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[moe training] Cast to mixed precision policy param dtype in fsdp_pre_all_gather hook #2455
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/2455
Note: Links to docs will display an error until the docs builds have been completed. This comment was automatically generated by Dr. CI and updates every 15 minutes. |
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/2455
Note: Links to docs will display an error until the docs builds have been completed. ❌ 1 New Failure, 5 PendingAs of commit bb9626e with merge base ac14d92 ( NEW FAILURE - The following job has failed:
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out._data.copy_(data) | ||
return | ||
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# For training step 0, out=None, so we need to return a new ScaledGroupedMMTensor. |
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do we have a test for this?
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We have a test for float MoE + FSDP training. We don't have a test verifying which code branch is followed in this fsdp_post_all_gather hook at training step 0 vs 1, but I think the FSDP test alone is sufficient. Let me know if you have other thoughts.
MPS test failures are unrelated to this change |
Stack
Summary
out != None
(see code comments for details)dtype
param from ScaledGroupedMM tensor, as it is no longer needed when doing the casting in pre all gather rather than post all gather.Test plan
./test/prototype/moe_training/test_fsdp.sh
NGPU=2 CONFIG_FILE="./torchtitan/experiments/llama4/train_configs/debug_model.toml" ./run_train.sh --training.steps=10 --model.converters="float8" --float8.recipe_name="rowwise" --float8.moe_fqns_prototype="experts"