Is it possible to use inspect.getcallargs to convert *args and **kwargs to a canonical kwarg representation in DL?

Given a NN class, is there something specific we need to care of when converting \*args and \*\*kwargs to a canonical kwarg representation? I ask this because in this code from Google ([https://github.com/google-research/google-research/blob/c56b47713b08c95ad427d5f93ee0dbb9ad008964/social\_rl/multiagent\_tfagents/joint\_attention/attention\_networks.py#L557](https://github.com/google-research/google-research/blob/c56b47713b08c95ad427d5f93ee0dbb9ad008964/social_rl/multiagent_tfagents/joint_attention/attention_networks.py#L557)) they use a TFDecorator-aware replacement for inspect.getcallargs, instead of using getcallargs directly. So my questions are:


\- Is it possible to use inspect.getcallargs to convert \*args and \*\*kwargs to a canonical kwarg representation?
\- If no, is there an equivalent in PyTorch? I couldn't find any, so …

canonical deeplearning dl representation