Rethrow original exception in GeneratorEnqueuer. (#8485)

* Fix randint usage in test_multiprocessing

* Rethrow original exception in GeneratorEnqueuer.

* Use multiprocessing.Manager to obtain a race-free Queue.

keras/utils/data_utils.py

@@ -11,6 +11,7 @@ import sys
 import tarfile
 import threading
 import time
+import traceback
 import zipfile
 from abc import abstractmethod
 from multiprocessing.pool import ThreadPool
@@ -553,7 +554,7 @@ class OrderedEnqueuer(SequenceEnqueuer):
                     yield inputs
         except Exception as e:
             self.stop()
-            raise StopIteration(e)
+            six.raise_from(StopIteration(e), e)
 
     def _send_sequence(self):
         """Send current Sequence to all workers."""
@@ -614,6 +615,7 @@ class GeneratorEnqueuer(SequenceEnqueuer):
         self._use_multiprocessing = use_multiprocessing
         self._threads = []
         self._stop_event = None
+        self._manager = None
         self.queue = None
         self.seed = seed
 
@@ -631,18 +633,27 @@ class GeneratorEnqueuer(SequenceEnqueuer):
                 try:
                     if self._use_multiprocessing or self.queue.qsize() < max_queue_size:
                         generator_output = next(self._generator)
-                        self.queue.put(generator_output)
+                        self.queue.put((True, generator_output))
                     else:
                         time.sleep(self.wait_time)
                 except StopIteration:
                     break
-                except Exception:
+                except Exception as e:
+                    # Can't pick tracebacks.
+                    # As a compromise, print the traceback and pickle None instead.
+                    if self._use_multiprocessing:
+                        traceback.print_exc()
+                        setattr(e, '__traceback__', None)
+                    elif not hasattr(e, '__traceback__'):
+                        setattr(e, '__traceback__', sys.exc_info()[2])
+                    self.queue.put((False, e))
                     self._stop_event.set()
-                    raise
+                    break
 
         try:
             if self._use_multiprocessing:
-                self.queue = multiprocessing.Queue(maxsize=max_queue_size)
+                self._manager = multiprocessing.Manager()
+                self.queue = self._manager.Queue(maxsize=max_queue_size)
                 self._stop_event = multiprocessing.Event()
             else:
                 self.queue = queue.Queue()
@@ -686,9 +697,8 @@ class GeneratorEnqueuer(SequenceEnqueuer):
                 else:
                     thread.join(timeout)
 
-        if self._use_multiprocessing:
-            if self.queue is not None:
-                self.queue.close()
+        if self._manager:
+            self._manager.shutdown()
 
         self._threads = []
         self._stop_event = None
@@ -704,12 +714,22 @@ class GeneratorEnqueuer(SequenceEnqueuer):
         """
         while self.is_running():
             if not self.queue.empty():
-                inputs = self.queue.get()
-                if inputs is not None:
-                    yield inputs
+                success, value = self.queue.get()
+                # Rethrow any exceptions found in the queue
+                if not success:
+                    six.reraise(value.__class__, value, value.__traceback__)
+                # Yield regular values
+                if value is not None:
+                    yield value
             else:
                 all_finished = all([not thread.is_alive() for thread in self._threads])
                 if all_finished and self.queue.empty():
                     raise StopIteration()
                 else:
                     time.sleep(self.wait_time)
+
+        # Make sure to rethrow the first exception in the queue, if any
+        while not self.queue.empty():
+            success, value = self.queue.get()
+            if not success:
+                six.reraise(value.__class__, value, value.__traceback__)

tests/keras/utils/data_utils_test.py

@@ -182,7 +182,7 @@ def test_generator_enqueuer_fail_threads():
         FaultSequence()), use_multiprocessing=False)
     enqueuer.start(3, 10)
     gen_output = enqueuer.get()
-    with pytest.raises(StopIteration):
+    with pytest.raises(IndexError):
         next(gen_output)
 
 
@@ -191,7 +191,7 @@ def test_generator_enqueuer_fail_processes():
         FaultSequence()), use_multiprocessing=True)
     enqueuer.start(3, 10)
     gen_output = enqueuer.get()
-    with pytest.raises(StopIteration):
+    with pytest.raises(IndexError):
         next(gen_output)
 
 

tests/test_multiprocessing.py

@@ -232,7 +232,7 @@ def test_multiprocessing_fit_error():
         """Raises an exception after a few good batches"""
         for i in range(good_batches):
             yield (np.random.randint(batch_size, 256, (50, 2)),
-                   np.random.randint(batch_size, 2, 50))
+                   np.random.randint(batch_size, 12, 50))
         raise RuntimeError
 
     model = Sequential()
@@ -241,13 +241,13 @@ def test_multiprocessing_fit_error():
 
     samples = batch_size * (good_batches + 1)
 
-    with pytest.raises(StopIteration):
+    with pytest.raises(RuntimeError):
         model.fit_generator(
             custom_generator(), samples, 1,
             workers=4, use_multiprocessing=True,
         )
 
-    with pytest.raises(StopIteration):
+    with pytest.raises(RuntimeError):
         model.fit_generator(
             custom_generator(), samples, 1,
             use_multiprocessing=False,
@@ -258,25 +258,26 @@ def test_multiprocessing_fit_error():
 def test_multiprocessing_evaluate_error():
     batch_size = 10
     good_batches = 3
+    workers = 4
 
     def custom_generator():
         """Raises an exception after a few good batches"""
         for i in range(good_batches):
             yield (np.random.randint(batch_size, 256, (50, 2)),
-                   np.random.randint(batch_size, 2, 50))
+                   np.random.randint(batch_size, 12, 50))
         raise RuntimeError
 
     model = Sequential()
     model.add(Dense(1, input_shape=(2, )))
     model.compile(loss='mse', optimizer='adadelta')
 
-    with pytest.raises(StopIteration):
+    with pytest.raises(RuntimeError):
         model.evaluate_generator(
-            custom_generator(), good_batches + 1, 1,
-            workers=4, use_multiprocessing=True,
+            custom_generator(), good_batches * workers + 1, 1,
+            workers=workers, use_multiprocessing=True,
         )
 
-    with pytest.raises(StopIteration):
+    with pytest.raises(RuntimeError):
         model.evaluate_generator(
             custom_generator(), good_batches + 1, 1,
             use_multiprocessing=False,
@@ -299,13 +300,13 @@ def test_multiprocessing_predict_error():
     model.add(Dense(1, input_shape=(5,)))
     model.compile(loss='mse', optimizer='adadelta')
 
-    with pytest.raises(StopIteration):
+    with pytest.raises(RuntimeError):
         model.predict_generator(
             custom_generator(), good_batches * workers + 1, 1,
             workers=workers, use_multiprocessing=True,
         )
 
-    with pytest.raises(StopIteration):
+    with pytest.raises(RuntimeError):
         model.predict_generator(
             custom_generator(), good_batches + 1, 1,
             use_multiprocessing=False,