __call__(self):
         assert self._tensor_reader is not None, \
@@ -77,7 +74,7 @@ class PyReader(object):
 
             def next(self):
                 ret = self._reader.read_next()
-                if len(ret):
+                if ret:
                     return ret
                 else:
                     self._reset()
@@ -86,18 +83,11 @@ class PyReader(object):
         return Iterator(self)
 
     def _reset(self):
-        if not self._exited:
-            for q in self._queues:
-                q.close()
-
         if self._thread:
+            self._reader.reset()
             self._thread.join()
 
-        self._reader.reset()
-
         def __thread_main__():
-            queue_num = len(self._queues)
-            idx = 0
             for tensors in self._tensor_reader():
                 array = core.LoDTensorArray()
                 for item in tensors:
@@ -108,19 +98,13 @@ class PyReader(object):
 
                     array.append(item)
 
-                if not self._queues[idx].push(array):
+                if not self.queue.push(array):
                     break
 
-                idx = (idx + 1) % queue_num
-
-            for q in self._queues:
-                q.close()
-
-            self._exited = True
+            self.queue.close()
 
         self._thread = threading.Thread(target=__thread_main__)
         self._thread.daemon = True
-        self._exited = False
         self._thread.start()
 
     def set_numpy_reader(self, reader):

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

@@ -31,7 +31,7 @@ def random_reader():
         yield image, label
 
 
-def simple_fc_net(places, use_legacy_py_reader):
+def simple_fc_net(places, use_legacy_py_reader, lock_free=False):
     startup_prog = fluid.Program()
     main_prog = fluid.Program()
     startup_prog.random_seed = 1
@@ -55,7 +55,8 @@ def simple_fc_net(places, use_legacy_py_reader):
                 py_reader = fluid.layers.py_reader(
                     capacity=4,
                     shapes=[(-1, 784), (-1, 1)],
-                    dtypes=['float32', 'int64'])
+                    dtypes=['float32', 'int64'],
+                    lock_free=lock_free)
                 image, label = fluid.layers.read_file(py_reader)
                 py_reader.decorate_paddle_reader(reader)
 
@@ -82,7 +83,8 @@ def simple_fc_net(places, use_legacy_py_reader):
 
 class TestBase(unittest.TestCase):
     def run_main(self, use_legacy_py_reader, with_data_parallel, places):
-        with fluid.scope_guard(fluid.Scope()):
+        scope = fluid.Scope()
+        with fluid.scope_guard(scope):
             startup_prog, main_prog, py_reader, loss = simple_fc_net(
                 places, use_legacy_py_reader)
             exe = fluid.Executor(place=places[0])
@@ -94,21 +96,29 @@ class TestBase(unittest.TestCase):
                     loss_name=loss.name, places=places)
 
             step = 0
+            step_list = []
             start_t = time.time()
             if use_legacy_py_reader:
                 for _ in six.moves.range(EPOCH_NUM):
+                    step = 0
                     py_reader.start()
                     while True:
                         try:
-                            L, = exe.run(program=prog, fetch_list=[loss])
+                            L, = exe.run(program=prog,
+                                         fetch_list=[loss],
+                                         use_program_cache=True)
+                            # print('runned', step, py_reader.queue.is_closed(), py_reader.queue.size())
                             step += 1
                         except fluid.core.EOFException:
+                            # print('try to reset')
                             py_reader.reset()
+                            # print('reseted')
                             break
+                    step_list.append(step)
             else:
                 for _ in six.moves.range(EPOCH_NUM):
+                    step = 0
                     for d in py_reader():
-                        '''
                         assert len(d) == len(places)
                         for i, item in enumerate(d):
                             image = item['image']
@@ -117,18 +127,25 @@ class TestBase(unittest.TestCase):
                             assert label.shape() == [BATCH_SIZE, 1]
                             assert image._place()._equals(places[i])
                             assert label._place()._equals(places[i])
-                        '''
-                        L, = exe.run(program=prog, feed=d, fetch_list=[loss])
+                        L, = exe.run(program=prog,
+                                     feed=d,
+                                     fetch_list=[loss],
+                                     use_program_cache=True)
                         step += 1
+                    step_list.append(step)
             end_t = time.time()
-            return {"time": end_t - start_t, "step": step}
-
-    def prepare_places(self, with_data_parallel):
-        places = [[fluid.CPUPlace()], ]
-        if with_data_parallel:
-            places.append([fluid.CPUPlace()] * 2)
+            ret = {"time": end_t - start_t, "step": step_list}
+            scope._remove_from_pool()
+            return ret
+
+    def prepare_places(self, with_data_parallel, with_cpu=False, with_gpu=True):
+        places = []
+        if with_cpu:
+            places.append([fluid.CPUPlace()])
+            if with_data_parallel:
+                places.append([fluid.CPUPlace()] * 2)
 
-        if fluid.core.is_compiled_with_cuda():
+        if with_gpu and fluid.core.is_compiled_with_cuda():
             tmp = fluid.cuda_places()
             assert len(tmp) > 0, "no gpu detected"
             if with_data_parallel:
@@ -140,7 +157,10 @@ class TestBase(unittest.TestCase):
         for with_data_parallel in [True, False]:
             for p in self.prepare_places(with_data_parallel):
                 t = []
-                for use_legacy_py_reader in [False, True]:
+                for use_legacy_py_reader in [
+                        False
+                ]:  #[True, False]:  #[False, True]:
+                    print(p, use_legacy_py_reader)
                     ret = self.run_main(
                         use_legacy_py_reader=use_legacy_py_reader,
                         with_data_parallel=with_data_parallel,
@@ -148,7 +168,7 @@ class TestBase(unittest.TestCase):
                     ret['legacy'] = use_legacy_py_reader
                     ret['data_parallel'] = with_data_parallel
                     ret['places'] = p
-                    t.append(ret)
+                    t.append([ret['step'], ])  #, ret['places']])
 
                 print(t)