(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)
| 547 | - batch_size (int): number of examples in a batch. |
| 548 | """ |
| 549 | def __init__(self, dataset, total_iter, batch_size, world_size=None, rank=None, last_iter=-1, |
| 550 | shuffle_strategy=0, random_seed=0, imageNumPerClass=4, ret_save_path=None): |
| 551 | self.batch_size = batch_size |
| 552 | self.world_size = world_size if world_size is not None else get_world_size() |
| 553 | self.num_instances = imageNumPerClass |
| 554 | self.num_pids_per_batch = self.batch_size // self.num_instances |
| 555 | self.index_dic = defaultdict(list) |
| 556 | self.random_seed = random_seed |
| 557 | self.total_iter = total_iter |
| 558 | self.total_size = self.total_iter*self.batch_size |
| 559 | self.last_iter = last_iter |
| 560 | self.dataset = dataset |
| 561 | |
| 562 | labels = self.dataset.labels |
| 563 | printlog('using RandomIdentityBatchSampler, initializing class map...') |
| 564 | self.index_dic = collections.defaultdict(list) |
| 565 | for i,l in enumerate(labels): |
| 566 | self.index_dic[l].append(i) |
| 567 | |
| 568 | self.pids = np.array(list(self.index_dic.keys())) |
| 569 | self.rank = rank if rank is not None else get_rank() |
| 570 | |
| 571 | def __iter__(self): |
| 572 | np.random.seed(self.random_seed) |
nothing calls this directly
no test coverage detected