Source code for sparseml.pytorch.base

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#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#    http://www.apache.org/licenses/LICENSE-2.0
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import functools
from typing import Optional

from sparseml.base import check_version


try:
    import torch

    torch_err = None
except Exception as err:
    torch = object()  # TODO: populate with fake object for necessary imports
    torch_err = err

try:
    import torchvision

    torchvision_err = None
except Exception as err:
    torchvision = object()  # TODO: populate with fake object for necessary imports
    torchvision_err = err


__all__ = [
    "torch",
    "torch_err",
    "torchvision",
    "torchvision_err",
    "check_torch_install",
    "check_torchvision_install",
    "require_torch",
    "require_torchvision",
]


_TORCH_MIN_VERSION = "1.0.0"
_TORCH_MAX_VERSION = "1.9.100"  # set bug to 100 to support all future 1.9.X  versions


[docs]def check_torch_install( min_version: Optional[str] = _TORCH_MIN_VERSION, max_version: Optional[str] = _TORCH_MAX_VERSION, raise_on_error: bool = True, ) -> bool: """ Check that the torch package is installed. If raise_on_error, will raise an ImportError if it is not installed or the required version range, if set, is not installed. If not raise_on_error, will return True if installed with required version and False otherwise. :param min_version: The minimum version for torch that it must be greater than or equal to, if unset will require no minimum version :type min_version: str :param max_version: The maximum version for torch that it must be less than or equal to, if unset will require no maximum version. :type max_version: str :param raise_on_error: True to raise any issues such as not installed, minimum version, or maximum version as ImportError. False to return the result. :type raise_on_error: bool :return: If raise_on_error, will return False if torch is not installed or the version is outside the accepted bounds and True if everything is correct. :rtype: bool """ if torch_err is not None: if raise_on_error: raise torch_err return False return check_version("torch", min_version, max_version, raise_on_error)
[docs]def check_torchvision_install( min_version: Optional[str] = None, max_version: Optional[str] = None, raise_on_error: bool = True, ) -> bool: """ Check that the torchvision package is installed. If raise_on_error, will raise an ImportError if it is not installed or the required version range, if set, is not installed. If not raise_on_error, will return True if installed with required version and False otherwise. :param min_version: The minimum version for torchvision that it must be greater than or equal to, if unset will require no minimum version :type min_version: str :param max_version: The maximum version for torchvision that it must be less than or equal to, if unset will require no maximum version. :type max_version: str :param raise_on_error: True to raise any issues such as not installed, minimum version, or maximum version as ImportError. False to return the result. :type raise_on_error: bool :return: If raise_on_error, will return False if torchvision is not installed or the version is outside the accepted bounds and True if everything is correct. :rtype: bool """ if torchvision_err is not None: if raise_on_error: raise torchvision_err return False return check_version("torchvision", min_version, max_version, raise_on_error)
[docs]def require_torch( min_version: Optional[str] = _TORCH_MIN_VERSION, max_version: Optional[str] = _TORCH_MAX_VERSION, ): """ Decorator function to require use of torch. Will check that torch package is installed and within the bounding ranges of min_version and max_version if they are set before calling the wrapped function. See :func:`check_torch_install` for more info. :param min_version: The minimum version for torch that it must be greater than or equal to, if unset will require no minimum version :type min_version: str :param max_version: The maximum version for torch that it must be less than or equal to, if unset will require no maximum version. :type max_version: str """ def _decorator(func): @functools.wraps(func) def _wrapper(*args, **kwargs): check_torch_install(min_version, max_version) return func(*args, **kwargs) return _wrapper return _decorator
[docs]def require_torchvision( min_version: Optional[str] = None, max_version: Optional[str] = None ): """ Decorator function to require use of torchvision. Will check that torchvision package is installed and within the bounding ranges of min_version and max_version if they are set before calling the wrapped function. See :func:`check_torchvision_install` for more info. :param min_version: The minimum version for torchvision that it must be greater than or equal to, if unset will require no minimum version :type min_version: str :param max_version: The maximum version for torchvision that it must be less than or equal to, if unset will require no maximum version. :type max_version: str """ def _decorator(func): @functools.wraps(func) def _wrapper(*args, **kwargs): check_torchvision_install(min_version, max_version) return func(*args, **kwargs) return _wrapper return _decorator