Accelerator से पहले और बाद के ट्रेनिंग लूप्स

for batch in train_dataloader:
    optimizer.zero_grad()
    inputs, targets = batch["input_ids"], batch["labels"]
    # Update the lines so Accelerator handles device placement
    inputs = inputs.to(device)
    targets = targets.to(device)
    outputs = model(inputs, labels=targets)
    loss = outputs.loss
    # Modify the gradient computation to use Accelerator
    ____.backward(____)
    optimizer.step()
    lr_scheduler.step()