Merge branch 'pytorch:master' into master

torch_xla/distributed/parallel_loader.py

@@ -95,12 +95,14 @@ def __init__(self,
     self._done = False
     self._queues = dict()
     self._input_sharding = input_sharding
+    self._threads = []
     for device in self._devices:
       self._queues[device] = PerDeviceQueue(device, loader_prefetch_size,
                                             device_prefetch_size)
     thread = threading.Thread(target=self._loader_worker)
     thread.daemon = True
     thread.start()
+    self._threads.append(thread)
     for dqueue in self._queues.values():
       for i in range(host_to_device_transfer_threads):
         thread = threading.Thread(
@@ -111,6 +113,7 @@ def __init__(self,
             ))
         thread.daemon = True
         thread.start()
+        self._threads.append(thread)
 
   def per_device_loader(self, device):
     """Retrieves the loader iterator object for the given device.
@@ -139,6 +142,9 @@ def close(self):
       dqueue.queue.close()
       dqueue.loader_queue.close()
 
+    for thread in self._threads:
+      thread.join()
+
   @property
   def batches_per_execution(self):
     return self._batches_per_execution
@@ -147,18 +153,21 @@ def _loader_worker(self):
     queues = list(self._queues.values())
     data_iter = enumerate(self._loader)
     batch = []
-    while not self._done:
-      try:
-        _, data = next(data_iter)
-      except StopIteration:
-        break
-      batch.append(data)
-      if len(batch) == len(self._devices):
-        for queue_no, device_batch in enumerate(batch):
-          queues[queue_no].loader_queue.put(device_batch)
-        batch = []
-    for dqueue in queues:
-      dqueue.loader_queue.close_write()
+
+    try:
+      while not self._done:
+        try:
+          _, data = next(data_iter)
+        except StopIteration:
+          break
+        batch.append(data)
+        if len(batch) == len(self._devices):
+          for queue_no, device_batch in enumerate(batch):
+            queues[queue_no].loader_queue.put(device_batch)
+          batch = []
+    finally:
+      for dqueue in queues:
+        dqueue.loader_queue.close_write()
 
   def _get_batch(self, dqueue):
     batch = []
@@ -171,16 +180,21 @@ def _get_batch(self, dqueue):
 
   def _worker(self, dqueue, host_to_device_transfer_threads):
     device = torch.device(dqueue.device)
-    while True:
-      batch = self._get_batch(dqueue)
-      if not batch:
-        break
-      batch = xm.send_cpu_data_to_device(batch, device, self._input_sharding)
-      for data in batch:
-        dqueue.queue.put(data)
-    close_queue_count = next(dqueue.close_queue_count)
-    if close_queue_count == host_to_device_transfer_threads - 1:
-      dqueue.queue.close_write()
+
+    try:
+      while True:
+        batch = self._get_batch(dqueue)
+        if not batch:
+          break
+        with torch.no_grad():
+          batch = xm.send_cpu_data_to_device(batch, device,
+                                             self._input_sharding)
+        for data in batch:
+          dqueue.queue.put(data)
+    finally:
+      close_queue_count = next(dqueue.close_queue_count)
+      if close_queue_count == host_to_device_transfer_threads - 1:
+        dqueue.queue.close_write()
 
 
 class MpDeviceLoader(object):
@@ -206,11 +220,15 @@ def __init__(self, loader, device, **kwargs):
     self._loader = loader
     self._device = device
     self._parallel_loader_kwargs = kwargs
+    self._parallel_loader = None
 
   def __iter__(self):
-    parallel_loader = ParallelLoader(self._loader, [self._device],
-                                     **self._parallel_loader_kwargs)
-    return parallel_loader.per_device_loader(self._device)
+    if self._parallel_loader is not None:
+      self._parallel_loader.close()
+      self._parallel_loader = None
+    self._parallel_loader = ParallelLoader(self._loader, [self._device],
+                                           **self._parallel_loader_kwargs)
+    return self._parallel_loader.per_device_loader(self._device)
 
   def __len__(self):
     return len(self._loader)