Dataset & torch.utils.data.DataLoader Dataset & Dataloader Training: True Testing: False ● Dataset: stores data samples and expected values ● Dataloader: groups data in batches, enables multiprocessing

values needs to be stored with each image. Another alternate and space efficient representation simply stores the index of the correct class, instead of the full vector. Labels Images Source Source Hard19

from previous situations and learned to make decisions based on context in training. Meanwhile, RNN stores the past information and all its decisions are taken from what it has learnt from the past. This

support for channel-last layout for convolutions ‣ Support for loop unrolling and vectorized loads and stores in TensorIterator ‣ Support for input activations with more than 231 values PyTorch Release 20