examples/research_projects/seq2seq-distillation/utils.py/DistributedSortishSampler/__init__
class DistributedSortishSampler:    def __init__(self, dataset, batch_size, num_replicas=None, rank=None, add_extra_examples=True, shuffle=True):
        if num_replicas is None:
            if not dist.is_available():
                raise RuntimeError("Requires distributed package to be available")
            num_replicas = dist.get_world_size()
        if rank is None:
            if not dist.is_available():
                raise RuntimeError("Requires distributed package to be available")
            rank = dist.get_rank()
        self.dataset = dataset
        self.num_replicas = num_replicas
        self.rank = rank
        self.epoch = 0
        if add_extra_examples:
            self.num_samples = int(math.ceil(len(self.dataset) * 1.0 / self.num_replicas))
            self.total_size = self.num_samples * self.num_replicas
        else:
            self.total_size = len(dataset)
            self.num_samples = len(self.available_indices)
        self.batch_size = batch_size
        self.add_extra_examples = add_extra_examples
        self.shuffle = shuffle