Exemplo n.º 1
0
  def _remap_default(self, remove_input_map=True, remove_output_map=True):
    """Remap in the place the inputs and/or outputs to the default mapping.

    Args:
      remove_input_map: if True the input map is reset to the default one.
      remove_output_map: if True the output map is reset to the default one.
    """
    if not remove_input_map and not remove_output_map:
      return

    # Compute inside and outside tensor
    inputs, outputs, _ = select.compute_boundary_ts(self._ops)
    if remove_input_map:
      self._input_ts = list(inputs) + self._passthrough_ts
    if remove_output_map:
      self._output_ts = list(outputs) + self._passthrough_ts
Exemplo n.º 2
0
    def __init__(self, inside_ops=(), passthrough_ts=()):
        """Create a subgraph containing the given ops and the "passthrough" tensors.

    Args:
      inside_ops: an object convertible to a list of `gde.Node`. This list
        defines all the operations in the subgraph.
      passthrough_ts: an object convertible to a list of `gde.Tensor`. This list
        define all the "passthrough" tensors. A passthrough tensor is a tensor
        which goes directly from the input of the subgraph to it output, without
        any intermediate operations. All the non passthrough tensors are
        silently ignored.
    Raises:
      TypeError: if inside_ops cannot be converted to a list of `gde.Node`
        or if `passthrough_ts` cannot be converted to a list of `gde.Tensor`.
    """

        inside_ops = util.make_list_of_op(inside_ops)
        passthrough_ts = util.make_list_of_t(passthrough_ts)
        ops_and_ts = inside_ops + passthrough_ts
        if ops_and_ts:
            self._graph = util.get_unique_graph(ops_and_ts)
            self._ops = inside_ops

            # Compute inside and outside tensor
            inputs, outputs, insides = select.compute_boundary_ts(inside_ops)

            # Compute passthrough tensors, silently ignoring the non-passthrough ones.
            all_tensors = frozenset(inputs + outputs + list(insides))
            self._passthrough_ts = [
                t for t in passthrough_ts if t not in all_tensors
            ]

            # Set inputs and outputs.
            self._input_ts = inputs + self._passthrough_ts
            self._output_ts = outputs + self._passthrough_ts
        else:
            self._graph = None
            self._passthrough_ts = []
            self._input_ts = []
            self._output_ts = []
            self._ops = []