Fix FP8 checkpoint resumption with onnx export flag #2907
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dskhudia
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@j316chuck : Thinking a bit more about it, I think we should apply it when we are creating a checkpoint instead of the time when we are requesting precision. |
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@dskhudia I think it's a bit more clean to cast when requesting precision since the checkpoint code save/load is a bit scattered throughout checkpoint.py and I have to add this context manager in multiple places (10+ lines vs 1 line). Wdyt?
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@j316chuck : sounds good. I looked at the defintion of this context manager and it doesn't do much besides setting a global variable. I was worried about this slowing down training but it probably doesn't. Feel free to merge. |
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What does this PR do?
Before this PR, checkpoint resumption on FP8 did not work since checkpoints serialized extra FP8 buffers in bytes which is incompatible with torch's
load_sharded_optimizersAfter this PR checkpoint resumption from fp8 serializes out extra fp8 buffers in tensor onnx mode.
Tests
Torch 2.1
mpt-125m-sharded-regression-fp8-ignore-td0frt🔴mpt-125m-sharded-regression-fp8-ignore-6DD62n✅Torch 2.3
mpt-125m-sharded-regression-fp8-ignore-tAGCla✅mpt-125m-sharded-regression-fp8-ignore-8bZirC✅