Usage

How to Use

To add custom models and/or pretrained weights: 1. add your model to src/othermodels/ 2. add pt files to src/othermodels/state_dicts 3. modify getNetwork() in src/util.py to correspond to the dataset and model name. 4. also add the appropriate import in /src/util.py

Your model.py file in src/othermodels/ should have a few general attributes: 1. A codeblock similar to easily find your model versions

__all__ = [
    "baseline",
    "v1",
    "v2",
]

  1. A separate function for each name in Step 1, which instantiates your model and extracts the correct model parameters from /src/othermodels/state_dicts/. As an example, check out: https://github.com/huyvnphan/PyTorch_CIFAR10/blob/master/cifar10_models/resnet.py

Model accuracy

In order to evaluate the accuracy of your model, you can directly use the accuracy_profile script, which will run the preprocess, profile, and split_data python scripts from src/

./scripts/accuracy_profile.sh NETWORK BATCH FORMAT BITWIDTH RADIX

Model Resiliency

In order to evaluate the resiliency of your model, you should run the end_to_end script, which will run all the python scripts from src/ in order (preprocess, profile, split_data, injections and postprocess)

./scripts/end_to_end.sh NETWORK DATASET BATCH FORMAT BITWIDTH RADIX INJECTIONS_LOC

Domain Space Exploration

In order to conduct Domain Space Exploration, you should run the script sweep.sh which will run the python file sweep_num_formats.py

./scripts/sweep.sh