state_dict_factory: llama checkpoint - support SWIGLU #5601
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DeepSpeed supports loading a checkpoint for inference with different DP/TP/PP. This requires to split/merge parameters based on their TP attributes. Currently, this is done by using model specific parameter names. This is not a good practice and should be modified. This commit handles the required changes to support MDS LLaMA model. There are 2 changes: - Support for lm_head.weight - Support for mlp.h_to_4h.weight for SWIGLU SWIGLU requires different handling, however there is no meta data available that identifies mlp.h_to_4h.weight as SWIGLU. Therefore, for now we use a hack to detect it.
tjruwase
requested review from
samadejacobs and
tohtana
and removed request for
mrwyattii
tjruwase
reviewed
Jun 21, 2024
| new_client_sd[key] = torch.cat(value_list, axis=0) | ||
| elif "mlp.dense_h_to_4h.weight" in key: |
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@nelyahu, this logic is very old and hacky. Could it not be replaced with Universal Checkpointing?
|
@nelyahu Do we have any update? |
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DeepSpeed supports loading a checkpoint for inference with different DP/TP/PP. This requires to split/merge parameters based on their TP attributes. Currently, this is done by using model specific parameter names. This is not a good practice and should be modified.
This commit handles the required changes to support MDS LLaMA model. There are 2 changes:
SWIGLU requires different handling, however there is no meta data available that identifies mlp.h_to_4h.weight as SWIGLU. Therefore, for now we use a hack to detect it.