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|
| import importlib
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| import importlib.util
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| import logging
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| import numpy as np
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| import os
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| import random
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| import sys
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| from datetime import datetime
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| import torch
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|
|
| __all__ = ["seed_all_rng"]
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|
|
|
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| TORCH_VERSION = tuple(int(x) for x in torch.__version__.split(".")[:2])
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| """
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| PyTorch version as a tuple of 2 ints. Useful for comparison.
|
| """
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|
|
|
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| DOC_BUILDING = os.getenv("_DOC_BUILDING", False)
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| """
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| Whether we're building documentation.
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| """
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|
|
|
|
| def seed_all_rng(seed=None):
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| """
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| Set the random seed for the RNG in torch, numpy and python.
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|
|
| Args:
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| seed (int): if None, will use a strong random seed.
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| """
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| if seed is None:
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| seed = (
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| os.getpid()
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| + int(datetime.now().strftime("%S%f"))
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| + int.from_bytes(os.urandom(2), "big")
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| )
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| logger = logging.getLogger(__name__)
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| logger.info("Using a generated random seed {}".format(seed))
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| np.random.seed(seed)
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| torch.manual_seed(seed)
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| random.seed(seed)
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| os.environ["PYTHONHASHSEED"] = str(seed)
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|
|
|
|
|
|
| def _import_file(module_name, file_path, make_importable=False):
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| spec = importlib.util.spec_from_file_location(module_name, file_path)
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| module = importlib.util.module_from_spec(spec)
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| spec.loader.exec_module(module)
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| if make_importable:
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| sys.modules[module_name] = module
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| return module
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|
|
|
|
| def _configure_libraries():
|
| """
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| Configurations for some libraries.
|
| """
|
|
|
|
|
| disable_cv2 = int(os.environ.get("DETECTRON2_DISABLE_CV2", False))
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| if disable_cv2:
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| sys.modules["cv2"] = None
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| else:
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|
|
|
|
| os.environ["OPENCV_OPENCL_RUNTIME"] = "disabled"
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| try:
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| import cv2
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|
|
| if int(cv2.__version__.split(".")[0]) >= 3:
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| cv2.ocl.setUseOpenCL(False)
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| except ModuleNotFoundError:
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|
|
|
|
|
|
| pass
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|
|
| def get_version(module, digit=2):
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| return tuple(map(int, module.__version__.split(".")[:digit]))
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|
|
|
|
| assert get_version(torch) >= (1, 4), "Requires torch>=1.4"
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| import fvcore
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| assert get_version(fvcore, 3) >= (0, 1, 2), "Requires fvcore>=0.1.2"
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| import yaml
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| assert get_version(yaml) >= (5, 1), "Requires pyyaml>=5.1"
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|
|
|
|
|
|
| _ENV_SETUP_DONE = False
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|
|
|
|
| def setup_environment():
|
| """Perform environment setup work. The default setup is a no-op, but this
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| function allows the user to specify a Python source file or a module in
|
| the $DETECTRON2_ENV_MODULE environment variable, that performs
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| custom setup work that may be necessary to their computing environment.
|
| """
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| global _ENV_SETUP_DONE
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| if _ENV_SETUP_DONE:
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| return
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| _ENV_SETUP_DONE = True
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|
|
| _configure_libraries()
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|
|
| custom_module_path = os.environ.get("DETECTRON2_ENV_MODULE")
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|
|
| if custom_module_path:
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| setup_custom_environment(custom_module_path)
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| else:
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|
|
| pass
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|
|
|
|
| def setup_custom_environment(custom_module):
|
| """
|
| Load custom environment setup by importing a Python source file or a
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| module, and run the setup function.
|
| """
|
| if custom_module.endswith(".py"):
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| module = _import_file("detectron2.utils.env.custom_module", custom_module)
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| else:
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| module = importlib.import_module(custom_module)
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| assert hasattr(module, "setup_environment") and callable(module.setup_environment), (
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| "Custom environment module defined in {} does not have the "
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| "required callable attribute 'setup_environment'."
|
| ).format(custom_module)
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| module.setup_environment()
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|
|
|
|
| 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()
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|
|
| def fix_one(qualname, name, obj):
|
|
|
|
|
| if id(obj) in seen_ids:
|
| return
|
| seen_ids.add(id(obj))
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|
|
| mod = getattr(obj, "__module__", None)
|
| if mod is not None and (mod.startswith(module_name) or mod.startswith("fvcore.")):
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| obj.__module__ = module_name
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|
|
|
|
|
|
| if hasattr(obj, "__name__") and "." not in obj.__name__:
|
| obj.__name__ = name
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| obj.__qualname__ = qualname
|
| if isinstance(obj, type):
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| for attr_name, attr_value in obj.__dict__.items():
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| fix_one(objname + "." + attr_name, attr_name, attr_value)
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|
|
| if keys is None:
|
| keys = namespace.keys()
|
| for objname in keys:
|
| if not objname.startswith("_"):
|
| obj = namespace[objname]
|
| fix_one(objname, objname, obj)
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|
|