Fix AttributeError in Qwen3.5 GDN layers with quantized models#37448
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mgoin merged 4 commits intovllm-project:mainfrom Mar 19, 2026
Merged
Fix AttributeError in Qwen3.5 GDN layers with quantized models#37448mgoin merged 4 commits intovllm-project:mainfrom
mgoin merged 4 commits intovllm-project:mainfrom
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The changes correctly resolve the AttributeError encountered in Qwen3.5 GDN layers when using quantized models. By replacing the access to .weight.shape[0] with sum(.output_sizes), the pull request ensures compatibility with MergedColumnParallelLinear layers that do not expose a .weight attribute under quantization. This is a direct and effective fix for the identified issue.
Replace self.in_proj_qkvz.weight.shape[0] and self.in_proj_ba.weight.shape[0] with sum(self.in_proj_qkvz.output_sizes) and sum(self.in_proj_ba.output_sizes). MergedColumnParallelLinear does not expose a .weight attribute when using quantization methods like compressed-tensors/AWQ, causing an AttributeError during the forward pass. The output_sizes attribute is always available on MergedColumnParallelLinear and provides the same information. Fixes vllm-project#37444 Signed-off-by: Jim Smith <jim@joshua8.ai>
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Thanks for the fix! Sorry to break AWQ models. |
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I got the following error when using fp8 models |
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JaheimLee, Were those errors in the existing code or after the PR I submitted? |
It's also caused by #36795 in the existing code |
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@JaheimLee I don't see an error to run fp8 model. Which model did you run? Thanks! |
I use the official 27B fp8 model. |
Signed-off-by: mgoin <mgoin64@gmail.com>
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@JaheimLee Thanks for reporting this! This is because of shape mismatch. Need to change to: |
Co-authored-by: Xin Yang <105740670+xyang16@users.noreply.github.com> Signed-off-by: Michael Goin <mgoin64@gmail.com>
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…project#37448) Signed-off-by: Jim Smith <jim@joshua8.ai> Signed-off-by: mgoin <mgoin64@gmail.com> Signed-off-by: Michael Goin <mgoin64@gmail.com> Co-authored-by: mgoin <mgoin64@gmail.com> Co-authored-by: Xin Yang <105740670+xyang16@users.noreply.github.com>
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…project#37448) Signed-off-by: Jim Smith <jim@joshua8.ai> Signed-off-by: mgoin <mgoin64@gmail.com> Signed-off-by: Michael Goin <mgoin64@gmail.com> Co-authored-by: mgoin <mgoin64@gmail.com> Co-authored-by: Xin Yang <105740670+xyang16@users.noreply.github.com>
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…project#37448) Signed-off-by: Jim Smith <jim@joshua8.ai> Signed-off-by: mgoin <mgoin64@gmail.com> Signed-off-by: Michael Goin <mgoin64@gmail.com> Co-authored-by: mgoin <mgoin64@gmail.com> Co-authored-by: Xin Yang <105740670+xyang16@users.noreply.github.com>
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Summary
self.in_proj_qkvz.weight.shape[0]andself.in_proj_ba.weight.shape[0]withsum(self.in_proj_qkvz.output_sizes)andsum(self.in_proj_ba.output_sizes)in bothqwen3_5.pyandqwen3_next.pyMergedColumnParallelLineardoes not expose a.weightattribute when using quantization methods like compressed-tensors/AWQ, causing anAttributeErrorduring the forward passoutput_sizesattribute is always available onMergedColumnParallelLinearand provides the same total output dimension needed by thegdn_in_projcustom op for shape tracingMotivation
This fixes a regression introduced in #36795 where the new
gdn_in_projcustom op accessesself.in_proj_qkvz.weight.shape[0]andself.in_proj_ba.weight.shape[0]. With quantized models (e.g.,cyankiwi/Qwen3.5-9B-AWQ-4bitusing compressed-tensors), theMergedColumnParallelLinearlayer does not have a.weightattribute — the weight is managed by the quantization kernel. This causes:Fixes #37444
Test plan
cyankiwi/Qwen3.5-9B-AWQ-4bitloads and runs inference without error🤖 Generated with Claude Code