フリー問題

PyTorch Certified Associate のフリー問題 17 / 20 問目

問題文

A developer implements gradient accumulation over 4 micro-batches. Where should the gradient reset and the optimizer step go?

選択肢

  1. Reset before each micro-batch and step once after the group, so each micro-batch contributes its own gradients.
  2. Reset once before the group of 4, run backward for each micro-batch, then step once after the group.
  3. Reset after the step and never before.
  4. Reset and step for every micro-batch, which produces the same effective batch size because the four updates together move the parameters by the same total amount as one larger update would.

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