Function with_dependencies

tensorflow/python/ops/control_flow_ops.py:2802–2837

Produces the content of `output_tensor` only after `dependencies`. In some cases, a user may want the output of an operation to be consumed externally only after some other dependencies have run first. This function ensures returns `output_tensor`, but only after all operations in `dependen

(dependencies, output_tensor, name=None)

def with_dependencies(dependencies, output_tensor, name=None):
  """Produces the content of `output_tensor` only after `dependencies`.

  In some cases, a user may want the output of an operation to be
  consumed externally only after some other dependencies have run
  first. This function ensures returns `output_tensor`, but only after all
  operations in `dependencies` have run. Note that this means that there is
  no guarantee that `output_tensor` will be evaluated after any `dependencies`
  have run.

  See also `tf.tuple` and `tf.group`.

  Args:
    dependencies: Iterable of operations to run before this op finishes.
    output_tensor: A `Tensor` or `IndexedSlices` that will be returned.
    name: (Optional) A name for this operation.

  Returns:
    Same as `output_tensor`.

  Raises:
    TypeError: if `output_tensor` is not a `Tensor` or `IndexedSlices`.
  """
  if context.executing_eagerly():
    return output_tensor
  with ops.name_scope(name, "control_dependency",
                      list(dependencies) + [output_tensor]) as name:
    with ops.colocate_with(output_tensor):
      with ops.control_dependencies(dependencies):
        output_tensor = ops.convert_to_tensor_or_composite(output_tensor)
        if isinstance(output_tensor, ops.Tensor):
          return _Identity(output_tensor, name=name)
        else:
          return ops.IndexedSlices(
              _Identity(output_tensor.values, name=name), output_tensor.indices,
              output_tensor.dense_shape)


def _GroupControlDeps(dev, deps, name=None):