Function get_backward_walk_ops

tensorflow/python/ops/op_selector.py:237–308

Do a backward graph walk and return all the visited ops. Args: seed_ops: an iterable of operations from which the backward graph walk starts. If a list of tensors is given instead, the seed_ops are set to be the generators of those tensors. inclusive: if True the given seed_op

(seed_ops,
                          inclusive=True,
                          within_ops=None,
                          within_ops_fn=None,
                          stop_at_ts=(),
                          control_inputs=False,
                          only_differentiable=False)

def get_backward_walk_ops(seed_ops,
                          inclusive=True,
                          within_ops=None,
                          within_ops_fn=None,
                          stop_at_ts=(),
                          control_inputs=False,
                          only_differentiable=False):
  """Do a backward graph walk and return all the visited ops.

  Args:
    seed_ops: an iterable of operations from which the backward graph
      walk starts. If a list of tensors is given instead, the seed_ops are set
      to be the generators of those tensors.
    inclusive: if True the given seed_ops are also part of the resulting set.
    within_ops: an iterable of `tf.Operation` within which the search is
      restricted. If `within_ops` is `None`, the search is performed within
      the whole graph.
    within_ops_fn: if provided, a function on ops that should return True iff
      the op is within the graph traversal. This can be used along within_ops,
      in which case an op is within if it is also in within_ops.
    stop_at_ts: an iterable of tensors at which the graph walk stops.
    control_inputs: if True, control inputs will be used while moving backward.
    only_differentiable: if True, only traverse ops which are differentiable.
      This includes natively differentiable ops, or ops with custom gradients.
  Returns:
    A Python set of all the `tf.Operation` behind `seed_ops`.
  Raises:
    TypeError: if `seed_ops` or `within_ops` cannot be converted to a list of
      `tf.Operation`.
  """
  control_inputs = control_inputs and (not only_differentiable)

  if not is_iterable(seed_ops):
    seed_ops = [seed_ops]
  if not seed_ops:
    return []
  if isinstance(seed_ops[0], ops.Tensor):
    ts = make_list_of_t(seed_ops, allow_graph=False)
    seed_ops = get_generating_ops(ts)
  else:
    seed_ops = make_list_of_op(seed_ops, allow_graph=False)

  stop_at_ts = object_identity.ObjectIdentitySet(make_list_of_t(stop_at_ts))
  seed_ops = object_identity.ObjectIdentitySet(make_list_of_op(seed_ops))
  if within_ops:
    within_ops = make_list_of_op(within_ops, allow_graph=False)
    within_ops = object_identity.ObjectIdentitySet(within_ops)
    seed_ops &= within_ops

  def is_within(op):
    return (within_ops is None or op in within_ops) and (
        within_ops_fn is None or within_ops_fn(op))

  result = list(seed_ops)
  wave = set(seed_ops)
  while wave:
    new_wave = set()
    for op in wave: