Data loading is a critical aspect of deep learning workflows, whether you’re focused on training or inference. However, it often presents a paradox: the need for a highly convenient solution that is simultaneously customizable. These two goals are notoriously difficult to reconcile. One of the traditional solutions to this problem is to scale out the processing and parallelize the user…
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