parameters: (registered_name, operation, ignore_dtype=None)
docstring: Creates a `Transform` that wraps a unary tensorflow operation.
  
    If `registered_name` is specified, the `Transform` is registered as a member
    function of `Series`.
  
    Args:
      registered_name: the name of the member function of `Series` corresponding
        to the returned `Transform`.
      operation: a unary TensorFlow operation.
      ignore_dtype: an optional dtype, not used here but needed for symmetry with
        test.
docstring_summary: Creates a `Transform` that wraps a unary tensorflow operation.
docstring_tokens: Creates a Transform that wraps a unary tensorflow operation .
function: def register_unary_op(registered_name, operation, ignore_dtype=None):
    """Creates a `Transform` that wraps a unary tensorflow operation.
  
    If `registered_name` is specified, the `Transform` is registered as a member
    function of `Series`.
  
    Args:
      registered_name: the name of the member function of `Series` corresponding
        to the returned `Transform`.
      operation: a unary TensorFlow operation.
      ignore_dtype: an optional dtype, not used here but needed for symmetry with
        test.
    """
  
    doc = DOC_FORMAT_STRING.format(operation.__name__, operation.__doc__)
  
    @property
    def name(self):
      return operation.__name__
  
    @property
    def input_valency(self):
      return 1
  
    @property
    def _output_names(self):
      return "output"
  
    def _apply_transform(self, input_tensors, **kwargs):
      input_tensor = input_tensors[0]
      if isinstance(input_tensor, ops.SparseTensor):
        result = ops.SparseTensor(input_tensor.indices,
                                  operation(input_tensor.values),
                                  input_tensor.shape)
      else:
        result = operation(input_tensor)
      # pylint: disable=not-callable
      return self.return_type(result)
  
    cls = type(operation.__name__,
               (transform.Transform,),
               {"name": name,
                "__doc__": doc,
                "input_valency": input_valency,
                "_output_names": _output_names,
                "_apply_transform": _apply_transform})
  
    series.Series.register_unary_op(registered_name)(cls)
function_tokens: def register_unary_op ( registered_name , operation , ignore_dtype = None ) : doc = DOC_FORMAT_STRING . format ( operation . __name__ , operation . __doc__ ) @ property def name ( self ) : return operation . __name__ @ property def input_valency ( self ) : return 1 @ property def _output_names ( self ) : return "output" def _apply_transform ( self , input_tensors , * * kwargs ) : input_tensor = input_tensors [ 0 ] if isinstance ( input_tensor , ops . SparseTensor ) : result = ops . SparseTensor ( input_tensor . indices , operation ( input_tensor . values ) , input_tensor . shape ) else : result = operation ( input_tensor ) # pylint: disable=not-callable return self . return_type ( result ) cls = type ( operation . __name__ , ( transform . Transform , ) , { "name" : name , "__doc__" : doc , "input_valency" : input_valency , "_output_names" : _output_names , "_apply_transform" : _apply_transform } ) series . Series . register_unary_op ( registered_name ) ( cls )