In this example, the loss is scaled by a factor of 128 before computing the gradients. This helps to prevent exploding gradients and results in stable training.
(loss scaling built-in)
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You don’t need to implement loss scaling manually. It’s built into major deep learning libraries: In this example, the loss is scaled by