Change betastatus doc warning and v2 import warning (#7329)

Author: NicolasHug

docs/source/beta_status.py

@@ -4,15 +4,26 @@
 
 class BetaStatus(Directive):
     has_content = True
+    text = "The {api_name} is in Beta stage, and backward compatibility is not guaranteed."
 
     def run(self):
-        api_name = " ".join(self.content)
-        text = f"The {api_name} is in Beta stage, and backward compatibility is not guaranteed."
+        text = self.text.format(api_name=" ".join(self.content))
         return [nodes.warning("", nodes.paragraph("", "", nodes.Text(text)))]
 
 
+class V2BetaStatus(BetaStatus):
+    text = (
+        "The {api_name} is in Beta stage, and while we do not expect major breaking changes, "
+        "some APIs may still change according to user feedback. Please submit any feedback you may have "
+        "in this issue: https://github.com/pytorch/vision/issues/6753, and you can also check "
+        "out https://github.com/pytorch/vision/issues/7319 to learn "
+        "more about the APIs that we suspect might involve future changes."
+    )
+
+
 def setup(app):
     app.add_directive("betastatus", BetaStatus)
+    app.add_directive("v2betastatus", V2BetaStatus)
     return {
         "version": "0.1",
         "parallel_read_safe": True,

docs/source/transforms.rst

@@ -16,10 +16,10 @@ Transforming and augmenting images
     :ref:`sphx_glr_auto_examples_plot_transforms_v2_e2e.py`.
     Note that these transforms are still BETA, and while we don't expect major
     breaking changes in the future, some APIs may still change according to user
-    feedback. Please submit any feedback you may have in
-    https://github.com/pytorch/vision/issues/6753, and you can also check out
-    https://github.com/pytorch/vision/issues/7319 to learn more about the APIs
-    that we suspect might involve future changes.
+    feedback. Please submit any feedback you may have `here
+    <https://github.com/pytorch/vision/issues/6753>`_, and you can also check
+    out `this issue <https://github.com/pytorch/vision/issues/7319>`_ to learn
+    more about the APIs that we suspect might involve future changes.
 
 Transforms are common image transformations available in the
 ``torchvision.transforms`` module. They can be chained together using

torchvision/__init__.py

@@ -100,10 +100,11 @@ def _is_tracing():
 _WARN_ABOUT_BETA_TRANSFORMS = True
 _BETA_TRANSFORMS_WARNING = (
     "The torchvision.datapoints and torchvision.transforms.v2 namespaces are still Beta. "
-    "While we will try our best to maintain backward compatibility, "
-    "some APIs or behaviors might change without a deprecation cycle. "
-    "To help us improve these new features, please provide your feedback "
-    "here: https://github.com/pytorch/vision/issues/6753."
+    "While we do not expect major breaking changes, some APIs may still change "
+    "according to user feedback. Please submit any feedback you may have in "
+    "this issue: https://github.com/pytorch/vision/issues/6753, and you can also "
+    "check out https://github.com/pytorch/vision/issues/7319 to learn more about "
+    "the APIs that we suspect might involve future changes. "
     "You can silence this warning by calling torchvision.disable_beta_transform_warning()."
 )
 

torchvision/transforms/v2/_augment.py

@@ -15,7 +15,7 @@
 class RandomErasing(_RandomApplyTransform):
     """[BETA] Randomly select a rectangle region in the input image or video and erase its pixels.
 
-    .. betastatus:: RandomErasing transform
+    .. v2betastatus:: RandomErasing transform
 
     This transform does not support PIL Image.
     'Random Erasing Data Augmentation' by Zhong et al. See https://arxiv.org/abs/1708.04896

torchvision/transforms/v2/_auto_augment.py

@@ -165,7 +165,7 @@ class AutoAugment(_AutoAugmentBase):
     r"""[BETA] AutoAugment data augmentation method based on
     `"AutoAugment: Learning Augmentation Strategies from Data" <https://arxiv.org/pdf/1805.09501.pdf>`_.
 
-    .. betastatus:: AutoAugment transform
+    .. v2betastatus:: AutoAugment transform
 
     This transformation works on images and videos only.
 
@@ -342,7 +342,7 @@ class RandAugment(_AutoAugmentBase):
     `"RandAugment: Practical automated data augmentation with a reduced search space"
     <https://arxiv.org/abs/1909.13719>`_.
 
-    .. betastatus:: RandAugment transform
+    .. v2betastatus:: RandAugment transform
 
     This transformation works on images and videos only.
 
@@ -425,7 +425,7 @@ class TrivialAugmentWide(_AutoAugmentBase):
     r"""[BETA] Dataset-independent data-augmentation with TrivialAugment Wide, as described in
     `"TrivialAugment: Tuning-free Yet State-of-the-Art Data Augmentation" <https://arxiv.org/abs/2103.10158>`_.
 
-    .. betastatus:: TrivialAugmentWide transform
+    .. v2betastatus:: TrivialAugmentWide transform
 
     This transformation works on images and videos only.
 
@@ -496,7 +496,7 @@ class AugMix(_AutoAugmentBase):
     r"""[BETA] AugMix data augmentation method based on
     `"AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty" <https://arxiv.org/abs/1912.02781>`_.
 
-    .. betastatus:: AugMix transform
+    .. v2betastatus:: AugMix transform
 
     This transformation works on images and videos only.
 

torchvision/transforms/v2/_color.py

@@ -13,7 +13,7 @@
 class Grayscale(Transform):
     """[BETA] Convert images or videos to grayscale.
 
-    .. betastatus:: Grayscale transform
+    .. v2betastatus:: Grayscale transform
 
     If the input is a :class:`torch.Tensor`, it is expected
     to have [..., 3 or 1, H, W] shape, where ... means an arbitrary number of leading dimensions
@@ -42,7 +42,7 @@ def _transform(self, inpt: Any, params: Dict[str, Any]) -> Any:
 class RandomGrayscale(_RandomApplyTransform):
     """[BETA] Randomly convert image or videos to grayscale with a probability of p (default 0.1).
 
-    .. betastatus:: RandomGrayscale transform
+    .. v2betastatus:: RandomGrayscale transform
 
     If the input is a :class:`torch.Tensor`, it is expected to have [..., 3 or 1, H, W] shape,
     where ... means an arbitrary number of leading dimensions
@@ -76,7 +76,7 @@ def _transform(self, inpt: Any, params: Dict[str, Any]) -> Any:
 class ColorJitter(Transform):
     """[BETA] Randomly change the brightness, contrast, saturation and hue of an image or video.
 
-    .. betastatus:: ColorJitter transform
+    .. v2betastatus:: ColorJitter transform
 
     If the input is a :class:`torch.Tensor`, it is expected
     to have [..., 1 or 3, H, W] shape, where ... means an arbitrary number of leading dimensions.
@@ -182,7 +182,7 @@ class RandomPhotometricDistort(Transform):
     """[BETA] Randomly distorts the image or video as used in `SSD: Single Shot
     MultiBox Detector <https://arxiv.org/abs/1512.02325>`_.
 
-    .. betastatus:: RandomPhotometricDistort transform
+    .. v2betastatus:: RandomPhotometricDistort transform
 
     This transform relies on :class:`~torchvision.transforms.v2.ColorJitter`
     under the hood to adjust the contrast, saturation, hue, brightness, and also
@@ -282,7 +282,7 @@ def _transform(
 class RandomEqualize(_RandomApplyTransform):
     """[BETA] Equalize the histogram of the given image or video with a given probability.
 
-    .. betastatus:: RandomEqualize transform
+    .. v2betastatus:: RandomEqualize transform
 
     If the input is a :class:`torch.Tensor`, it is expected
     to have [..., 1 or 3, H, W] shape, where ... means an arbitrary number of leading dimensions.
@@ -301,7 +301,7 @@ def _transform(self, inpt: Any, params: Dict[str, Any]) -> Any:
 class RandomInvert(_RandomApplyTransform):
     """[BETA] Inverts the colors of the given image or video with a given probability.
 
-    .. betastatus:: RandomInvert transform
+    .. v2betastatus:: RandomInvert transform
 
     If img is a Tensor, it is expected to be in [..., 1 or 3, H, W] format,
     where ... means it can have an arbitrary number of leading dimensions.
@@ -321,7 +321,7 @@ class RandomPosterize(_RandomApplyTransform):
     """[BETA] Posterize the image or video with a given probability by reducing the
     number of bits for each color channel.
 
-    .. betastatus:: RandomPosterize transform
+    .. v2betastatus:: RandomPosterize transform
 
     If the input is a :class:`torch.Tensor`, it should be of type torch.uint8,
     and it is expected to have [..., 1 or 3, H, W] shape, where ... means an arbitrary number of leading dimensions.
@@ -346,7 +346,7 @@ class RandomSolarize(_RandomApplyTransform):
     """[BETA] Solarize the image or video with a given probability by inverting all pixel
     values above a threshold.
 
-    .. betastatus:: RandomSolarize transform
+    .. v2betastatus:: RandomSolarize transform
 
     If img is a Tensor, it is expected to be in [..., 1 or 3, H, W] format,
     where ... means it can have an arbitrary number of leading dimensions.
@@ -370,7 +370,7 @@ def _transform(self, inpt: Any, params: Dict[str, Any]) -> Any:
 class RandomAutocontrast(_RandomApplyTransform):
     """[BETA] Autocontrast the pixels of the given image or video with a given probability.
 
-    .. betastatus:: RandomAutocontrast transform
+    .. v2betastatus:: RandomAutocontrast transform
 
     If the input is a :class:`torch.Tensor`, it is expected
     to have [..., 1 or 3, H, W] shape, where ... means an arbitrary number of leading dimensions.
@@ -389,7 +389,7 @@ def _transform(self, inpt: Any, params: Dict[str, Any]) -> Any:
 class RandomAdjustSharpness(_RandomApplyTransform):
     """[BETA] Adjust the sharpness of the image or video with a given probability.
 
-    .. betastatus:: RandomAdjustSharpness transform
+    .. v2betastatus:: RandomAdjustSharpness transform
 
     If the input is a :class:`torch.Tensor`,
     it is expected to have [..., 1 or 3, H, W] shape, where ... means an arbitrary number of leading dimensions.

torchvision/transforms/v2/_container.py

@@ -10,7 +10,7 @@
 class Compose(Transform):
     """[BETA] Composes several transforms together.
 
-    .. betastatus:: Compose transform
+    .. v2betastatus:: Compose transform
 
     This transform does not support torchscript.
     Please, see the note below.
@@ -61,7 +61,7 @@ def extra_repr(self) -> str:
 class RandomApply(Transform):
     """[BETA] Apply randomly a list of transformations with a given probability.
 
-    .. betastatus:: RandomApply transform
+    .. v2betastatus:: RandomApply transform
 
     .. note::
         In order to script the transformation, please use ``torch.nn.ModuleList`` as input instead of list/tuple of
@@ -116,7 +116,7 @@ def extra_repr(self) -> str:
 class RandomChoice(Transform):
     """[BETA] Apply single transformation randomly picked from a list.
 
-    .. betastatus:: RandomChoice transform
+    .. v2betastatus:: RandomChoice transform
 
     This transform does not support torchscript.
 
@@ -155,7 +155,7 @@ def forward(self, *inputs: Any) -> Any:
 class RandomOrder(Transform):
     """[BETA] Apply a list of transformations in a random order.
 
-    .. betastatus:: RandomOrder transform
+    .. v2betastatus:: RandomOrder transform
 
     This transform does not support torchscript.
 

torchvision/transforms/v2/_deprecated.py

@@ -12,7 +12,7 @@
 class ToTensor(Transform):
     """[BETA] Convert a PIL Image or ndarray to tensor and scale the values accordingly.
 
-    .. betastatus:: ToTensor transform
+    .. v2betastatus:: ToTensor transform
 
     .. warning::
         :class:`v2.ToTensor` is deprecated and will be removed in a future release.