neural_compressor.compression.pruner.schedulers

Scheduler module.

Classes

PruningScheduler	Pruning Scheduler.
OneshotScheduler	Pruning Scheduler.
IterativeScheduler	Pruning Scheduler.

Functions

register_scheduler(name)	Class decorator used to register a Scheduler subclass to the registry.
get_scheduler(config)	Get registered scheduler class.

Module Contents

neural_compressor.compression.pruner.schedulers.register_scheduler(name)

Class decorator used to register a Scheduler subclass to the registry.

Decorator function used before a Scheduler subclass. Make sure that the Scheduler class decorated by this function can be registered in SCHEDULERS.

Parameters:

• cls (class) – The class of register.

• name – A string that defines the scheduler type.

Returns:

The class of register.

Return type:

cls

neural_compressor.compression.pruner.schedulers.get_scheduler(config)

Get registered scheduler class.

Get a scheduler object from SCHEDULERS.

Parameters:

config – A config dict object that contains the scheduler information.

Returns:

A Scheduler object.

class neural_compressor.compression.pruner.schedulers.PruningScheduler(config)

Pruning Scheduler.

The class which defines a sparsity changing process during pruning. Mainly contains two types:

1. iterative scheduler. Prune the model from dense to target sparsity gradually.

2. one-shot scheduler. Prune the model in a single step and reach the target sparsity.

Parameters:

config – A config dict object that contains the scheduler information.

config

A config dict object that contains the scheduler information.

class neural_compressor.compression.pruner.schedulers.OneshotScheduler(config)

Pruning Scheduler.

A Scheduler class derived from Scheduler. Prune the model to target sparsity once.

Parameters:

config – A config dict object that contains the scheduler information.

Inherit from parent class Scheduler.

class neural_compressor.compression.pruner.schedulers.IterativeScheduler(config)

Pruning Scheduler.

A Scheduler class derived from Scheduler. Prune the model from dense to target sparsity in several steps.

Parameters:

config – A config dict object that contains the scheduler information.

Inherit from parent class Scheduler.