sequence_example_decoder.py 文件源码

def decode(self, serialized_example, items=None):
    """Decodes the given serialized TF-example.
    Args:
      serialized_example: a serialized TF-example tensor.
      items: the list of items to decode. These must be a subset of the item
        keys in self._items_to_handlers. If `items` is left as None, then all
        of the items in self._items_to_handlers are decoded.
    Returns:
      the decoded items, a list of tensor.
    """
    context, sequence = tf.parse_single_sequence_example(
        serialized_example, self._context_keys_to_features,
        self._sequence_keys_to_features)

    # Merge context and sequence features
    example = {}
    example.update(context)
    example.update(sequence)

    all_features = {}
    all_features.update(self._context_keys_to_features)
    all_features.update(self._sequence_keys_to_features)

    # Reshape non-sparse elements just once:
    for k, value in all_features.items():
      if isinstance(value, tf.FixedLenFeature):
        example[k] = tf.reshape(example[k], value.shape)

    if not items:
      items = self._items_to_handlers.keys()

    outputs = []
    for item in items:
      handler = self._items_to_handlers[item]
      keys_to_tensors = {key: example[key] for key in handler.keys}
      outputs.append(handler.tensors_to_item(keys_to_tensors))
    return outputs