gaussian-splatting-my/envs/gaussian_splatting/Lib/site-packages/torchvision/__init__.py

import os
import warnings

import torch
from torchvision import datasets
from torchvision import io
from torchvision import models
from torchvision import ops
from torchvision import transforms
from torchvision import 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"]:
        raise ValueError("Invalid video backend '%s'. Options are 'pyav' and 'video_reader'" % backend)
    if backend == "video_reader" and not io._HAS_VIDEO_OPT:
        message = "video_reader video backend is not available. Please compile torchvision from source and try again"
        warnings.warn(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()