(self, data: Mapping[Hashable, torch.Tensor])
| 281 | self.adjuster = EnsureChannelFirst(strict_check=strict_check, channel_dim=channel_dim) |
| 282 | |
| 283 | def __call__(self, data: Mapping[Hashable, torch.Tensor]) -> dict[Hashable, torch.Tensor]: |
| 284 | d = dict(data) |
| 285 | for key in self.key_iterator(d): |
| 286 | meta_dict = d[key].meta if isinstance(d[key], MetaTensor) else None # type: ignore[attr-defined] |
| 287 | d[key] = self.adjuster(d[key], meta_dict) |
| 288 | return d |
| 289 | |
| 290 | |
| 291 | class RepeatChanneld(MapTransform): |
nothing calls this directly
no test coverage detected