Returns a new array in `output_type`, the array shares the same underlying storage when the output is a numpy array. Changes to self tensor will be reflected in the ndarray and vice versa. Args: output_type: output type, see also: :py:func:`monai.utils.convert_d
(self, output_type=np.ndarray, dtype=None, device=None, *_args, **_kwargs)
| 354 | return self.as_subclass(torch.Tensor) |
| 355 | |
| 356 | def get_array(self, output_type=np.ndarray, dtype=None, device=None, *_args, **_kwargs): |
| 357 | """ |
| 358 | Returns a new array in `output_type`, the array shares the same underlying storage when the output is a |
| 359 | numpy array. Changes to self tensor will be reflected in the ndarray and vice versa. |
| 360 | |
| 361 | Args: |
| 362 | output_type: output type, see also: :py:func:`monai.utils.convert_data_type`. |
| 363 | dtype: dtype of output data. Converted to correct library type (e.g., |
| 364 | `np.float32` is converted to `torch.float32` if output type is `torch.Tensor`). |
| 365 | If left blank, it remains unchanged. |
| 366 | device: if the output is a `torch.Tensor`, select device (if `None`, unchanged). |
| 367 | _args: currently unused parameters. |
| 368 | _kwargs: currently unused parameters. |
| 369 | """ |
| 370 | return convert_data_type(self, output_type=output_type, dtype=dtype, device=device, wrap_sequence=True)[0] |
| 371 | |
| 372 | def set_array(self, src, non_blocking: bool = False, *_args, **_kwargs): |
| 373 | """ |
no test coverage detected