parameters: (self, columns_to_tensors)
docstring: Apply transformation and inserts it into columns_to_tensors.
  
      Args:
        columns_to_tensors: A mapping from feature columns to tensors. 'string'
          key means a base feature (not-transformed). It can have _FeatureColumn
          as a key too. That means that _FeatureColumn is already transformed.
docstring_summary: Apply transformation and inserts it into columns_to_tensors.
docstring_tokens: Apply transformation and inserts it into columns_to_tensors .
function: def insert_transformed_feature(self, columns_to_tensors):
      """Apply transformation and inserts it into columns_to_tensors.
  
      Args:
        columns_to_tensors: A mapping from feature columns to tensors. 'string'
          key means a base feature (not-transformed). It can have _FeatureColumn
          as a key too. That means that _FeatureColumn is already transformed.
      """
      raise NotImplementedError("Transform is not implemented for {}.".format(
          self))
function_tokens: def insert_transformed_feature ( self , columns_to_tensors ) : raise NotImplementedError ( "Transform is not implemented for {}." . format ( self ) )