sparseml.sparsification package

Submodules

sparseml.sparsification.info module

Functionality related to describing availability and information of sparsification algorithms to models within in the ML frameworks.

The file is executable and will get the sparsification info for a given framework:

Compile the available setup and information for the sparsification of a model in a given framework.

positional arguments:

framework the ML framework or path to a framework file to load the: sparsification info for

optional arguments:

-h, --help: show this help message and exit
--path PATH: A full file path to save the sparsification info to. If not supplied, will print out the sparsification info to the console.

class sparseml.sparsification.info.ModifierInfo(*, name: str, description: str, type_: sparseml.sparsification.info.ModifierType = <ModifierType.misc: 'misc'>, props: List[sparseml.sparsification.info.ModifierPropInfo] = [], warnings: List[str] = None)[source]

Bases: pydantic.main.BaseModel

Class for storing information and associated metadata for a given Modifier. Extends pydantics BaseModel class for serialization to and from json in addition to proper type checking on construction.

description: str

name: str

props: List[sparseml.sparsification.info.ModifierPropInfo]

type_: sparseml.sparsification.info.ModifierType

warnings: Optional[List[str]]

class sparseml.sparsification.info.ModifierPropInfo(*, name: str, description: str, type_: str, restrictions: List[Any] = None)[source]

Bases: pydantic.main.BaseModel

Class for storing information and associated metadata for a property on a given Modifier. Extends pydantics BaseModel class for serialization to and from json in addition to proper type checking on construction.

description: str

name: str

restrictions: Optional[List[Any]]

type_: str

class sparseml.sparsification.info.ModifierType(value)[source]

Bases: enum.Enum

Types of modifiers for grouping what functionality a Modifier falls under.

act_sparsity = 'act_sparsity'

general = 'general'

misc = 'misc'

pruning = 'pruning'

quantization = 'quantization'

training = 'training'

class sparseml.sparsification.info.SparsificationInfo(*, modifiers: List[sparseml.sparsification.info.ModifierInfo] = [])[source]

Bases: pydantic.main.BaseModel

Class for storing the information for sparsifying in a given framework. Extends pydantics BaseModel class for serialization to and from json in addition to proper type checking on construction.

modifiers: List[sparseml.sparsification.info.ModifierInfo]

type_modifiers(type_: sparseml.sparsification.info.ModifierType) → List[sparseml.sparsification.info.ModifierInfo][source]: Get the contained Modifiers for a specific ModifierType. :param type_: The ModifierType to filter the returned list of Modifiers by. :type type_: ModifierType :return: The filtered list of Modifiers that match the given type_. :rtype: List[ModifierInfo]

sparseml.sparsification.info.load_sparsification_info(load: str) → sparseml.sparsification.info.SparsificationInfo [source]

Load the sparsification info from a file or raw json. If load exists as a path, will read from the file and use that. Otherwise will try to parse the input as a raw json str.

Parameters: load (str) – Either a file path to a json file or a raw json string.
Returns: The loaded sparsification info.
Return type: SparsificationInfo

sparseml.sparsification.info.save_sparsification_info(framework: Any, path: Optional[str] = None)[source]

Save the sparsification info for a given framework. If path is provided, will save to a json file at that path. If path is not provided, will print out the info.

Parameters

framework (Any) – The item to detect the ML framework for. See detect_framework() for more information.
path (Optional[str]) – The path, if any, to save the info to in json format. If not provided will print out the info.

sparseml.sparsification.info.sparsification_info(framework: Any) → sparseml.sparsification.info.SparsificationInfo [source]

Get the available setup for sparsifying model in the given framework.

Parameters: framework (Any) – The item to detect the ML framework for. See detect_framework() for more information.
Returns: The sparsification info for the given framework
Return type: SparsificationInfo

Module contents

Functionality related to applying, describing, and supporting sparsification algorithms to models within in ML frameworks.