(self, im1, im2)
| 63 | |
| 64 | @torch.no_grad() |
| 65 | def inference_model(self, im1, im2): |
| 66 | self.network.eval() |
| 67 | output = self.network(im1, im2, iters=self.args.iters, test_mode=True) |
| 68 | ''' |
| 69 | if output is tuple: |
| 70 | print(len(output)) |
| 71 | if output[1] is tuple: |
| 72 | print(len(output[1])) |
| 73 | print(output[1][0].shape) |
| 74 | ''' |
| 75 | return output[1] |
| 76 |