nni.common.framework 源代码

# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.

__all__ = ['set_default_framework', 'get_default_framework', 'shortcut_module', 'shortcut_framework']

import importlib
import os
import sys
from typing import Optional, cast

from typing_extensions import Literal

framework_type = Literal['pytorch', 'tensorflow', 'mxnet', 'none']
"""Supported framework types."""


def framework_from_env() -> framework_type:
    framework = os.getenv(ENV_NNI_FRAMEWORK, 'pytorch')
    if framework not in framework_type.__args__:  # type: ignore
        raise ValueError(f'{framework} does not belong to {framework_type.__args__}')  # type: ignore
    return cast(framework_type, framework)

DEFAULT_FRAMEWORK = framework_from_env()

[文档]def set_default_framework(framework: framework_type) -> None: """Set default deep learning framework to simplify imports. Some functionalities in NNI (e.g., NAS / Compression), relies on an underlying DL framework. For different DL frameworks, the implementation of NNI can be very different. Thus, users need import things tailored for their own framework. For example: :: from nni.nas.xxx.pytorch import yyy rather than: :: from nni.nas.xxx import yyy By setting a default framework, shortcuts will be made. As such ``nni.nas.xxx`` will be equivalent to ``nni.nas.xxx.pytorch``. Another way to setting it is through environment variable ``NNI_FRAMEWORK``, which needs to be set before the whole process starts. If you set the framework with :func:`set_default_framework`, it should be done before all imports (except nni itself) happen, because it will affect other import's behaviors. And the behavior is undefined if the framework is "re"-set in the middle. The supported frameworks here are listed below. It doesn't mean that they are fully supported by NAS / Compression in NNI. * ``pytorch`` (default) * ``tensorflow`` * ``mxnet`` * ``none`` (to disable the shortcut-import behavior). Examples -------- >>> import nni >>> nni.set_default_framework('tensorflow') >>> # then other imports >>> from nni.nas.xxx import yyy """ # In case 'none' is written as None. if framework is None: framework = 'none' global DEFAULT_FRAMEWORK DEFAULT_FRAMEWORK = framework
[文档]def get_default_framework() -> framework_type: """Retrieve default deep learning framework set either with env variables or manually.""" return DEFAULT_FRAMEWORK
[文档]def shortcut_module(current: str, target: str, package: Optional[str] = None) -> None: """Make ``current`` module an alias of ``target`` module in ``package``.""" # Reference: https://github.com/dmlc/dgl/blob/d70a362dba8d46fd9838c79d76998a5e33f22cb7/python/dgl/nn/__init__.py#L27 mod = importlib.import_module(target, package) thismod = sys.modules[current] for api, obj in mod.__dict__.items(): setattr(thismod, api, obj)
[文档]def shortcut_framework(current: str) -> None: """Make ``current`` a shortcut of ``current.framework``.""" if get_default_framework() != 'none': # Throw ModuleNotFoundError if framework is not supported shortcut_module(current, '.' + get_default_framework(), current)