Compose¶
- class torchvision.transforms.v2.Compose(transforms: Sequence[Callable])[source]¶
[BETA] Composes several transforms together.
Note
The Compose transform is in Beta stage, and while we do not expect disruptive breaking changes, some APIs may slightly change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753.
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/segmentation example
Transforms v2: End-to-end object detection/segmentation exampleHow to use CutMix and MixUpHow to write your own v2 transforms
How to write your own v2 transformsTorchscript support- 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]¶
Define 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.