mmagic.models.editors.liif.liif

Module Contents

Classes

LIIF	LIIF model for single image super-resolution.

class mmagic.models.editors.liif.liif.LIIF(generator: dict, pixel_loss: dict, train_cfg: Optional[dict] = None, test_cfg: Optional[dict] = None, init_cfg: Optional[dict] = None, data_preprocessor: Optional[dict] = None)

Bases: mmagic.models.base_models.BaseEditModel

LIIF model for single image super-resolution.

Paper: Learning Continuous Image Representation with

Local Implicit Image Function

Parameters

• generator (dict) – Config for the generator.

• pixel_loss (dict) – Config for the pixel loss.

• pretrained (str) – Path for pretrained model. Default: None.

• data_preprocessor (dict, optional) – The pre-process config of BaseDataPreprocessor.

forward_tensor(inputs, data_samples=None, **kwargs)

Forward tensor. Returns result of simple forward.

Parameters

• inputs (torch.Tensor) – batch input tensor collated by data_preprocessor.

• data_samples (List[BaseDataElement], optional) – data samples collated by data_preprocessor.

Returns

result of simple forward.

Return type

Tensor

forward_inference(inputs, data_samples=None, **kwargs)

Forward inference. Returns predictions of validation, testing, and simple inference.

Parameters

• inputs (torch.Tensor) – batch input tensor collated by data_preprocessor.

• data_samples (BaseDataElement, optional) – data samples collated by data_preprocessor.

Returns

predictions.

Return type

List[DataSample]