2025-08-08 nightly release (4a6ae15)

Author: pytorchbot

.github/scripts/setup-env.sh

@@ -80,22 +80,8 @@ if [[ $GPU_ARCH_TYPE == 'cuda' ]]; then
 fi
 echo '::endgroup::'
 
-echo '::group::Install third party dependencies prior to TorchVision install'
-# Installing with `easy_install`, e.g. `python setup.py install` or `python setup.py develop`, has some quirks when
-# when pulling in third-party dependencies. For example:
-# - On Windows, we often hit an SSL error although `pip` can install just fine.
-# - It happily pulls in pre-releases, which can lead to more problems down the line.
-#   `pip` does not unless explicitly told to do so.
-# Thus, we use `easy_install` to extract the third-party dependencies here and install them upfront with `pip`.
-python setup.py egg_info
-# The requires.txt cannot be used with `pip install -r` directly. The requirements are listed at the top and the
-# optional dependencies come in non-standard syntax after a blank line. Thus, we just extract the header.
-sed -e '/^$/,$d' *.egg-info/requires.txt | tee requirements.txt
-pip install --progress-bar=off -r requirements.txt
-echo '::endgroup::'
-
 echo '::group::Install TorchVision'
-python setup.py develop
+pip install -e . -v --no-build-isolation
 echo '::endgroup::'
 
 echo '::group::Install torchvision-extra-decoders'

CONTRIBUTING.md

@@ -58,11 +58,11 @@ details.
 ```bash
 git clone https://github.com/pytorch/vision.git
 cd vision
-python setup.py develop  # use install instead of develop if you don't care about development.
+pip install -e . -v --no-build-isolation  # leave out the -e switch if you don't care about development.
 # or, for OSX
-# MACOSX_DEPLOYMENT_TARGET=10.9 CC=clang CXX=clang++ python setup.py develop
+# MACOSX_DEPLOYMENT_TARGET=10.9 CC=clang CXX=clang++ pip install -e . -v --no-build-isolation
 # for C++ debugging, use DEBUG=1
-# DEBUG=1 python setup.py develop
+# DEBUG=1 pip install -e . -v --no-build-isolation
 ```
 
 By default, GPU support is built if CUDA is found and `torch.cuda.is_available()` is true. It's possible to force

README.md

@@ -71,7 +71,7 @@ Torchvision currently supports the following video backends:
 
 ```
 conda install -c conda-forge 'ffmpeg<4.3'
-python setup.py install
+pip install . -v --no-build-isolation
 ```
 
 # Using the models on C++

test/test_transforms_v2.py

@@ -2520,14 +2520,29 @@ def test_errors(self):
             with pytest.raises(TypeError, match="Argument transforms should be a sequence of callables"):
                 cls(lambda x: x)
 
-        with pytest.raises(ValueError, match="at least one transform"):
-            transforms.Compose([])
+        for cls in (
+            transforms.Compose,
+            transforms.RandomApply,
+            transforms.RandomChoice,
+            transforms.RandomOrder,
+        ):
+
+            with pytest.raises(ValueError, match="at least one transform"):
+                cls([])
 
         for p in [-1, 2]:
             with pytest.raises(ValueError, match=re.escape("value in the interval [0.0, 1.0]")):
                 transforms.RandomApply([lambda x: x], p=p)
 
-        for transforms_, p in [([lambda x: x], []), ([], [1.0])]:
+        for transforms_, p in [
+            ([lambda x: x], []),
+            (
+                [lambda x: x, lambda x: x],
+                [
+                    1.0,
+                ],
+            ),
+        ]:
             with pytest.raises(ValueError, match="Length of p doesn't match the number of transforms"):
                 transforms.RandomChoice(transforms_, p=p)
 

torchvision/csrc/io/decoder/gpu/README.rst

@@ -18,4 +18,4 @@ GPU decoder depends on ffmpeg for demuxing, uses NVDECODE APIs from the nvidia-v
 
 .. code:: bash
 
-    python setup.py install
+    pip install . -v --no-build-isolation

torchvision/transforms/v2/_container.py

@@ -87,6 +87,8 @@ def __init__(self, transforms: Union[Sequence[Callable], nn.ModuleList], p: floa
 
         if not isinstance(transforms, (Sequence, nn.ModuleList)):
             raise TypeError("Argument transforms should be a sequence of callables or a `nn.ModuleList`")
+        elif not transforms:
+            raise ValueError("Pass at least one transform")
         self.transforms = transforms
 
         if not (0.0 <= p <= 1.0):
@@ -133,7 +135,8 @@ def __init__(
     ) -> None:
         if not isinstance(transforms, Sequence):
             raise TypeError("Argument transforms should be a sequence of callables")
-
+        elif not transforms:
+            raise ValueError("Pass at least one transform")
         if p is None:
             p = [1] * len(transforms)
         elif len(p) != len(transforms):
@@ -163,6 +166,8 @@ class RandomOrder(Transform):
     def __init__(self, transforms: Sequence[Callable]) -> None:
         if not isinstance(transforms, Sequence):
             raise TypeError("Argument transforms should be a sequence of callables")
+        elif not transforms:
+            raise ValueError("Pass at least one transform")
         super().__init__()
         self.transforms = transforms