Merge branch 'main' into please_dont_modify_this_branch_unless_you_ar…

…e_just_merging_with_main__

README.md

@@ -21,6 +21,7 @@ versions.
 | `torch`            | `torchvision`      | Python              |
 | ------------------ | ------------------ | ------------------- |
 | `main` / `nightly` | `main` / `nightly` | `>=3.9`, `<=3.12`   |
+| `2.5`              | `0.20`             | `>=3.9`, `<=3.12`   |
 | `2.4`              | `0.19`             | `>=3.8`, `<=3.12`   |
 | `2.3`              | `0.18`             | `>=3.8`, `<=3.12`   |
 | `2.2`              | `0.17`             | `>=3.8`, `<=3.11`   |

setup.py

@@ -366,7 +366,7 @@ def make_image_extension():
         else:
             warnings.warn("Building torchvision without AVIF support")
 
-    if USE_NVJPEG and torch.cuda.is_available():
+    if USE_NVJPEG and (torch.cuda.is_available() or FORCE_CUDA):
         nvjpeg_found = CUDA_HOME is not None and (Path(CUDA_HOME) / "include/nvjpeg.h").exists()
 
         if nvjpeg_found:
@@ -376,6 +376,8 @@ def make_image_extension():
             Extension = CUDAExtension
         else:
             warnings.warn("Building torchvision without NVJPEG support")
+    elif USE_NVJPEG:
+        warnings.warn("Building torchvision without NVJPEG support")
 
     return Extension(
         name="torchvision.image",

test/test_image.py

@@ -4,6 +4,7 @@
 import os
 import re
 import sys
+from contextlib import nullcontext
 from pathlib import Path
 
 import numpy as np
@@ -13,6 +14,7 @@
 import torchvision.transforms.v2.functional as F
 from common_utils import assert_equal, cpu_and_cuda, IN_OSS_CI, needs_cuda
 from PIL import __version__ as PILLOW_VERSION, Image, ImageOps, ImageSequence
+from torchvision._internally_replaced_utils import IN_FBCODE
 from torchvision.io.image import (
     _decode_avif,
     _decode_heic,
@@ -1076,5 +1078,13 @@ def test_mode_str():
     assert decode_image(path, mode="RGBA").shape[0] == 4
 
 
+def test_avif_heic_fbcode():
+    cm = nullcontext() if IN_FBCODE else pytest.raises(ImportError, match="cannot import")
+    with cm:
+        from torchvision.io import decode_heic  # noqa
+    with cm:
+        from torchvision.io import decode_avif  # noqa
+
+
 if __name__ == "__main__":
     pytest.main([__file__])

torchvision/_internally_replaced_utils.py

@@ -6,6 +6,7 @@
 
 _HOME = os.path.join(_get_torch_home(), "datasets", "vision")
 _USE_SHARDED_DATASETS = False
+IN_FBCODE = False
 
 
 def _download_file_from_remote_location(fpath: str, url: str) -> None:

torchvision/io/__init__.py

@@ -74,3 +74,10 @@
     "Video",
     "VideoReader",
 ]
+
+from .._internally_replaced_utils import IN_FBCODE
+
+if IN_FBCODE:
+    from .image import _decode_avif as decode_avif, _decode_heic as decode_heic
+
+    __all__ += ["decode_avif", "decode_heic"]

torchvision/utils.py

@@ -604,9 +604,9 @@ def _parse_colors(
                 f"Number of colors must be equal or larger than the number of objects, but got {len(colors)} < {num_objects}."
             )
     elif not isinstance(colors, (tuple, str)):
-        raise ValueError("`colors` must be a tuple or a string, or a list thereof, but got {colors}.")
+        raise ValueError(f"`colors` must be a tuple or a string, or a list thereof, but got {colors}.")
     elif isinstance(colors, tuple) and len(colors) != 3:
-        raise ValueError("If passed as tuple, colors should be an RGB triplet, but got {colors}.")
+        raise ValueError(f"If passed as tuple, colors should be an RGB triplet, but got {colors}.")
     else:  # colors specifies a single color for all objects
         colors = [colors] * num_objects