For numpy interoperability, so that we can compute ``MetaTensor([1.0]) >= np.asarray([1.0])``. This is for pytorch > 1.8.
(self, ufunc, method, *inputs, **kwargs)
| 322 | return func(*_args, **_kwargs) |
| 323 | |
| 324 | def __array_ufunc__(self, ufunc, method, *inputs, **kwargs): |
| 325 | """ |
| 326 | For numpy interoperability, so that we can compute ``MetaTensor([1.0]) >= np.asarray([1.0])``. |
| 327 | This is for pytorch > 1.8. |
| 328 | """ |
| 329 | try: |
| 330 | if not type(ufunc).__module__.startswith("numpy"): |
| 331 | return NotImplemented |
| 332 | except AttributeError: |
| 333 | return NotImplemented |
| 334 | if method != "__call__": |
| 335 | return NotImplemented |
| 336 | _inputs = map(MetaTensor._convert, inputs) |
| 337 | _kwargs = {k: MetaTensor._convert(v) for k, v in kwargs.items()} |
| 338 | if "out" in _kwargs: |
| 339 | return NotImplemented # not supported |
| 340 | try: |
| 341 | return getattr(ufunc, method)(*_inputs, **_kwargs) |
| 342 | except AttributeError: |
| 343 | return NotImplemented |
| 344 | |
| 345 | @staticmethod |
| 346 | def get_default_affine(dtype=torch.float64) -> torch.Tensor: |