o pi 5 @s~dZddlZddlmZeeZGdddejZddd d d d d ddddd Zddddddddddddd Z ddddddddddd Z idddd dd!dd"dd#dd$dd%dd&d'd(d)d*d+d,d-d.d/d0d1d2d3d4d5d6Z dd d!d"d#d$d%d&d7d8d9d:d; Z dZ eje eje iZeje eje iZeje iZd?d@iZdAdBZdMdCdDZdMdEdFZdGdHZdIdJZdMdKdLZdS)NzI State dict utilities: utility methods for converting state dicts easily N) get_loggerc@s eZdZdZdZdZdZdZdS) StateDictTypez6 The mode to use when converting state dicts. diffusers_oldkohya_sspeft diffusersN)__name__ __module__ __qualname____doc__ DIFFUSERS_OLDKOHYA_SSPEFT DIFFUSERSrr^/home/ubuntu/SoloSpeech/.venv/lib/python3.10/site-packages/diffusers/utils/state_dict_utils.pyrs rz.to_out.0.lora_Bz.to_out.0.lora_Az .to_q.lora_Az .to_q.lora_Bz .to_k.lora_Az .to_k.lora_Bz .to_v.lora_Az .to_v.lora_Bz.lora_B.lora_Az.to_out.0.lora_magnitude_vector) .to_out_lora.up.to_out_lora.down.to_q_lora.down .to_q_lora.up.to_k_lora.down .to_k_lora.up.to_v_lora.down .to_v_lora.upz.lora.upz .lora.down.to_out.lora_magnitude_vectorz.q_proj.lora_Bz.q_proj.lora_Az.k_proj.lora_Bz.k_proj.lora_Az.v_proj.lora_Bz.v_proj.lora_Az.out_proj.lora_Bz.out_proj.lora_Aztext_projection.lora_A.weightztext_projection.lora_B.weight) .q_proj.lora_linear_layer.up.q_proj.lora_linear_layer.down.k_proj.lora_linear_layer.up.k_proj.lora_linear_layer.down.v_proj.lora_linear_layer.up.v_proj.lora_linear_layer.down.out_proj.lora_linear_layer.up .out_proj.lora_linear_layer.down.lora_linear_layer.up.lora_linear_layer.downz text_projection.lora.down.weightztext_projection.lora.up.weight) rrrrrrrrr%r&rrrr r!r"r#r$z to_k.lora_Azto_k.lora.downz to_k.lora_Bz to_k.lora.upz to_q.lora_Azto_q.lora.downz to_q.lora_Bz to_q.lora.upz to_v.lora_Azto_v.lora.downz to_v.lora_Bz to_v.lora.upzto_out.0.lora_Azto_out.0.lora.downzto_out.0.lora_Bzto_out.0.lora.upz.k_proj.lora_magnitude_vectorz.v_proj.lora_magnitude_vectorz.q_proj.lora_magnitude_vectorz.out_proj.lora_magnitude_vector) rrrrrrrrz.to_k.lora_magnitude_vectorz.to_v.lora_magnitude_vectorz.to_q.lora_magnitude_vectorr lora_downlora_up)lora_Alora_Bz .processor..cCszi}|D]4\}}tD]}||vrt|}|||}q|D]}||vr5||}|||}nq#|||<q|S)a& Simply iterates over the state dict and replaces the patterns in `mapping` with the corresponding values. Args: state_dict (`dict[str, torch.Tensor]`): The state dict to convert. mapping (`dict[str, str]`): The mapping to use for conversion, the mapping should be a dictionary with the following structure: - key: the pattern to replace - value: the pattern to replace with Returns: converted_state_dict (`dict`) The converted state dict. )itemsKEYS_TO_ALWAYS_REPLACEkeysreplace) state_dictmappingconverted_state_dictkvpattern new_patternrrrconvert_state_dicts     r7cKsz|dur&tdd|Drtj}ntdd|Dr"tj}ntd|tvr4td|dt|}t||S)a Converts a state dict to the PEFT format The state dict can be from previous diffusers format (`OLD_DIFFUSERS`), or new diffusers format (`DIFFUSERS`). The method only supports the conversion from diffusers old/new to PEFT for now. Args: state_dict (`dict[str, torch.Tensor]`): The state dict to convert. original_type (`StateDictType`, *optional*): The original type of the state dict, if not provided, the method will try to infer it automatically. Ncs|]}d|vVqdS to_out_loraNr.0r3rrr z-convert_state_dict_to_peft..csr8lora_linear_layerNrr;rrrr=r>-Could not automatically infer state dict typeOriginal type  is not supported)anyr.rr r ValueErrorPEFT_STATE_DICT_MAPPINGSr7r0 original_typekwargsr1rrrconvert_state_dict_to_pefts   rJc s|dddurdnd|durFtdd|Dr$tj}n"tfdd|Dr5tj}ntdd|DrB|Std |tvrTtd |d t|}t||S) a Converts a state dict to new diffusers format. The state dict can be from previous diffusers format (`OLD_DIFFUSERS`), or PEFT format (`PEFT`) or new diffusers format (`DIFFUSERS`). In the last case the method will return the state dict as is. The method only supports the conversion from diffusers old, PEFT to diffusers new for now. Args: state_dict (`dict[str, torch.Tensor]`): The state dict to convert. original_type (`StateDictType`, *optional*): The original type of the state dict, if not provided, the method will try to infer it automatically. kwargs (`dict`, *args*): Additional arguments to pass to the method. - **adapter_name**: For example, in case of PEFT, some keys will be pre-pended with the adapter name, therefore needs a special handling. By default PEFT also takes care of that in `get_peft_model_state_dict` method: https://github.com/huggingface/peft/blob/ba0477f2985b1ba311b83459d29895c809404e99/src/peft/utils/save_and_load.py#L92 but we add it here in case we don't want to rely on that method. adapter_nameNr+csr8r9rr;rrrr=r>z2convert_state_dict_to_diffusers..c3 |] }dd|vVqdSrz.weightNrr;peft_adapter_namerrr=csr8r?rr;rrrr=r>rArBrC) poprDr.rr rrEDIFFUSERS_STATE_DICT_MAPPINGSr7rGrrOrconvert_state_dict_to_diffuserss    rTcCst}t||S)za Converts a state dict from UNet format to diffusers format - i.e. by removing some keys )UNET_TO_DIFFUSERSr7)r0r1rrrconvert_unet_state_dict_to_pefts rVc Cslzt|}Wnty$}zt|dkrt|}nWYd}~nd}~wwtdd|Ds4td|S)z Attempts to first `convert_state_dict_to_peft`, and if it doesn't detect `lora_linear_layer` for a valid `DIFFUSERS` LoRA for example, attempts to exclusively convert the Unet `convert_unet_state_dict_to_peft` rANcss |] }d|vp d|vVqdS)r)r*Nr)r<keyrrrr= rQz1convert_all_state_dict_to_peft..z#Your LoRA was not converted to PEFT)rJ ExceptionstrrVrDr.rE)r0 peft_dicterrrconvert_all_state_dict_to_pefts    r\c  shzddl}Wn tytdw|dddur#dnd|dur9tfdd|Dr9tj}|t vrGt d |d t |t tj}i}| D]\\}}d |vrd| d d }n d |vro| d d}nd|vrz| dd}n d|vr| dd}| dd|dd}| d}|||<d|vr|ddd}|t|||<qU|S)a Converts a `PEFT` state dict to `Kohya` format that can be used in AUTOMATIC1111, ComfyUI, SD.Next, InvokeAI, etc. The method only supports the conversion from PEFT to Kohya for now. Args: state_dict (`dict[str, torch.Tensor]`): The state dict to convert. original_type (`StateDictType`, *optional*): The original type of the state dict, if not provided, the method will try to infer it automatically. kwargs (`dict`, *args*): Additional arguments to pass to the method. - **adapter_name**: For example, in case of PEFT, some keys will be pre-pended with the adapter name, therefore needs a special handling. By default PEFT also takes care of that in `get_peft_model_state_dict` method: https://github.com/huggingface/peft/blob/ba0477f2985b1ba311b83459d29895c809404e99/src/peft/utils/save_and_load.py#L92 but we add it here in case we don't want to rely on that method. rNzDConverting PEFT state dicts to Kohya requires torch to be installed.rKr+rLc3rMrNrr;rOrrr=3rQz.convert_state_dict_to_kohya..rBrCztext_encoder_2.z lora_te2.z text_encoder.z lora_te1.unet lora_unetlora_magnitude_vector dora_scale_r'z.alpha)torch ImportErrorloggererrorrRrDr.rrKOHYA_STATE_DICT_MAPPINGSrEr7r,r/countsplittensorlen) r0rHrIrckohya_ss_partial_state_dictkohya_ss_state_dict kohya_keyweight alpha_keyrrOrconvert_state_dict_to_kohyasD        rq)N)r enumloggingrr reEnumrrUDIFFUSERS_TO_PEFTDIFFUSERS_OLD_TO_PEFTPEFT_TO_DIFFUSERSDIFFUSERS_OLD_TO_DIFFUSERSPEFT_TO_KOHYA_SSr rrFrrSrgr-r7rJrTrVr\rqrrrrs           ! /