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104 lines
3.3 KiB
104 lines
3.3 KiB
5 months ago
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import os
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import warnings
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from modulefinder import Module
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import torch
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from torchvision import _meta_registrations, datasets, io, models, ops, transforms, utils
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from .extension import _HAS_OPS
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try:
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from .version import __version__ # noqa: F401
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except ImportError:
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pass
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# Check if torchvision is being imported within the root folder
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if not _HAS_OPS and os.path.dirname(os.path.realpath(__file__)) == os.path.join(
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os.path.realpath(os.getcwd()), "torchvision"
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):
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message = (
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"You are importing torchvision within its own root folder ({}). "
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"This is not expected to work and may give errors. Please exit the "
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"torchvision project source and relaunch your python interpreter."
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)
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warnings.warn(message.format(os.getcwd()))
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_image_backend = "PIL"
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_video_backend = "pyav"
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def set_image_backend(backend):
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"""
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Specifies the package used to load images.
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Args:
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backend (string): Name of the image backend. one of {'PIL', 'accimage'}.
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The :mod:`accimage` package uses the Intel IPP library. It is
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generally faster than PIL, but does not support as many operations.
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"""
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global _image_backend
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if backend not in ["PIL", "accimage"]:
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raise ValueError(f"Invalid backend '{backend}'. Options are 'PIL' and 'accimage'")
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_image_backend = backend
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def get_image_backend():
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"""
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Gets the name of the package used to load images
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"""
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return _image_backend
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def set_video_backend(backend):
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"""
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Specifies the package used to decode videos.
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Args:
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backend (string): Name of the video backend. one of {'pyav', 'video_reader'}.
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The :mod:`pyav` package uses the 3rd party PyAv library. It is a Pythonic
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binding for the FFmpeg libraries.
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The :mod:`video_reader` package includes a native C++ implementation on
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top of FFMPEG libraries, and a python API of TorchScript custom operator.
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It generally decodes faster than :mod:`pyav`, but is perhaps less robust.
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.. note::
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Building with FFMPEG is disabled by default in the latest `main`. If you want to use the 'video_reader'
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backend, please compile torchvision from source.
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"""
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global _video_backend
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if backend not in ["pyav", "video_reader", "cuda"]:
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raise ValueError("Invalid video backend '%s'. Options are 'pyav', 'video_reader' and 'cuda'" % backend)
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if backend == "video_reader" and not io._HAS_VIDEO_OPT:
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# TODO: better messages
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message = "video_reader video backend is not available. Please compile torchvision from source and try again"
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raise RuntimeError(message)
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elif backend == "cuda" and not io._HAS_GPU_VIDEO_DECODER:
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# TODO: better messages
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message = "cuda video backend is not available."
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raise RuntimeError(message)
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else:
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_video_backend = backend
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def get_video_backend():
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"""
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Returns the currently active video backend used to decode videos.
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Returns:
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str: Name of the video backend. one of {'pyav', 'video_reader'}.
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"""
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return _video_backend
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def _is_tracing():
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return torch._C._get_tracing_state()
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def disable_beta_transforms_warning():
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# Noop, only exists to avoid breaking existing code.
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# See https://github.com/pytorch/vision/issues/7896
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pass
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