Ejemplo n.º 1
0
  def _build(self, inputs):
    """Connects the MergeDims module into the graph.

    Args:
      inputs: Tensor or a nested list of Tensors to merge. Its rank must be
          greater than or equal to `start` + `size`.

    Returns:
      The merged Tensor or a nested list of merged Tensors.

    Raises:
      ValueError: If any of the `inputs` tensors has insufficient rank.
    """
    if nest.is_sequence(inputs):
      merged_tensors = [self._merge(tensor) for tensor in nest.flatten(inputs)]
      return nest.pack_sequence_as(inputs, merged_tensors)

    # inputs is a single tf.Tensor
    return self._merge(inputs)
Ejemplo n.º 2
0
  def _build(self, inputs):
    """Connects the MergeDims module into the graph.

    Args:
      inputs: Tensor or a nested list of Tensors to merge. Its rank must be
          greater than or equal to `start` + `size`.

    Returns:
      The merged Tensor or a nested list of merged Tensors.

    Raises:
      ValueError: If any of the `inputs` tensors has insufficient rank.
    """
    if nest.is_sequence(inputs):
      merged_tensors = [self._merge(tensor) for tensor in nest.flatten(inputs)]
      return nest.pack_sequence_as(inputs, merged_tensors)

    # inputs is a single tf.Tensor
    return self._merge(inputs)