# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
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