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assume Python 3.8+
Summary: Remove workarounds for Python 3.7 Reviewed By: davidsonic Differential Revision: D42451534 fbshipit-source-id: 461dd311f3bccf7bef120ffe0b97fbbd173d95be
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@ -57,19 +57,3 @@ def get_device(x, device: Optional[Device] = None) -> torch.device:
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# Default device is cpu
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return torch.device("cpu")
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# Provide get_origin and get_args even in Python 3.7.
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if sys.version_info >= (3, 8, 0):
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from typing import get_args, get_origin
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elif sys.version_info >= (3, 7, 0):
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def get_origin(cls): # pragma: no cover
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return getattr(cls, "__origin__", None)
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def get_args(cls): # pragma: no cover
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return getattr(cls, "__args__", None)
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else:
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raise ImportError("This module requires Python 3.7+")
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@ -9,10 +9,21 @@ import dataclasses
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import gzip
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import json
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from dataclasses import dataclass, Field, MISSING
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from typing import Any, cast, Dict, IO, Optional, Tuple, Type, TypeVar, Union
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from typing import (
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Any,
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cast,
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Dict,
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get_args,
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get_origin,
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IO,
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Optional,
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Tuple,
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Type,
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TypeVar,
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Union,
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)
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import numpy as np
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from pytorch3d.common.datatypes import get_args, get_origin
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_X = TypeVar("_X")
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@ -12,10 +12,21 @@ import warnings
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from collections import Counter, defaultdict
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from enum import Enum
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from functools import partial
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from typing import Any, Callable, Dict, List, Optional, Tuple, Type, TypeVar, Union
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from typing import (
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Any,
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Callable,
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Dict,
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get_args,
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get_origin,
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List,
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Optional,
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Tuple,
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Type,
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TypeVar,
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Union,
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)
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from omegaconf import DictConfig, OmegaConf, open_dict
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from pytorch3d.common.datatypes import get_args, get_origin
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"""
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@ -7,7 +7,7 @@
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import contextlib
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import pathlib
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import warnings
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from typing import ContextManager, IO, Optional, Union
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from typing import cast, ContextManager, IO, Optional, Union
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import numpy as np
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import torch
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@ -17,14 +17,6 @@ from PIL import Image
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from ..common.datatypes import Device
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@contextlib.contextmanager
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def nullcontext(x):
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"""
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This is just like contextlib.nullcontext but also works in Python 3.6.
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"""
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yield x
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PathOrStr = Union[pathlib.Path, str]
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@ -36,7 +28,7 @@ def _open_file(f, path_manager: PathManager, mode: str = "r") -> ContextManager[
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f = f.open(mode)
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return contextlib.closing(f)
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else:
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return nullcontext(f)
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return contextlib.nullcontext(cast(IO, f))
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def _make_tensor(
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