bi VddlZddlZddlZddlZddlmZddlmZmZm Z m Z m Z ddl Z ddl Z ddlmZddlmZddlmZddlmZmZddlmZmZmZmZmZmZmZmZm Z m!Z!m"Z"m#Z#m$Z$m%Z%m&Z&m'Z'm(Z(dd l)m*Z*dd l+m,Z,e"rdd l-m.Z.e rdd l/m0Z0er dd l1m2Z2m3Z3m4Z4e$jje6Z7dZ8dZ9dZ:d#dZ;dZ< d$de e e=e=fde dde e e>e e>e dffdZ?d%de dfdZ@d%de dfdZAdZB d%dZC d&dZDdZE d'deFfdZGd ZHGd!d"ZIy)(N)Path)CallableDictListOptionalUnion) model_info)HF_HUB_OFFLINE) ModelMixinload_state_dict)USE_PEFT_BACKEND_get_model_fileconvert_state_dict_to_diffusersconvert_state_dict_to_peftdelete_adapter_layers deprecateget_adapter_nameis_accelerate_availableis_peft_availableis_peft_versionis_transformers_availableis_transformers_versionloggingrecurse_remove_peft_layersscale_lora_layersset_adapter_layers!set_weights_and_activate_adapters)_create_lora_config)_load_sft_state_dict_metadata)PreTrainedModel)BaseTunerLayer)AlignDevicesHook CpuOffloadremove_hook_from_modulezpytorch_lora_weights.binz pytorch_lora_weights.safetensorslora_adapter_metadatacBd|i}|jD]}t|ts|dk7r|j|t t j |jj}d|vr||d<nd|vr | td|jdi|y)ai Fuses LoRAs for the text encoder. Args: text_encoder (`torch.nn.Module`): The text encoder module to set the adapter layers for. If `None`, it will try to get the `text_encoder` attribute. lora_scale (`float`, defaults to 1.0): Controls how much to influence the outputs with the LoRA parameters. safe_fusing (`bool`, defaults to `False`): Whether to check fused weights for NaN values before fusing and if values are NaN not fusing them. adapter_names (`List[str]` or `str`): The names of the adapters to use. safe_merge? adapter_namesNzThe `adapter_names` argument is not supported with your PEFT version. 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NText Encoder not found.Fenabledr4rr5s r;disable_lora_for_text_encoderrRs 233|U3r=c8| tdt|dy)a Enables the LoRA layers for the text encoder. Args: text_encoder (`torch.nn.Module`, *optional*): The text encoder module to enable the LoRA layers for. If `None`, it will try to get the `text_encoder` attribute. 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Otherwise, open an issue if you think it's unexpected: https://github.com/huggingface/diffusers/issues/newr+)'hooks.group_offloadingrrr4rrrkeysr startswith removeprefixrFrinforr named_modulesrishapesplitrr#_func_optionally_disable_offloading load_adapterrtorgrenable_model_cpu_offloadenable_sequential_cpu_offload componentsvaluesr-rmnnModule __class____name__r)rxnetwork_alphasr5rr6rr _pipelinerrrvr peft_kwargskvrankname_rank_key alpha_keys lora_configis_model_cpu_offloadis_sequential_cpu_offloadis_group_offload componentmodel_class_names ` r;_load_lora_into_text_encoderr@sT DEE(effKtX.D 'sH5T ,= '( #). fF3M:??;LMMvwwBLBRBRBTs$!QXYXdXdhngoopeqXrannxq\2A5s s  DLNNDTsDAqXYXdXdhngoopeqXr&|4a7sHs : hvha()4Z@ 0 ; #113 CGD!}}[\"V>2z)%/%9%?%?%BDN  C  %%3%8%8%:qall6>RWXW^W^_bWcdeWfjpWp!qJqJXJ^J^J`t$!Qdeisdsannxq\:A=tNt**nhPT^cd   +L9LMp M I79I " !! %)#    ,z:|22,:L:LM  . . 0 &  3 3 5 &1188: J i9>yI J *'11::)*:);;SF9UT !B B #-sts"rts6)MM5M$M$ M* M*8M* M/M/cddlm}d}d}d}|O|jB|jj D]\}}t |t js!|xs||}t|ds:|xst |jt}|xs[t |jtxs?t|jdxr't |jjdt}|s|rktjd|jj D]9\}}t |t jr t|ds-t||;|||fS) ah Optionally removes offloading in case the pipeline has been already sequentially offloaded to CPU. Args: _pipeline (`DiffusionPipeline`): The pipeline to disable offloading for. Returns: tuple: A tuple indicating if `is_model_cpu_offload` or `is_sequential_cpu_offload` or `is_group_offload` is True. r )_is_group_offload_enabledF_hf_hookhooksrzAccelerate hooks detected. Since you have called `load_lora_weights()`, the previous hooks will be first removed. Then the LoRA parameters will be loaded and the hooks will be applied again.)recurse)rr hf_device_maprrr-rrhasattrrr$r#rrrr%)rrrrrrrs r;rrsbC  %!8!8!@%00668 LAyi3/W3LY3W 9j1#7#e:iFXFXZd;e (A)9--/?@N9--w7Ny1177:t |j tsYt|ey)z Unloads the LoRA parameters. Examples: ```python >>> # Assuming `pipeline` is already loaded with the LoRA parameters. >>> pipeline.unload_lora_weights() >>> ... ``` rN) rr4_lora_loadable_modulesrW issubclassrr unload_lorar!rYrrmodels r;unload_lora_weightsz!LoraBaseMixin.unload_lora_weightssl HI I44 =ID)T2E eooz:%%'A5e<  =r=r)FNrr6r7r*c @d|vrd}tdd|d|vrd}tdd|d|vrd}tdd|t|dk(r td t}|D](}||jvrt|d |jd t ||d } | =t | jtr^| j||| | jD]7} t| ts|jt| j9t | jtst!| |||| jD]7} t| ts|jt| j9+|j"|z|_y )a Fuses the LoRA parameters into the original parameters of the corresponding blocks. This is an experimental API. Args: components: (`List[str]`): List of LoRA-injectable components to fuse the LoRAs into. lora_scale (`float`, defaults to 1.0): Controls how much to influence the outputs with the LoRA parameters. safe_fusing (`bool`, defaults to `False`): Whether to check fused weights for NaN values before fusing and if values are NaN not fusing them. adapter_names (`List[str]`, *optional*): Adapter names to be used for fusing. If nothing is passed, all active adapters will be fused. Example: ```py from diffusers import DiffusionPipeline import torch pipeline = DiffusionPipeline.from_pretrained( "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16 ).to("cuda") pipeline.load_lora_weights("nerijs/pixel-art-xl", weight_name="pixel-art-xl.safetensors", adapter_name="pixel") pipeline.fuse_lora(lora_scale=0.7) ``` fuse_unetzPassing `fuse_unet` to `fuse_lora()` is deprecated and will be ignored. Please use the `components` argument and provide a list of the components whose LoRAs are to be fused. `fuse_unet` will be removed in a future version.1.0.0fuse_transformerzPassing `fuse_transformer` to `fuse_lora()` is deprecated and will be ignored. Please use the `components` argument and provide a list of the components whose LoRAs are to be fused. `fuse_transformer` will be removed in a future version.fuse_text_encoderzPassing `fuse_text_encoder` to `fuse_lora()` is deprecated and will be ignored. Please use the `components` argument and provide a list of the components whose LoRAs are to be fused. `fuse_text_encoder` will be removed in a future version.r%`components` cannot be an empty list.- is not found in self._lora_loadable_modules=rN)r7r*)r6r7r*)rrFr4setrrWrrr fuse_lorar,r-r"updatemerged_adaptersr!r<r) rrr6r7r*r depr_messagemerged_adapter_namesfuse_componentrr9s r;rzLoraBaseMixin.fuse_lorasN & }L    'KL "  & (ML #  z?a DE E #u( UNT%@%@@ N#33aTE`E`Dbbc!deeD.$7E eooz:OOJKWdOe"'--/U%fn=077F This is an experimental API. Args: components (`List[str]`): List of LoRA-injectable components to unfuse LoRA from. unfuse_unet (`bool`, defaults to `True`): Whether to unfuse the UNet LoRA parameters. unfuse_text_encoder (`bool`, defaults to `True`): Whether to unfuse the text encoder LoRA parameters. If the text encoder wasn't monkey-patched with the LoRA parameters then it won't have any effect. unfuse_unetzPassing `unfuse_unet` to `unfuse_lora()` is deprecated and will be ignored. Please use the `components` argument. `unfuse_unet` will be removed in a future version.runfuse_transformerzPassing `unfuse_transformer` to `unfuse_lora()` is deprecated and will be ignored. Please use the `components` argument. `unfuse_transformer` will be removed in a future version.unfuse_text_encoderzPassing `unfuse_text_encoder` to `unfuse_lora()` is deprecated and will be ignored. Please use the `components` argument. `unfuse_text_encoder` will be removed in a future version.rrrrN)rrFr4rrWrrr r!r,r-r"rr rr?)rrrr r rr9adapters r; unfuse_lorazLoraBaseMixin.unfuse_lorarsY$ F "BL   6 )PL $  !F *RL %  z?a DE E( -NT%@%@@ N#33aTE`E`Dbbc!deeD.$7E eoo O/LM"'--/-%fn=+.v/E/E+F^#*w$:O:O/O<@ ot , #O$8$8$: ; !$"="=>O!'(9O(K!L !bcubvwFFJFaFaEbcMM 5D4I4I4K"kDAqqXjOj1a4"k"k+5mS+I} --8/40./#m2DDO } _!5 5*3}+=*>>ijmn}j~iA ..0 0=0D0D0F_HV^_7__ _}- <  1 $"#3"44Z[gZhhij (   1D1D1F^~tX'U]J]d^ ^  &("44 kID)T2E}),]O)L X% ggt,07 It0L-0<RfgsRtAt"@kZcYdeDDP>Qopyoz{33?.G[\hGiFjjk!m18-*55iD*95<<=VW! X$%//:6""=2LY2WXEOO_=-mUD^_hDij9 k?#l `_ s0 KKK K$# K0K4K$K$c ts td|jD]c}t||d}|t |j t r|j>t |j tsYt|ey)a$ Disables the active LoRA layers of the pipeline. Example: ```py from diffusers import AutoPipelineForText2Image import torch pipeline = AutoPipelineForText2Image.from_pretrained( "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16 ).to("cuda") pipeline.load_lora_weights( "jbilcke-hf/sdxl-cinematic-1", weight_name="pytorch_lora_weights.safetensors", adapter_name="cinematic" ) pipeline.disable_lora() ``` rN) rr4rrWrrr disable_lorar!rRrs r;r+zLoraBaseMixin.disable_lorasl& HI I44 9ID)T2E eooz:&&(A1%8  9r=c ts td|jD]c}t||d}|t |j t r|j>t |j tsYt|ey)a" Enables the active LoRA layers of the pipeline. Example: ```py from diffusers import AutoPipelineForText2Image import torch pipeline = AutoPipelineForText2Image.from_pretrained( "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16 ).to("cuda") pipeline.load_lora_weights( "jbilcke-hf/sdxl-cinematic-1", weight_name="pytorch_lora_weights.safetensors", adapter_name="cinematic" ) pipeline.enable_lora() ``` rN) rr4rrWrrr enable_lorar!rTrs r;r-zLoraBaseMixin.enable_lora0sl& HI I44 8ID)T2E eooz:%%'A07  8r=cBts tdt|tr|g}|jD]l}t ||d}|t |jtr|j|?t |jtsZ|D]}t||ny)a Delete an adapter's LoRA layers from the pipeline. Args: adapter_names (`Union[List[str], str]`): The names of the adapters to delete. Example: ```py from diffusers import AutoPipelineForText2Image import torch pipeline = AutoPipelineForText2Image.from_pretrained( "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16 ).to("cuda") pipeline.load_lora_weights( "jbilcke-hf/sdxl-cinematic-1", weight_name="pytorch_lora_weights.safetensors", adapter_names="cinematic" ) pipeline.delete_adapters("cinematic") ``` rN) rr4r-rJrrWrrr delete_adaptersr!r)rr*rrrs r;r/zLoraBaseMixin.delete_adaptersNs. HI I mS )*OM44 CID)T2E eooz:))-8A(5C -e\BC  Cr=c ts tdg}|jD]`}t||d}|t |j t s.|jD] }t|ts|j}`b|S)a Gets the list of the current active adapters. Example: ```python from diffusers import DiffusionPipeline pipeline = DiffusionPipeline.from_pretrained( "stabilityai/stable-diffusion-xl-base-1.0", ).to("cuda") pipeline.load_lora_weights("CiroN2022/toy-face", weight_name="toy_face_sdxl.safetensors", adapter_name="toy") pipeline.get_active_adapters() ``` iPEFT backend is required for this method. Please install the latest version of PEFT `pip install -U peft`N) rr4rrWrrr r,r-r"active_adapters)rr2rrr9s r;get_active_adaptersz!LoraBaseMixin.get_active_adaptersts  { 44 ID)T2E Z%L#mmoF!&.9*0*@*@ r=cts tdi}|jD]f}t||d}|t |j t tfs4t|dsAt|jj||<h|S)zR Gets the current list of all available adapters in the pipeline. r1NrV) rr4rrWrrr r!rr/rVr)rrrrs r;rzLoraBaseMixin.get_list_adapterss {  44 IID)T2E!u_0MNE=1*.u/@/@/E/E/G*H Y' Ir=rgcts td|jD]}t||d}||j D]}t |t s|D]}||jvr|j|j||j|j|t|ds[|jh||jvsw|j|j||j|<y)a/ Moves the LoRAs listed in `adapter_names` to a target device. Useful for offloading the LoRA to the CPU in case you want to load multiple adapters and free some GPU memory. After offloading the LoRA adapters to CPU, as long as the rest of the model is still on GPU, the LoRA adapters can no longer be used for inference, as that would cause a device mismatch. Remember to set the device back to GPU before using those LoRA adapters for inference. ```python >>> pipe.load_lora_weights(path_1, adapter_name="adapter-1") >>> pipe.load_lora_weights(path_2, adapter_name="adapter-2") >>> pipe.set_adapters("adapter-1") >>> image_1 = pipe(**kwargs) >>> # switch to adapter-2, offload adapter-1 >>> pipeline.set_lora_device(adapter_names=["adapter-1"], device="cpu") >>> pipeline.set_lora_device(adapter_names=["adapter-2"], device="cuda:0") >>> pipe.set_adapters("adapter-2") >>> image_2 = pipe(**kwargs) >>> # switch back to adapter-1, offload adapter-2 >>> pipeline.set_lora_device(adapter_names=["adapter-2"], device="cpu") >>> pipeline.set_lora_device(adapter_names=["adapter-1"], device="cuda:0") >>> pipe.set_adapters("adapter-1") >>> ... ``` Args: adapter_names (`List[str]`): List of adapters to send device to. device (`Union[torch.device, str, int]`): Device to send the adapters to. Can be either a torch device, a str or an integer. rNlora_magnitude_vector) rr4rrWr,r-r"lora_Arlora_Brr6)rr*rgrrr9rs r;set_lora_devicezLoraBaseMixin.set_lora_devices@ HI I44 1ID)T2E #mmo1F!&.9,9 1L+6==@ ("MM,7::6B"MM,7::6B&v/FGFLhLhLt#/63O3O#OQWQmQm(4R&&(bj%+$@$@$N 11 1r=c |jjD]3\}}t|ds||jvs"|jdi|5y)aH Hotswap adapters without triggering recompilation of a model or if the ranks of the loaded adapters are different. Args: target_rank (`int`): The highest rank among all the adapters that will be loaded. check_compiled (`str`, *optional*, defaults to `"error"`): How to handle a model that is already compiled. The check can return the following messages: - "error" (default): raise an error - "warn": issue a warning - "ignore": do nothing enable_lora_hotswapNr+)rrrrr;)rrrrs r;r;z!LoraBaseMixin.enable_lora_hotswapsO#oo335 8NCy"78cTE`E`>`- --77 8r=ct|tjjr|j n|}t ||Sr)r-rmrrrxr)layersrlayers_weightss r; pack_weightszLoraBaseMixin.pack_weightss10:6588??0S**,Y_%nf==r=rxsave_directoryis_main_processrs save_functionsafe_serializationr&ctjj|rtj d|dyr |s t drt ts td||rfd}ntj}tj|d||rt}nt}t||j}|||tj!d |y) zLWrites the state dict of the LoRA layers (optionally with metadata) to disk.zProvided path (z#) should be a directory, not a fileNzP`lora_adapter_metadata` cannot be specified when not using `safe_serialization`.z/`lora_adapter_metadata` must be of type `dict`.cddi}rVjD]$\}}t|tst||<&t j dd|t <tjj|||S)Nformatptr T)indent sort_keys)rv) rr-rr/jsondumpsLORA_ADAPTER_METADATA_KEYrlrm save_file)rGfilenamervrrr&s r;rBz6LoraBaseMixin.write_lora_layers..save_functions ($/H,*?*E*E*GIJC)%5=A%[ 5c :I?Cjj1!t?!:;',,66wS[6\\r=T)exist_okzModel weights saved in )rrrrerrorr4r-rh TypeErrorrmsavemakedirsrkrqras_posixr)rxr@rArsrBrCr& save_paths ` r;write_lora_layerszLoraBaseMixin.write_lora_layerss 77>>. ) LL?>*::]^ _  );op p 4I4)PMN N  ! ]!&  NT2  !3 . 5>>@ j), -i[9:r=ct|S)N)r)r)rrs r;_optionally_disable_offloadingz,LoraBaseMixin._optionally_disable_offloading+s 2YGGr=r)rN)+r __module__ __qualname____doc__rrrpropertyfloatr6rrr classmethodrrrrrJboolrrrrrrr+r-r/r3rrmrgintr9r; staticmethodr?TensorrrhrVrXr+r=r;rrsa+u IEII**%%OLLMM=2!#!-1 XMIXMXM XM  S * XMt357-d3i7-xRVekT#Y^,ek"%tT%[$t*(L"MNekN9<8<$CU49c>-B$CLT#YB4T#Y#7,41T#Y41ellTWY\F\@]41bf41l8$>>150;ell*+0;0;0; 0;  0; ! 0; (~0;0;dHHr=r)r)FN)NNr)r[F)Nr)r5NNFFN)Jrr0rJrpathlibrtypingrrrrrrlrmtorch.nnrhuggingface_hubr huggingface_hub.constantsr models.modeling_utilsr r utilsrrrrrrrrrrrrrrrrrutils.peft_utilsrutils.state_dict_utilsr transformersr!peft.tuners.tuners_utilsr"accelerate.hooksr#r$r% get_loggerrrrqrkrLr<r@rJr]rKrRrTrYrzrjrr_rrrr+r=r;rps~  88 &4?&3B,7VV   H %-:3!)H  15LP)YcC()Y,-)Y#5U T$Z)G#HI)YX 49J0K 4 3x8I/J 33(L `\a$N $ o o d)OXO HO Hr=