neural_compressor.compression.pruner.pruners.retrain_free

Retrain free pruner.

Classes

PytorchRetrainFreePruner

Pruning Pruner.

Module Contents

class neural_compressor.compression.pruner.pruners.retrain_free.PytorchRetrainFreePruner(config, modules)

Pruning Pruner. The retrain_free pruner_class is derived from BasePruner. This pruner references the mask search and mask rearrangement strategies in fast retraining free. RetrainFreePruner supports one-shot pruning (same effect as fast retraining free) and iterative pruning. Please refer to A Fast Post-Training Pruning Framework for Transformers

(https://arxiv.org/abs/2204.09656)

1. Defines pruning functions called at step begin/end, before/after optimize and epoch begin/end.

2. Defines the pruning criterion and fixed weight parameters.

3. Obtain block masks and its grads.

4. Rearrange block masks.

Parameters:

• modules – A dict {“module_name”: Tensor} that stores the pruning modules’ weights.

• config – A config dict object that contains the pruner information.

pattern

A Pattern object that defines pruning weights’ arrangements within space.

criterion

A Criterion Object that defines which weights are to be pruned

scheduler

A Scheduler object that defines how the model’s sparsity changes as training/pruning proceeds.

reg

A Reg object that defines regulization terms.