Method __call__

monai/transforms/spatial/array.py:1210–1221

Args: img: channel first array, must have shape: (num_channels, H[, W, ..., ]), lazy: a flag to indicate whether this transform should execute lazily or not during this call. Setting this to False or True overrides the ``lazy`` flag set

(self, img: torch.Tensor, lazy: bool | None = None)

        self.spatial_axes = spatial_axes_

    def __call__(self, img: torch.Tensor, lazy: bool | None = None) -> torch.Tensor:
        """
        Args:
            img: channel first array, must have shape: (num_channels, H[, W, ..., ]),
            lazy: a flag to indicate whether this transform should execute lazily or not
                during this call. Setting this to False or True overrides the ``lazy`` flag set
                during initialization for this call. Defaults to None.
        """
        img = convert_to_tensor(img, track_meta=get_track_meta())
        axes = map_spatial_axes(img.ndim, self.spatial_axes)
        lazy_ = self.lazy if lazy is None else lazy
        return rotate90(img, axes, self.k, lazy=lazy_, transform_info=self.get_transform_info())  # type: ignore

    def inverse(self, data: torch.Tensor) -> torch.Tensor:
        transform = self.pop_transform(data)