def _check_non_variable(self, need_check):
    '\n        Raises warning if output of traced function contains non-tensor type values.\n        '
    if need_check:
        warning_types = set()
        for var in self.tolist():
            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)))
Raises warning if output of traced function contains non-tensor type values.
def _check_non_variable(self, need_check):
    '\n        \n        '
    if need_check:
        warning_types = set()
        for var in self.tolist():
            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)))