(self, dataset, total_iter, batch_size, world_size=None, rank=None, last_iter=-1,
shuffle_strategy=0, random_seed=0, imageNumPerClass=4, ret_save_path=None)
| 638 | - batch_size (int): number of examples in a batch. |
| 639 | """ |
| 640 | def __init__(self, dataset, total_iter, batch_size, world_size=None, rank=None, last_iter=-1, |
| 641 | shuffle_strategy=0, random_seed=0, imageNumPerClass=4, ret_save_path=None): |
| 642 | self.batch_size = batch_size |
| 643 | self.world_size = world_size if world_size is not None else get_world_size() |
| 644 | self.num_instances = imageNumPerClass |
| 645 | self.num_pids_per_batch = self.batch_size // self.num_instances |
| 646 | self.index_dic = defaultdict(list) |
| 647 | self.random_seed = random_seed |
| 648 | self.total_iter = total_iter |
| 649 | self.total_size = self.total_iter*self.batch_size |
| 650 | self.last_iter = last_iter |
| 651 | self.dataset = dataset |
| 652 | |
| 653 | labels = self.dataset.labels |
| 654 | printlog('using RandomIdentityBatchSampler, initializing class map...') |
| 655 | self.index_dic = collections.defaultdict(list) |
| 656 | for i,l in enumerate(labels): |
| 657 | self.index_dic[l].append(i) |
| 658 | |
| 659 | self.pids = np.array(list(self.index_dic.keys())) |
| 660 | self.rank = rank if rank is not None else get_rank() |
| 661 | |
| 662 | def __iter__(self): |
| 663 | np.random.seed(self.random_seed) |
nothing calls this directly
no test coverage detected