[Draft]Support Optimizer-in-the-backward #1530
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Context
What is the purpose of this PR? Is it to
Please link to any issues this PR addresses.
Changelog
What are the changes made in this PR?
In FullFinetuneDistributed, switch self._optimizer to self._optimizer_in_bwd that runs in backwards
Running in the backwards could save the peak memory cost during
loss.backward()
By the local testing with llama2/7B_full, peak memory is optimized from 31.5GB to 21.2GB, saves 32.6%
Test plan
Please make sure to do each of the following if applicable to your PR. (If you're not sure about any one of these just ask and we will happily help. We also have a contributing page for some guidance on contributing.)
pre-commit install
)pytest tests
pytest tests -m integration_test
UX
If your function changed a public API, please add a dummy example of what the user experience will look like when calling it.
Example of docstring:
torchtune/torchtune/modules/vision_transformer.py
Line 285 in 6a7951f
Example in our docs: https://pytorch.org/torchtune/main/tutorials/qat_finetune.html#applying-qat-to-llama3-models