(self, C)
| 31 | class SolverDeter(Solver): |
| 32 | |
| 33 | def __init__(self, C): |
| 34 | super().__init__(C) |
| 35 | |
| 36 | if self.config.get('deterministic', False): |
| 37 | if self.config.get('cudnn_deterministic', True): |
| 38 | cudnn.deterministic = True |
| 39 | cudnn.benchmark = False |
| 40 | else: |
| 41 | cudnn.benchmark = True |
| 42 | seed = self.config.get('random_seed', 0) |
| 43 | worker_rank = self.config.get('worker_rank', False) |
| 44 | if worker_rank: |
| 45 | worker_init = WorkerInit(self.C.rank, self.config.workers) |
| 46 | else: |
| 47 | worker_init = WorkerInit(0, 0) |
| 48 | self.worker_init_fn = worker_init.func |
| 49 | random.seed(seed) |
| 50 | np.random.seed(seed) |
| 51 | torch.manual_seed(seed) |
| 52 | torch.cuda.manual_seed(seed) |
| 53 | dist.barrier() |
| 54 | if self.C.rank == 0: |
| 55 | self.logger.info(f'deterministic mode, seed: {seed}, worker_rank: {worker_rank},\ |
| 56 | cudnn_deterministic: {self.config.get("cudnn_deterministic", True)}') |
| 57 | dist.barrier() |
| 58 | else: |
| 59 | self.worker_init_fn = None |
| 60 | |
| 61 | def create_dataloader(self): |
| 62 | config = self.config |
nothing calls this directly
no test coverage detected