o ٷi @svddlmZddlmZddlmZddlmZddlm Z m Z m Z m Z m Z mZdd d Zd ddZ d!d"ddZdS)#) annotationsN)PretrainedConfig) LoRAConfig)%DiffusionColumnParallelLinearWithLoRA+DiffusionMergedColumnParallelLinearWithLoRA(DiffusionMergedQKVParallelLinearWithLoRA"DiffusionQKVParallelLinearWithLoRA!DiffusionReplicatedLinearWithLoRA"DiffusionRowParallelLinearWithLoRA module_namestrtarget_modules list[str]returnboolcs ddltfdd|DS)zFfrom vllm/lora/model_manager.py _match_target_modules, helper functionrNc3s,|]}d|dp|kVqdS)z.*\.$N)match).0 target_moduler reR/home/ubuntu/.local/lib/python3.10/site-packages/vllm_omni/diffusion/lora/utils.py s  z(_match_target_modules..)regexany)r r rrr_match_target_modulessrsupported_modulesset[str]packed_modules_mappingdict[str, list[str]] | NonecCs8t|}|s|S|D] \}}||vr||q |S)uExpand expected LoRA module suffixes for packed (fused) projections. Some diffusion models use packed projections like `to_qkv` or `w13`, while LoRA checkpoints are typically saved against the logical sub-projections (e.g. `to_q`/`to_k`/`to_v`, `w1`/`w3`). The packed layer name is present in `supported_modules`, but the sublayer names are not. Expanding the set ensures these sublayer keys are not dropped when loading a LoRA checkpoint. The packed→sublayer mapping is model-specific (see each diffusion model's `packed_modules_mapping`) so new packed layers are added alongside the model implementation rather than hard-coded in the LoRA framework. )setitemsupdate)rrexpanded packed_name sub_namesrrr*_expand_expected_modules_for_packed_layerss r'layer nn.Module max_lorasint lora_configrpacked_modules_list model_configPretrainedConfig | NonecCsNttttttg}|D]}|j||||dr$||}|||||Sq |S)zN Diffusion-specific layer replacement. similar to vLLM's `from_layer` ) source_layerr,r-r.)rrrrr r can_replace_layercreate_lora_weights)r(r*r,r-r.diffusion_lora_classeslora_clsinstancerrrfrom_layer_diffusion9s&   r6)r r r rrr)rrrr rr)N) r(r)r*r+r,rr-rr.r/rr)) __future__rtorch.nnnn transformersrvllm_omni.config.lorarvllm_omni.diffusion.lora.layersrrrrr r rr'r6rrrrs