RandomApply

class torchvision.transforms.v2.RandomApply(transforms: Union[Sequence[Callable], ModuleList], p: float = 0.5)

Apply randomly a list of transformations with a given probability.

Note

In order to script the transformation, please use torch.nn.ModuleList as input instead of list/tuple of transforms as shown below:

>>> transforms = transforms.RandomApply(torch.nn.ModuleList([
>>>     transforms.ColorJitter(),
>>> ]), p=0.3)
>>> scripted_transforms = torch.jit.script(transforms)

Make sure to use only scriptable transformations, i.e. that work with torch.Tensor, does not require lambda functions or PIL.Image.

Parameters:

• transforms (sequence or torch.nn.Module) – list of transformations

• p (float) – probability of applying the list of transforms

Examples using RandomApply:

Illustration of transforms

Illustration of transforms

extra_repr() → str

Return the extra representation of the module.

To print customized extra information, you should re-implement this method in your own modules. Both single-line and multi-line strings are acceptable.

forward(*inputs: Any) → Any

Do not override this! Use transform() instead.