Method map

webui/js/transformers@3.0.2.js:226–226

(e)

/*!*****************************!*\
  !*** ./src/utils/tensor.js ***!
  \*****************************/(e,t,n)=>{n.r(t),n.d(t,{Tensor:()=>o,cat:()=>y,full:()=>T,full_like:()=>k,interpolate:()=>u,interpolate_4d:()=>d,layer_norm:()=>f,matmul:()=>c,mean:()=>x,mean_pooling:()=>m,ones:()=>$,ones_like:()=>C,permute:()=>l,quantize_embeddings:()=>E,rfft:()=>p,stack:()=>b,std_mean:()=>v,topk:()=>h,zeros:()=>S,zeros_like:()=>P});var r=n(/*! ./maths.js */"./src/utils/maths.js"),a=n(/*! ../backends/onnx.js */"./src/backends/onnx.js"),s=n(/*! ../ops/registry.js */"./src/ops/registry.js");const i=Object.freeze({float32:Float32Array,float16:Uint16Array,float64:Float64Array,string:Array,int8:Int8Array,uint8:Uint8Array,int16:Int16Array,uint16:Uint16Array,int32:Int32Array,uint32:Uint32Array,int64:BigInt64Array,uint64:BigUint64Array,bool:Uint8Array});class o{get dims(){return this.ort_tensor.dims}set dims(e){this.ort_tensor.dims=e}get type(){return this.ort_tensor.type}get data(){return this.ort_tensor.data}get size(){return this.ort_tensor.size}get location(){return 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/*!*****************************!*\
  !*** ./src/transformers.js ***!
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bertaTokenizer,Gu=s.XLMTokenizer,Uu=s.XLMWithLMHeadModel,Wu=s.XVectorOutput,Hu=s.YolosFeatureExtractor,Xu=s.YolosForObjectDetection,Ku=s.YolosModel,Qu=s.YolosObjectDetectionOutput,Yu=s.YolosPreTrainedModel,Zu=s.ZeroShotAudioClassificationPipeline,Ju=s.ZeroShotClassificationPipeline,ed=s.ZeroShotImageClassificationPipeline,td=s.ZeroShotObjectDetectionPipeline,nd=s.bankers_round,rd=s.cat,ad=s.cos_sim,sd=s.dot,id=s.dynamic_time_warping,od=s.env,ld=s.full,ud=s.full_like,dd=s.getKeyValueShapes,cd=s.hamming,pd=s.hanning,hd=s.interpolate,md=s.interpolate_4d,fd=s.interpolate_data,gd=s.is_chinese_char,_d=s.layer_norm,wd=s.log_softmax,yd=s.magnitude,bd=s.matmul,vd=s.max,xd=s.mean,Md=s.mean_pooling,Td=s.medianFilter,kd=s.mel_filter_bank,$d=s.min,Cd=s.ones,Sd=s.ones_like,Pd=s.permute,Ed=s.permute_data,Fd=s.pipeline,Ad=s.quantize_embeddings,Id=s.read_audio,zd=s.rfft,Od=s.round,Bd=s.softmax,Ld=s.spectrogram,Dd=s.stack,Rd=s.std_mean,Nd=s.topk,Vd=s.window_function,jd=s.zeros,qd=s.zeros_like;export{w as ASTFeatureExtractor,y as ASTForAudioClassification,b as ASTModel,v as ASTPreTrainedModel,x as AlbertForMaskedLM,M as AlbertForQuestionAnswering,T as AlbertForSequenceClassification,k as AlbertModel,$ as AlbertPreTrainedModel,C as AlbertTokenizer,S as AudioClassificationPipeline,P as AutoConfig,E as AutoModel,F as AutoModelForAudioClassification,A as AutoModelForAudioFrameClassification,I as AutoModelForCTC,z as AutoModelForCausalLM,O as AutoModelForDepthEstimation,B as AutoModelForDocumentQuestionAnswering,L as AutoModelForImageClassification,D as AutoModelForImageFeatureExtraction,R as AutoModelForImageMatting,N as AutoModelForImageSegmentation,V as AutoModelForImageToImage,j as AutoModelForMaskGeneration,q as AutoModelForMaskedLM,G as AutoModelForNormalEstimation,U as AutoModelForObjectDetection,W as AutoModelForQuestionAnswering,H as AutoModelForSemanticSegmentation,X as AutoModelForSeq2SeqLM,K as AutoModelForSequenceClassification,Q as AutoModelForSpeechSeq2Seq,Y as AutoModelForTextToSpectrogram,Z as AutoModelForTextToWaveform,J as AutoModelForTokenClassification,ee as AutoModelForUniversalSegmentation,te as AutoModelForVision2Seq,ne as AutoModelForXVector,re as AutoModelForZeroShotObjectDetection,ae as AutoProcessor,se as AutoTokenizer,ie as AutomaticSpeechRecognitionPipeline,oe as BartForConditionalGeneration,le as BartForSequenceClassification,ue as BartModel,de as BartPretrainedModel,ce as BartTokenizer,pe as BaseModelOutput,he as BaseStreamer,me as BeitFeatureExtractor,fe as BeitForImageClassification,ge as BeitModel,_e as BeitPreTrainedModel,we as BertForMaskedLM,ye as BertForQuestionAnswering,be as BertForSequenceClassification,ve as BertForTokenClassification,xe as BertModel,Me as BertPreTrainedModel,Te as BertTokenizer,ke as BitImageProcessor,$e as BlenderbotForConditionalGeneration,Ce as BlenderbotModel,Se as BlenderbotPreTrainedModel,Pe as BlenderbotSmallForConditionalGeneration,Ee as BlenderbotSmallModel,Fe as BlenderbotSmallPreTrainedModel,Ae as BlenderbotSmallTokenizer,Ie as BlenderbotTokenizer,ze as BloomForCausalLM,Oe as BloomModel,Be as BloomPreTrainedModel,Le as BloomTokenizer,De as CLIPFeatureExtractor,Re as CLIPImageProcessor,Ne as CLIPModel,Ve as CLIPPreTrainedModel,je as CLIPSegForImageSegmentation,qe as CLIPSegModel,Ge as CLIPSegPreTrainedModel,Ue as CLIPTextModel,We as CLIPTextModelWithProjection,He as CLIPTokenizer,Xe as CLIPVisionModel,Ke as CLIPVisionModelWithProjection,Qe as CamembertForMaskedLM,Ye as CamembertForQuestionAnswering,Ze as CamembertForSequenceClassification,Je as CamembertForTokenClassification,et as CamembertModel,tt as CamembertPreTrainedModel,nt as CamembertTokenizer,rt as CausalLMOutput,at as CausalLMOutputWithPast,st as ChineseCLIPFeatureExtractor,it as ChineseCLIPModel,ot as ChineseCLIPPreTrainedModel,lt as ClapAudioModelWithProjection,ut as ClapFeatureExtractor,dt as ClapModel,ct as ClapPreTrainedModel,pt as ClapTextModelWithProjection,ht as CodeGenForCausalLM,mt as CodeGenModel,ft as CodeGenPreTrainedModel,gt as CodeGenTokenizer,_t as CodeLlamaTokenizer,wt as CohereForCausalLM,yt as CohereModel,bt as CoherePreTrainedModel,vt as CohereTokenizer,xt as ConvBertForMaskedLM,Mt as ConvBertForQuestionAnswering,Tt as ConvBertForSequenceClassification,kt as ConvBertForTokenClassification,$t as ConvBertModel,Ct as ConvBertPreTrainedModel,St as ConvBertTokenizer,Pt as ConvNextFeatureExtractor,Et as ConvNextForImageClassification,Ft as ConvNextImageProcessor,At as ConvNextModel,It as ConvNextPreTrainedModel,zt as ConvNextV2ForImageClassification,Ot as ConvNextV2Model,Bt as ConvNextV2PreTrainedModel,Lt as DPTFeatureExtractor,Dt as DPTForDepthEstimation,Rt as DPTImageProcessor,Nt as DPTModel,Vt as DPTPreTrainedModel,jt as DebertaForMaskedLM,qt as DebertaForQuestionAnswering,Gt as DebertaForSequenceClassification,Ut as DebertaForTokenClassification,Wt as DebertaModel,Ht as DebertaPreTrainedModel,Xt as DebertaTokenizer,Kt as DebertaV2ForMaskedLM,Qt as DebertaV2ForQuestionAnswering,Yt as DebertaV2ForSequenceClassification,Zt as DebertaV2ForTokenClassification,Jt as DebertaV2Model,en as DebertaV2PreTrainedModel,tn as DebertaV2Tokenizer,nn as DecisionTransformerModel,rn as DecisionTransformerPreTrainedModel,an as DeiTFeatureExtractor,sn as DeiTForImageClassification,on as DeiTModel,ln as DeiTPreTrainedModel,un as DepthAnythingForDepthEstimation,dn as DepthAnythingPreTrainedModel,cn as DepthEstimationPipeline,pn as DepthProForDepthEstimation,hn as DepthProPreTrainedModel,mn as DetrFeatureExtractor,fn as DetrForObjectDetection,gn as DetrForSegmentation,_n as DetrModel,wn as DetrObjectDetectionOutput,yn as DetrPreTrainedModel,bn as DetrSegmentationOutput,vn as Dinov2ForImageClassification,xn as Dinov2Model,Mn as Dinov2PreTrainedModel,Tn as DistilBertForMaskedLM,kn as DistilBertForQuestionAnswering,$n as DistilBertForSequenceClassification,Cn as DistilBertForTokenClassification,Sn as DistilBertModel,Pn as DistilBertPreTrainedModel,En as DistilBertTokenizer,Fn as DocumentQuestionAnsweringPipeline,An as DonutFeatureExtractor,In as DonutImageProcessor,zn as DonutSwinModel,On as DonutSwinPreTrainedModel,Bn as EfficientNetForImageClassification,Ln as EfficientNetImageProcessor,Dn as EfficientNetModel,Rn as EfficientNetPreTrainedModel,Nn as ElectraForMaskedLM,Vn as ElectraForQuestionAnswering,jn as ElectraForSequenceClassification,qn as ElectraForTokenClassification,Gn as ElectraModel,Un as ElectraPreTrainedModel,Wn as ElectraTokenizer,Hn as EosTokenCriteria,Xn as EsmForMaskedLM,Kn as EsmForSequenceClassification,Qn as EsmForTokenClassification,Yn as EsmModel,Zn as EsmPreTrainedModel,Jn as EsmTokenizer,er as FFT,tr as FalconForCausalLM,nr as FalconModel,rr as FalconPreTrainedModel,ar as FalconTokenizer,sr as FastViTForImageClassification,ir as FastViTModel,or as FastViTPreTrainedModel,lr as FeatureExtractionPipeline,ur as FeatureExtractor,dr as FillMaskPipeline,cr as Florence2ForConditionalGeneration,pr as Florence2PreTrainedModel,hr as Florence2Processor,mr as GLPNFeatureExtractor,fr as GLPNForDepthEstimation,gr as GLPNModel,_r as GLPNPreTrainedModel,wr as GPT2LMHeadModel,yr as GPT2Model,br as GPT2PreTrainedModel,vr as GPT2Tokenizer,xr as GPTBigCodeForCausalLM,Mr as GPTBigCodeModel,Tr as GPTBigCodePreTrainedModel,kr as GPTJForCausalLM,$r as GPTJModel,Cr as GPTJPreTrainedModel,Sr as GPTNeoForCausalLM,Pr as GPTNeoModel,Er as GPTNeoPreTrainedModel,Fr as GPTNeoXForCausalLM,Ar as GPTNeoXModel,Ir as GPTNeoXPreTrainedModel,zr as GPTNeoXTokenizer,Or as Gemma2ForCausalLM,Br as Gemma2Model,Lr as Gemma2PreTrainedModel,Dr as GemmaForCausalLM,Rr as GemmaModel,Nr as GemmaPreTrainedModel,Vr as GemmaTokenizer,jr as GraniteForCausalLM,qr as GraniteModel,Gr as GranitePreTrainedModel,Ur as Grok1Tokenizer,Wr as GroupViTModel,Hr as GroupViTPreTrainedModel,Xr as HerbertTokenizer,Kr as HieraForImageClassification,Qr as HieraModel,Yr as HieraPreTrainedModel,Zr as HubertForCTC,Jr as HubertForSequenceClassification,ea as HubertModel,ta as HubertPreTrainedModel,na as ImageClassificationPipeline,ra as ImageFeatureExtractionPipeline,aa as ImageFeatureExtractor,sa as ImageMattingOutput,ia as ImageSegmentationPipeline,oa as ImageToImagePipeline,la as ImageToTextPipeline,ua as InterruptableStoppingCriteria,da as JAISLMHeadModel,ca as JAISModel,pa as JAISPreTrainedModel,ha as LlamaForCausalLM,ma as LlamaModel,fa as LlamaPreTrainedModel,ga as LlamaTokenizer,_a as LlavaForConditionalGeneration,wa as LlavaPreTrainedModel,ya as LongT5ForConditionalGeneration,ba as LongT5Model,va as LongT5PreTrainedModel,xa as M2M100ForConditionalGeneration,Ma as M2M100Model,Ta as M2M100PreTrainedModel,ka as M2M100Tokenizer,$a as MBart50Tokenizer,Ca as MBartForCausalLM,Sa as MBartForConditionalGeneration,Pa as MBartForSequenceClassification,Ea as MBartModel,Fa as MBartPreTrainedModel,Aa as MBartTokenizer,Ia as MPNetForMaskedLM,za as MPNetForQuestionAnswering,Oa as MPNetForSequenceClassification,Ba as MPNetForTokenClassification,La as MPNetModel,Da as MPNetPreTrainedModel,Ra as MPNetTokenizer,Na as MT5ForConditionalGeneration,Va as MT5Model,ja as MT5PreTrainedModel,qa as MarianMTModel,Ga as MarianModel,Ua as MarianPreTrainedModel,Wa as MarianTokenizer,Ha as MaskFormerFeatureExtractor,Xa as MaskFormerForInstanceSegmentation,Ka as MaskFormerModel,Qa as MaskFormerPreTrainedModel,Ya as MaskedLMOutput,Za as MaxLengthCriteria,Ja as MistralForCausalLM,es as MistralModel,ts as MistralPreTrainedModel,ns as MobileBertForMaskedLM,rs as MobileBertForQuestionAnswering,as as MobileBertForSequenceClassification,ss as MobileBertModel,is as MobileBertPreTrainedModel,os as MobileBertTokenizer,ls as MobileLLMForCausalLM,us as MobileLLMModel,ds as MobileLLMPreTrainedModel,cs as MobileNetV1FeatureExtractor,ps as MobileNetV1ForImageClassification,hs as MobileNetV1Model,ms as MobileNetV1PreTrainedModel,fs as MobileNetV2FeatureExtractor,gs as MobileNetV2ForImageClassification,_s as MobileNetV2Model,ws as MobileNetV2PreTrainedModel,ys as MobileNetV3FeatureExtractor,bs as MobileNetV3ForImageClassification,vs as MobileNetV3Model,xs as MobileNetV3PreTrainedModel,Ms as MobileNetV4FeatureExtractor,Ts as MobileNetV4ForImageClassification,ks as MobileNetV4Model,$s as MobileNetV4PreTrainedModel,Cs as MobileViTFeatureExtractor,Ss as MobileViTForImageClassification,Ps as MobileViTImageProcessor,Es as MobileViTModel,Fs as MobileViTPreTrainedModel,As as MobileViTV2ForImageClassification,Is as MobileViTV2Model,zs as MobileViTV2PreTrainedModel,Os as ModelOutput,Bs as Moondream1ForConditionalGeneration,Ls as MptForCausalLM,Ds as MptModel,Rs as MptPreTrainedModel,Ns as MusicgenForCausalLM,Vs as MusicgenForConditionalGeneration,js as MusicgenModel,qs as MusicgenPreTrainedModel,Gs as NllbTokenizer,Us as NomicBertModel,Ws as NomicBertPreTrainedModel,Hs as NougatImageProcessor,Xs as NougatTokenizer,Ks as OPTForCausalLM,Qs as OPTModel,Ys as OPTPreTrainedModel,Zs as ObjectDetectionPipeline,Js as OlmoForCausalLM,ei as OlmoModel,ti as OlmoPreTrainedModel,ni as OpenELMForCausalLM,ri as OpenELMModel,ai as OpenELMPreTrainedModel,si as OwlViTFeatureExtractor,ii as OwlViTForObjectDetection,oi as OwlViTModel,li as OwlViTPreTrainedModel,ui as OwlViTProcessor,di as Owlv2ForObjectDetection,ci as Owlv2ImageProcessor,pi as Owlv2Model,hi as Owlv2PreTrainedModel,mi as Phi3ForCausalLM,fi as Phi3Model,gi as Phi3PreTrainedModel,_i as PhiForCausalLM,wi as PhiModel,yi as PhiPreTrainedModel,bi as Pipeline,vi as PreTrainedModel,xi as PreTrainedTokenizer,Mi as PretrainedConfig,Ti as PretrainedMixin,ki as Processor,$i as PvtForImageClassification,Ci as PvtImageProcessor,Si as PvtModel,Pi as PvtPreTrainedModel,Ei as PyAnnoteFeatureExtractor,Fi as PyAnnoteForAudioFrameClassification,Ai as PyAnnoteModel,Ii as PyAnnotePreTrainedModel,zi as PyAnnoteProcessor,Oi as QuestionAnsweringModelOutput,Bi as QuestionAnsweringPipeline,Li as Qwen2ForCausalLM,Di as Qwen2Model,Ri as Qwen2PreTrainedModel,Ni as Qwen2Tokenizer,Vi as RTDetrForObjectDetection,ji as RTDetrImageProcessor,qi as RTDetrModel,Gi as RTDetrObjectDetectionOutput,Ui as RTDetrPreTrainedModel,Wi as RawImage,Hi as ResNetForImageClassification,Xi as ResNetModel,Ki as ResNetPreTrainedModel,Qi as RoFormerForMaskedLM,Yi as RoFormerForQuestionAnswering,Zi as RoFormerForSequenceClassification,Ji as RoFormerForTokenClassification,eo as RoFormerModel,to as RoFormerPreTrainedModel,no as RoFormerTokenizer,ro as RobertaForMaskedLM,ao as RobertaForQuestionAnswering,so as RobertaForSequenceClassification,io as RobertaForTokenClassification,oo as RobertaModel,lo as RobertaPreTrainedModel,uo as RobertaTokenizer,co as SamImageProcessor,po as SamImageSegmentationOutput,ho as SamModel,mo as SamPreTrainedModel,fo as SamProcessor,go as SapiensFeatureExtractor,_o as SapiensForDepthEstimation,wo as SapiensForNormalEstimation,yo as SapiensForSemanticSegmentation,bo as SapiensPreTrainedModel,vo as SeamlessM4TFeatureExtractor,xo as SegformerFeatureExtractor,Mo as SegformerForImageClassification,To as SegformerForSemanticSegmentation,ko as SegformerModel,$o as SegformerPreTrainedModel,Co as Seq2SeqLMOutput,So as SequenceClassifierOutput,Po as SiglipImageProcessor,Eo as SiglipModel,Fo as SiglipPreTrainedModel,Ao as SiglipTextModel,Io as SiglipTokenizer,zo as SiglipVisionModel,Oo as SpeechT5FeatureExtractor,Bo as SpeechT5ForSpeechToText,Lo as SpeechT5ForTextToSpeech,Do as SpeechT5HifiGan,Ro as SpeechT5Model,No as SpeechT5PreTrainedModel,Vo as SpeechT5Processor,jo as SpeechT5Tokenizer,qo as SqueezeBertForMaskedLM,Go as SqueezeBertForQuestionAnswering,Uo as SqueezeBertForSequenceClassification,Wo as SqueezeBertModel,Ho as SqueezeBertPreTrainedModel,Xo as SqueezeBertTokenizer,Ko as StableLmForCausalLM,Qo as StableLmModel,Yo as StableLmPreTrainedModel,Zo as Starcoder2ForCausalLM,Jo as Starcoder2Model,el as Starcoder2PreTrainedModel,tl as StoppingCriteria,nl as StoppingCriteriaList,rl as SummarizationPipeline,al as Swin2SRForImageSuperResolution,sl as Swin2SRImageProcessor,il as Swin2SRModel,ol as Swin2SRPreTrainedModel,ll as SwinForImageClassification,ul as SwinModel,dl as SwinPreTrainedModel,cl as T5ForConditionalGeneration,pl as T5Model,hl as T5PreTrainedModel,ml as T5Tokenizer,fl as TableTransformerForObjectDetection,gl as TableTransformerModel,_l as TableTransformerObjectDetectionOutput,wl as TableTransformerPreTrainedModel,yl as Tensor,bl as Text2TextGenerationPipeline,vl as TextClassificationPipeline,xl as TextGenerationPipeline,Ml as TextStreamer,Tl as TextToAudioPipeline,kl as TokenClassificationPipeline,$l as TokenClassifierOutput,Cl as TokenizerModel,Sl as TrOCRForCausalLM,Pl as TrOCRPreTrainedModel,El as TranslationPipeline,Fl as UniSpeechForCTC,Al as UniSpeechForSequenceClassification,Il as UniSpeechModel,zl as UniSpeechPreTrainedModel,Ol as UniSpeechSatForAudioFrameClassification,Bl as UniSpeechSatForCTC,Ll as UniSpeechSatForSequenceClassification,Dl as UniSpeechSatModel,Rl as UniSpeechSatPreTrainedModel,Nl as ViTFeatureExtractor,Vl as ViTForImageClassification,jl as ViTImageProcessor,ql as ViTMAEModel,Gl as ViTMAEPreTrainedModel,Ul as ViTMSNForImageClassification,Wl as ViTMSNModel,Hl as ViTMSNPreTrainedModel,Xl as ViTModel,Kl as ViTPreTrainedModel,Ql as VisionEncoderDecoderModel,Yl as VitMatteForImageMatting,Zl as VitMatteImageProcessor,Jl as VitMattePreTrainedModel,eu as VitsModel,tu as VitsModelOutput,nu as VitsPreTrainedModel,ru as VitsTokenizer,au as Wav2Vec2BertForCTC,su as Wav2Vec2BertForSequenceClassification,iu as Wav2Vec2BertModel,ou as Wav2Vec2BertPreTrainedModel,lu as Wav2Vec2CTCTokenizer,uu as Wav2Vec2FeatureExtractor,du as Wav2Vec2ForAudioFrameClassification,cu as Wav2Vec2ForCTC,pu as Wav2Vec2ForSequenceClassification,hu as Wav2Vec2Model,mu as Wav2Vec2PreTrainedModel,fu as Wav2Vec2ProcessorWithLM,gu as WavLMForAudioFrameClassification,_u as WavLMForCTC,wu as WavLMForSequenceClassification,yu as WavLMForXVector,bu as WavLMModel,vu as WavLMPreTrainedModel,xu as WeSpeakerFeatureExtractor,Mu as WeSpeakerResNetModel,Tu as WeSpeakerResNetPreTrainedModel,ku as WhisperFeatureExtractor,$u as WhisperForConditionalGeneration,Cu as WhisperModel,Su as WhisperPreTrainedModel,Pu as WhisperProcessor,Eu as WhisperTextStreamer,Fu as WhisperTokenizer,Au as XLMForQuestionAnswering,Iu as XLMForSequenceClassification,zu as XLMForTokenClassification,Ou as XLMModel,Bu as XLMPreTrainedModel,Lu as XLMRobertaForMaskedLM,Du as XLMRobertaForQuestionAnswering,Ru as XLMRobertaForSequenceClassification,Nu as XLMRobertaForTokenClassification,Vu as XLMRobertaModel,ju as XLMRobertaPreTrainedModel,qu as XLMRobertaTokenizer,Gu as XLMTokenizer,Uu as XLMWithLMHeadModel,Wu as XVectorOutput,Hu as YolosFeatureExtractor,Xu as YolosForObjectDetection,Ku as YolosModel,Qu as YolosObjectDetectionOutput,Yu as YolosPreTrainedModel,Zu as ZeroShotAudioClassificationPipeline,Ju as ZeroShotClassificationPipeline,ed as ZeroShotImageClassificationPipeline,td as ZeroShotObjectDetectionPipeline,nd as bankers_round,rd as cat,ad as cos_sim,sd as dot,id as dynamic_time_warping,od as env,ld as full,ud as full_like,dd as getKeyValueShapes,cd as hamming,pd as hanning,hd as interpolate,md as interpolate_4d,fd as interpolate_data,gd as is_chinese_char,_d as layer_norm,wd as log_softmax,yd as magnitude,bd as matmul,vd as max,xd as mean,Md as mean_pooling,Td as medianFilter,kd as mel_filter_bank,$d as min,Cd as ones,Sd as ones_like,Pd as permute,Ed as permute_data,Fd as pipeline,Ad as quantize_embeddings,Id as read_audio,zd as rfft,Od as round,Bd as softmax,Ld as spectrogram,Dd as stack,Rd as std_mean,Nd as topk,Vd as window_function,jd as zeros,qd as zeros_like};