3j>$SrSSKrSSKrSSKrSSKJr SSKJr SSKJ r J r J r SSK J r \R"\5r\ "5(aSSKrSrS rSS \S-4S jjrSS jrS rSSjrSrSrSS\4SjjrS\SS4SjrSSjrSrSr g)z3 PEFT utilities: Utilities related to peft library N)version)logging)is_peft_availableis_peft_versionis_torch_available)empty_device_cachec SSKJn SnUR5H!n[X15(dM[ US5n O U(avSSKJn UR5VVs/sHupVSU;dM UPM nnnUH<nU"X5upn [ U S5(dM"[XU R55 M> U$SSK J n UR5GHup[[UR!555S:a [#U5 Sn [X;5(a[U[$R&R(5(a[$R&R)UR*UR,UR.SLS 9R1UR2R45nUR2UlUR.bUR.UlS n O[X;5(a[U[$R&R65(a[$R&R7UR8UR:UR<UR>UR@URBURD5R1UR2R45nUR2UlUR.bUR.UlS n U (dGM[X W5 A[G5 GM" U$s snnf![a GMf=f) z\ Recursively replace all instances of `LoraLayer` with corresponding new layers in `model`. rBaseTunerLayerF base_layer)_get_submoduleslora) LoraLayerN)biasT)$peft.tuners.tuners_utilsr modules isinstancehasattr peft.utilsr named_modulesAttributeErrorsetattrget_base_layerpeft.tuners.lorarnamed_childrenlenlistchildrenrecurse_remove_peft_layerstorchnnLinear in_features out_featuresrtoweightdeviceConv2d in_channels out_channels kernel_sizestridepaddingdilationgroupsr )modelr has_base_layer_patternmodulerkey_key_listparenttarget target_namernamemodule_replaced new_modules T/home/wildlama/miniconda3/lib/python3.13/site-packages/diffusers/utils/peft_utils.pyr r #sk8"--/ f - -%,V\%B " " .&+&9&9&;Q&;FCvS?PC&;QC .=e.I+ v|,,V-B-B-DE h LU /!002LD4)*+a/*62#O&,,FEHHOO1T1T"XX__&&''D0-"V]]))*  %+MM !;;*&,kkJO"&F..:fehhoo3V3V"XX__&&''&&MMNNOOMM"V]]))*%+MM !;;*&,kkJO"&Z0"$O3P LkR"  s K7.K7= K== L  L cSSKJn US:XagUR5H&n[X25(dMUR U5 M( g)z Adjust the weightage given to the LoRA layers of the model. Args: model (`torch.nn.Module`): The model to scale. weight (`float`): The weight to be given to the LoRA layers. rr ?N)rr rr scale_layer)r1r'r r3s r=scale_lora_layersrAjs:8 }--/ f - -   v &"r'cSSKJn UbUS:XagUR5HSn[X25(dMUS:waUR U5 M.UR HnUR US5 M MU g)a Removes the previously passed weight given to the LoRA layers of the model. Args: model (`torch.nn.Module`): The model to scale. weight (`float`, *optional*): The weight to be given to the LoRA layers. If no scale is passed the scale of the lora layer will be re-initialized to the correct value. If 0.0 is passed, we will re-initialize the scale with the correct value. rr Nr?)rr rr unscale_layeractive_adapters set_scale)r1r'r r3 adapter_names r=unscale_lora_layersrH~se8 ~3--/ f - -{$$V,$*$:$:L$$\37%; "rBc ^^0n0n[UR55S=mm[[UR555S:a[R "UR55R 5SSm[[U4SjUR555nUR5VV s0sHupURS5SU _M nnn UGb[U5S:Gas[[UR555S:Ga%[R "UR55R 5SSm[[U4SjUR555nU(afUR5VV s0sHHupSRURS5SRS55RSS 5U _MJ nnn OUR5VV s0sH;upSRURS 5SRS5SS 5U _M= nnn O'[UR55R5m[UR5V s1sHoRS 5SiM sn 5n [S U55n [SU55n TTUUU U U S.nU$s sn nfs sn nfs sn nfs sn f)Nrrc>UST:g$Nr)xrs r=!get_peft_kwargs..s QqTQYrBz.lora_B.c>UST:g$rKrL)rM lora_alphas r=rOrPs!A$*2DrB.z.lora_A.z.alphaz.down.z.lorac3,# UH nSU;v M g7f)lora_magnitude_vectorNrL.0ks r= "get_peft_kwargs..sIA*a/sc3\# UH"nSU;=(a URS5v M$ g7f)lora_Bz.biasN)endswithrXs r=r[r\s%S?aHM9ajj&99?s*,)rNrR rank_pattern alpha_patterntarget_modulesuse_dora lora_bias)rvaluesrset collectionsCounter most_commondictfilteritemssplitjoinreplacepopkeysany) rank_dictnetwork_alpha_dictpeft_state_dictis_unetmodel_state_dictrGr`rarZvr:rbrcrdlora_config_kwargsrRrNs @@r=get_peft_kwargsrzsLM)**,-a00A  3y! "#a'    0 0 2 3 ? ? A! DQ GF#6 8IJK >J>P>P>RS>Rda +A.1>R S%#.@*AA*E s%,,./ 01 4$,,-?-F-F-HIUUWXYZ[\]J!(DFXF^F^F`!abM!. 3 3 5! 5HHQWWZ0399#>?GGRTUWXX 5! `m_r_r_t u_tW[WX!''(*;A*>*D*DS*I#2*N!OQR!R_t u /6689==?Jo>R>R>TU>Td::g.q1>TUVNIIIHS?SSI $&( ET! !vVs=!KAK;AK?K%cSSKJn UR5H-n[X!5(dMS[ UR 53s $ g)Nrr default_ default_0)rr rrrrN)r1r r3s r=get_adapter_namer~s:7--/ f - -c&((m_- -" rBcSSKJn UR5HCn[X25(dM[ US5(aUR US9 M7U(+UlME g)Nrr enable_adapters)enabled)rr rrrrdisable_adapters)r1rr r3s r=set_adapter_layersrsI7--/ f - -v011&&w&7.5+' "rBcSSKJn UR5HBn[X25(dM[ US5(aUR U5 M9[ S5e [USS5(aR[ US5(a@URRUS5 [UR5S:Xa U?SUl gggg)Nrr delete_adapterzdThe version of PEFT you are using is not compatible, please use a version that is greater than 0.6.1_hf_peft_config_loadedF peft_config) rr rrrr ValueErrorgetattrrrprr)r1rGr r3s r=delete_adapter_layersrs7--/ f - -v/00%%l3 z "u.6675-;X;X lD1 u  !Q &!+/E ( ' .get_module_weights,d33% %#5#;#;#= J($>!!#&q !E!H:\%(<)--c37 rB set_adapter) rr rrrractive_adapterziprF) r1 adapter_namesweightsr rrr3rGr's r=!set_weights_and_activate_adaptersrsy7 %224 f - -v}--""=1(5%),M(C$   /@/UV)D 5rB kwargs_namec^U4SjnU$)a Decorator to automatically handle LoRA layer scaling/unscaling in forward methods. This decorator extracts the `lora_scale` from the specified kwargs parameter, applies scaling before the forward pass, and ensures unscaling happens after, even if an exception occurs. Args: kwargs_name (`str`, defaults to `"joint_attention_kwargs"`): The name of the keyword argument that contains the LoRA scale. Common values include "joint_attention_kwargs", "attention_kwargs", "cross_attention_kwargs", etc. cJ>^[R"T5UU4Sj5nU$)Ncl>SSKJn SnURT5nUbLUR5nXRT'UR SS5nU(dUS:wa[ R STS35 U(a [X5 T"U/UQ70UD6nUU(a [X5 $$!U(a [X5 ff=f)Nr)USE_PEFT_BACKENDr?scalezPassing `scale` via `z1` when not using the PEFT backend is ineffective.) rTrrcopyrploggerwarningrArH) selfargskwargsr lora_scaleattention_kwargsresult forward_fnrs r=wrapper4apply_lora_scale..decorator..wrapper$s *J%zz+6 +#3#8#8#: &6{#-11'3? 'J#,=NN/ }.decorator#s%  $ : % ::rBrL)rrs` r=apply_lora_scalersB rB min_versionreturnc[5(d [S5e[R"[R RS55[R"U5:nU(d[SU35eg)zx Checks if the version of PEFT is compatible. Args: version (`str`): The version of PEFT to check against. z@PEFT is not installed. Please install it with `pip install peft`peftz_The version of PEFT you are using is not compatible, please use a version that is greater than N)rrrparse importlibmetadata)ris_peft_version_compatibles r=check_peft_versionrGso   [\\!(y/A/A/I/I&/Q!RU\UbUbcnUo!o % M #   &rBc JSSKJn UbUnO[UUUUUUS9n[U5 SU;a&US(a[ SS5(a [ S5eSU;a&US(a[ S S 5(a [ S 5eU"S 0UD6$![ an [ S 5U eSn A ff=f)Nr) LoraConfig)rtrurvrwrGrc= 0.9.0. Please upgrade.rdz<=z0.13.2z2lora_bias requires PEFT >= 0.14.0. Please upgrade.z-`LoraConfig` class could not be instantiated.rL)rrrz%_maybe_raise_error_for_ambiguous_keysrr TypeError) state_dictnetwork_alphasrrank_pattern_dictrvrwrGrryes r=_create_lora_configr[s %, -&-%  **<='',>z,J 3 ( (KL L((-? -L 4 * *QR RP/.// PGHaOPs?B B" BB"cVUSR5nUSn[UR55HjnUVs/sH oDU:XdM UPM nnUVs/sHoCU;dM XC:wdMUPM nnU(dMEU(dMN[SS5(dMa[ S5e gs snfs snf)Nr`rbrz0.14.1zzThere are ambiguous keys present in this LoRA. To load it, please update your `peft` installation - `pip install -U peft`.)rrrqrr)configr`rbr4mod exact_matchessubstring_matchess r=rr}s.)..0L,-NL%%'( )7E* E,:XNSSjSSZSNX =..sH-- Q) FXs B!B! B&B&&B&cSnUb[USS5nU(a=UVs/sHnSU;dM X;dMUPM nnU(aSSRU5S3n[USS5nU(a@UVs/sHnSU;dM X;dMUPM nnU(aUSSRU5S 3- nU(a[RU5 ggs snfs snf) NrTunexpected_keyslora_zSLoading adapter weights from state_dict led to unexpected keys found in the model: z, z. missing_keyszJLoading adapter weights from state_dict led to missing keys in the model: rS)rrnrr)incompatible_keysrGwarn_msgrrZlora_unexpected_keysrlora_missing_keyss r=_maybe_warn_for_unhandled_keysrsH$!"35FM />#e!'Q,AS_SdA #e# "678< 0.$G ,8 _LqGqL\M^L  _  "345Q8 x #$f!`s! C C C / C=CC)N)TNN)T)joint_attention_kwargs)!__doc__rgrr packagingrrTr import_utilsrrr torch_utilsr get_logger__name__rr!r rAfloatrHrzr~rrrstrrrrrrrLrBr=rsPP+   H %DN'(8ut|88gk/d 60,W@.#.b C D *ptPD(!rB