neural_compressor.objective

The objectives supported by neural_compressor, which is driven by accuracy.

To support new objective, developers just need implement a new subclass in this file.

Module Contents

Classes

Objective	The base class for precise benchmark supported by neural_compressor.
Accuracy	Configuration Accuracy class.
Performance	Configuration Performance class.
Footprint	Configuration Footprint class.
ModelSize	Configuration ModelSize class.
MultiObjective	The base class for multiple benchmarks supported by neural_compressor.

Functions

objective_registry(cls)	The class decorator used to register all Objective subclasses.
objective_custom_registry(name, obj_cls)	Register a customized objective.

neural_compressor.objective.objective_registry(cls)

The class decorator used to register all Objective subclasses.

Parameters:

cls (object) – The class of register.

Returns:

The class of register.

Return type:

cls (object)

neural_compressor.objective.objective_custom_registry(name, obj_cls)

Register a customized objective.

Example:

from eural_compressor.objective import objective_custom_registry

objective_cls = type(user_objective)
name = user_objective.__class__.__name__
objective_cfg = name if deep_get(self.conf.usr_cfg, "tuning.objective") else [name]
deep_set(self.conf.usr_cfg, user_obj_cfg, objective_cfg)
self.conf.usr_cfg = DotDict(self.conf.usr_cfg)
objective_custom_registry(name, objective_cls)

class neural_compressor.objective.Objective

The base class for precise benchmark supported by neural_compressor.

With built-in objectives, users can compress models with different objectives easily. In special cases, users can also register their own objective classes.

class neural_compressor.objective.Accuracy

Configuration Accuracy class.

Evaluate the accuracy.

class neural_compressor.objective.Performance

Configuration Performance class.

Evaluate the inference time.

class neural_compressor.objective.Footprint

Configuration Footprint class.

Evaluate the peak size of memory blocks during inference.

class neural_compressor.objective.ModelSize

Configuration ModelSize class.

Evaluate the model size.

class neural_compressor.objective.MultiObjective(objectives, accuracy_criterion, metric_criterion=[True], metric_weight=None, obj_criterion=None, obj_weight=None, is_measure=False)

The base class for multiple benchmarks supported by neural_compressor.

Example:

from neural_compressor.objective import MultiObjective
obj = MultiObjective(
    objectives=['accuracy', 'modelsize', 'performance'],
    accuracy_criterion={'relative': 0.1},
    obj_criterion=[True, False, False],
    obj_weight=[0.7, 0.2, 0.1])