(self, C_train, C_test)
| 19 | class TesterDeter(Tester): |
| 20 | |
| 21 | def __init__(self, C_train, C_test): |
| 22 | super().__init__(C_train, C_test) |
| 23 | |
| 24 | if self.config.get('deterministic', False): |
| 25 | if self.config.get('cudnn_deterministic', True): |
| 26 | cudnn.deterministic = True |
| 27 | cudnn.benchmark = False |
| 28 | else: |
| 29 | cudnn.benchmark = True |
| 30 | seed = self.config.get('random_seed', 0) |
| 31 | worker_rank = self.config.get('worker_rank', False) |
| 32 | if worker_rank: |
| 33 | worker_init = WorkerInit(self.C_train.rank, self.config.workers) |
| 34 | else: |
| 35 | worker_init = WorkerInit(0, 0) |
| 36 | self.worker_init_fn = worker_init.func |
| 37 | random.seed(seed) |
| 38 | np.random.seed(seed) |
| 39 | torch.manual_seed(seed) |
| 40 | torch.cuda.manual_seed(seed) |
| 41 | dist.barrier() |
| 42 | if self.C_train.rank == 0: |
| 43 | self.logger.info(f'deterministic mode, seed: {seed}, worker_rank: {worker_rank},\ |
| 44 | cudnn_deterministic: {self.config.get("cudnn_deterministic", True)}') |
| 45 | dist.barrier() |
| 46 | else: |
| 47 | self.worker_init_fn = None |
nothing calls this directly
no test coverage detected