PyTorch

Datasets: —need len and get_item

Dataloaders —collate_fn defines how the different data examples should be turned into a batch

Backwards: —fills “grad” field of every tensor that requires it

Zero_grad —turns “grad” field of every tensor that requires it to 0

optimizer.step() —the optimizer has a bunch of parameters stored in it, and it looks at the gradient of all the parameters and then does a backward step

Use register_buffer to add a desired tensor to the model, so it gets moved to the right device. persistent=False will make it not part of the state_dict. Last Reviewed: 1/20/25