Model Fine-Tuner

class condensa.finetune.FineTuner(w, layer_types=None, biases=True)

Condensa model fine-tuner. Can be used for retraining compressed models while keeping all zero-valued parameters clipped to zero.

__init__(w, layer_types=None, biases=True)

Initialize self. See help(type(self)) for accurate signature.

run(epochs, lr, lr_end, momentum, weight_decay, criterion, trainloader, testloader, valloader, debugging_flags={})

Fine-tunes a compressed model. Currently only supports SGD.

Parameters

• epochs (int) – Number of epochs

• lr (float) – Learning rate

• lr_end (float) – End learning rate

• momentum (float) – Momentum

• weight_decay (float) – Weight decay

• criterion – Loss criterion

• trainloader – Training dataloader

• testloader – Test dataloader

• valloader – Validation dataloader

• debugging_flags (dict) – Debugging flags