o Ti @sdZddlZGdddejZiddddd d d d d ddddddddddddddddddd d!d"d#d$Zddd d ddddd%ZejeejeiZd&d'iZ d(d)Z d,d*d+Z dS)-z State dict utilities: utility methods for converting state dicts easily File copied from diffusers to avoid import issues and make TRL compatible with most of diffusers versions. Nc@seZdZdZdZdZdS) StateDictTypez6 The mode to use when converting state dicts. diffusers_oldpeftN)__name__ __module__ __qualname____doc__ DIFFUSERS_OLDPEFTr r G/home/ubuntu/.local/lib/python3.10/site-packages/trl/models/sd_utils.pyrsrz.q_proj.lora_Bz.q_proj.lora_linear_layer.upz.q_proj.lora_Az.q_proj.lora_linear_layer.downz.k_proj.lora_Bz.k_proj.lora_linear_layer.upz.k_proj.lora_Az.k_proj.lora_linear_layer.downz.v_proj.lora_Bz.v_proj.lora_linear_layer.upz.v_proj.lora_Az.v_proj.lora_linear_layer.downz.out_proj.lora_Bz.out_proj.lora_linear_layer.upz.out_proj.lora_Az .out_proj.lora_linear_layer.downz to_k.lora_Azto_k.lora.downz to_k.lora_Bz to_k.lora.upz to_q.lora_Azto_q.lora.downz to_q.lora_Bz to_q.lora.upz to_v.lora_Azto_v.lora.downz to_v.lora_Bz to_v.lora.upzto_out.0.lora_Azto_out.0.lora.downzto_out.0.lora_Bzto_out.0.lora.up)z .to_q_lora.upz.to_q_lora.downz .to_k_lora.upz.to_k_lora.downz .to_v_lora.upz.to_v_lora.downz.to_out_lora.upz.to_out_lora.downz .processor..cCszi}|D]4\}}tD]}||vrt|}|||}q|D]}||vr5||}|||}nq#|||<q|S)a& Simply iterates over the state dict and replaces the patterns in `mapping` with the corresponding values. Args: state_dict (`dict[str, torch.Tensor]`): The state dict to convert. mapping (`dict[str, str]`): The mapping to use for conversion, the mapping should be a dictionary with the following structure: - key: the pattern to replace - value: the pattern to replace with Returns: converted_state_dict (`dict`) The converted state dict. )itemsKEYS_TO_ALWAYS_REPLACEkeysreplace) state_dictmappingconverted_state_dictkvpattern new_patternr r r convert_state_dictHs     rc s|dddurdnd|durFtdd|Dr$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 cs|]}d|vVqdS) to_out_loraNr .0rr r r z2convert_state_dict_to_diffusers..c3s |] }dd|vVqdS)z.lora_Az.weightNr rpeft_adapter_namer r r scsr)lora_linear_layerNr rr r r r r!z-Could not automatically infer state dict typezOriginal type z is not supported) popanyrrr r ValueErrorDIFFUSERS_STATE_DICT_MAPPINGSr)r original_typekwargsrr r"r convert_state_dict_to_diffusersis    r+)N) renumEnumrPEFT_TO_DIFFUSERSDIFFUSERS_OLD_TO_DIFFUSERSr r r(rrr+r r r r sh       !