Method get

tensorflow/python/keras/utils/data_utils.py:886–922

Creates a generator to extract data from the queue. Skip the data if it is `None`. Yields: The next element in the queue, i.e. a tuple `(inputs, targets)` or `(inputs, targets, sample_weights)`.

(self)

            executor.apply_async(next_sample, (self.uid,)), block=True)

  def get(self):
    """Creates a generator to extract data from the queue.

    Skip the data if it is `None`.

    Yields:
        The next element in the queue, i.e. a tuple
        `(inputs, targets)` or
        `(inputs, targets, sample_weights)`.
    """
    try:
      while self.is_running():
        inputs = self.queue.get(block=True).get()
        self.queue.task_done()
        if inputs is not None:
          yield inputs
    except StopIteration:
      # Special case for finite generators
      last_ones = []
      while self.queue.qsize() > 0:
        last_ones.append(self.queue.get(block=True))
      # Wait for them to complete
      for f in last_ones:
        f.wait()
      # Keep the good ones
      last_ones = [future.get() for future in last_ones if future.successful()]
      for inputs in last_ones:
        if inputs is not None:
          yield inputs
    except Exception as e:  # pylint: disable=broad-except
      self.stop()
      if 'generator already executing' in str(e):
        raise RuntimeError(
            'Your generator is NOT thread-safe. '
            'Keras requires a thread-safe generator when '
            '`use_multiprocessing=False, workers > 1`. ')
      six.reraise(*sys.exc_info())