Remove BETA status for v2 transforms (#8111)

torchvision/transforms/v2/functional/_utils.py

@@ -67,7 +67,7 @@ _BUILTIN_DATAPOINT_TYPES = {
 
 
 def register_kernel(functional, tv_tensor_cls):
-    """[BETA] Decorate a kernel to register it for a functional and a (custom) tv_tensor type.
+    """Decorate a kernel to register it for a functional and a (custom) tv_tensor type.
 
     See :ref:`sphx_glr_auto_examples_transforms_plot_custom_tv_tensors.py` for usage
     details.

torchvision/tv_tensors/__init__.py

@@ -13,7 +13,7 @@ from ._video import Video
 # Until `disable` is removed, there will be graph breaks after all calls to functional transforms
 @torch.compiler.disable
 def wrap(wrappee, *, like, **kwargs):
-    """[BETA] Convert a :class:`torch.Tensor` (``wrappee``) into the same :class:`~torchvision.tv_tensors.TVTensor` subclass as ``like``.
+    """Convert a :class:`torch.Tensor` (``wrappee``) into the same :class:`~torchvision.tv_tensors.TVTensor` subclass as ``like``.
 
     If ``like`` is a :class:`~torchvision.tv_tensors.BoundingBoxes`, the ``format`` and ``canvas_size`` of
     ``like`` are assigned to ``wrappee``, unless they are passed as ``kwargs``.

torchvision/tv_tensors/_bounding_boxes.py

@@ -10,7 +10,7 @@ from ._tv_tensor import TVTensor
 
 
 class BoundingBoxFormat(Enum):
-    """[BETA] Coordinate format of a bounding box.
+    """Coordinate format of a bounding box.
 
     Available formats are
 
@@ -25,7 +25,7 @@ class BoundingBoxFormat(Enum):
 
 
 class BoundingBoxes(TVTensor):
-    """[BETA] :class:`torch.Tensor` subclass for bounding boxes.
+    """:class:`torch.Tensor` subclass for bounding boxes.
 
     .. note::
         There should be only one :class:`~torchvision.tv_tensors.BoundingBoxes`

torchvision/tv_tensors/_dataset_wrapper.py

@@ -17,9 +17,7 @@ __all__ = ["wrap_dataset_for_transforms_v2"]
 
 
 def wrap_dataset_for_transforms_v2(dataset, target_keys=None):
-    """[BETA] Wrap a ``torchvision.dataset`` for usage with :mod:`torchvision.transforms.v2`.
-
-    .. v2betastatus:: wrap_dataset_for_transforms_v2 function
+    """Wrap a ``torchvision.dataset`` for usage with :mod:`torchvision.transforms.v2`.
 
     Example:
         >>> dataset = torchvision.datasets.CocoDetection(...)

torchvision/tv_tensors/_image.py

@@ -9,7 +9,7 @@ from ._tv_tensor import TVTensor
 
 
 class Image(TVTensor):
-    """[BETA] :class:`torch.Tensor` subclass for images.
+    """:class:`torch.Tensor` subclass for images.
 
     .. note::
 

torchvision/tv_tensors/_mask.py

@@ -9,7 +9,7 @@ from ._tv_tensor import TVTensor
 
 
 class Mask(TVTensor):
-    """[BETA] :class:`torch.Tensor` subclass for segmentation and detection masks.
+    """:class:`torch.Tensor` subclass for segmentation and detection masks.
 
     Args:
         data (tensor-like, PIL.Image.Image): Any data that can be turned into a tensor with :func:`torch.as_tensor` as

torchvision/tv_tensors/_torch_function_helpers.py

@@ -16,7 +16,7 @@ class _ReturnTypeCM:
 
 
 def set_return_type(return_type: str):
-    """[BETA] Set the return type of torch operations on :class:`~torchvision.tv_tensors.TVTensor`.
+    """Set the return type of torch operations on :class:`~torchvision.tv_tensors.TVTensor`.
 
     This only affects the behaviour of torch operations. It has no effect on
     ``torchvision`` transforms or functionals, which will always return as

torchvision/tv_tensors/_tv_tensor.py

@@ -13,7 +13,7 @@ D = TypeVar("D", bound="TVTensor")
 
 
 class TVTensor(torch.Tensor):
-    """[Beta] Base class for all TVTensors.
+    """Base class for all TVTensors.
 
     You probably don't want to use this class unless you're defining your own
     custom TVTensors. See

torchvision/tv_tensors/_video.py

@@ -8,7 +8,7 @@ from ._tv_tensor import TVTensor
 
 
 class Video(TVTensor):
-    """[BETA] :class:`torch.Tensor` subclass for videos.
+    """:class:`torch.Tensor` subclass for videos.
 
     Args:
         data (tensor-like): Any data that can be turned into a tensor with :func:`torch.as_tensor`.