Vprtempo

- Easier installation with conda-forge packaging, can now simply install with conda install vprtempo -c conda-forge
- Added options to plot metrics, similarity matrices, and additionally output precision and recall in json file
- Modified model names so that they're clearer, also rather than model names simply being network architecture dims more information such as the datasets themselves included so multiple models with the same architecture can be trained across different datsets without overwriting them.

- Modified codebase into a singular module
- Easing module import (e.g. for blitnet, metrics, etc)
- Needed for conda-forge deployment

- Minor fixes to PyPi packaging

- Full integration of VPRTempo into torch.nn architecture
- Quantization Aware Training (QAT) enabled to train weights in int8 space
- Addition of tutorials in Jupyter Notebooks to learn how to use VPRTempo as well as explain the computational logic
- Simplification of weight operations, reducing to a single weight tensor - allowing positive and negative connections to change sign during training
- Easier dependency installation with PyPi/pip
- And more!