Describe the technique of gradient accumulation and its role in training with large batch sizes.

Gradient accumulation is a technique used to simulate training with a large batch size when the available memory is insufficient to fit the entire batch in memory at once. It involves dividing the large batch into smaller mini-batches and processing each mini-batch sequentially. Instead of updating the model's weights after each mini-batch, the gradients computed for each mini-batch are accumulated over several mini-batches. Once the gradients have been accumulated for all mini-batches that make up the large batch, the a....