Fix AuraFlow attn processors applying norm_added_q to key projection#13533
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yiyixuxu merged 1 commit intohuggingface:mainfrom Apr 21, 2026
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Both AuraFlowAttnProcessor2_0 and FusedAuraFlowAttnProcessor2_0 were calling attn.norm_added_q on encoder_hidden_states_key_proj while guarded by a check on attn.norm_added_k. This applies the query normalization layer to the key, which is a copy-paste error. Consistent with every other attention processor in this file that defines both norm_added_q and norm_added_k (e.g. FluxAttnProcessor, CogVideoXAttnProcessor, HunyuanAttnProcessor), where norm_added_k is applied to the added key projection.
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…uggingface#13533) Both AuraFlowAttnProcessor2_0 and FusedAuraFlowAttnProcessor2_0 were calling attn.norm_added_q on encoder_hidden_states_key_proj while guarded by a check on attn.norm_added_k. This applies the query normalization layer to the key, which is a copy-paste error. Consistent with every other attention processor in this file that defines both norm_added_q and norm_added_k (e.g. FluxAttnProcessor, CogVideoXAttnProcessor, HunyuanAttnProcessor), where norm_added_k is applied to the added key projection.
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What does this PR do?
Both
AuraFlowAttnProcessor2_0andFusedAuraFlowAttnProcessor2_0inattention_processor.pycontain a copy-paste error whereattn.norm_added_qis called on the encoder key projection while guarded by a check onattn.norm_added_k:This silently applies the query's added-QK norm to the key projection, which is wrong whenever the two layers have different parameters (and is definitely wrong as a logical statement of the attention equations).
Every other attention processor in this file that defines both
norm_added_qandnorm_added_k(e.g.FluxAttnProcessor,CogVideoXAttnProcessor,HunyuanAttnProcessor, etc.) correctly appliesnorm_added_kto the key.This PR fixes both occurrences (lines 2143 and 2240).
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Who can review?
@yiyixuxu @sayakpaul