So I guess PyTorch might have some “trade-off” policy for samples in the same batch. If you want maximal precision for the 1st sample in a batch, you might lose more precision in other samples of the batch. And the “trade-off” policy is why I slightly different results for different batch sizes. Is my understanding correct?