Adding all project files

venv/Lib/site-packages/torchvision/__init__.py

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+import os
+import warnings
+from modulefinder import Module
+
+import torch
+
+# Don't re-order these, we need to load the _C extension (done when importing
+# .extensions) before entering _meta_registrations.
+from .extension import _HAS_OPS  # usort:skip
+from torchvision import _meta_registrations, datasets, io, models, ops, transforms, utils  # usort:skip
+
+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_CPU_VIDEO_DECODER:
+        # 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