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| # Copyright (c) Facebook, Inc. and its affiliates. | |
| import importlib | |
| import importlib.util | |
| import logging | |
| import numpy as np | |
| import os | |
| import random | |
| import sys | |
| from datetime import datetime | |
| import torch | |
| __all__ = ["seed_all_rng"] | |
| TORCH_VERSION = tuple(int(x) for x in torch.__version__.split(".")[:2]) | |
| """ | |
| PyTorch version as a tuple of 2 ints. Useful for comparison. | |
| """ | |
| DOC_BUILDING = os.getenv("_DOC_BUILDING", False) # set in docs/conf.py | |
| """ | |
| Whether we're building documentation. | |
| """ | |
| def seed_all_rng(seed=None): | |
| """ | |
| Set the random seed for the RNG in torch, numpy and python. | |
| Args: | |
| seed (int): if None, will use a strong random seed. | |
| """ | |
| if seed is None: | |
| seed = ( | |
| os.getpid() | |
| + int(datetime.now().strftime("%S%f")) | |
| + int.from_bytes(os.urandom(2), "big") | |
| ) | |
| logger = logging.getLogger(__name__) | |
| logger.info("Using a generated random seed {}".format(seed)) | |
| np.random.seed(seed) | |
| torch.manual_seed(seed) | |
| random.seed(seed) | |
| os.environ["PYTHONHASHSEED"] = str(seed) | |
| # from https://stackoverflow.com/questions/67631/how-to-import-a-module-given-the-full-path | |
| def _import_file(module_name, file_path, make_importable=False): | |
| spec = importlib.util.spec_from_file_location(module_name, file_path) | |
| module = importlib.util.module_from_spec(spec) | |
| spec.loader.exec_module(module) | |
| if make_importable: | |
| sys.modules[module_name] = module | |
| return module | |
| def _configure_libraries(): | |
| """ | |
| Configurations for some libraries. | |
| """ | |
| # An environment option to disable `import cv2` globally, | |
| # in case it leads to negative performance impact | |
| disable_cv2 = int(os.environ.get("DETECTRON2_DISABLE_CV2", False)) | |
| if disable_cv2: | |
| sys.modules["cv2"] = None | |
| else: | |
| # Disable opencl in opencv since its interaction with cuda often has negative effects | |
| # This envvar is supported after OpenCV 3.4.0 | |
| os.environ["OPENCV_OPENCL_RUNTIME"] = "disabled" | |
| try: | |
| import cv2 | |
| if int(cv2.__version__.split(".")[0]) >= 3: | |
| cv2.ocl.setUseOpenCL(False) | |
| except ModuleNotFoundError: | |
| # Other types of ImportError, if happened, should not be ignored. | |
| # Because a failed opencv import could mess up address space | |
| # https://github.com/skvark/opencv-python/issues/381 | |
| pass | |
| def get_version(module, digit=2): | |
| return tuple(map(int, module.__version__.split(".")[:digit])) | |
| # fmt: off | |
| assert get_version(torch) >= (1, 4), "Requires torch>=1.4" | |
| import fvcore | |
| assert get_version(fvcore, 3) >= (0, 1, 2), "Requires fvcore>=0.1.2" | |
| import yaml | |
| assert get_version(yaml) >= (5, 1), "Requires pyyaml>=5.1" | |
| # fmt: on | |
| _ENV_SETUP_DONE = False | |
| def setup_environment(): | |
| """Perform environment setup work. The default setup is a no-op, but this | |
| function allows the user to specify a Python source file or a module in | |
| the $DETECTRON2_ENV_MODULE environment variable, that performs | |
| custom setup work that may be necessary to their computing environment. | |
| """ | |
| global _ENV_SETUP_DONE | |
| if _ENV_SETUP_DONE: | |
| return | |
| _ENV_SETUP_DONE = True | |
| _configure_libraries() | |
| custom_module_path = os.environ.get("DETECTRON2_ENV_MODULE") | |
| if custom_module_path: | |
| setup_custom_environment(custom_module_path) | |
| else: | |
| # The default setup is a no-op | |
| pass | |
| def setup_custom_environment(custom_module): | |
| """ | |
| Load custom environment setup by importing a Python source file or a | |
| module, and run the setup function. | |
| """ | |
| if custom_module.endswith(".py"): | |
| module = _import_file("detectron2.utils.env.custom_module", custom_module) | |
| else: | |
| module = importlib.import_module(custom_module) | |
| assert hasattr(module, "setup_environment") and callable(module.setup_environment), ( | |
| "Custom environment module defined in {} does not have the " | |
| "required callable attribute 'setup_environment'." | |
| ).format(custom_module) | |
| module.setup_environment() | |
| def fixup_module_metadata(module_name, namespace, keys=None): | |
| """ | |
| Fix the __qualname__ of module members to be their exported api name, so | |
| when they are referenced in docs, sphinx can find them. Reference: | |
| https://github.com/python-trio/trio/blob/6754c74eacfad9cc5c92d5c24727a2f3b620624e/trio/_util.py#L216-L241 | |
| """ | |
| if not DOC_BUILDING: | |
| return | |
| seen_ids = set() | |
| def fix_one(qualname, name, obj): | |
| # avoid infinite recursion (relevant when using | |
| # typing.Generic, for example) | |
| if id(obj) in seen_ids: | |
| return | |
| seen_ids.add(id(obj)) | |
| mod = getattr(obj, "__module__", None) | |
| if mod is not None and (mod.startswith(module_name) or mod.startswith("fvcore.")): | |
| obj.__module__ = module_name | |
| # Modules, unlike everything else in Python, put fully-qualitied | |
| # names into their __name__ attribute. We check for "." to avoid | |
| # rewriting these. | |
| if hasattr(obj, "__name__") and "." not in obj.__name__: | |
| obj.__name__ = name | |
| obj.__qualname__ = qualname | |
| if isinstance(obj, type): | |
| for attr_name, attr_value in obj.__dict__.items(): | |
| fix_one(objname + "." + attr_name, attr_name, attr_value) | |
| if keys is None: | |
| keys = namespace.keys() | |
| for objname in keys: | |
| if not objname.startswith("_"): | |
| obj = namespace[objname] | |
| fix_one(objname, objname, obj) | |