Build PyTorch DataLoader. In distributed training, each GPU/process has a dataloader. In non-distributed training, there is only one dataloader for all GPUs. Args: dataset (Dataset): A PyTorch dataset. samples_per_gpu (int): Number of training samples on each GPU, i.e.,
(dataset,
samples_per_gpu,
workers_per_gpu,
num_gpus=1,
dist=True,
shuffle=True,
seed=None,
shuffler_sampler=None,
nonshuffler_sampler=None,
**kwargs)
source not stored for this graph (policy: none)