Initial values for the hidden/cell state for LSTM and GRU models in Pytorch

This PR addresses https://github.com/fastmachinelearning/hls4ml/issues/1074 and implements the passing of initial values for the hidden and cell states in GRU and LSTM models, which is supported in pytorch. This first version implements this only for the pytorch parser, but it should be able to be extended it for keras and other parsers.

I have tested this for Vivado, Vitis, and Quartus. I don't have access to Catapult or oneAPI at the moment, so I haven't implemented this fort those backends.

Note that this currently only works in io_parallel. In io_stream I was having some conceptual issues and was unsure if I should treat these initial states are streamed inputs or not. Might be good enough for now and I can revisit io_stream if there are any suggestions how to tackle that.

Type of change

[x] Bug fix (non-breaking change that fixes an issue)
[x] New feature (non-breaking change which adds functionality)

Tests

Tested in both standalone scripts and also the pytests to ensure that model parsing and evaluation work with and without passing these optional tensors.

Checklist

[x] I have read the guidelines for contributing.
[x] I have commented my code, particularly in hard-to-understand areas.
[x] I have made corresponding changes to the documentation.
[x] My changes generate no new warnings.
[x] I have installed and run pre-commit on the files I edited or added.
[x] I have added tests that prove my fix is effective or that my feature works.

fastmachinelearning / hls4ml