de naming conventions used here, please see the
    :ref:`relevant subheading <about-node-names>` in the
    `documentation <https://pytorch.org/vision/stable/feature_extraction.html>`_.

    Args:
        model (nn.Module): model for which we'd like to print node names
        tracer_kwargs (dict, optional): a dictionary of keyword arguments for
            ``NodePathTracer`` (they are eventually passed onto
            `torch.fx.Tracer <https://pytorch.org/docs/stable/fx.html#torch.fx.Tracer>`_).
            By default, it will be set to wrap and make leaf nodes all torchvision ops:
            {"autowrap_modules": (math, torchvision.ops,),"leaf_modules": _get_leaf_modules_for_ops(),}
            WARNING: In case the user provides tracer_kwargs, above default arguments will be appended to the user
            provided dictionary.

        suppress_diff_warning (bool, optional): whether to suppress a warning
            when there are discrepancies between the train and eval version of
            the graph. Defaults to False.

    Returns:
        tuple(list, list): a list of node names from tracing the model in
        train mode, and another from tracing the model in eval mode.

    Examples::

        >>> model = torchvision.models.resnet18()
        >>> train_nodes, eval_nodes = get_graph_node_names(model)
    Nr