SynaptogenML is a python package based on Synaptogen, which allows to run simulated memristor arrays with PyTorch. It includes code to aid with quantization aware training, as well as memristor-based drop-ins for neural network layers such as the "nn.Linear" and "nn.Conv" modules.
SynaptogenML is not a ready-to-use framework, but contains specific modules to allow for a manual modification of existing PyTorch networks.
The examples folder contains a toy example in order to understand how SynaptogenML can be used. Please have a look at create_example_env.sh to setup a virtual environment for launching the examples.