parameters: (return_value)
return_statement: return ops.control_dependencies(return_value)
docstring: Create a TF control dependency on the return values of a function.
  
    If the function had no return value, a no-op context is returned.
  
    Args:
      return_value: The return value to set as control dependency.
  
    Returns:
      A context manager.
docstring_summary: Create a TF control dependency on the return values of a function.
docstring_tokens: Create a TF control dependency on the return values of a function .
function: def control_dependency_on_returns(return_value):
    """Create a TF control dependency on the return values of a function.
  
    If the function had no return value, a no-op context is returned.
  
    Args:
      return_value: The return value to set as control dependency.
  
    Returns:
      A context manager.
    """
    def control_dependency_handle(t):
      if isinstance(t, tensor_array_ops.TensorArray):
        return t.flow
      return t
  
    if return_value is None:
      return contextlib.contextmanager(lambda: (yield))()
    # TODO(mdan): Filter to tensor objects.
    if not isinstance(return_value, (list, tuple)):
      return_value = (return_value,)
    return_value = tuple(control_dependency_handle(t) for t in return_value)
    return ops.control_dependencies(return_value)
function_tokens: def control_dependency_on_returns ( return_value ) : def control_dependency_handle ( t ) : if isinstance ( t , tensor_array_ops . TensorArray ) : return t . flow return t if return_value is None : return contextlib . contextmanager ( lambda : ( yield ) ) ( ) # TODO(mdan): Filter to tensor objects. if not isinstance ( return_value , ( list , tuple ) ) : return_value = ( return_value , ) return_value = tuple ( control_dependency_handle ( t ) for t in return_value ) return ops . control_dependencies ( return_value )