Traktor/myenv/Lib/site-packages/torchvision/__init__.py
2024-05-26 05:12:46 +02:00

104 lines
3.3 KiB
Python

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