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PRISM / SegMamba /monai /__init__.py
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# Copyright (c) MONAI Consortium
# 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.
from __future__ import annotations
import os
import sys
from ._version import get_versions
PY_REQUIRED_MAJOR = 3
PY_REQUIRED_MINOR = 8
version_dict = get_versions()
__version__: str = version_dict.get("version", "0+unknown")
__revision_id__: str = version_dict.get("full-revisionid")
del get_versions, version_dict
__copyright__ = "(c) MONAI Consortium"
__basedir__ = os.path.dirname(__file__)
if sys.version_info.major != PY_REQUIRED_MAJOR or sys.version_info.minor < PY_REQUIRED_MINOR:
import warnings
warnings.warn(
f"MONAI requires Python {PY_REQUIRED_MAJOR}.{PY_REQUIRED_MINOR} or higher. "
f"But the current Python is: {sys.version}",
category=RuntimeWarning,
)
from .utils.module import load_submodules # noqa: E402
# handlers_* have some external decorators the users may not have installed
# *.so files and folder "_C" may not exist when the cpp extensions are not compiled
excludes = "|".join(
[
"(^(monai.handlers))",
"(^(monai.bundle))",
"(^(monai.fl))",
"((\\.so)$)",
"(^(monai._C))",
"(.*(__main__)$)",
"(.*(video_dataset)$)",
"(.*(nnunet).*$)",
]
)
# load directory modules only, skip loading individual files
load_submodules(sys.modules[__name__], False, exclude_pattern=excludes)
# load all modules, this will trigger all export decorations
load_submodules(sys.modules[__name__], True, exclude_pattern=excludes)
__all__ = [
"apps",
"auto3dseg",
"bundle",
"config",
"data",
"engines",
"fl",
"handlers",
"inferers",
"losses",
"metrics",
"networks",
"optimizers",
"transforms",
"utils",
"visualize",
]
try:
from .utils.tf32 import detect_default_tf32
detect_default_tf32()
import torch
# workaround related to https://github.com/Project-MONAI/MONAI/issues/7575
if hasattr(torch.cuda.device_count, "cache_clear"):
torch.cuda.device_count.cache_clear()
except BaseException:
from .utils.misc import MONAIEnvVars
if MONAIEnvVars.debug():
raise