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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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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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torch.cuda.manual_seed_all(str(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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"""
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Configurations for some libraries.
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"""
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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():
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"""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
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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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"""
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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):
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"""
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Load custom environment setup by importing a Python source file or a
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module, and run the setup function.
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"""
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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'."
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).format(custom_module)
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module.setup_environment()
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def fixup_module_metadata(module_name, namespace, keys=None):
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"""
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Fix the __qualname__ of module members to be their exported api name, so
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when they are referenced in docs, sphinx can find them. Reference:
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https://github.com/python-trio/trio/blob/6754c74eacfad9cc5c92d5c24727a2f3b620624e/trio/_util.py#L216-L241
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"""
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if not DOC_BUILDING:
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return
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seen_ids = set()
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def fix_one(qualname, name, obj):
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if id(obj) in seen_ids:
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return
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seen_ids.add(id(obj))
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mod = getattr(obj, "__module__", None)
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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__:
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obj.__name__ = name
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obj.__qualname__ = qualname
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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:
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keys = namespace.keys()
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for objname in keys:
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if not objname.startswith("_"):
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obj = namespace[objname]
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fix_one(objname, objname, obj)
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