Add final norm for LoRA models #1446
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Pull Request Overview
This PR fixes issues related to the handling of LoRA models by adding support for identifying the final normalization layer and cleaning up model builder class methods. Key changes include renaming function parameters in packed MatMul calls to ensure consistency and updating the final norm detection logic (via has_final_norm) to handle PEFT models correctly.
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src/python/py/models/builder.py:920
- The parameter 'basename' replaces the previous 'name' in this function; please ensure that all call sites are updated consistently to prevent mismatches between the naming of the MatMul nodes.
def make_packed_matmul_fp16_or_fp32(self, q_matmul, k_matmul, v_matmul, basename, root_input, **kwargs):
RyanUnderhill
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May 7, 2025
RyanUnderhill
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May 12, 2025
### Description This PR adds the missing pattern to identify the final norm layer in LoRA models. It also cleans up some of the classes in the model builder. ### Motivation and Context The missing final norm layer in LoRA models caused the generated LoRA models to be incorrect.
baijumeswani
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May 14, 2025
Address previous PR review comments from #1470 (#1473) Address QNN specific regressions (#1470) Fix array eos_token_id handling (#1463) Constrained decoding integration (#1381) Remove BF16 CPU from valid GQA configuration (#1469) Avoid adding providers if not requested (#1464) Persist provider options across ClearProviders, AppendProvider where possible (#1454) Fix accuracy issues with Gemma models (#1448) Add bfloat16 support in model builder (#1447) Add final norm for LoRA models (#1446) Update version to 0.8.0-rc3 --------- Co-authored-by: kunal-vaishnavi <115581922+kunal-vaishnavi@users.noreply.github.com> Co-authored-by: Nenad Banfic <46795300+nenad1002@users.noreply.github.com> Co-authored-by: Nenad Banfic <nebanfic@microsoft.com> Co-authored-by: Baiju Meswani <bmeswani@microsoft.com> Co-authored-by: Abhishek Jindal <abjindal@microsoft.com> Co-authored-by: Ying Xiong <yingxiong@microsoft.com> Co-authored-by: Michał Moskal <michal@moskal.me> Co-authored-by: Kunal Vaishnavi <kvaishnavi@microsoft.com>
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Description
This PR adds the missing pattern to identify the final norm layer in LoRA models. It also cleans up some of the classes in the model builder.
Motivation and Context
The missing final norm layer in LoRA models caused the generated LoRA models to be incorrect.