parameters: (self, need_check)
docstring: Raises warning if output of traced function contains non-tensor type values.
docstring_summary: Raises warning if output of traced function contains non-tensor type values.
docstring_tokens: Raises warning if output of traced function contains non - tensor type values .
function: def _check_non_variable(self, need_check):
          """
          Raises warning if output of traced function contains non-tensor type values.
          """
          if need_check:
              warning_types = set()
              for var in self.__input_list:
                  if not isinstance(var, (framework.Variable, core.VarBase)):
                      warning_types.add(type(var))
              if warning_types:
                  logging_utils.warn(
                      "Output of traced function contains non-tensor type values: {}. "
                      "Currently, We don't support to update them while training and will return "
                      "what we first saw. Please try to return them as tensor.".
                      format(list(warning_types)))
function_tokens: def _check_non_variable ( self , need_check ) : if need_check : warning_types = set ( ) for var in self . __input_list : if not isinstance ( var , ( framework . Variable , core . VarBase ) ) : warning_types . add ( type ( var ) ) if warning_types : logging_utils . warn ( "Output of traced function contains non-tensor type values: {}. " "Currently, We don't support to update them while training and will return " "what we first saw. Please try to return them as tensor." . format ( list ( warning_types ) ) )