siammot/data/image_dataset.py [215:232]:
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                           amodal=True)

    batch_size = 16
    sampler = torch.utils.data.sampler.RandomSampler(dataset)
    batch_sampler = torch.utils.data.sampler.BatchSampler(
        sampler, batch_size, drop_last=False)
    dataloader = data.DataLoader(dataset,
                                 num_workers=4,
                                 batch_sampler=batch_sampler,
                                 collate_fn=collator
                                 )
    import time
    tic = time.time()
    for iteration, (image, target, image_ids) in enumerate(dataloader):
        data_time = time.time() - tic
        print("Data loading time: {}".format(data_time))
        tic = time.time()
        print(image_ids)
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siammot/data/video_dataset.py [178:195]:
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                           amodal=True)

    batch_size = 16
    sampler = torch.utils.data.sampler.RandomSampler(dataset)
    batch_sampler = torch.utils.data.sampler.BatchSampler(
        sampler, batch_size, drop_last=False)
    dataloader = data.DataLoader(dataset,
                                 num_workers=4,
                                 batch_sampler=batch_sampler,
                                 collate_fn=collator
                                 )
    import time
    tic = time.time()
    for iteration, (image, target, image_ids) in enumerate(dataloader):
        data_time = time.time() - tic
        print("Data loading time: {}".format(data_time))
        tic = time.time()
        print(image_ids)
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