parameters: (self, input_tensors, **kwargs)
return_statement: return self.return_type(sparse_ops.sparse_to_dense(
          s.indices, s.shape, s.values, default_value=self.default_value))
docstring: Applies the transformation to the `transform_input`.
  
      Args:
        input_tensors: a list of Tensors representing the input to
          the Transform.
        **kwargs: Additional keyword arguments, unused here.
  
      Returns:
          A namedtuple of Tensors representing the transformed output.
docstring_summary: Applies the transformation to the `transform_input`.
docstring_tokens: Applies the transformation to the transform_input .
function: def _apply_transform(self, input_tensors, **kwargs):
      """Applies the transformation to the `transform_input`.
  
      Args:
        input_tensors: a list of Tensors representing the input to
          the Transform.
        **kwargs: Additional keyword arguments, unused here.
  
      Returns:
          A namedtuple of Tensors representing the transformed output.
      """
      s = input_tensors[0]
  
       # pylint: disable=not-callable
      return self.return_type(sparse_ops.sparse_to_dense(
          s.indices, s.shape, s.values, default_value=self.default_value))
function_tokens: def _apply_transform ( self , input_tensors , * * kwargs ) : s = input_tensors [ 0 ] # pylint: disable=not-callable return self . return_type ( sparse_ops . sparse_to_dense ( s . indices , s . shape , s . values , default_value = self . default_value ) )