R4V: Refactoring for Verification

Installation

The following command should install the necessary python environment. Requires python3.6+ and venv to be installed on the system.

./install.sh

To load the environment, run:

. .env.d/openenv.sh

Network Info

To show information about an onnx model (i.e., its layers), use the following command.

python -m r4v info MODEL

For example, to see info about the layers in the ResNet-34 model, run:

python -m r4v info networks/resnet34/model.onnx

Distillation

The following command will run distillation using the configuration defined in the provided configuration file. The distillation process outputs a model in ONNX format.

python -m r4v distill CONFIG_FILE

The configuration file is specified in the TOML format. Some example configuration files are provided in the configs directory.

The available strategies are drop_layer, scale_layer, and scale_input. A drop_layer strategy can be specified as:

[[distillation.strategies.drop_layer]]
layer_id=[0,1]

Where layer_id specifies a list of indices, where each index is the index of the layer (in the original network) to be dropped.

A scale_layer strategy can be specified as:

[[distillation.strategies.scale_layer]]
layer_id=[0,1]
factor=0.5

Where layer_id is specified the same way as for drop_layer, and factor specifies the scale factor for the layers.

A scale_input strategy can be defined as:

[[distillation.strategies.scale_input]]
factor=[1.0, 1.0, 0.5, 0.5]

Where factor is a list of scale factors, one for each dimension of the input.