.pytorch()
dataloader because it is not fully random, which in some cases may affect model performance.buffer_size
parameter in ds.pytorch(buffer_size = 2048)
. First, the dataloader randomly selects chunks of from the applicable tensors until the shuffle buffer is full. Next, the indices that are available in shuffle buffer are randomly sampled to construct the batches that are returned by the dataloader. As the data in the shuffle buffer is consumed, new chunks are randomly selected and added to the buffer.