(self, data: torch.Tensor, transform)
| 892 | return self.inverse_transform(data, transform) |
| 893 | |
| 894 | def inverse_transform(self, data: torch.Tensor, transform) -> torch.Tensor: |
| 895 | orig_size = transform[TraceKeys.ORIG_SIZE] |
| 896 | mode = transform[TraceKeys.EXTRA_INFO]["mode"] |
| 897 | align_corners = transform[TraceKeys.EXTRA_INFO]["align_corners"] |
| 898 | dtype = transform[TraceKeys.EXTRA_INFO]["dtype"] |
| 899 | xform = Resize( |
| 900 | spatial_size=orig_size, |
| 901 | mode=mode, |
| 902 | align_corners=None if align_corners == TraceKeys.NONE else align_corners, |
| 903 | dtype=dtype, |
| 904 | ) |
| 905 | with xform.trace_transform(False): |
| 906 | data = xform(data) |
| 907 | for _ in range(transform[TraceKeys.EXTRA_INFO]["new_dim"]): |
| 908 | data = data.squeeze(-1) # remove the additional dims |
| 909 | return data |
| 910 | |
| 911 | |
| 912 | class Rotate(InvertibleTransform, LazyTransform): |
no test coverage detected