Light-V
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issues of
Light-V
When using distributed training, the process with local_rank!=0 will not call torch.distributed.barrier() and cause a deadlock.
I've made a small optimization in data loading process that reduces peak memory usage when handling large datasets. Previously, we were using np.array() to convert large datasets from h5py objects...