Hi, I am trying to get predicted results after model training. Since the input data is too large to fit into memory, I would need to divide the data into batches for evaluation. I know it is possible to do the following in pytorch:
with torch.no_grad(): result_list =  for batch in dataloader: result = net(batch) result_list.append(result) # then concatenate list to get predicted results
I am just wondering if there are simpler ways to do this, something like
mode.predict(input, batch_size=batch_size) in Keras where
batch_size option automatically takes care of the splitting and recombination process?