Compose¶
- class torchvision.transforms.v2.Compose(transforms: Sequence[Callable])[source]¶
[BETA] Composes several transforms together.
Warning
The Compose transform 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.
This transform does not support torchscript. Please, see the note below.
- Parameters:
transforms (list of
Transform
objects) – list of transforms to compose.
Example
>>> transforms.Compose([ >>> transforms.CenterCrop(10), >>> transforms.PILToTensor(), >>> transforms.ConvertImageDtype(torch.float), >>> ])
Note
In order to script the transformations, please use
torch.nn.Sequential
as below.>>> transforms = torch.nn.Sequential( >>> transforms.CenterCrop(10), >>> transforms.Normalize((0.485, 0.456, 0.406), (0.229, 0.224, 0.225)), >>> ) >>> 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 orPIL.Image
.Examples using
Compose
:Getting started with transforms v2
Getting started with transforms v2Transforms v2: End-to-end object detection example
Transforms v2: End-to-end object detection example- extra_repr() str [source]¶
Set 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 [source]¶
Defines the computation performed at every call.
Should be overridden by all subclasses.
Note
Although the recipe for forward pass needs to be defined within this function, one should call the
Module
instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.