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

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docs/source/beta_status.py
View file @ a27522cb
......@@ -4,15 +4,26 @@ from docutils.parsers.rst import Directive
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
View file @ a27522cb
......@@ -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
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......@@ -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
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......@@ -15,7 +15,7 @@ from .utils import is_simple_tensor, query_chw
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
View file @ a27522cb
......@@ -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
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......@@ -13,7 +13,7 @@ from .utils import is_simple_tensor, query_chw
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 @@ class Grayscale(Transform):
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 @@ class RandomGrayscale(_RandomApplyTransform):
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 @@ class RandomPhotometricDistort(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 @@ class RandomEqualize(_RandomApplyTransform):
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 @@ class RandomSolarize(_RandomApplyTransform):
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 @@ class RandomAutocontrast(_RandomApplyTransform):
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
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......@@ -10,7 +10,7 @@ from torchvision.transforms.v2 import Transform
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 @@ class Compose(Transform):
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 @@ class RandomApply(Transform):
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 @@ class RandomChoice(Transform):
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
View file @ a27522cb
......@@ -12,7 +12,7 @@ from torchvision.transforms.v2 import Transform
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.
......
torchvision/transforms/v2/_geometry.py
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......@@ -28,7 +28,7 @@ from .utils import has_all, has_any, is_simple_tensor, query_bounding_box, query
class RandomHorizontalFlip(_RandomApplyTransform):
"""[BETA] Horizontally flip the input with a given probability.
.. betastatus:: RandomHorizontalFlip transform
.. v2betastatus:: RandomHorizontalFlip transform
If the input is a :class:`torch.Tensor` or a ``Datapoint`` (e.g. :class:`~torchvision.datapoints.Image`,
:class:`~torchvision.datapoints.Video`, :class:`~torchvision.datapoints.BoundingBox` etc.)
......@@ -48,7 +48,7 @@ class RandomHorizontalFlip(_RandomApplyTransform):
class RandomVerticalFlip(_RandomApplyTransform):
"""[BETA] Vertically flip the input with a given probability.
.. betastatus:: RandomVerticalFlip transform
.. v2betastatus:: RandomVerticalFlip transform
If the input is a :class:`torch.Tensor` or a ``Datapoint`` (e.g. :class:`~torchvision.datapoints.Image`,
:class:`~torchvision.datapoints.Video`, :class:`~torchvision.datapoints.BoundingBox` etc.)
......@@ -68,7 +68,7 @@ class RandomVerticalFlip(_RandomApplyTransform):
class Resize(Transform):
"""[BETA] Resize the input to the given size.
.. betastatus:: Resize transform
.. v2betastatus:: Resize transform
If the input is a :class:`torch.Tensor` or a ``Datapoint`` (e.g. :class:`~torchvision.datapoints.Image`,
:class:`~torchvision.datapoints.Video`, :class:`~torchvision.datapoints.BoundingBox` etc.)
......@@ -162,7 +162,7 @@ class Resize(Transform):
class CenterCrop(Transform):
"""[BETA] Crop the input at the center.
.. betastatus:: CenterCrop transform
.. v2betastatus:: CenterCrop transform
If the input is a :class:`torch.Tensor` or a ``Datapoint`` (e.g. :class:`~torchvision.datapoints.Image`,
:class:`~torchvision.datapoints.Video`, :class:`~torchvision.datapoints.BoundingBox` etc.)
......@@ -190,7 +190,7 @@ class CenterCrop(Transform):
class RandomResizedCrop(Transform):
"""[BETA] Crop a random portion of the input and resize it to a given size.
.. betastatus:: RandomResizedCrop transform
.. v2betastatus:: RandomResizedCrop transform
If the input is a :class:`torch.Tensor` or a ``Datapoint`` (e.g. :class:`~torchvision.datapoints.Image`,
:class:`~torchvision.datapoints.Video`, :class:`~torchvision.datapoints.BoundingBox` etc.)
......@@ -316,7 +316,7 @@ ImageOrVideoTypeJIT = Union[datapoints._ImageTypeJIT, datapoints._VideoTypeJIT]
class FiveCrop(Transform):
"""[BETA] Crop the image or video into four corners and the central crop.
.. betastatus:: FiveCrop transform
.. v2betastatus:: FiveCrop transform
If the input is a :class:`torch.Tensor` or a :class:`~torchvision.datapoints.Image` or a
:class:`~torchvision.datapoints.Video` it can have arbitrary number of leading batch dimensions.
......@@ -379,7 +379,7 @@ class TenCrop(Transform):
"""[BETA] Crop the image or video into four corners and the central crop plus the flipped version of
these (horizontal flipping is used by default).
.. betastatus:: TenCrop transform
.. v2betastatus:: TenCrop transform
If the input is a :class:`torch.Tensor` or a :class:`~torchvision.datapoints.Image` or a
:class:`~torchvision.datapoints.Video` it can have arbitrary number of leading batch dimensions.
......@@ -437,7 +437,7 @@ class TenCrop(Transform):
class Pad(Transform):
"""[BETA] Pad the input on all sides with the given "pad" value.
.. betastatus:: Pad transform
.. v2betastatus:: Pad transform
If the input is a :class:`torch.Tensor` or a ``Datapoint`` (e.g. :class:`~torchvision.datapoints.Image`,
:class:`~torchvision.datapoints.Video`, :class:`~torchvision.datapoints.BoundingBox` etc.)
......@@ -512,7 +512,7 @@ class RandomZoomOut(_RandomApplyTransform):
"""[BETA] "Zoom out" transformation from
`"SSD: Single Shot MultiBox Detector" <https://arxiv.org/abs/1512.02325>`_.
.. betastatus:: RandomZoomOut transform
.. v2betastatus:: RandomZoomOut transform
This transformation randomly pads images, videos, bounding boxes and masks creating a zoom out effect.
Output spatial size is randomly sampled from original size up to a maximum size configured
......@@ -581,7 +581,7 @@ class RandomZoomOut(_RandomApplyTransform):
class RandomRotation(Transform):
"""[BETA] Rotate the input by angle.
.. betastatus:: RandomRotation transform
.. v2betastatus:: RandomRotation transform
If the input is a :class:`torch.Tensor` or a ``Datapoint`` (e.g. :class:`~torchvision.datapoints.Image`,
:class:`~torchvision.datapoints.Video`, :class:`~torchvision.datapoints.BoundingBox` etc.)
......@@ -654,7 +654,7 @@ class RandomRotation(Transform):
class RandomAffine(Transform):
"""[BETA] Random affine transformation the input keeping center invariant.
.. betastatus:: RandomAffine transform
.. v2betastatus:: RandomAffine transform
If the input is a :class:`torch.Tensor` or a ``Datapoint`` (e.g. :class:`~torchvision.datapoints.Image`,
:class:`~torchvision.datapoints.Video`, :class:`~torchvision.datapoints.BoundingBox` etc.)
......@@ -775,7 +775,7 @@ class RandomAffine(Transform):
class RandomCrop(Transform):
"""[BETA] Crop the input at a random location.
.. betastatus:: RandomCrop transform
.. v2betastatus:: RandomCrop transform
If the input is a :class:`torch.Tensor` or a ``Datapoint`` (e.g. :class:`~torchvision.datapoints.Image`,
:class:`~torchvision.datapoints.Video`, :class:`~torchvision.datapoints.BoundingBox` etc.)
......@@ -930,7 +930,7 @@ class RandomCrop(Transform):
class RandomPerspective(_RandomApplyTransform):
"""[BETA] Perform a random perspective transformation of the input with a given probability.
.. betastatus:: RandomPerspective transform
.. v2betastatus:: RandomPerspective transform
If the input is a :class:`torch.Tensor` or a ``Datapoint`` (e.g. :class:`~torchvision.datapoints.Image`,
:class:`~torchvision.datapoints.Video`, :class:`~torchvision.datapoints.BoundingBox` etc.)
......@@ -1016,7 +1016,7 @@ class RandomPerspective(_RandomApplyTransform):
class ElasticTransform(Transform):
"""[BETA] Transform the input with elastic transformations.
.. betastatus:: RandomPerspective transform
.. v2betastatus:: RandomPerspective transform
If the input is a :class:`torch.Tensor` or a ``Datapoint`` (e.g. :class:`~torchvision.datapoints.Image`,
:class:`~torchvision.datapoints.Video`, :class:`~torchvision.datapoints.BoundingBox` etc.)
......@@ -1108,7 +1108,7 @@ class RandomIoUCrop(Transform):
"""[BETA] Random IoU crop transformation from
`"SSD: Single Shot MultiBox Detector" <https://arxiv.org/abs/1512.02325>`_.
.. betastatus:: RandomIoUCrop transform
.. v2betastatus:: RandomIoUCrop transform
This transformation requires an image or video data and ``datapoints.BoundingBox`` in the input.
......@@ -1232,7 +1232,7 @@ class ScaleJitter(Transform):
"""[BETA] Perform Large Scale Jitter on the input according to
`"Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation" <https://arxiv.org/abs/2012.07177>`_.
.. betastatus:: ScaleJitter transform
.. v2betastatus:: ScaleJitter transform
If the input is a :class:`torch.Tensor` or a ``Datapoint`` (e.g. :class:`~torchvision.datapoints.Image`,
:class:`~torchvision.datapoints.Video`, :class:`~torchvision.datapoints.BoundingBox` etc.)
......@@ -1298,7 +1298,7 @@ class ScaleJitter(Transform):
class RandomShortestSize(Transform):
"""[BETA] Randomly resize the input.
.. betastatus:: RandomShortestSize transform
.. v2betastatus:: RandomShortestSize transform
If the input is a :class:`torch.Tensor` or a ``Datapoint`` (e.g. :class:`~torchvision.datapoints.Image`,
:class:`~torchvision.datapoints.Video`, :class:`~torchvision.datapoints.BoundingBox` etc.)
......@@ -1366,7 +1366,7 @@ class RandomShortestSize(Transform):
class RandomResize(Transform):
"""[BETA] Randomly resize the input.
.. betastatus:: RandomResize transform
.. v2betastatus:: RandomResize transform
This transformation can be used together with ``RandomCrop`` as data augmentations to train
models on image segmentation task.
......
torchvision/transforms/v2/_meta.py
View file @ a27522cb
......@@ -11,7 +11,7 @@ from .utils import is_simple_tensor
class ConvertBoundingBoxFormat(Transform):
"""[BETA] Convert bounding box coordinates to the given ``format``, eg from "CXCYWH" to "XYXY".
.. betastatus:: ConvertBoundingBoxFormat transform
.. v2betastatus:: ConvertBoundingBoxFormat transform
Args:
format (str or datapoints.BoundingBoxFormat): output bounding box format.
......@@ -34,7 +34,7 @@ class ConvertBoundingBoxFormat(Transform):
class ConvertDtype(Transform):
"""[BETA] Convert input image or video to the given ``dtype`` and scale the values accordingly.
.. betastatus:: ConvertDtype transform
.. v2betastatus:: ConvertDtype transform
This function does not support PIL Image.
......@@ -77,7 +77,7 @@ class ClampBoundingBox(Transform):
The clamping is done according to the bounding boxes' ``spatial_size`` meta-data.
.. betastatus:: ClampBoundingBox transform
.. v2betastatus:: ClampBoundingBox transform
"""
......
torchvision/transforms/v2/_misc.py
View file @ a27522cb
......@@ -24,7 +24,7 @@ class Identity(Transform):
class Lambda(Transform):
"""[BETA] Apply a user-defined function as a transform.
.. betastatus:: Lambda transform
.. v2betastatus:: Lambda transform
This transform does not support torchscript.
......@@ -55,7 +55,7 @@ class Lambda(Transform):
class LinearTransformation(Transform):
"""[BETA] Transform a tensor image or video with a square transformation matrix and a mean_vector computed offline.
.. betastatus:: LinearTransformation transform
.. v2betastatus:: LinearTransformation transform
This transform does not support PIL Image.
Given transformation_matrix and mean_vector, will flatten the torch.*Tensor and
......@@ -138,7 +138,7 @@ class LinearTransformation(Transform):
class Normalize(Transform):
"""[BETA] Normalize a tensor image or video with mean and standard deviation.
.. betastatus:: Normalize transform
.. v2betastatus:: Normalize transform
This transform does not support PIL Image.
Given mean: ``(mean[1],...,mean[n])`` and std: ``(std[1],..,std[n])`` for ``n``
......@@ -178,7 +178,7 @@ class Normalize(Transform):
class GaussianBlur(Transform):
"""[BETA] Blurs image with randomly chosen Gaussian blur.
.. betastatus:: GausssianBlur transform
.. v2betastatus:: GausssianBlur transform
If the input is a Tensor, it is expected
to have [..., C, H, W] shape, where ... means an arbitrary number of leading dimensions.
......@@ -225,7 +225,7 @@ class GaussianBlur(Transform):
class ToDtype(Transform):
"""[BETA] Converts the input to a specific dtype - this does not scale values.
.. betastatus:: ToDtype transform
.. v2betastatus:: ToDtype transform
Args:
dtype (``torch.dtype`` or dict of ``Datapoint`` -> ``torch.dtype``): The dtype to convert to.
......@@ -258,7 +258,7 @@ class ToDtype(Transform):
class SanitizeBoundingBox(Transform):
"""[BETA] Remove degenerate/invalid bounding boxes and their corresponding labels and masks.
.. betastatus:: SanitizeBoundingBox transform
.. v2betastatus:: SanitizeBoundingBox transform
This transform removes bounding boxes and their associated labels/masks that:
......
torchvision/transforms/v2/_temporal.py
View file @ a27522cb
......@@ -9,7 +9,7 @@ from torchvision.transforms.v2.utils import is_simple_tensor
class UniformTemporalSubsample(Transform):
"""[BETA] Uniformly subsample ``num_samples`` indices from the temporal dimension of the video.
.. betastatus:: UniformTemporalSubsample transform
.. v2betastatus:: UniformTemporalSubsample transform
Videos are expected to be of shape ``[..., T, C, H, W]`` where ``T`` denotes the temporal dimension.
......
torchvision/transforms/v2/_type_conversion.py
View file @ a27522cb
......@@ -13,7 +13,7 @@ from torchvision.transforms.v2.utils import is_simple_tensor
class PILToTensor(Transform):
"""[BETA] Convert a PIL Image to a tensor of the same type - this does not scale values.
.. betastatus:: PILToTensor transform
.. v2betastatus:: PILToTensor transform
This transform does not support torchscript.
......@@ -30,7 +30,7 @@ class ToImageTensor(Transform):
"""[BETA] Convert a tensor, ndarray, or PIL Image to :class:`~torchvision.datapoints.Image`
; this does not scale values.
.. betastatus:: ToImageTensor transform
.. v2betastatus:: ToImageTensor transform
This transform does not support torchscript.
"""
......@@ -46,7 +46,7 @@ class ToImageTensor(Transform):
class ToImagePIL(Transform):
"""[BETA] Convert a tensor or an ndarray to PIL Image - this does not scale values.
.. betastatus:: ToImagePIL transform
.. v2betastatus:: ToImagePIL transform
This transform does not support torchscript.
......
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