Doing the loss reduction in foundry instead of in the loss functions. #1079
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Co-authored-by: Vitaliy Chiley <6439018+vchiley@users.noreply.github.com>
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…mosaicml#1079) * setting loss_fn reduction to None * fixing a unit test * add error message * adding test to check reduction * adding test to check reduction * Update llmfoundry/models/mpt/modeling_mpt.py Co-authored-by: Vitaliy Chiley <6439018+vchiley@users.noreply.github.com> * preserving batch dimension of targets * minor change --------- Co-authored-by: Vitaliy Chiley <6439018+vchiley@users.noreply.github.com> Co-authored-by: Daniel King <43149077+dakinggg@users.noreply.github.com>
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…#1079) * setting loss_fn reduction to None * fixing a unit test * add error message * adding test to check reduction * adding test to check reduction * Update llmfoundry/models/mpt/modeling_mpt.py Co-authored-by: Vitaliy Chiley <6439018+vchiley@users.noreply.github.com> * preserving batch dimension of targets * minor change --------- Co-authored-by: Vitaliy Chiley <6439018+vchiley@users.noreply.github.com> Co-authored-by: Daniel King <43149077+dakinggg@users.noreply.github.com>
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This PR gives us more flexibility to reduce losses in foundry in custom ways.
We see that the changes do not affect the MFU or the convergence for 125M and 7B models.
Memory consumption is also similar: