(self)
| 47 | |
| 48 | @torch.no_grad() |
| 49 | def run_test(self): |
| 50 | self.test_mode() |
| 51 | self.before_all_iter(self.hooks_dict[self._mode]) |
| 52 | all_results = [] |
| 53 | for batch_idx, batch_data in tqdm( |
| 54 | enumerate(self.datas[self._mode].dataloader)): |
| 55 | self.before_iter(self.hooks_dict[self._mode]) |
| 56 | if self.sample_args: |
| 57 | batch_data.update(self.sample_args.get_lowercase_dict()) |
| 58 | with torch.autocast(device_type='cuda', |
| 59 | enabled=self.use_amp, |
| 60 | dtype=self.dtype): |
| 61 | results = self.run_step_eval(transfer_data_to_cuda(batch_data), |
| 62 | batch_idx, |
| 63 | step=self.total_iter, |
| 64 | rank=we.rank) |
| 65 | all_results.extend(results) |
| 66 | self.after_iter(self.hooks_dict[self._mode]) |
| 67 | log_data, log_label = self.save_results(all_results) |
| 68 | self.register_probe({'test_label': log_label}) |
| 69 | self.register_probe({ |
| 70 | 'test_image': |
| 71 | ProbeData(log_data, |
| 72 | is_image=True, |
| 73 | build_html=True, |
| 74 | build_label=log_label) |
| 75 | }) |
| 76 | |
| 77 | self.after_all_iter(self.hooks_dict[self._mode]) |
| 78 | |
| 79 | def run_step_val(self, batch_data, batch_idx=0, step=None, rank=None): |
| 80 | sample_id_list = batch_data['sample_id'] |
nothing calls this directly
no test coverage detected