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.
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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.
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description
: str¶
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name
: str¶
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props
: List[sparseml.sparsification.info.ModifierPropInfo]¶
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warnings
: Optional[List[str]]¶
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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.
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description
: str¶
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name
: str¶
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restrictions
: Optional[List[Any]]¶
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type_
: str¶
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class
sparseml.sparsification.info.
ModifierType
(value)[source]¶ Bases:
enum.Enum
Types of modifiers for grouping what functionality a Modifier falls under.
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act_sparsity
= 'act_sparsity'¶
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general
= 'general'¶
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misc
= 'misc'¶
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pruning
= 'pruning'¶
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quantization
= 'quantization'¶
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training
= 'training'¶
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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.
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modifiers
: List[sparseml.sparsification.info.ModifierInfo]¶
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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]
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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
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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.
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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
Module contents¶
Functionality related to applying, describing, and supporting sparsification algorithms to models within in ML frameworks.