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| Interrompere | Solleva un'eccezione per interrompere il processo quando viene chiamato. |
| Interrompi.Opzioni | Attributi facoltativi per Abort |
| Abs <T estende TNumero > | Calcola il valore assoluto di un tensore. |
| AbstractDataBuffer <T> | |
| AbstractDataBufferWindow <B estende DataBuffer <?>> | |
| AbstractDenseNdArray <T, U estende NdArray <T>> | |
| AbstractNdArray <T, U estende NdArray <T>> | |
| AbstractTF_Buffer | |
| AbstractTF_Graph | |
| AbstractTF_ImportGraphDefOptions | |
| AbstractTF_Session | |
| AbstractTF_SessionOptions | |
| AbstractTF_Status | |
| AbstractTF_Tensore | |
| AbstractTFE_Contesto | |
| AbstractTFE_ContextOptions | |
| AbstractTFE_Op | |
| AbstractTFE_TensorHandle | |
| AccumulaN <T estende TType > | Restituisce la somma degli elementi di una lista di tensori. |
| AccumulatoreApplicaGradiente | Applica un gradiente a un determinato accumulatore. |
| AccumulatoreNumAccumulato | Restituisce il numero di gradienti aggregati negli accumulatori specificati. |
| AccumulatoreImpostaGlobalStep | Aggiorna l'accumulatore con un nuovo valore per global_step. |
| AccumulatorTakeGradient <T estende TType > | Estrae il gradiente medio nel ConditionalAccumulatore specificato. |
| Acos <T estende TType > | Calcola acos di x a livello di elemento. |
| Acosh <T estende TType > | Calcola il coseno iperbolico inverso di x rispetto agli elementi. |
| L'attivazione <T estende TNumero > | Classe base astratta per le attivazioni Nota: l'attributo |
| AdaDelta | Ottimizzatore che implementa l'algoritmo Adadelta. |
| AdaGrad | Ottimizzatore che implementa l'algoritmo Adagrad. |
| AdaGradDA | Ottimizzatore che implementa l'algoritmo Adagrad Dual-Averaging. |
| Adamo | Ottimizzatore che implementa l'algoritmo di Adam. |
| Adamax | Ottimizzatore che implementa l'algoritmo Adamax. |
| Aggiungi <T estende TType > | Restituisce x + y per elemento. |
| AggiungiManySparseToTensorsMap | Aggiungi un `N`-minibatch `SparseTensor` a un `SparseTensorsMap`, restituisci `N` handle. |
| AddManySparseToTensorsMap.Options | Attributi facoltativi per AddManySparseToTensorsMap |
| AddN <T estende TType > | Aggiungi tutti i tensori di input in termini di elementi. |
| AggiungiSparseToTensorsMap | Aggiungi uno `SparseTensor` a uno `SparseTensorsMap` che restituisce il suo handle. |
| AddSparseToTensorsMap.Options | Attributi facoltativi per AddSparseToTensorsMap |
| RegolaContrasto <T estende TNumero > | Regola il contrasto di una o più immagini. |
| RegolaHue <T estende TNumero > | Regola la tonalità di una o più immagini. |
| RegolaSaturazione <T estende TNumero > | Regola la saturazione di una o più immagini. |
| Tutto | Calcola la "logica e" degli elementi attraverso le dimensioni di un tensore. |
| Tutte.Opzioni | Attributi facoltativi per All |
| AllCandidateSampler | Genera etichette per il campionamento dei candidati con una distribuzione unigramma appresa. |
| AllCandidateSampler.Options | Attributi facoltativi per AllCandidateSampler |
| Descrizione dell'allocazione | Tipo di protocollo tensorflow.AllocationDescription |
| AllocationDescription.Builder | Tipo di protocollo tensorflow.AllocationDescription |
| AllocazioneDescrizioneOrBuilder | |
| AllocazioneDescrizioneProtos | |
| Record di allocazione | An allocation/de-allocation operation performed by the allocator. |
| AllocationRecord.Builder | An allocation/de-allocation operation performed by the allocator. |
| AllocazioneRecordOrBuilder | |
| AllocatorMemoryUsed | Tipo di protocollo tensorflow.AllocatorMemoryUsed |
| AllocatorMemoryUsed.Builder | Tipo di protocollo tensorflow.AllocatorMemoryUsed |
| AllocatorMemoryUsedOrBuilder | |
| AllReduce <T estende TNumero > | Riduce reciprocamente più tensori di identico tipo e forma. |
| AllReduce.Options | Attributi facoltativi per AllReduce |
| AllToAll <T estende TType > | Un'operazione per scambiare dati tra repliche TPU. |
| Angolo <U estende TNumero > | Restituisce l'argomento di un numero complesso. |
| AnonymousIterator | Un contenitore per una risorsa iteratore. |
| AnonymousMemoryCache | |
| AnonimoMultiDeviceIterator | Un contenitore per una risorsa iteratore multidispositivo. |
| Generatore di semi casuali anonimo | |
| Generatore di semi anonimo | |
| Qualunque | Calcola l'"or logico" degli elementi attraverso le dimensioni di un tensore. |
| Qualsiasi.Opzione | Attributi facoltativi per Any |
| ApiDef | Used to specify and override the default API & behavior in the generated code for client languages, from what you would get from the OpDef alone. |
| ApiDef.Arg | Tipo di protocollo tensorflow.ApiDef.Arg |
| ApiDef.Arg.Builder | Tipo di protocollo tensorflow.ApiDef.Arg |
| ApiDef.ArgOrBuilder | |
| ApiDef.Attr | Description of the graph-construction-time configuration of this Op. |
| ApiDef.Attr.Builder | Description of the graph-construction-time configuration of this Op. |
| ApiDef.AttrOrBuilder | |
| ApiDef.Builder | Used to specify and override the default API & behavior in the generated code for client languages, from what you would get from the OpDef alone. |
| ApiDef.Endpoint | If you specify any endpoint, this will replace all of the inherited endpoints. |
| ApiDef.Endpoint.Builder | If you specify any endpoint, this will replace all of the inherited endpoints. |
| ApiDef.EndpointOrBuilder | |
| ApiDef.Visibilità | Protobuf enum tensorflow.ApiDef.Visibility |
| ApiDefOrBuilder | |
| ApiDefProtos | |
| ApiDef | Tipo di protocollo tensorflow.ApiDefs |
| ApiDefs.Builder | Tipo di protocollo tensorflow.ApiDefs |
| ApiDefsOrBuilder | |
| ApplyAdadelta <T estende TType > | Aggiorna '*var' secondo lo schema adadelta. |
| ApplicaAdadelta.Options | Attributi facoltativi per ApplyAdadelta |
| ApplyAdagrad <T estende TType > | Aggiorna '*var' secondo lo schema adagrad. |
| ApplicaAdagrad.Options | Attributi facoltativi per ApplyAdagrad |
| ApplyAdagradDa <T estende TType > | Aggiorna '*var' secondo lo schema adagrad prossimale. |
| ApplicaAdagradDa.Options | Attributi facoltativi per ApplyAdagradDa |
| ApplyAdagradV2 <T estende TType > | Aggiorna '*var' secondo lo schema adagrad. |
| ApplicaAdagradV2.Options | Attributi facoltativi per ApplyAdagradV2 |
| ApplyAdam <T estende TType > | Aggiorna '*var' secondo l'algoritmo di Adam. |
| ApplicaAdam.Options | Attributi facoltativi per ApplyAdam |
| ApplyAdaMax <T estende TType > | Aggiorna '*var' secondo l'algoritmo AdaMax. |
| ApplicaAdaMax.Options | Attributi facoltativi per ApplyAdaMax |
| ApplyAddSign <T estende TType > | Aggiorna "*var" in base all'aggiornamento AddSign. |
| ApplyAddSign.Options | Attributi facoltativi per ApplyAddSign |
| ApplyCenteredRmsProp <T estende TType > | Aggiorna '*var' in base all'algoritmo RMSProp centrato. |
| ApplyCenteredRmsProp.Options | Attributi facoltativi per ApplyCenteredRmsProp |
| ApplyFtrl <T estende TType > | Aggiorna '*var' secondo lo schema Ftrl-prossimale. |
| ApplyFtrl.Options | Attributi facoltativi per ApplyFtrl |
| ApplyGradientDescent <T estende TType > | Aggiorna '*var' sottraendo da esso 'alpha' * 'delta'. |
| ApplicaGradientDescent.Options | Attributi facoltativi per ApplyGradientDescent |
| ApplyMomentum <T estende TType > | Aggiorna '*var' secondo lo schema del momentum. |
| ApplyMomentum.Options | Attributi facoltativi per ApplyMomentum |
| ApplyPowerSign <T estende TType > | Aggiorna "*var" in base all'aggiornamento AddSign. |
| ApplicaPowerSign.Options | Attributi facoltativi per ApplyPowerSign |
| ApplyProximalAdagrad <T estende TType > | Aggiorna '*var' e '*accum' secondo FOBOS con il tasso di apprendimento di Adagrad. |
| ApplicaProximalAdagrad.Options | Attributi facoltativi per ApplyProximalAdagrad |
| ApplyProximalGradientDescent <T estende TType > | Aggiorna '*var' come algoritmo FOBOS con velocità di apprendimento fissa. |
| ApplicaProximalGradientDescent.Options | Attributi facoltativi per ApplyProximalGradientDescent |
| ApplyRmsProp <T estende TType > | Aggiorna '*var' in base all'algoritmo RMSProp. |
| ApplicaRmsProp.Options | Attributi facoltativi per ApplyRmsProp |
| Approssimativo Uguale | Restituisce il valore di verità di abs(xy) < tolleranza per elemento. |
| OpzioniApprossimateEqual | Attributi facoltativi per ApproximateEqual |
| ArgMax <V estende TNumero > | Restituisce l'indice con il valore maggiore tra le dimensioni di un tensore. |
| ArgMin <V estende TNumero > | Restituisce l'indice con il valore più piccolo tra le dimensioni di un tensore. |
| Asin <T estende TType > | Calcola il seno inverso trignometrico di x rispetto agli elementi. |
| Asinh <T estende TType > | Calcola il seno iperbolico inverso di x rispetto agli elementi. |
| AssertCardinalityDataset | |
| AssertNextDataset | Una trasformazione che stabilisce quali trasformazioni avverranno dopo. |
| AssertNextDataset | |
| Afferma questo | Afferma che la condizione data è vera. |
| AssertThat.Options | Attributi facoltativi per AssertThat |
| AssetFileDef | An asset file def for a single file or a set of sharded files with the same name. |
| AssetFileDef.Builder | An asset file def for a single file or a set of sharded files with the same name. |
| AssetFileDefOrBuilder | |
| Assegna <T estende TType > | Aggiorna "ref" assegnandogli "valore". |
| Assegna.Opzioni | Attributi facoltativi per Assign |
| AssignAdd <T estende TType > | Aggiorna "ref" aggiungendovi "valore". |
| AssegnaAdd.Options | Attributi facoltativi per AssignAdd |
| AssegnaAggiungiVariabileOp | Aggiunge un valore al valore corrente di una variabile. |
| AssignSub <T estende TType > | Aggiorna "ref" sottraendo "value" da esso. |
| AssignSub.Options | Attributi facoltativi per AssignSub |
| AssegnaSubVariableOp | Sottrae un valore dal valore corrente di una variabile. |
| AssegnaVariabileOp | Assegna un nuovo valore a una variabile. |
| AsString | Converte ogni voce nel tensore specificato in stringhe. |
| AsString.Options | Attributi facoltativi per AsString |
| Atan <T estende TType > | Calcola la tangente inversa trignometrica di x rispetto agli elementi. |
| Atan2 <T estende TNumero > | Calcola l'arcotangente di `y/x` in termini di elemento, rispettando i segni degli argomenti. |
| Atanh <T estende TType > | Calcola la tangente iperbolica inversa di x rispetto agli elementi. |
| AttrValue | Protocol buffer representing the value for an attr used to configure an Op. |
| AttrValue.Builder | Protocol buffer representing the value for an attr used to configure an Op. |
| AttrValue.ListValue | LINT.IfChangeTipo di protocollo tensorflow.AttrValue.ListValue |
| AttrValue.ListValue.Builder | LINT.IfChangeTipo di protocollo tensorflow.AttrValue.ListValue |
| AttrValue.ListValueOrBuilder | |
| AttrValue.ValueCase | |
| AttrValueOrBuilder | |
| AttrValueProtos | |
| Audiospettrogramma | Produce una visualizzazione dei dati audio nel tempo. |
| AudioSpettrogramma.Opzioni | Attributi facoltativi per AudioSpectrogram |
| Riepilogo audio | Emette un buffer di protocollo "Riepilogo" con audio. |
| AudioSummary.Opzioni | Attributi facoltativi per AudioSummary |
| Opzioni di parallelo automatico | Tipo di protocollo tensorflow.AutoParallelOptions |
| AutoParallelOptions.Builder | Tipo di protocollo tensorflow.AutoParallelOptions |
| AutoParallelOptionsOrBuilder | |
| Set di dati AutoShard | Crea un set di dati che suddivide in partizioni il set di dati di input. |
| Set di dati AutoShard | Crea un set di dati che suddivide in partizioni il set di dati di input. |
| AutoShardDataset.Options | Attributi facoltativi per AutoShardDataset |
| AutoShardDataset.Options | Attributi facoltativi per AutoShardDataset |
| Informazioni sul dispositivo disponibile | Matches DeviceAttributesTipo di protocollo tensorflow.AvailableDeviceInfo |
| AvailableDeviceInfo.Builder | Matches DeviceAttributesTipo di protocollo tensorflow.AvailableDeviceInfo |
| AvailableDeviceInfoOrBuilder | |
| AvgPool <T estende TNumber > | Esegue il pooling medio sull'input. |
| AvgPool.Opzioni | Attributi facoltativi per AvgPool |
| AvgPool3d <T estende TNumero > | Esegue il pooling medio 3D sull'input. |
| AvgPool3d.Opzioni | Attributi facoltativi per AvgPool3d |
| AvgPool3dGrad <T estende TNumero > | Calcola i gradienti della funzione di pooling media. |
| AvgPool3dGrad.Opzioni | Attributi facoltativi per AvgPool3dGrad |
| AvgPoolGrad <T estende TNumero > | Calcola i gradienti della funzione di pooling media. |
| AvgPoolGrad.Opzioni | Attributi facoltativi per AvgPoolGrad |
B
| BandedTriangularSolve <T estende TType > | |
| BandedTriangularSolve.Options | Attributi facoltativi per BandedTriangularSolve |
| BandPart <T estende TType > | Copia un tensore impostando a zero tutto ciò che è al di fuori di una banda centrale in ciascuna matrice più interna. |
| Barriera | Definisce una barriera che persiste tra diverse esecuzioni del grafico. |
| Opzioni.Barriera | Attributi facoltativi per Barrier |
| BarrieraChiudi | Chiude la barriera data. |
| BarrierClose.Opzioni | Attributi facoltativi per BarrierClose |
| BarrieraIncompletaDimensione | Calcola il numero di elementi incompleti nella barriera data. |
| BarrieraInserisciMolti | Per ogni chiave, assegna il rispettivo valore al componente specificato. |
| BarrierReadySize | Calcola il numero di elementi completi nella barriera data. |
| BarrieraPrendiMolti | Prende il numero indicato di elementi completati da una barriera. |
| BarrierTakeMany.Options | Attributi facoltativi per BarrierTakeMany |
| BaseInitializer <T estende TType > | Classe base astratta per tutti gli inizializzatori |
| Lotto | Raggruppa tutti i tensori di input in modo non deterministico. |
| Opzioni.batch | Attributi facoltativi per Batch |
| BatchCholesky <T estende TNumero > | |
| BatchCholeskyGrad <T estende TNumero > | |
| Set di dati batch | |
| Set di dati batch | Crea un set di dati che raggruppa gli elementi "batch_size" da "input_dataset". |
| BatchDataset.Options | Attributi facoltativi per BatchDataset |
| BatchFft | |
| BatchFft2d | |
| BatchFft3d | |
| BatchIft | |
| BatchIft2d | |
| BatchIfft3d | |
| BatchMatMul <T estende TType > | Moltiplica le fette di due tensori in batch. |
| BatchMatMul.Opzioni | Attributi facoltativi per BatchMatMul |
| BatchMatrixBandPart <T estende TType > | |
| BatchMatrixDeterminant <T estende TType > | |
| BatchMatrixDiag <T estende TType > | |
| BatchMatrixDiagPart <T estende TType > | |
| BatchMatrixInverse <T estende TNumero > | |
| BatchMatrixInverse.Options | Attributi facoltativi per BatchMatrixInverse |
| BatchMatrixSetDiag <T estende TType > | |
| BatchMatrixSolve <T estende TNumero > | |
| BatchMatrixSolve.Options | Attributi facoltativi per BatchMatrixSolve |
| BatchMatrixSolveLs <T estende TNumero > | |
| BatchMatrixSolveLs.Options | Attributi facoltativi per BatchMatrixSolveLs |
| BatchMatrixTriangularSolve <T estende TNumero > | |
| BatchMatrixTriangularSolve.Options | Attributi facoltativi per BatchMatrixTriangularSolve |
| BatchNormWithGlobalNormalization <T estende TType > | Normalizzazione batch. |
| BatchNormWithGlobalNormalizationGrad <T estende TType > | Gradienti per la normalizzazione batch. |
| BatchSelfAdjointEig <T estende TNumero > | |
| BatchSelfAdjointEig.Options | Attributi facoltativi per BatchSelfAdjointEig |
| BatchSvd <T estende TType > | |
| BatchSvd.Options | Attributi facoltativi per BatchSvd |
| BatchToSpace <T estende TType > | BatchToSpace per tensori 4-D di tipo T. |
| BatchToSpaceNd <T estende TType > | BatchToSpace per tensori ND di tipo T. |
| Voci di benchmark | Tipo di protocollo tensorflow.BenchmarkEntries |
| BenchmarkEntries.Builder | Tipo di protocollo tensorflow.BenchmarkEntries |
| BenchmarkEntriesOrBuilder | |
| Ingresso benchmark | Each unit test or benchmark in a test or benchmark run provides some set of information. |
| BenchmarkEntry.Builder | Each unit test or benchmark in a test or benchmark run provides some set of information. |
| BenchmarkEntryOrBuilder | |
| BesselI0 <T estende TNumero > | |
| BesselI0e <T estende TNumero > | |
| BesselI1 <T estende TNumero > | |
| BesselI1e <T estende TNumero > | |
| BesselJ0 <T estende TNumero > | |
| BesselJ1 <T estende TNumero > | |
| BesselK0 <T estende TNumero > | |
| BesselK0e <T estende TNumero > | |
| BesselK1 <T estende TNumero > | |
| BesselK1e <T estende TNumero > | |
| BesselY0 <T estende TNumero > | |
| BesselY1 <T estende TNumero > | |
| Betainc <T estende TNumero > | Calcolare l'integrale beta incompleto regolarizzato \\(I_x(a, b)\\). |
| BfcMemoryMapProtos | |
| Bfloat16Layout | Layout dei dati che converte i float a 32 bit da/a 16 bit, troncando la mantissa a 7 bit ma preservando l'esponente a 8 bit con lo stesso bias. |
| BiasAdd <T estende TType > | Aggiunge "bias" a "valore". |
| BiasAdd.Options | Attributi facoltativi per BiasAdd |
| BiasAddGrad <T estende TType > | L'operazione all'indietro per "BiasAdd" sul tensore "bias". |
| BiasAddGrad.Options | Attributi facoltativi per BiasAddGrad |
| Crossentropia binaria | Calcola la perdita di entropia incrociata tra le etichette reali e quelle previste. |
| BinaryCrossentropy <T estende TNumero > | Una metrica che calcola la perdita binaria di entropia incrociata tra le etichette vere e quelle previste. |
| Bincount <T estende TNumero > | Conta il numero di occorrenze di ciascun valore in una matrice di numeri interi. |
| BinSummary | Tipo di protobuf tensorflow.BinSummary |
| BinSummary.Builder | Tipo di protobuf tensorflow.BinSummary |
| BinSummaryOrBuilder | |
| Bitcast <U estende TType > | Bitcast un tensore da un tipo a un altro senza copiare i dati. |
| BitwiseAnd <T estende TNumero > | Elementwise calcola l'AND bit per bit di "x" e "y". |
| BitwiseOr <T estende TNumero > | Elementwise calcola l'OR bit per bit di "x" e "y". |
| BitwiseXor <T estende TNumero > | Elementwise calcola lo XOR bit a bit di "x" e "y". |
| BlockLSTM <T estende TNumero > | Calcola la propagazione in avanti della cella LSTM per tutti i passaggi temporali. |
| BlockLSTM.Opzioni | Attributi facoltativi per BlockLSTM |
| BlockLSTMGrad <T estende TNumero > | Calcola la propagazione all'indietro della cella LSTM per l'intera sequenza temporale. |
| BooleanDataBuffer | Un DataBuffer di booleani. |
| BooleanDataLayout <S estende DataBuffer <?>> | Un DataLayout che converte i dati archiviati in un buffer in valori booleani. |
| BooleanDenseNdArray | |
| BooleanMask | |
| BooleanMask.Options | Attributi facoltativi per BooleanMask |
| BooleanMaskUpdate | |
| BooleanMaskUpdate.Options | Attributi facoltativi per BooleanMaskUpdate |
| BooleanNdArray | Un NdArray di booleani. |
| BoolLayout | Layout dei dati che converte booleani da/in byte. |
| BoostedTreesAggregateStats | Aggrega il riepilogo delle statistiche accumulate per il batch. |
| BoostedTreesBucketize | Classifica ciascuna funzionalità in un bucket in base ai limiti del bucket. |
| BoostedTreesCalcolaBestFeatureDividi | Calcola i guadagni per ciascuna funzionalità e restituisce le migliori informazioni di suddivisione possibili per la funzionalità. |
| BoostedTreesCalculateBestFeatureSplit.Options | Attributi facoltativi per BoostedTreesCalculateBestFeatureSplit |
| BoostedTreesCalcolaBestFeatureDividiV2 | Calcola i guadagni per ciascuna funzionalità e restituisce le migliori informazioni di suddivisione possibili per ciascun nodo. |
| Alberi potenziatiCalcola i migliori guadagni per funzione | Calcola i guadagni per ciascuna funzionalità e restituisce le migliori informazioni di suddivisione possibili per la funzionalità. |
| BoostedTreesCenterBias | Calcola il prior dai dati di training (il bias) e riempie il primo nodo con il prior dei logit. |
| BoostedTreesCreateEnsemble | Crea un modello di insieme di alberi e restituisce un handle. |
| BoostedTreesCreateQuantileStreamResource | Creare la risorsa per i flussi quantili. |
| BoostedTreesCreateQuantileStreamResource.Options | Attributi facoltativi per BoostedTreesCreateQuantileStreamResource |
| BoostedTreesDeserializeEnsemble | Deserializza una configurazione di insieme di alberi serializzati e sostituisce l'albero corrente insieme. |
| BoostedTreesEnsembleResourceHandleOp | Crea un handle per un BoostedTreesEnsembleResource |
| BoostedTreesEnsembleResourceHandleOp.Options | Attributi facoltativi per BoostedTreesEnsembleResourceHandleOp |
| BoostedTreesEsempioDebugOutputs | Output di debug/interpretabilità del modello per ogni esempio. |
| BoostedTreesFlushQuantileSummaries | Svuota i riepiloghi dei quantili da ciascuna risorsa del flusso quantile. |
| BoostedTreesGetEnsembleStates | Recupera il token del timbro della risorsa dell'insieme di alberi, il numero di alberi e le statistiche di crescita. |
| BoostedTreesCrea riepiloghi quantili | Crea il riepilogo dei quantili per il batch. |
| BoostedTreesMakeStatsSummary | Crea il riepilogo delle statistiche accumulate per il batch. |
| BoostedTreesPredict | Esegue più predittori di ensemble di regressione additiva su istanze di input e calcola i logit. |
| BoostedTreesQuantileStreamResourceAddSummaries | Aggiungere i riepiloghi dei quantili a ciascuna risorsa del flusso quantile. |
| BoostedTreesQuantileStreamResourceDeserialize | Deserializza i limiti del bucket e prepara il flag nell'attuale QuantileAccumulator. |
| BoostedTreesQuantileStreamResourceFlush | Svuota i riepiloghi per una risorsa flusso quantile. |
| BoostedTreesQuantileStreamResourceFlush.Options | Attributi facoltativi per BoostedTreesQuantileStreamResourceFlush |
| BoostedTreesQuantileStreamResourceGetBucketBoundaries | Genera i limiti del bucket per ciascuna funzionalità in base ai riepiloghi accumulati. |
| BoostedTreesQuantileStreamResourceHandleOp | Crea un handle per BoostedTreesQuantileStreamResource. |
| BoostedTreesQuantileStreamResourceHandleOp.Options | Attributi facoltativi per BoostedTreesQuantileStreamResourceHandleOp |
| BoostedTreesSerializeEnsemble | Serializza l'insieme dell'albero in un proto. |
| BoostedTreesSparseAggregateStats | Aggrega il riepilogo delle statistiche accumulate per il batch. |
| BoostedTreesSparseCalculateBestFeatureDividi | Calcola i guadagni per ciascuna funzionalità e restituisce le migliori informazioni di suddivisione possibili per la funzionalità. |
| BoostedTreesSparseCalculateBestFeatureSplit.Options | Attributi facoltativi per BoostedTreesSparseCalculateBestFeatureSplit |
| BoostedTreesTrainingPredict | Esegue più predittori di ensemble di regressione additiva su istanze di input e calcola l'aggiornamento ai logit memorizzati nella cache. |
| BoostedTreesUpdateEnsemble | Aggiorna l'insieme degli alberi aggiungendo un livello all'ultimo albero in crescita o iniziando un nuovo albero. |
| BoostedTreesUpdateEnsembleV2 | Aggiorna l'insieme degli alberi aggiungendo un livello all'ultimo albero in crescita o iniziando un nuovo albero. |
| BoostedTreesUpdateEnsembleV2.Options | Attributi facoltativi per BoostedTreesUpdateEnsembleV2 |
| BoundedTensorSpecProto | A protobuf to represent tf.BoundedTensorSpec. |
| BoundedTensorSpecProto.Builder | A protobuf to represent tf.BoundedTensorSpec. |
| BoundedTensorSpecProtoOrBuilder | |
| BroadcastDynamicShape <T estende TNumero > | Restituisce la forma di s0 op s1 con broadcast. |
| BroadcastGradientArgs <T estende TNumber > | Restituisce gli indici di riduzione per il calcolo dei gradienti di s0 op s1 con broadcast. |
| BroadcastHelper <T estende TType > | Operatore di supporto per l'esecuzione di trasmissioni in stile XLA Trasmette "lhs" e "rhs" allo stesso rango, aggiungendo dimensioni di dimensione 1 a quello tra "lhs" e "rhs" che ha il rango inferiore, utilizzando le regole di trasmissione XLA per gli operatori binari. |
| BroadcastRecv <T estende TType > | Riceve un valore tensore trasmesso da un altro dispositivo. |
| BroadcastRecv.Opzioni | Attributi facoltativi per BroadcastRecv |
| BroadcastSend <T estende TType > | Trasmette un valore tensore a uno o più altri dispositivi. |
| BroadcastSend.Options | Attributi facoltativi per BroadcastSend |
| BroadcastTo <T estende TType > | Trasmetti un array per una forma compatibile. |
| Mettere in ordine | Classifica gli "input" in base ai "confini". |
| CostruisciConfigurazione | Tipo di protocollo tensorflow.BuildConfiguration |
| BuildConfiguration.Builder | Tipo di protocollo tensorflow.BuildConfiguration |
| BuildConfigurationOrBuilder | |
| BundleEntryProto | Describes the metadata related to a checkpointed tensor. |
| BundleEntryProto.Builder | Describes the metadata related to a checkpointed tensor. |
| BundleEntryProtoOrBuilder | |
| BundleHeaderProto | Special header that is associated with a bundle. |
| BundleHeaderProto.Builder | Special header that is associated with a bundle. |
| BundleHeaderProto.Endianness | An enum indicating the endianness of the platform that produced this bundle. |
| BundleHeaderProtoOrBuilder | |
| ByteDataBuffer | Un DataBuffer di byte. |
| ByteDataLayout <S estende DataBuffer <?>> | Oggetto DataLayout che converte i dati archiviati in un buffer in byte. |
| ByteDenseNdArray | |
| ByteNdArray | Un NdArray di byte. |
| ByteSequenceProvider <T> | Produce una sequenza di byte da archiviare in un ByteSequenceTensorBuffer . |
| ByteSequenceTensorBuffer | Buffer per la memorizzazione dei dati del tensore di stringa. |
| Elenco byte | Containers to hold repeated fundamental values. |
| BytesList.Builder | Containers to hold repeated fundamental values. |
| BytesListOrBuilder | |
| BytesProducedStatsDataset | Registra la dimensione in byte di ciascun elemento di "input_dataset" in uno StatsAggregator. |
| BytesProducedStatsDataset | Registra la dimensione in byte di ciascun elemento di "input_dataset" in uno StatsAggregator. |
C
| CacheDataset | Crea un set di dati che memorizza nella cache gli elementi da "input_dataset". |
| CacheDatasetV2 | |
| CallableOptions | Defines a subgraph in another `GraphDef` as a set of feed points and nodes to be fetched or executed. |
| CallableOptions.Builder | Defines a subgraph in another `GraphDef` as a set of feed points and nodes to be fetched or executed. |
| CallableOptionsOrBuilder | |
| Cast <U estende TType > | Cast x di tipo SrcT in y di DstT. |
| Opzioni.cast | Attributi facoltativi per Cast |
| CastHelper | Una classe helper per lanciare un operando |
| Crossentropia categorica | Calcola la perdita di entropia incrociata tra le etichette e le previsioni. |
| Entropia incrociata categoriale <T estende TNumero > | Una metrica che calcola la perdita di entropia incrociata categorica tra le etichette vere e quelle previste. |
| CategorialeCerniera | Calcola la perdita di cerniera categoriale tra etichette e previsioni. |
| CategoricalHinge <T estende TNumero > | Una metrica che calcola la metrica della perdita di cerniera categoriale tra etichette e previsioni. |
| Ceil <T estende TNumero > | Restituisce il numero intero più piccolo in termini di elemento non inferiore a x. |
| CheckNumerics <T estende TNumers > | Controlla un tensore per i valori NaN, -Inf e +Inf. |
| Cholesky <T estende TType > | Calcola la scomposizione di Cholesky di una o più matrici quadrate. |
| CholeskyGrad <T estende TNumero > | Calcola il gradiente retropropagato in modalità inversa dell'algoritmo di Cholesky. |
| Scegli il set di dati più veloce | |
| Scegli il set di dati più veloce | |
| ClipByValue <T estende TType > | Ritaglia i valori del tensore su un minimo e un massimo specificati. |
| ChiudiSummaryWriter | |
| ClusterDef | Defines a TensorFlow cluster as a set of jobs. |
| ClusterDef.Builder | Defines a TensorFlow cluster as a set of jobs. |
| ClusterDefOrBuilder | |
| ClusterDeviceFilters | Defines the device filters for jobs in a cluster. |
| ClusterDeviceFilters.Builder | Defines the device filters for jobs in a cluster. |
| ClusterDeviceFiltersOrBuilder | |
| ClusterOutput <T estende TType > | Operatore che collega l'output di un calcolo XLA ad altri nodi del grafico consumer. |
| ClusterProtos | |
| Codice | The canonical error codes for TensorFlow APIs. |
| CodeLocation | Code location information: A stack trace with host-name information. |
| CodeLocation.Builder | Code location information: A stack trace with host-name information. |
| CodeLocationOrBuilder | |
| CollezioneDef | CollectionDef should cover most collections. |
| CollectionDef.AnyList | AnyList is used for collecting Any protos. |
| CollectionDef.AnyList.Builder | AnyList is used for collecting Any protos. |
| CollectionDef.AnyListOrBuilder | |
| CollectionDef.Builder | CollectionDef should cover most collections. |
| CollectionDef.BytesList | BytesList is used for collecting strings and serialized protobufs. |
| CollectionDef.BytesList.Builder | BytesList is used for collecting strings and serialized protobufs. |
| CollectionDef.BytesListOrBuilder | |
| CollectionDef.FloatList | FloatList is used for collecting float values. |
| CollectionDef.FloatList.Builder | FloatList is used for collecting float values. |
| CollectionDef.FloatListOrBuilder | |
| CollezioneDef.Int64List | Int64List is used for collecting int, int64 and long values. |
| CollectionDef.Int64List.Builder | Int64List is used for collecting int, int64 and long values. |
| CollectionDef.Int64ListOrBuilder | |
| CollezioneDef.KindCase | |
| CollectionDef.NodeList | NodeList is used for collecting nodes in graph. |
| CollectionDef.NodeList.Builder | NodeList is used for collecting nodes in graph. |
| CollectionDef.NodeListOrBuilder | |
| CollezioneDefOrBuilder | |
| CollectiveGather <T estende TNumber > | Accumula reciprocamente più tensori di identico tipo e forma. |
| CollectiveGather.Options | Attributi facoltativi per CollectiveGather |
| CollectivePermute <T estende TType > | Un'operazione per permutare i tensori tra le istanze TPU replicate. |
| Soppressione combinata NonMax | Seleziona avidamente un sottoinsieme di riquadri di delimitazione in ordine decrescente di punteggio, Questa operazione esegue non_max_suppression sugli input per batch, in tutte le classi. |
| CombinedNonMaxSuppression.Options | Attributi facoltativi per CombinedNonMaxSuppression |
| ID impegno | Tipo di protocollo tensorflow.CommitId |
| CommitId.Builder | Tipo di protocollo tensorflow.CommitId |
| CommitId.KindCase | |
| CommitIdOrBuilder | |
| ConfrontaAndBitpack | Confronta i valori di "input" con "threshold" e comprime i bit risultanti in un "uint8". |
| Risultato compilazione | Restituisce il risultato di una compilazione TPU. |
| CompileSucceededAssert | Afferma che la compilazione è riuscita. |
| Il complesso <U estende TType > | Converte due numeri reali in un numero complesso. |
| ComplexAbs <U estende TNumero > | Calcola il valore assoluto complesso di un tensore. |
| Elemento compresso | Comprime un elemento del set di dati. |
| Compute_func_Pointer_TF_OpKernelContext | |
| Calcola colpi accidentali | Calcola gli ID delle posizioni in sampled_candidates che corrispondono a true_labels. |
| ComputeAccidentalHits.Options | Attributi facoltativi per ComputeAccidentalHits |
| Calcola dimensione batch | Calcola la dimensione batch statica di un set di dati senza batch parziali. |
| Concat <T estende TType > | Concatena i tensori lungo una dimensione. |
| ConcatenateDataset | Crea un set di dati che concatena "input_dataset" con "another_dataset". |
| FunzioneConcreta | Un grafico che può essere richiamato come una singola funzione, con una firma di input e output. |
| CondContestoDef | Protocol buffer representing a CondContext object. |
| CondContextDef.Builder | Protocol buffer representing a CondContext object. |
| CondContextDefOrBuilder | |
| Accumulatore condizionale | Un accumulatore condizionale per l'aggregazione dei gradienti. |
| ConditionalAccumulatore.Opzioni | Attributi facoltativi per ConditionalAccumulator |
| ConfigProto | Session configuration parameters. |
| ConfigProto.Builder | Session configuration parameters. |
| ConfigProto.Experimental | Everything inside Experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat. |
| ConfigProto.Experimental.Builder | Everything inside Experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat. |
| ConfigProto.Experimental.MlirBridgeRollout | An enum that describes the state of the MLIR bridge rollout. |
| ConfigProto.ExperimentalOrBuilder | |
| ConfigProtoOrBuilder | |
| ConfigProtos | |
| ConfiguraTPU distribuito | Configura le strutture centralizzate per un sistema TPU distribuito. |
| ConfigureDistributedTPU.Options | Attributi facoltativi per ConfigureDistributedTPU |
| Configura l'incorporamentoTPUE | Configura TPUEmbedding in un sistema TPU distribuito. |
| Conj <T estende TType > | Restituisce il complesso coniugato di un numero complesso. |
| ConjugateTranspose <T estende TType > | Mescola le dimensioni di x secondo una permutazione e coniuga il risultato. |
| Costante <T estende TType > | Inizializzatore che genera tensori con un valore costante. |
| Costante <T estende TType > | Un operatore che produce un valore costante. |
| Vincolo | Classe base per Vincoli. |
| ConsumaMutexLock | Questa operazione utilizza un blocco creato da "MutexLock". |
| ControlFlowContextDef | Container for any kind of control flow context. |
| ControlFlowContextDef.Builder | Container for any kind of control flow context. |
| ControlFlowContextDef.CtxtCase | |
| ControlFlowContextDefOrBuilder | |
| ControlFlowProtos | |
| ControlTrigger | Non fa nulla. |
| Conv <T estende TType > | Avvolge l'operatore XLA ConvGeneralDilated, documentato in https://www.tensorflow.org/performance/xla/Operation_semantics#conv_convolution. |
| Conv2d <T estende TNumero > | Calcola una convoluzione 2-D dati i tensori "input" e "filtro" 4-D. |
| Conv2d.Opzioni | Attributi facoltativi per Conv2d |
| Conv2dBackpropFilter <T estende TNumero > | Calcola i gradienti di convoluzione rispetto al filtro. |
| Conv2dBackpropFilter.Options | Attributi facoltativi per Conv2dBackpropFilter |
| Conv2dBackpropInput <T estende TNumber > | Calcola i gradienti di convoluzione rispetto all'input. |
| Conv2dBackpropInput.Options | Attributi facoltativi per Conv2dBackpropInput |
| Conv3d <T estende TNumero > | Calcola una convoluzione 3-D dati i tensori "input" e "filtro" 5-D. |
| Conv3d.Opzioni | Attributi facoltativi per Conv3d |
| Conv3dBackpropFilter <T estende TNumber > | Calcola i gradienti della convoluzione 3D rispetto al filtro. |
| Conv3dBackpropFilter.Opzioni | Attributi facoltativi per Conv3dBackpropFilter |
| Conv3dBackpropInput <U estende TNumber > | Calcola i gradienti della convoluzione 3D rispetto all'input. |
| Conv3dBackpropInput.Options | Attributi facoltativi per Conv3dBackpropInput |
| Copia <T estende TType > | Copia un tensore da CPU a CPU o da GPU a GPU. |
| Copia.Opzioni | Attributi facoltativi per Copy |
| CopyHost <T estende TType > | Copia un tensore su host. |
| CopyHost.Options | Attributi facoltativi per CopyHost |
| Cos <T estende TType > | Calcola il cos di x in termini di elementi. |
| Cosh <T estende TType > | Calcola il coseno iperbolico di x rispetto agli elementi. |
| Somiglianza coseno | Calcola la somiglianza del coseno tra etichette e previsioni. |
| CosenoSimilarità <T estende TNumero > | Una metrica che calcola la metrica di similarità del coseno tra etichette e previsioni. |
| CostoGraphDef | Tipo di protocollo tensorflow.CostGraphDef |
| CostGraphDef.AggregateCost | Total cost of this graph, typically used for balancing decisions. |
| CostGraphDef.AggregatedCost.Builder | Total cost of this graph, typically used for balancing decisions. |
| CostGraphDef.AggregatedCostOrBuilder | |
| CostGraphDef.Builder | Tipo di protocollo tensorflow.CostGraphDef |
| CostGraphDef.Node | Tipo di protocollo tensorflow.CostGraphDef.Node |
| CostGraphDef.Node.Builder | Tipo di protocollo tensorflow.CostGraphDef.Node |
| CostGraphDef.Node.InputInfo | Inputs of this node. |
| CostGraphDef.Node.InputInfo.Builder | Inputs of this node. |
| CostGraphDef.Node.InputInfoOrBuilder | |
| CostGraphDef.Node.OutputInfo | Outputs of this node. |
| CostGraphDef.Node.OutputInfo.Builder | Outputs of this node. |
| CostGraphDef.Node.OutputInfoOrBuilder | |
| CostGraphDef.NodeOrBuilder | |
| CostGraphDefOrBuilder | |
| CostGraphProtos | |
| CountUpTo <T estende TNumero > | Incrementa 'ref' fino a raggiungere 'limit'. |
| Informazioni sulla CPU | Tipo di protocollo tensorflow.CPUInfo |
| CPUInfo.Builder | Tipo di protocollo tensorflow.CPUInfo |
| CPUInfoOrBuilder | |
| Create_func_TF_OpKernelConstruction | |
| CreateSummaryDbWriter | |
| CreateSummaryFileWriter | |
| Ritaglia e ridimensiona | Estrae i ritagli dal tensore dell'immagine di input e li ridimensiona. |
| CropAndResize.Options | Attributi facoltativi per CropAndResize |
| CropAndResizeGradBoxes | Calcola il gradiente dell'operazione crop_and_resize rispetto al tensore delle caselle di input. |
| CropAndResizeGradBoxes.Options | Attributi facoltativi per CropAndResizeGradBoxes |
| CropAndResizeGradImage <T estende TNumero > | Calcola il gradiente dell'operazione crop_and_resize rispetto al tensore dell'immagine in input. |
| CropAndResizeGradImage.Options | Attributi facoltativi per CropAndResizeGradImage |
| Croce <T estende TNumero > | Calcola il prodotto incrociato a coppie. |
| CrossReplicaSum <T estende TNumber > | Un'operazione per sommare gli input tra le istanze TPU replicate. |
| CSRSparseMatrixComponents <T estende TType > | Legge i componenti CSR nell'indice batch. |
| CSRSparseMatrixToDense <T estende TType > | Convertire un CSRSparseMatrix (possibilmente in batch) in denso. |
| CSRSparseMatrixToSparseTensor <T estende TType > | Converte un CSRSparesMatrix (possibilmente in batch) in uno SparseTensor. |
| CSVDataset | |
| CSVDataset | |
| CSVDatasetV2 | |
| CtcBeamSearchDecoder <T estende TNumber > | Esegue la decodifica della ricerca del fascio sui logit forniti in input. |
| CtcBeamSearchDecoder.Options | Attributi facoltativi per CtcBeamSearchDecoder |
| CtcGreedyDecoder <T estende TNumero > | Esegue la decodifica greedy sui logit forniti negli input. |
| CtcGreedyDecoder.Options | Attributi facoltativi per CtcGreedyDecoder |
| CtcLoss <T estende TNumber > | Calcola la perdita CTC (probabilità logaritmica) per ciascuna voce batch. |
| CtcLoss.Opzioni | Attributi facoltativi per CtcLoss |
| CTLossV2 | Calcola la perdita CTC (probabilità logaritmica) per ciascuna voce batch. |
| CTLossV2.Options | Attributi facoltativi per CTCLossV2 |
| CudnnRNN <T estende TNumero > | Una RNN supportata da cuDNN. |
| CudnnRNN.Opzioni | Attributi facoltativi per CudnnRNN |
| CudnnRNNBackprop <T estende TNumero > | Passaggio di backprop di CudnnRNNV3. |
| CudnnRNNBackprop.Opzioni | Attributi facoltativi per CudnnRNNBackprop |
| CudnnRNNCanonalToParams <T estende TNumber > | Converte i parametri CudnnRNN dalla forma canonica alla forma utilizzabile. |
| CudnnRNNCanonalToParams.Options | Attributi facoltativi per CudnnRNNCanonicalToParams |
| CudnnRnnParamsSize <U estende TNumber > | Calcola la dimensione dei pesi che possono essere utilizzati da un modello Cudnn RNN. |
| CudnnRnnParamsSize.Options | Attributi facoltativi per CudnnRnnParamsSize |
| CudnnRNNParamsToCanonical <T estende TNumber > | Recupera i parametri CudnnRNN in forma canonica. |
| CudnnRNNParamsToCanonical.Options | Attributi facoltativi per CudnnRNNParamsToCanonical |
| Cumprod <T estende TType > | Calcola il prodotto cumulativo del tensore "x" lungo l'asse. |
| Cumprod.Opzioni | Attributi facoltativi per Cumprod |
| Somma cumulata <T estende TType > | Calcola la somma cumulativa del tensore "x" lungo l'asse. |
| Opzioni cumsum | Attributi facoltativi per Cumsum |
| CumulativeLogsumexp <T estende TNumber > | Calcola il prodotto cumulativo del tensore "x" lungo l'asse. |
| CumulativeLogsumexp.Options | Attributi facoltativi per CumulativeLogsumexp |
D
| Buffer dati <T> | Un contenitore di dati di un tipo specifico. |
| DataBufferAdapterFactory | Fabbrica di adattatori per buffer dati. |
| Buffer di dati | Classe helper per la creazione di istanze DataBuffer . |
| DataBufferWindow <B estende DataBuffer <?>> | Un contenitore modificabile per visualizzare parte di un DataBuffer . |
| DataClass | Protobuf enum tensorflow.DataClass |
| DataFormatDimMap <T estende TNumber > | Restituisce l'indice della dimensione nel formato dati di destinazione dato quello in il formato dei dati di origine. |
| DataFormatDimMap.Options | Attributi facoltativi per DataFormatDimMap |
| DataFormatVecPermute <T estende TNumber > | Permuta il tensore di input da `src_format` a `dst_format`. |
| DataFormatVecPermute.Options | Attributi facoltativi per DataFormatVecPermute |
| Datalayout <s estende DataBuffer <?>, T> | Converte i dati archiviati in un buffer in un determinato tipo. |
| Datalayouts | Espone le istanze DataLayout di formati di dati frequentemente utilizzati nel calcolo dell'algebra lineare. |
| DataServicetaSet | |
| DataServicetaSet.options | Attributi opzionali per DataServiceDataset |
| Set di dati | Rappresenta un elenco potenzialmente ampio di elementi indipendenti (campioni) e consente di eseguire l'iterazione e le trasformazioni tra questi elementi. |
| DatasetCardinality | Restituisce la cardinalità di `input_dataset`. |
| DatasetCardinality | Restituisce la cardinalità di `input_dataset`. |
| DatasetFromgraph | Crea un set di dati dal dato `graph_def`. |
| DataSetiterator | Rappresenta lo stato di un'iterazione attraverso un tatSet TF.Data. |
| DataseToptional | Un opzionale rappresenta il risultato di un set di dati GetNext che potrebbe fallire, quando è stata raggiunta la fine del set di dati. |
| Datasettograph | Restituisce un grafico serializzato che rappresenta `input_dataset`. |
| DataSettograph.options | Attributi opzionali per DatasetToGraph |
| DataSettosingleElement | Emette il singolo elemento dal set di dati dato. |
| DataseTotTrecord | Scrive il set di dati indicato nel file dato usando il formato Tfrecord. |
| DataseTotTrecord | Scrive il set di dati indicato nel file dato usando il formato Tfrecord. |
| DataStorageVisitor <R> | Visita l'archiviazione di supporto delle istanze DataBuffer . |
| Tipo di dati | (== suppress_warning documentation-presence ==) LINT.IfChangeProtobuf enum tensorflow.DataType |
| Dawsn <t estende tnumber > | |
| Deallocator_pointer_long_pointer | |
| Debugevent | An Event related to the debugging of a TensorFlow program. |
| Debugevent.Builder | An Event related to the debugging of a TensorFlow program. |
| Debugevent.whatcase | |
| Debugeventorbuilder | |
| DebugeventProtos | |
| DebuggedDevice | A device on which ops and/or tensors are instrumented by the debugger. |
| DebuggedDevice.Builder | A device on which ops and/or tensors are instrumented by the debugger. |
| DebuggedDeviceOrbuilder | |
| DebuggedGraph | A debugger-instrumented graph. |
| DebuggedGraph.Builder | A debugger-instrumented graph. |
| DebuggedGraphorbuilder | |
| DebuggedSourcefile | tensorflow.DebuggedSourceFile di tipo protobuf.debuggedsourcefile |
| DebuggedSourcefile.Builder | tensorflow.DebuggedSourceFile di tipo protobuf.debuggedsourcefile |
| DebuggedSourcefileorbuilder | |
| DebuggedSourceFiles | Protobuf type tensorflow.DebuggedSourceFiles |
| DebuggedSourceFiles.Builder | Protobuf type tensorflow.DebuggedSourceFiles |
| DebuggedSourceFilesorbuilder | |
| DebuggradientIdentity <T estende TType > | Identity OP per il debug per gradiente. |
| DebuggradienTrefidenty <T estende TType > | Identity OP per il debug per gradiente. |
| DebugIdentity <T estende TType > | Debug Identity v2 op. |
| DebugIdentity.options | Attributi opzionali per DebugIdentity |
| Debugmetadata | Metadata about the debugger and the debugged TensorFlow program. |
| DebugMetadata.Builder | Metadata about the debugger and the debugged TensorFlow program. |
| DebugMetadataorbuilder | |
| Debugnancount | Debug Nan Value Counter op. |
| Debugnancount.options | Attributi opzionali per DebugNanCount |
| Debuggnumericsummary <u estende tnumber > | DEBUG NUMERIC SINTEMARIO V2 OP. |
| Debuggnumericsummary.options | Attributi opzionali per DebugNumericsSummary |
| Debuggoptions | Options for initializing DebuggerState in TensorFlow Debugger (tfdbg). |
| Debugoptions.Builder | Options for initializing DebuggerState in TensorFlow Debugger (tfdbg). |
| Debugoptionsorbuilder | |
| DebugProtos | |
| DebugtensorWatch | Option for watching a node in TensorFlow Debugger (tfdbg). |
| DebugtensorWatch.Builder | Option for watching a node in TensorFlow Debugger (tfdbg). |
| DebugtensorWatchorbuilder | |
| Decodeandrcropjpeg | Decodifica e ritaglia un'immagine codificata da JPEG su un tensore UINT8. |
| Decodeandrcropjpeg.options | Attributi opzionali per DecodeAndCropJpeg |
| Decodebase64 | DECODIRE STRINGI SUFFE Web Base64. |
| Decodebmp | Decodifica il primo frame di un'immagine codificata da BMP su un tensore UINT8. |
| Decodebmp.options | Attributi opzionali per DecodeBmp |
| Decodecpresso | Decomprimere le stringhe. |
| Decodecompressed.options | Attributi opzionali per DecodeCompressed |
| Decodecsv | Converti i record CSV in tensori. |
| Decodecsv.options | Attributi opzionali per DecodeCsv |
| Decodegif | Decodifica i frame (i) di un'immagine codificata da GIF su un tensore UINT8. |
| DecodeImage <t estende tnumber > | Funzione per decode_bmp, decode_gif, decode_jpeg e decode_png. |
| DecodeImage.options | Attributi opzionali per DecodeImage |
| Decodejpeg | Decodifica un'immagine codificata da JPEG su un tensore UINT8. |
| Decodejpeg.options | Attributi opzionali per DecodeJpeg |
| Decodejsonexample | Converti i record di esempio codificati da JSON in stringhe tampone di protocollo binario. |
| Decodepaddedraw <t estende tnumber > | Reinterpretare i byte di una stringa come vettore di numeri. |
| Decodepaddedraw.options | Attributi opzionali per DecodePaddedRaw |
| Decodepng <t estende tnumber > | Decodifica un'immagine codificata da PNG su un tensore UINT8 o UINT16. |
| Decodepng.options | Attributi opzionali per DecodePng |
| Decodeproto | I campi estratti di OP da un messaggio di protocollo serializzato in tessori. |
| Decodeproto.options | Attributi opzionali per DecodeProto |
| Decoderaw <t estende tttype > | Reinterpretare i byte di una stringa come vettore di numeri. |
| Decoderaw.options | Attributi opzionali per DecodeRaw |
| Decodewav | Decodifica un file WAV PCM a 16 bit su un tensore galleggiante. |
| DecodeWav.options | Attributi opzionali per DecodeWav |
| DeepCopy <T estende TType > | Fa una copia di `x`. |
| Delete_func_pointer | |
| Deleteterator | Un contenitore per una risorsa iteratore. |
| Deletememorycache | |
| Deletemultideviceiterator | Un contenitore per una risorsa iteratore. |
| Deleterandomseedgenerator | |
| Deleteseedgenerator | |
| EleteSessionTensor | Elimina il tensore specificato dalla sua maniglia nella sessione. |
| Densebincount <u estende tnumber > | Conta il numero di occorrenze di ciascun valore in un array intero. |
| Densebincount.options | Attributi opzionali per DenseBincount |
| Densecountsparseutput <u estende tnumber > | Esegue il conteggio del bidone spara per un input TF.Tensor. |
| DenseCountsParseutput.options | Attributi opzionali per DenseCountSparseOutput |
| DensendArray <T> | |
| Densetocsrsparsematrix | Converte un tensore denso in una (possibilmente batch) CSRSPARSPARSEMATRIX. |
| Densetodensetoperation <t estende TType > | Applica il set di funzionamento lungo l'ultima dimensione degli ingressi di 2 `tensori. |
| Densetodensetoperation.options | Attributi opzionali per DenseToDenseSetOperation |
| Densetosparsebatchdataset | Crea un set di dati che leta gli elementi di input in uno sparsetensor. |
| Densetosparsebatchdataset | Crea un set di dati che leta gli elementi di input in uno sparsetensor. |
| DensetospaSeToperation <T estende TType > | Applica il set di funzionamento lungo l'ultima dimensione di `tensor` e` sparsetensor`. |
| DensetospaSeToperation.options | Attributi opzionali per DenseToSparseSetOperation |
| Profondità <t estende TType > | Profondità per i tensori di tipo T. |
| Profondità.options | Attributi opzionali per DepthToSpace |
| Profonditàwiseconv2dnative <t estende tnumber > | Calcola una convoluzione profondità 2-D data tensori 4-D input` e `filtro". |
| Profonditàwiseconv2dnative.options | Attributi opzionali per DepthwiseConv2dNative |
| Profonditàwiseconv2dnativebackpropfilter <t estende tnumber > | Calcola i gradienti di convoluzione in profondità rispetto al filtro. |
| Profonditàwiseconv2dnativebackpropfilter.options | Attributi opzionali per DepthwiseConv2dNativeBackpropFilter |
| Profonditàwiseconv2dnativebackpropinput <t estende tnumber > | Calcolo i gradienti della convoluzione in profondità rispetto all'input. |
| Profonditàwiseconv2dnativebackpropinput.options | Attributi opzionali per DepthwiseConv2dNativeBackpropInput |
| Dequarantize <u estende tnumber > | Dequarantizzare il tensore "input" in un tensore galleggiante o bfloat16. |
| Dequarantizzare | Prende l'ingresso uint32 pieno e disimballa l'ingresso su uint8 per fare DEQUANTIZZAZIONE sul dispositivo. |
| Dequarantize.options | Attributi opzionali per Dequantize |
| Deserializeterator | Converte il tensore variante dato in un iteratore e lo memorizza nella risorsa data. |
| DeseriaZeManysparse <t estende TType > | Diserializza e concatenano `sparsetensori 'da un minibatch serializzato. |
| DeserializesParse <U estende TType > | Diserializzano gli oggetti `sparsensor '. |
| DestroyResourceop | Elimina la risorsa specificata dall'impugnatura. |
| DestroyResourceop.options | Attributi opzionali per DestroyResourceOp |
| DestrodTemporaryVariable <T estende TType > | Distrugge la variabile temporanea e restituisce il suo valore finale. |
| Det <t estende TType > | Calcola il fattore determinante di una o più matrici quadrate. |
| Deviceattributes | tensorflow.DeviceAttributes di tipo protobuf.deviceattributes |
| Deviceattributes.Builder | tensorflow.DeviceAttributes di tipo protobuf.deviceattributes |
| DeviceattributeSorbuilder | |
| DeviceattributesProtos | |
| DeviceFiltersProtos | |
| DeviceIndex | Restituisce l'indice del dispositivo esegue l'OP. |
| Devicelocalità | tensorflow.DeviceLocality di tipo protobuf |
| Devicelocality.Builder | tensorflow.DeviceLocality di tipo protobuf |
| Devicalityorbuilder | |
| ProPerties Device | tensorflow.DeviceProperties di tipo protobuf |
| DeviceProperties.Builder | tensorflow.DeviceProperties di tipo protobuf |
| DevicePropertiesorbuilder | |
| DevicePropertiesProtos | |
| Dispositivo | Rappresenta una specifica (forse parziale) per un dispositivo Tensorflow. |
| DEVICESPEC.Builder | Una lezione di costruttore per la costruzione DeviceSpec . |
| DEVICESPEC.DeviceType | |
| DevicestePstats | tensorflow.DeviceStepStats di tipo protobuf |
| DevicestePstats.Builder | tensorflow.DeviceStepStats di tipo protobuf |
| DevicestepStatsorbuilder | |
| DictValue | Represents a Python dict keyed by `str`. |
| DictValue.Builder | Represents a Python dict keyed by `str`. |
| DictValueorbuilder | |
| Digamma <t estende tnumber > | Calcola psi, il derivato di lgamma (il log del valore assoluto di `Gamma (x)`), per quanto riguarda l'elemento. |
| Dilation2d <t estende tnumber > | Calcolo la dilatazione in scala di grigi dei tensori di filtro `input` e 3-D` 3-D. |
| Dilation2dbackpropfilter <t estende tnumber > | Calcola il gradiente della dilatazione morfologica 2-D rispetto al filtro. |
| Dilation2dbackpropinput <t estende tnumber > | Calcola il gradiente della dilatazione morfologica 2-D rispetto all'input. |
| Dimensione | |
| Dimensionalspace | |
| DirectedInterleaveAtaSet | Un sostituto di `interleavetaset` in un elenco fisso di set di dati` N`. |
| DirectedInterleaveAtaSet | Un sostituto di `interleavetaset` in un elenco fisso di set di dati` N`. |
| Div <t estende tType > | Restituisce l'elemento x / y. |
| Divnonan <t estende TType > | Restituisce 0 se il denominatore è zero. |
| Dot <t estende TType > | Avvolge l'operatore dotgenerale XLA, documentato a https://www.tensorflow.org/performance/xla/operation_semantics#dotgeneral. |
| DoubletaBuffer | Un DataBuffer di doppi. |
| Doubledatalayout <s estende databuffer <? >> | Un DataLayout che converte i dati archiviati in un buffer in doppio. |
| DoubleSendArray | |
| DoublendArray | Un NdArray di doppi. |
| DrawBoundingBoxes <t estende tnumber > | Disegna le scatole di delimitazione su un lotto di immagini. |
| DummyiterationCounter | |
| DummymemoryCache | |
| Dummyseedgenerator | |
| DynamicPartition <t estende TType > | Partizioni `data` in` num_partitions` tensori usando indici di `partizioni '. |
| DynamicsLice <t estende TType > | Avvolge l'operatore XLA DynamicsLice, documentato a https://www.tensorflow.org/performance/xla/operation_semantics#dynamicslice. |
| DynamicStitch <t estende TType > | Interleave i valori dai tensori `data` in un singolo tensore. |
| DynamicUpDateSlice <t estende TType > | Avvolge l'operatore XLA DynamicUpdatesLice, documentato a https://www.tensorflow.org/performance/xla/operation_semantics#dynamicupdateslice. |
E
| Eagersession | Un ambiente per l'esecuzione delle operazioni di tensorflow con impazienza. |
| Eagersession.DevicePlacementPolicy | Controlla come agire quando proviamo a eseguire un'operazione su un determinato dispositivo, ma alcuni tensori di input non sono su quel dispositivo. |
| Eagersession.options | |
| Editdistance | Calcola la distanza di modifica Levenshtein (possibilmente normalizzata). |
| EditDistance.options | Attributi opzionali per EditDistance |
| Eig <u estende TType > | Calcola la decomposizione di Eigen di una o più matrici quadrate. |
| Eig.options | Attributi opzionali per Eig |
| Einsum <t estende TType > | Contrazione tensore secondo la convenzione di somma di Einstein. |
| Einsum <t estende TType > | Un OP che supporta Einsum OP di base con 2 ingressi e 1 output. |
| Elu <t estende tnumber > | Calcola lineare esponenziale: `exp (caratteristiche) - 1` if <0,` caratteristiche` altrimenti. |
| Elu <t estende tfloating > | Unità lineare esponenziale. |
| Elugrad <t estende tnumber > | Calcola i gradienti per l'operazione lineare esponenziale (ELU). |
| Attivazioni incorporate | Un OP che abilita la differenziazione degli incorporamenti della TPU. |
| Vuoto <t estende TType > | Crea un tensore con la forma data. |
| Vuoto. Opzioni | Attributi opzionali per Empty |
| EmplodTensorList | Crea e restituisce un elenco di tensori vuoto. |
| EmployTensormap | Crea e restituisce una mappa del tensore vuoto. |
| ENCODEBASE64 | Codificare le stringhe nel formato Base64 Web-Safe. |
| ENCODEBASE64.OPTIONI | Attributi opzionali per EncodeBase64 |
| ENCODEJPEG | Jpeg-codifica un'immagine. |
| ENCODEJPEG.OPTIONS | Attributi opzionali per EncodeJpeg |
| ENCODEJPEGVARABLEQUALITY | JPEG ENCODE IMMAGINE INGRESSO con qualità di compressione fornita. |
| Encodepng | PNG-codifica un'immagine. |
| Encodepng.options | Attributi opzionali per EncodePng |
| Encodeproto | OP serializza i messaggi protobuf forniti nei tensori di input. |
| Encodeproto.options | Attributi opzionali per EncodeProto |
| ECCODEWAV | Codificare i dati audio utilizzando il formato del file WAV. |
| Endpoint | Annotazione utilizzata per contrassegnare un metodo di una classe annotata con @Operator che dovrebbe generare un endpoint in ERROR(Ops/org.tensorflow.op.Ops Ops) o uno dei suoi gruppi. |
| Enqueuetpuembeddingintegerbatch | Un OP che accende un elenco di tensori batch di input a TPueMBEDDING. |
| Enqueuetpuembeddingintegerbatch.options | Attributi opzionali per EnqueueTPUEmbeddingIntegerBatch |
| Enqueuetpuembeddingdingraggedtensorbatch | Allevia il porting del codice che utilizza tf.nn.embedding_lookup (). |
| Enqueuetpuembeddingdingraggedtensorbatch.options | Attributi opzionali per EnqueueTPUEmbeddingRaggedTensorBatch |
| Enqueuetpuembeddingsparsebatch | Un OP che accende gli indici di input di TPUeMBEDDING di uno sparsetensor. |
| Enqueuetpuembeddingsparsebatch.options | Attributi opzionali per EnqueueTPUEmbeddingSparseBatch |
| EnqueuetpuembeddingsParsetenSorbatch | Allevia il porting del codice che utilizza tf.nn.embedding_lookup_sparse (). |
| EnqueuetpuembeddingsParsetenSorbatch.options | Attributi opzionali per EnqueueTPUEmbeddingSparseTensorBatch |
| AssureSHape <t estende TType > | Assicura che la forma del tensore corrisponda alla forma prevista. |
| Immettere <t estende TType > | Crea o trova un frame figlio e rende `Data` disponibile per il frame figlio. |
| Enter.options | Attributi opzionali per Enter |
| Entryvalue | tensorflow.EntryValue di tipo protobuf |
| Entryvalue.Builder | tensorflow.EntryValue di tipo protobuf |
| Entryvalue.kindcase | |
| EntryValueOrbuilder | |
| Pari | Restituisce il valore della verità di (x == y) per l'elemento. |
| Uguali. Opzioni | Attributi opzionali per Equal |
| ERF <t estende tnumber > | Calcola la funzione di errore Gauss di `x` elemento. |
| ERFC <t estende tnumber > | Calcola la funzione di errore complementare di `x` elemento. |
| erfinv <t estende tnumber > | |
| Errorcodes | |
| ErrorCodesProtos | |
| Euclideannorm <t estende TType > | Calcola la norma euclidea degli elementi attraverso le dimensioni di un tensore. |
| Euclideannorm.options | Attributi opzionali per EuclideanNorm |
| Evento | Protocol buffer representing an event that happened during the execution of a Brain model. |
| Event.Builder | Protocol buffer representing an event that happened during the execution of a Brain model. |
| Event.whatcase | |
| Eventorbuilder | |
| EventProtos | |
| Esempio | tensorflow.Example di tipo protobuf |
| Esempio.Builder | tensorflow.Example di tipo protobuf |
| Esempio.orbuilder | |
| Esempio difigurazione | tensorflow.ExampleParserConfiguration di tipo protobuf.exampleConfiguration |
| EsempioParsConfiguration.Builder | tensorflow.ExampleParserConfiguration di tipo protobuf.exampleConfiguration |
| EXAMTPARSConfigurationorBuilder | |
| EsempioParsConfigurationProtos | |
| EsempioProtos | |
| Eseguire | OP che carica ed esegue un programma TPU su un dispositivo TPU. |
| Esecuteandupdatevariables | OP che esegue un programma con aggiornamenti variabili sul posto opzionali. |
| Esecuzione | Data relating to the eager execution of an op or a Graph. |
| Execution.Builder | Data relating to the eager execution of an op or a Graph. |
| ExecutionEnvironment | Definisce un ambiente per la creazione e l'esecuzione Operation di Tensorflow s. |
| ExecutionEnvironment.Types | |
| ExecutionOrbuilder | |
| Exit <t estende TType > | Esce il frame corrente sul frame genitore. |
| Exp <t estende TType > | Calcola esponenziale di X Element-Wise. |
| ExpandDims <t estende TType > | Inserisce una dimensione di 1 nella forma di un tensore. |
| EXPINT <t estende tnumber > | |
| Expm1 <t estende TType > | Calcola `exp (x) - 1` -wise. |
| Esponenziale <t estende tfloating > | Funzione di attivazione esponenziale. |
| Estratto | Estrae uno sguardo dal tensore di ingresso. |
| Extractglimpse.options | Attributi opzionali per ExtractGlimpse |
| ExtractImagePatchs <t estende TType > | Estrai `patch" da `immagini` e mettile nella dimensione di uscita" profondità ". |
| Extractjpegshape <t estende tnumber > | Estrai le informazioni di forma di un'immagine codificata da JPEG. |
| ExtractVolumePatchs <t estende tnumber > | Estrai `patchs` da` input` e mettili nella dimensione di output `" profondità ". |
F
| Fatto | Output un fatto sui fattoriali. |
| False quarantwithminmaxargs | Falso quantizzare il tensore "input", tipo galleggiante su "uscite" tensore dello stesso tipo. |
| FalseQuantWithMinmaxargs.options | Attributi opzionali per FakeQuantWithMinMaxArgs |
| FACETQUANTWITHMINMAXARGSGRADIENT | Calcola i gradienti per un funzionamento falso quadratiwithminmaxargs. |
| FalseQuantWithMinmaxargsGradient.options | Attributi opzionali per FakeQuantWithMinMaxArgsGradient |
| FalseQuantWithMinMaxvars | Falso quarantare il tensore di tipo "input" di tipo float tramite scalari float globali Falso quantizzare il tensore `Inputs" di tipo float tramite scalari float globali `min` e` max` a `outputs" Tensore della stessa forma di `Inputs`. |
| FalseQuantWithMinMaxvars.options | Attributi opzionali per FakeQuantWithMinMaxVars |
| FalseQuantWithMinMaxVarsgradient | Calcola i gradienti per un funzionamento falso quadratiwithminmaxvars. |
| FalseQuantWithMinMaxVarsgradient.options | Attributi opzionali per FakeQuantWithMinMaxVarsGradient |
| FalseQuantWithMinMaxvarsperChannel | Falso quarantare il tensore di tipo "input" di tipo galleggiante tramite carri per canali Falso-qualificare il tensore `inputs" di tipo float per canale e una delle forme: `[d]`, `[b, d]` `[b, h, w, d]` via per-canale ` Min` e `max` di forma` [d] `to` outputs "Tensor della stessa forma di` Inputs`. |
| FalseQuantWithMinMaxvarsperChannel.options | Attributi opzionali per FakeQuantWithMinMaxVarsPerChannel |
| FACETQUANTWITHINMAXVarsPerChannelgradient | Calcola i gradienti per un'operazione falsa quadratawithminmaxvarsperchannel. |
| FalseQuantWithMinmaxvarsperChannelGradient.options | Attributi opzionali per FakeQuantWithMinMaxVarsPerChannelGradient |
| FastElement sequence <t, u estende ndarray <t>> | Una sequenza che ricicla la stessa istanza NdArray durante iterazioni dei suoi elementi |
| Caratteristica | Containers for non-sequential data. |
| Feature.Builder | Containers for non-sequential data. |
| Caratteristica.kindcase | |
| FeatureConfiguration | tensorflow.FeatureConfiguration di tipo protobuf.featureConfiguration |
| FeatureConfiguration.Builder | tensorflow.FeatureConfiguration di tipo protobuf.featureConfiguration |
| FeatureConfiguration.configcase | |
| FeatureConfigurationorBuilder | |
| Featurelist | Containers for sequential data. |
| FeatureList.Builder | Containers for sequential data. |
| FeatureListorbuilder | |
| Featurelists | tensorflow.FeatureLists di tipo protobuf |
| Featurelists.Builder | tensorflow.FeatureLists di tipo protobuf |
| Featurelistsorbuilder | |
| FeatureRorbuilder | |
| FeatureProtos | |
| Caratteristiche | tensorflow.Features di tipo protobuf |
| Caratteristiche.Builder | tensorflow.Features di tipo protobuf |
| Caratteristicheorbuilder | |
| Fft <t estende TType > | Trasformata veloce di Fourier. |
| Fft2d <t estende TType > | Trasformata di Fourier veloce 2D. |
| Fft3d <t estende TType > | Trasformata di Fourier 3d Fast Fourier. |
| FIFAQUEUE | Una coda che produce elementi in primo ordine. |
| FIFOQUEUE.OPTIONS | Attributi opzionali per FifoQueue |
| Riempire <u estende TType > | Crea un tensore pieno di un valore scalare. |
| FilterbyLastComponentDataSet | Crea un set di dati contenente elementi del primo componente di `input_dataset` che ha vero nell'ultimo componente. |
| Impronta digitale | Genera valori di impronte digitali. |
| FiteLlenfeatureProto | tensorflow.FixedLenFeatureProto di tipo protobuf.fixedlenfeatureProto |
| Fissedlenfeatureproto.builder | tensorflow.FixedLenFeatureProto di tipo protobuf.fixedlenfeatureProto |
| FiteLlenfeatureProtoorBuilder | |
| FixtLengthRecordDataSet | |
| FixtLengthRecorder | Un lettore che emette record a lunghezza fissa da un file. |
| FixtLengthRecordreader.options | Attributi opzionali per FixedLengthRecordReader |
| FeedUnigramCandidateSampler | Genera etichette per il campionamento dei candidati con una distribuzione di unigram appresa. |
| Fissedunigramcandidatesampler.options | Attributi opzionali per FixedUnigramCandidateSampler |
| Float16layout | Layout dei dati che converte le galleggianti a 32 bit da/a 16 bit, di conseguenza alla specifica del punto galleggiante IEEE-754 a mezza precisione. |
| Floatdatabuffer | Un DataBuffer di galleggianti. |
| Floatdatalayout <s estende databuffer <? >> | Un DataLayout che converte i dati archiviati in un buffer per galleggiare. |
| FloatdensendArray | |
| Floatlist | tensorflow.FloatList di tipo protobuf |
| Floatlist.builder | tensorflow.FloatList di tipo protobuf |
| Floatlistorbuilder | |
| Floatndarray | Un NdArray di galleggianti. |
| Il pavimento <t estende tnumber > | Restituisce un numero intero più grande dell'elemento non maggiore di x. |
| Floordiv <t estende TType > | Restituisce x // y-elemento-wise. |
| Floormod <t estende tnumber > | Restituisce il resto della divisione. |
| Flushummarywriter | |
| FractionAlavgPool <t estende Tnumber > | Esegue un pool medio frazionario sull'input. |
| Fractionalavgpool.options | Attributi opzionali per FractionalAvgPool |
| FractionAlavgPoolgrad <T estende Tnumber > | Calcola il gradiente della funzione FractionAlavgpool. |
| Fractionalavgpoolgrad.options | Attributi opzionali per FractionalAvgPoolGrad |
| Fractionalmaxpool <t estende tnumber > | Esegue un pool di max frazionario sull'ingresso. |
| Fractionalmaxpool.options | Attributi opzionali per FractionalMaxPool |
| Fractionalmaxpoolgrad <t estende tnumber > | Calcola il gradiente della funzione FractionalMaxPool. |
| Fractionalmaxpoolgrad.options | Attributi opzionali per FractionalMaxPoolGrad |
| Fresnelcos <t estende tnumber > | |
| Fresnelsin <t estende tnumber > | |
| Ftrl | Ottimizzatore che implementa l'algoritmo FTRL. |
| Functiondef | A function can be instantiated when the runtime can bind every attr with a value. |
| Functiondef.argattrs | Attributes for function arguments. |
| Functiondef.argatts.builder | Attributes for function arguments. |
| Functiondef.argattsorbuilder | |
| Functiondef.builder | A function can be instantiated when the runtime can bind every attr with a value. |
| Functiondeflibrary | A library is a set of named functions. |
| Functiondeflibrary.builder | A library is a set of named functions. |
| Functiondeflibraryorbuilder | |
| Functiondeforbuilder | |
| Functionprotos | |
| Functionspec | Represents `FunctionSpec` used in `Function`. |
| Functionspec.builder | Represents `FunctionSpec` used in `Function`. |
| Functionspec.experimentalCompile | Whether the function should be compiled by XLA. |
| Functionspecorbuilder | |
| Fusedbatchnorm <t estende tnumber , u estende tnumber > | Normalizzazione batch. |
| Fusedbatchnorm.options | Attributi opzionali per FusedBatchNorm |
| Fusedbatchnormgrad <t estende tnumber , u estende tnumber > | Gradiente per la normalizzazione batch. |
| Fusedbatchnormgrad.options | Attributi opzionali per FusedBatchNormGrad |
| Fusedpadconv2d <t estende tnumber > | Esegue un'imbottitura come preprocesso durante una convoluzione. |
| FusedResizeAndpadConv2d <t estende tnumber > | Esegue un ridimensionamento e un'imbottitura come preprocesso durante una convoluzione. |
| FusedResizeAndpadConv2d.Options | Attributi opzionali per FusedResizeAndPadConv2d |
G
| Raccogli <t estende tnumber > | Accumula reciprocamente più tensori di tipo e forma identici. |
| Raccogli <t estende TType > | Raccogli fette dall'asse `parametri` asse `Secondo` indici '. |
| Raccogli <t estende TType > | Avvolge l'operatore di raccolta XLA documentato a https://www.tensorflow.org/xla/operation_semantics#gather |
| Gather.options | Attributi opzionali per Gather |
| Gather.options | Attributi opzionali per Gather |
| Gathend <t estende TType > | Raccogli le fette da `parametri 'in un tensore con forma specificata da` indici'. |
| Gallv2 <t estende tnumber > | Accumula reciprocamente più tensori di tipo e forma identici. |
| Gallv2.options | Attributi opzionali per GatherV2 |
| GenerateBoundingBoxProposals | Questo OP produce regioni di interesse dalle caselle di alimitazione (BBOX_DELTAS) codificate con le ancode WRT secondo Eq.2 in ARXIV: 1506.01497 L'OP seleziona le caselle di punteggio TOP `pre_nms_topn`, le decodifica rispetto agli ancore, applica una soppressione non maximal su caselle sovrapposte con un valore di intersezione-over-union (IOU) superiore a` min_size`. |
| GenerateBoundingBoxProposals.options | Attributi opzionali per GenerateBoundingBoxProposals |
| Generarevocabrapping | Dato un percorso per i nuovi e vecchi file del vocabolario, restituisce un tensore di rimappatura di Lunghezza `NUM_NEW_VOCAB`, dove` rimapping [i] `contiene il numero di riga nel vecchio vocabolario che corrisponde alla riga` I` nel nuovo vocabolario (a partire dalla riga `new_vocab_offset` e fino a` num_new_vocab` entità) o `- 1` se l'ingresso `io nel nuovo vocabolario non è nel vecchio vocabolario. |
| Generarevocabrapping.options | Attributi opzionali per GenerateVocabRemapping |
| GetSessionHandle | Conservare il tensore di input nello stato della sessione corrente. |
| GetSessionTensor <t estende TType > | Ottieni il valore del tensore specificato dalla sua maniglia. |
| GOROT <t estende tfloating > | L'inizializzatore Glorot, chiamato anche inizializzatore Xavier. |
| Gpuinfo | tensorflow.GPUInfo di tipo protobuf.gpuinfo |
| Gpuinfo.builder | tensorflow.GPUInfo di tipo protobuf.gpuinfo |
| Gpuinfoorbuilder | |
| Gpuoptions | tensorflow.GPUOptions di tipo protobuf |
| Gpuoptions.builder | tensorflow.GPUOptions di tipo protobuf |
| Gpuoptions.experimental | tensorflow.GPUOptions.Experimental di tipo protobuf.gpuoptions.experimental |
| Gpuoptions.experimental.builder | tensorflow.GPUOptions.Experimental di tipo protobuf.gpuoptions.experimental |
| Gpuoptions.experimental.virtualDevices | Configuration for breaking down a visible GPU into multiple "virtual" devices. |
| Gpuoptions.experimental.virtualdevices.builder | Configuration for breaking down a visible GPU into multiple "virtual" devices. |
| Gpuoptions.experimental.virtualdevicesorbuilder | |
| Gpuoptions.experimentalorbuilder | |
| Gpuoptionsorbuilder | |
| GradientDef | GradientDef defines the gradient function of a function defined in a function library. |
| GradientDef.Builder | GradientDef defines the gradient function of a function defined in a function library. |
| GradientDeForbuilder | |
| GradientDescent | Ottimizzatore di discesa gradiente stocastico di base. |
| Gradienti | Aggiunge le operazioni per calcolare i derivati parziali della somma di y s wrt x s, ie, d(y_1 + y_2 + ...)/dx_1, d(y_1 + y_2 + ...)/dx_2... |
| Gradients.options | Attributi opzionali per Gradients |
| Grafico | Un grafico del flusso di dati che rappresenta un calcolo Tensorflow. |
| Grafico.WhilesubgraphBuilder | Utilizzato per istanziare una classe astratta che prevalga il metodo buildSubgraph per costruire un sottografo condizionale o corporeo per un po '. |
| GraphDebuginfo | tensorflow.GraphDebugInfo di tipo protobuf.GRAPHDEBUGINFO |
| Graphdebuginfo.builder | tensorflow.GraphDebugInfo di tipo protobuf.GRAPHDEBUGINFO |
| Graphdebuginfo.fileLinecol | This represents a file/line location in the source code. |
| Graphdebuginfo.fileLinecol.builder | This represents a file/line location in the source code. |
| GraphDebuginfo.fileLineColorbuilder | |
| Graphdebuginfo.stacktrace | This represents a stack trace which is a ordered list of `FileLineCol`. |
| Graphdebuginfo.stacktrace.builder | This represents a stack trace which is a ordered list of `FileLineCol`. |
| Graphdebuginfo.stacktraceorbuilder | |
| GraphDebuginfoorbuilder | |
| Graphdebuginfoprotos | |
| GraphDef | Represents the graph of operations tensorflow.GraphDef di tipo protobuf |
| GraphDef.Builder | Represents the graph of operations tensorflow.GraphDef di tipo protobuf |
| GraphDeforbuilder | |
| Grafexecutiontrace | Data relating to an execution of a Graph (e.g., an eager execution of a FuncGraph). |
| Grafexecutiontrace.builder | Data relating to an execution of a Graph (e.g., an eager execution of a FuncGraph). |
| Grafexecutiontraceorbuilder | |
| Graphopcreation | The creation of an op in a TensorFlow Graph (e.g., FuncGraph in TF2). |
| Graphoppcreation.builder | The creation of an op in a TensorFlow Graph (e.g., FuncGraph in TF2). |
| Graphoppcreationorbuilder | |
| Graphoperation | Implementazione per Operation aggiunta come nodo a un Graph . |
| Graphoperationbuilder | Un OperationBuilder per l'aggiunta GraphOperation S a un Graph . |
| Grafopzioni | tensorflow.GraphOptions di tipo protobuf |
| Graphoptions.builder | tensorflow.GraphOptions di tipo protobuf |
| GraphOptionsorbuilder | |
| Graphprotos | |
| GraphTransferConstNodeInfo | tensorflow.GraphTransferConstNodeInfo di tipo protobuf.GraphTransferConstNodeInfo |
| GraphTransferConstNodeInfo.Builder | tensorflow.GraphTransferConstNodeInfo di tipo protobuf.GraphTransferConstNodeInfo |
| GraphTransferConstNodeInFoorbuilder | |
| GraphTransferGraphInputNodeInfo | tensorflow.GraphTransferGraphInputNodeInfo di tipo protobuf.GraphTransferGraphInputNodeInfo |
| GraphTransferGraphInputNodeInfo.Builder | tensorflow.GraphTransferGraphInputNodeInfo di tipo protobuf.GraphTransferGraphInputNodeInfo |
| GraphTransferGraphInputNodeInfoorBuilder | |
| GraphTransferGraphOutputNodeInfo | tensorflow.GraphTransferGraphOutputNodeInfo di tipo protobuf.GraphTransferGrapHoutPutNodeInfo |
| GraphTransferGraphOutputNodeInfo.Builder | tensorflow.GraphTransferGraphOutputNodeInfo di tipo protobuf.GraphTransferGrapHoutPutNodeInfo |
| GraphTransferGraphOutputPutNodeInfoorBuilder | |
| GraphTransferInfo | Protocol buffer representing a handle to a tensorflow resource. |
| GraphTransferInfo.Builder | Protocol buffer representing a handle to a tensorflow resource. |
| GraphTransferInfo.Destination | Protobuf enum tensorflow.GraphTransferInfo.Destination |
| GraphTransferInfoorBuilder | |
| GraphTransferInfoproto | |
| GraphTransferNodeInfo | tensorflow.GraphTransferNodeInfo di tipo protobuf.GraphTransferNodeInfo |
| GraphTransferNodeInfo.Builder | tensorflow.GraphTransferNodeInfo di tipo protobuf.GraphTransferNodeInfo |
| GraphTransferNodeInFoorbuilder | |
| GraphTransferNodeInput | tensorflow.GraphTransferNodeInput di tipo protobuf.GraphTransferNodeInput |
| GraphTransferNodeInput.Builder | tensorflow.GraphTransferNodeInput di tipo protobuf.GraphTransferNodeInput |
| GraphTransferNodeInputInfo | tensorflow.GraphTransferNodeInputInfo di tipo protobuf.GraphTransferNodeInputInfo |
| GraphTransferNodeInputInfo.Builder | tensorflow.GraphTransferNodeInputInfo di tipo protobuf.GraphTransferNodeInputInfo |
| GraphTransferNodeInputInfoorBuilder | |
| GraphTransferNodeInputorbuilder | |
| GraphTransferNodeOutputInfo | tensorflow.GraphTransferNodeOutputInfo di tipo protobuf.GraphTransferNodeOutputInfo |
| GraphTransferNodeOutputInfo.Builder | tensorflow.GraphTransferNodeOutputInfo di tipo protobuf.GraphTransferNodeOutputInfo |
| GraphTransferNodeOutputputInfoorBuilder | |
| Maggiore | Restituisce il valore della verità di (x> y) per l'elemento. |
| Più equal | Restituisce il valore della verità di (x> = y) dall'elemento. |
| GRUBLOCKCELL <t estende tnumber > | Calcola la propagazione della cella GRU per 1 fase temporale. |
| GRUBLOCKCELLGRAD <T estende Tnumber > | Calcola la propagazione del retro della cella GRU per 1 fase temporale. |
| GarantEConst <t estende TType > | Fornisce una garanzia al runtime TF che il tensore di input è una costante. |
H
| Hardsigmoid <t estende tfloating > | Attivazione del sigmoide duro. |
| Hashtable | Crea una tabella di hash non inizializzata. |
| Hashtable.options | Attributi opzionali per HashTable |
| Lui si estende tfloating > | Inizializzatore. |
| Aiutanti | Classe del contenitore per metodi core che aggiungono o eseguono diverse operazioni e ne restituiscono una. |
| Cerniera | Calcola la perdita di cerniera tra etichette e previsioni. |
| La cerniera si estende tnumber > | Una metrica che calcola la metrica per perdita di cerniera tra etichette e previsioni. |
| HistogramFixedWidth <U estende Tnumber > | Restituire l'istogramma dei valori. |
| Istogramma | Serialization format for histogram module in core/lib/histogram/histogram.h tensorflow.HistogramProto di tipo protobuf.histogramProto |
| Histogramproto.builder | Serialization format for histogram module in core/lib/histogram/histogram.h tensorflow.HistogramProto di tipo protobuf.histogramProto |
| IstogramProtoorBuilder | |
| Istogramma | Uscita un tampone di protocollo `Riepilogo` con un istogramma. |
| Hsvtorgb <t estende tnumber > | Converti una o più immagini da HSV a RGB. |
| Huber | Calcola la perdita di Huber tra etichette e previsioni. |
IO
| Identità <t estende tfloating > | Inizializzatore che genera la matrice di identità. |
| Identity <t estende TType > | Restituisci un tensore con la stessa forma e contenuto del tensore o del valore di ingresso. |
| Identityn | Restituisce un elenco di tensori con le stesse forme e contenuti dell'input tensori. |
| IdentityReader | Un lettore che produce il lavoro in coda sia come chiave che come valore. |
| IdentityReader.options | Attributi opzionali per IdentityReader |
| Iffft <t estende tType > | Trasformata inversa veloce di Fourier. |
| Ifft2d <t estende TType > | Trasformata inversa 2d veloce di Fourier. |
| IFFT3D <t estende TType > | Trasformata inversa 3d veloce di Fourier. |
| Igamma <t estende tnumber > | Calcola la funzione gamma incompleta regolarizzata inferiore `p (a, x)`. |
| Igammac <t estende tnumber > | Calcola la funzione gamma incompleta regolarizzata superiore `q (a, x)`. |
| Igammagrada <t estende tnumber > | Calcola il gradiente di `igamma (a, x)` wrt `a`. |
| IgnoreErrorsDataSet | Crea un set di dati che contiene gli elementi di `input_dataset` di ignorare gli errori. |
| IgnoreErrorsDataSet | Crea un set di dati che contiene gli elementi di `input_dataset` di ignorare gli errori. |
| IgnoreErrorsDataSet.options | Attributi opzionali per IgnoreErrorsDataset |
| IgnoreErrorsDataSet.options | Attributi opzionali per IgnoreErrorsDataset |
| IllealRankexception | Eccezione lanciata quando un'operazione non può essere completata a causa del rango dell'array mirato. |
| Imag <u estende tnumber > | Restituisce la parte immaginaria di un numero complesso. |
| ImageProjectETetransformv2 <t estende tnumber > | Applica la trasformata data a ciascuna delle immagini. |
| ImageProjectETransFormV2.Options | Attributi opzionali per ImageProjectiveTransformV2 |
| ImageProjectIVetransformv3 <t estende Tnumber > | Applica la trasformata data a ciascuna delle immagini. |
| ImageProjectETransFormV3.Options | Attributi opzionali per ImageProjectiveTransformV3 |
| IMMAGINIMARIO | Output un tampone di protocollo `Riepilogo` con immagini. |
| Imagesummary.options | Attributi opzionali per ImageSummary |
| ImmutableConst <t estende TType > | Restituisce un tensore immutabile dalla regione della memoria. |
| Importazione | |
| Indice | Un indice utilizzato per tagliare una vista da un array n-dimensionale. |
| Indicizzatore indicizzato | |
| IndiceSedPositionIterator.coordslongConsumer | |
| Indici | Classe di aiuto per istanziazione di oggetti Index . |
| Infeeddequeue <t estende TType > | Un OP segnaposto per un valore che verrà alimentato nel calcolo. |
| Infeeddequeuetuple | Prendi più valori da Aneed come una tupla XLA. |
| Infeedenqueue | Un OP che alimenta un singolo valore tensore nel calcolo. |
| Infeedenqueue.options | Attributi opzionali per InfeedEnqueue |
| InfeedenQueuePrelinearizedBuffer | Un OP che accentua il tampone preliminare in TPU. |
| InfeedenQueuePrelinearizedBuffer.options | Attributi opzionali per InfeedEnqueuePrelinearizedBuffer |
| Infeedenqueuetuple | Alimenta più valori di tensore nel calcolo come tupla XLA. |
| Infeedenqueuetuple.options | Attributi opzionali per InfeedEnqueueTuple |
| Init | |
| Initializer <T estende TType > | Un'interfaccia per inizializzatori |
| Inizializzabile | Inizializzatore della tabella che assume due tensori per le chiavi e i valori rispettivamente. |
| InitializetableFromDataSet | |
| InitializetableFromTextFile | Inizializza una tabella da un file di testo. |
| InitializetableFromTextFile.options | Attributi opzionali per InitializeTableFromTextFile |
| Inplaceadd <t estende TType > | Aggiunge V in file specificate di x. |
| Inplacesub <t estende TType > | Sottrae `V` in righe specificate di` x`. |
| Inplaceupdate <t estende tType > | Aggiornamenti Le righe specificate "i" con valori 'V'. |
| Int64list | tensorflow.Int64List di tipo protobuf.int64list |
| Int64List.Builder | tensorflow.Int64List di tipo protobuf.int64list |
| Int64Listorbuilder | |
| IntDataBuffer | Un DataBuffer di int. |
| IntDataLayout <s estende DataBuffer <? >> | Un DataLayout che converte i dati archiviati in un buffer in INT. |
| IntdensendArray | |
| Interconnectlink | tensorflow.InterconnectLink di tipo protobuf.InterConnectLink |
| Interconnectlink.builder | Protobuf type tensorflow.InterconnectLink |
| InterconnectLinkOrBuilder | |
| IntNdArray | An NdArray of integers. |
| InTopK | Says whether the targets are in the top `K` predictions. |
| Inv <T extends TType > | Computes the inverse of one or more square invertible matrices or their adjoints (conjugate transposes). |
| Inv.Options | Optional attributes for Inv |
| Invert <T extends TNumber > | Invert (flip) each bit of supported types; for example, type `uint8` value 01010101 becomes 10101010. |
| InvertPermutation <T extends TNumber > | Computes the inverse permutation of a tensor. |
| InvGrad <T extends TType > | Computes the gradient for the inverse of `x` wrt its input. |
| Irfft <U extends TNumber > | Inverse real-valued fast Fourier transform. |
| Irfft2d <U extends TNumber > | Inverse 2D real-valued fast Fourier transform. |
| Irfft3d <U extends TNumber > | Inverse 3D real-valued fast Fourier transform. |
| IsBoostedTreesEnsembleInitialized | Checks whether a tree ensemble has been initialized. |
| IsBoostedTreesQuantileStreamResourceInitialized | Checks whether a quantile stream has been initialized. |
| IsFinite | Returns which elements of x are finite. |
| IsInf | Returns which elements of x are Inf. |
| IsNan | Returns which elements of x are NaN. |
| IsotonicRegression <U extends TNumber > | Solves a batch of isotonic regression problems. |
| IsVariableInitialized | Checks whether a tensor has been initialized. |
| Iterator | |
| IteratorFromStringHandle | |
| IteratorFromStringHandle.Options | Optional attributes for IteratorFromStringHandle |
| IteratorGetDevice | Returns the name of the device on which `resource` has been placed. |
| IteratorGetDevice | Returns the name of the device on which `resource` has been placed. |
| IteratorGetNext | Gets the next output from the given iterator . |
| IteratorGetNextAsOptional | Gets the next output from the given iterator as an Optional variant. |
| IteratorGetNextSync | Gets the next output from the given iterator. |
| IteratorToStringHandle | Converts the given `resource_handle` representing an iterator to a string. |
J
| JobDef | Defines a single job in a TensorFlow cluster. |
| JobDef.Builder | Defines a single job in a TensorFlow cluster. |
| JobDefOrBuilder | |
| JobDeviceFilters | Defines the device filters for tasks in a job. |
| JobDeviceFilters.Builder | Defines the device filters for tasks in a job. |
| JobDeviceFiltersOrBuilder | |
| Giuntura | Joins the strings in the given list of string tensors into one tensor; with the given separator (default is an empty separator). |
| Join.Options | Optional attributes for Join |
K
| KernelDef | Protobuf type tensorflow.KernelDef |
| KernelDef.AttrConstraint | Protobuf type tensorflow.KernelDef.AttrConstraint |
| KernelDef.AttrConstraint.Builder | Protobuf type tensorflow.KernelDef.AttrConstraint |
| KernelDef.AttrConstraintOrBuilder | |
| KernelDef.Builder | Protobuf type tensorflow.KernelDef |
| KernelDefOrBuilder | |
| KernelDefProtos | |
| KernelList | A collection of KernelDefsProtobuf type tensorflow.KernelList |
| KernelList.Builder | A collection of KernelDefsProtobuf type tensorflow.KernelList |
| KernelListOrBuilder | |
| KeyValueSort <T extends TNumber , U extends TType > | Wraps the XLA Sort operator, documented at https://www.tensorflow.org/performance/xla/operation_semantics#sort . |
| KLDivergence | Computes Kullback-Leibler divergence loss between labels and predictions. |
| KLDivergence <T extends TNumber > | A metric that computes the Kullback-Leibler divergence loss metric between labels and predictions. |
| KMC2ChainInitialization | Returns the index of a data point that should be added to the seed set. |
| KmeansPlusPlusInitialization | Selects num_to_sample rows of input using the KMeans++ criterion. |
| KthOrderStatistic | Computes the Kth order statistic of a data set. |
l
| L2Loss <T extends TNumber > | L2 Loss. |
| LatencyStatsDataset | Records the latency of producing `input_dataset` elements in a StatsAggregator. |
| LatencyStatsDataset | Records the latency of producing `input_dataset` elements in a StatsAggregator. |
| LeakyRelu <T extends TNumber > | Computes rectified linear: `max(features, features * alpha)`. |
| LeakyRelu.Options | Optional attributes for LeakyRelu |
| LeakyReluGrad <T extends TNumber > | Computes rectified linear gradients for a LeakyRelu operation. |
| LeakyReluGrad.Options | Optional attributes for LeakyReluGrad |
| LearnedUnigramCandidateSampler | Generates labels for candidate sampling with a learned unigram distribution. |
| LearnedUnigramCandidateSampler.Options | Optional attributes for LearnedUnigramCandidateSampler |
| LeCun <T extends TFloating > | LeCun normal initializer. |
| LeftShift <T extends TNumber > | Elementwise computes the bitwise left-shift of `x` and `y`. |
| Meno | Returns the truth value of (x < y) element-wise. |
| LessEqual | Returns the truth value of (x <= y) element-wise. |
| Lgamma <T extends TNumber > | Computes the log of the absolute value of `Gamma(x)` element-wise. |
| Linear <U extends TNumber > | Linear activation function (pass-through). |
| LinSpace <T extends TNumber > | Generates values in an interval. |
| Listener_BytePointer | |
| Listener_String | |
| ListValue | Represents a Python list. |
| ListValue.Builder | Represents a Python list. |
| ListValueOrBuilder | |
| LMDBDataset | Creates a dataset that emits the key-value pairs in one or more LMDB files. |
| LmdbDataset | |
| LmdbReader | A Reader that outputs the records from a LMDB file. |
| LmdbReader.Options | Optional attributes for LmdbReader |
| LoadAndRemapMatrix | Loads a 2-D (matrix) `Tensor` with name `old_tensor_name` from the checkpoint at `ckpt_path` and potentially reorders its rows and columns using the specified remappings. |
| LoadAndRemapMatrix.Options | Optional attributes for LoadAndRemapMatrix |
| LoadTPUEmbeddingAdadeltaParameters | Load Adadelta embedding parameters. |
| LoadTPUEmbeddingAdadeltaParameters.Options | Optional attributes for LoadTPUEmbeddingAdadeltaParameters |
| LoadTPUEmbeddingAdadeltaParametersGradAccumDebug | Load Adadelta parameters with debug support. |
| LoadTPUEmbeddingAdadeltaParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingAdadeltaParametersGradAccumDebug |
| LoadTPUEmbeddingAdagradParameters | Load Adagrad embedding parameters. |
| LoadTPUEmbeddingAdagradParameters.Options | Optional attributes for LoadTPUEmbeddingAdagradParameters |
| LoadTPUEmbeddingAdagradParametersGradAccumDebug | Load Adagrad embedding parameters with debug support. |
| LoadTPUEmbeddingAdagradParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingAdagradParametersGradAccumDebug |
| LoadTPUEmbeddingADAMParameters | Load ADAM embedding parameters. |
| LoadTPUEmbeddingADAMParameters.Options | Optional attributes for LoadTPUEmbeddingADAMParameters |
| LoadTPUEmbeddingADAMParametersGradAccumDebug | Load ADAM embedding parameters with debug support. |
| LoadTPUEmbeddingADAMParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingADAMParametersGradAccumDebug |
| LoadTPUEmbeddingCenteredRMSPropParameters | Load centered RMSProp embedding parameters. |
| LoadTPUEmbeddingCenteredRMSPropParameters.Options | Optional attributes for LoadTPUEmbeddingCenteredRMSPropParameters |
| LoadTPUEmbeddingFTRLParameters | Load FTRL embedding parameters. |
| LoadTPUEmbeddingFTRLParameters.Options | Optional attributes for LoadTPUEmbeddingFTRLParameters |
| LoadTPUEmbeddingFTRLParametersGradAccumDebug | Load FTRL embedding parameters with debug support. |
| LoadTPUEmbeddingFTRLParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingFTRLParametersGradAccumDebug |
| LoadTPUEmbeddingMDLAdagradLightParameters | Load MDL Adagrad Light embedding parameters. |
| LoadTPUEmbeddingMDLAdagradLightParameters.Options | Optional attributes for LoadTPUEmbeddingMDLAdagradLightParameters |
| LoadTPUEmbeddingMomentumParameters | Load Momentum embedding parameters. |
| LoadTPUEmbeddingMomentumParameters.Options | Optional attributes for LoadTPUEmbeddingMomentumParameters |
| LoadTPUEmbeddingMomentumParametersGradAccumDebug | Load Momentum embedding parameters with debug support. |
| LoadTPUEmbeddingMomentumParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingMomentumParametersGradAccumDebug |
| LoadTPUEmbeddingProximalAdagradParameters | Load proximal Adagrad embedding parameters. |
| LoadTPUEmbeddingProximalAdagradParameters.Options | Optional attributes for LoadTPUEmbeddingProximalAdagradParameters |
| LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug | Load proximal Adagrad embedding parameters with debug support. |
| LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug |
| LoadTPUEmbeddingProximalYogiParameters | |
| LoadTPUEmbeddingProximalYogiParameters.Options | Optional attributes for LoadTPUEmbeddingProximalYogiParameters |
| LoadTPUEmbeddingProximalYogiParametersGradAccumDebug | |
| LoadTPUEmbeddingProximalYogiParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingProximalYogiParametersGradAccumDebug |
| LoadTPUEmbeddingRMSPropParameters | Load RMSProp embedding parameters. |
| LoadTPUEmbeddingRMSPropParameters.Options | Optional attributes for LoadTPUEmbeddingRMSPropParameters |
| LoadTPUEmbeddingRMSPropParametersGradAccumDebug | Load RMSProp embedding parameters with debug support. |
| LoadTPUEmbeddingRMSPropParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingRMSPropParametersGradAccumDebug |
| LoadTPUEmbeddingStochasticGradientDescentParameters | Load SGD embedding parameters. |
| LoadTPUEmbeddingStochasticGradientDescentParameters.Options | Optional attributes for LoadTPUEmbeddingStochasticGradientDescentParameters |
| LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug | Load SGD embedding parameters. |
| LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug |
| LocalLinks | Protobuf type tensorflow.LocalLinks |
| LocalLinks.Builder | Protobuf type tensorflow.LocalLinks |
| LocalLinksOrBuilder | |
| LocalResponseNormalization <T extends TNumber > | Local Response Normalization. |
| LocalResponseNormalization.Options | Optional attributes for LocalResponseNormalization |
| LocalResponseNormalizationGrad <T extends TNumber > | Gradients for Local Response Normalization. |
| LocalResponseNormalizationGrad.Options | Optional attributes for LocalResponseNormalizationGrad |
| Log <T extends TType > | Computes natural logarithm of x element-wise. |
| Log1p <T extends TType > | Computes natural logarithm of (1 + x) element-wise. |
| LogCosh | Computes Computes the logarithm of the hyperbolic cosine of the prediction error. |
| LogCoshError <T extends TNumber > | A metric that computes the logarithm of the hyperbolic cosine of the prediction error metric between labels and predictions. |
| LogicalAnd | Returns the truth value of x AND y element-wise. |
| LogicalNot | Returns the truth value of `NOT x` element-wise. |
| LogicalOr | Returns the truth value of x OR y element-wise. |
| LogMatrixDeterminant <T extends TType > | Computes the sign and the log of the absolute value of the determinant of one or more square matrices. |
| LogMemoryProtos | |
| LogMessage | Protocol buffer used for logging messages to the events file. |
| LogMessage.Builder | Protocol buffer used for logging messages to the events file. |
| LogMessage.Level | Protobuf enum tensorflow.LogMessage.Level |
| LogMessageOrBuilder | |
| LogSoftmax <T extends TNumber > | Computes log softmax activations. |
| LogUniformCandidateSampler | Generates labels for candidate sampling with a log-uniform distribution. |
| LogUniformCandidateSampler.Options | Optional attributes for LogUniformCandidateSampler |
| LongDataBuffer | A DataBuffer of longs. |
| LongDataLayout <S extends DataBuffer <?>> | A DataLayout that converts data stored in a buffer to longs. |
| LongDenseNdArray | |
| LongNdArray | An NdArray of longs. |
| LookupTableExport <T extends TType , U extends TType > | Outputs all keys and values in the table. |
| LookupTableFind <U extends TType > | Looks up keys in a table, outputs the corresponding values. |
| LookupTableImport | Replaces the contents of the table with the specified keys and values. |
| LookupTableInsert | Updates the table to associates keys with values. |
| LookupTableRemove | Removes keys and its associated values from a table. |
| LookupTableSize | Computes the number of elements in the given table. |
| LoopCond | Forwards the input to the output. |
| Perdita | |
| Perdite | Built-in loss functions. |
| LossesHelper | These are helper methods for Losses and Metrics and will be module private when Java modularity is applied to TensorFlow Java. |
| LossMetric <T extends TNumber > | Interface for Metrics that wrap Loss functions. |
| LossTuple <T extends TNumber > | A helper class for loss methods to return labels, target, and sampleWeights |
| Inferiore | Converts all uppercase characters into their respective lowercase replacements. |
| Lower.Options | Optional attributes for Lower |
| LowerBound <U extends TNumber > | Applies lower_bound(sorted_search_values, values) along each row. |
| LSTMBlockCell <T extends TNumber > | Computes the LSTM cell forward propagation for 1 time step. |
| LSTMBlockCell.Options | Optional attributes for LSTMBlockCell |
| LSTMBlockCellGrad <T extends TNumber > | Computes the LSTM cell backward propagation for 1 timestep. |
| Lu <T extends TType , U extends TNumber > | Computes the LU decomposition of one or more square matrices. |
M
| MachineConfiguration | Protobuf type tensorflow.MachineConfiguration |
| MachineConfiguration.Builder | Protobuf type tensorflow.MachineConfiguration |
| MachineConfigurationOrBuilder | |
| MakeIterator | Makes a new iterator from the given `dataset` and stores it in `iterator`. |
| MakeUnique | Make all elements in the non-Batch dimension unique, but \"close\" to their initial value. |
| MapClear | Op removes all elements in the underlying container. |
| MapClear.Options | Optional attributes for MapClear |
| MapDataset | |
| MapIncompleteSize | Op returns the number of incomplete elements in the underlying container. |
| MapIncompleteSize.Options | Optional attributes for MapIncompleteSize |
| MapIterator | |
| MapOptional | |
| MapPeek | Op peeks at the values at the specified key. |
| MapPeek.Options | Optional attributes for MapPeek |
| MapSize | Op returns the number of elements in the underlying container. |
| MapSize.Options | Optional attributes for MapSize |
| MapStage | Stage (key, values) in the underlying container which behaves like a hashtable. |
| MapStage.Options | Optional attributes for MapStage |
| MapUnstage | Op removes and returns the values associated with the key from the underlying container. |
| MapUnstage.Options | Optional attributes for MapUnstage |
| MapUnstageNoKey | Op removes and returns a random (key, value) from the underlying container. |
| MapUnstageNoKey.Options | Optional attributes for MapUnstageNoKey |
| MatchingFiles | Returns the set of files matching one or more glob patterns. |
| MatchingFilesDataset | |
| MatchingFilesDataset | |
| MatMul <T extends TType > | Multiply the matrix "a" by the matrix "b". |
| MatMul.Options | Optional attributes for MatMul |
| MatrixDiag <T extends TType > | Returns a batched diagonal tensor with given batched diagonal values. |
| MatrixDiagPart <T extends TType > | Returns the batched diagonal part of a batched tensor. |
| MatrixDiagPartV3 <T extends TType > | Returns the batched diagonal part of a batched tensor. |
| MatrixDiagPartV3.Options | Optional attributes for MatrixDiagPartV3 |
| MatrixDiagV3 <T extends TType > | Returns a batched diagonal tensor with given batched diagonal values. |
| MatrixDiagV3.Options | Optional attributes for MatrixDiagV3 |
| MatrixLogarithm <T extends TType > | Computes the matrix logarithm of one or more square matrices: \\(log(exp(A)) = A\\) This op is only defined for complex matrices. |
| MatrixSetDiag <T extends TType > | Returns a batched matrix tensor with new batched diagonal values. |
| MatrixSetDiag.Options | Optional attributes for MatrixSetDiag |
| MatrixSolveLs <T extends TType > | Solves one or more linear least-squares problems. |
| MatrixSolveLs.Options | Optional attributes for MatrixSolveLs |
| Max <T extends TType > | Computes the maximum of elements across dimensions of a tensor. |
| Max.Options | Optional attributes for Max |
| Maximum <T extends TNumber > | Returns the max of x and y (ie |
| MaxIntraOpParallelismDataset | Creates a dataset that overrides the maximum intra-op parallelism. |
| MaxIntraOpParallelismDataset | Creates a dataset that overrides the maximum intra-op parallelism. |
| MaxNorm | Constrains the weights incident to each hidden unit to have a norm less than or equal to a desired value. |
| MaxPool <T extends TType > | Performs max pooling on the input. |
| MaxPool.Options | Optional attributes for MaxPool |
| MaxPool3d <T extends TNumber > | Performs 3D max pooling on the input. |
| MaxPool3d.Options | Optional attributes for MaxPool3d |
| MaxPool3dGrad <U extends TNumber > | Computes gradients of 3D max pooling function. |
| MaxPool3dGrad.Options | Optional attributes for MaxPool3dGrad |
| MaxPool3dGradGrad <T extends TNumber > | Computes second-order gradients of the maxpooling function. |
| MaxPool3dGradGrad.Options | Optional attributes for MaxPool3dGradGrad |
| MaxPoolGrad <T extends TNumber > | Computes gradients of the maxpooling function. |
| MaxPoolGrad.Options | Optional attributes for MaxPoolGrad |
| MaxPoolGradGrad <T extends TNumber > | Computes second-order gradients of the maxpooling function. |
| MaxPoolGradGrad.Options | Optional attributes for MaxPoolGradGrad |
| MaxPoolGradGradWithArgmax <T extends TNumber > | Computes second-order gradients of the maxpooling function. |
| MaxPoolGradGradWithArgmax.Options | Optional attributes for MaxPoolGradGradWithArgmax |
| MaxPoolGradWithArgmax <T extends TNumber > | Computes gradients of the maxpooling function. |
| MaxPoolGradWithArgmax.Options | Optional attributes for MaxPoolGradWithArgmax |
| MaxPoolWithArgmax <T extends TNumber , U extends TNumber > | Performs max pooling on the input and outputs both max values and indices. |
| MaxPoolWithArgmax.Options | Optional attributes for MaxPoolWithArgmax |
| Mean <T extends TNumber > | A metric that that implements a weighted mean WEIGHTED_MEAN |
| Mean <T extends TType > | Computes the mean of elements across dimensions of a tensor. |
| Mean.Options | Optional attributes for Mean |
| MeanAbsoluteError | Computes the mean of absolute difference between labels and predictions. |
| MeanAbsoluteError <T extends TNumber > | A metric that computes the mean of absolute difference between labels and predictions. |
| MeanAbsolutePercentageError | Computes the mean absolute percentage error between labels and predictions. |
| MeanAbsolutePercentageError <T extends TNumber > | A metric that computes the mean of absolute difference between labels and predictions. |
| MeanMetricWrapper <T extends TNumber > | A class that bridges a stateless loss function with the Mean metric using a reduction of WEIGHTED_MEAN . |
| MeanSquaredError | Computes the mean of squares of errors between labels and predictions. |
| MeanSquaredError <T extends TNumber > | A metric that computes the mean of absolute difference between labels and predictions. |
| MeanSquaredLogarithmicError | Computes the mean squared logarithmic errors between labels and predictions. |
| MeanSquaredLogarithmicError <T extends TNumber > | A metric that computes the mean of absolute difference between labels and predictions. |
| MemAllocatorStats | Some of the data from AllocatorStatsProtobuf type tensorflow.MemAllocatorStats |
| MemAllocatorStats.Builder | Some of the data from AllocatorStatsProtobuf type tensorflow.MemAllocatorStats |
| MemAllocatorStatsOrBuilder | |
| MemChunk | Protobuf type tensorflow.MemChunk |
| MemChunk.Builder | Protobuf type tensorflow.MemChunk |
| MemChunkOrBuilder | |
| MemmappedFileSystemDirectory | A directory of regions in a memmapped file. |
| MemmappedFileSystemDirectory.Builder | A directory of regions in a memmapped file. |
| MemmappedFileSystemDirectoryElement | A message that describes one region of memmapped file. |
| MemmappedFileSystemDirectoryElement.Builder | A message that describes one region of memmapped file. |
| MemmappedFileSystemDirectoryElementOrBuilder | |
| MemmappedFileSystemDirectoryOrBuilder | |
| MemmappedFileSystemProtos | |
| MemoryDump | Protobuf type tensorflow.MemoryDump |
| MemoryDump.Builder | Protobuf type tensorflow.MemoryDump |
| MemoryDumpOrBuilder | |
| MemoryInfo | Protobuf type tensorflow.MemoryInfo |
| MemoryInfo.Builder | Protobuf type tensorflow.MemoryInfo |
| MemoryInfoOrBuilder | |
| MemoryLogRawAllocation | Protobuf type tensorflow.MemoryLogRawAllocation |
| MemoryLogRawAllocation.Builder | Protobuf type tensorflow.MemoryLogRawAllocation |
| MemoryLogRawAllocationOrBuilder | |
| MemoryLogRawDeallocation | Protobuf type tensorflow.MemoryLogRawDeallocation |
| MemoryLogRawDeallocation.Builder | Protobuf type tensorflow.MemoryLogRawDeallocation |
| MemoryLogRawDeallocationOrBuilder | |
| MemoryLogStep | Protobuf type tensorflow.MemoryLogStep |
| MemoryLogStep.Builder | Protobuf type tensorflow.MemoryLogStep |
| MemoryLogStepOrBuilder | |
| MemoryLogTensorAllocation | Protobuf type tensorflow.MemoryLogTensorAllocation |
| MemoryLogTensorAllocation.Builder | Protobuf type tensorflow.MemoryLogTensorAllocation |
| MemoryLogTensorAllocationOrBuilder | |
| MemoryLogTensorDeallocation | Protobuf type tensorflow.MemoryLogTensorDeallocation |
| MemoryLogTensorDeallocation.Builder | Protobuf type tensorflow.MemoryLogTensorDeallocation |
| MemoryLogTensorDeallocationOrBuilder | |
| MemoryLogTensorOutput | Protobuf type tensorflow.MemoryLogTensorOutput |
| MemoryLogTensorOutput.Builder | Protobuf type tensorflow.MemoryLogTensorOutput |
| MemoryLogTensorOutputOrBuilder | |
| MemoryStats | For memory tracking. |
| MemoryStats.Builder | For memory tracking. |
| MemoryStatsOrBuilder | |
| Merge <T extends TType > | Forwards the value of an available tensor from `inputs` to `output`. |
| MergeSummary | Merges summaries. |
| MergeV2Checkpoints | V2 format specific: merges the metadata files of sharded checkpoints. |
| MergeV2Checkpoints.Options | Optional attributes for MergeV2Checkpoints |
| MetaGraphDef | NOTE: This protocol buffer is evolving, and will go through revisions in the coming months. |
| MetaGraphDef.Builder | NOTE: This protocol buffer is evolving, and will go through revisions in the coming months. |
| MetaGraphDef.MetaInfoDef | Meta information regarding the graph to be exported. |
| MetaGraphDef.MetaInfoDef.Builder | Meta information regarding the graph to be exported. |
| MetaGraphDef.MetaInfoDefOrBuilder | |
| MetaGraphDefOrBuilder | |
| MetaGraphProtos | |
| Metric <T extends TNumber > | Base class for Metrics |
| MetricEntry | Protobuf type tensorflow.MetricEntry |
| MetricEntry.Builder | Protobuf type tensorflow.MetricEntry |
| MetricEntryOrBuilder | |
| MetricReduction | Defines the different types of metric reductions |
| Metrica | Helper class with built-in metrics functions. |
| MetricsHelper | These are helper methods for Metrics and will be module private when Java modularity is applied to TensorFlow Java. |
| Mfcc | Transforms a spectrogram into a form that's useful for speech recognition. |
| Mfcc.Options | Optional attributes for Mfcc |
| Min <T extends TType > | Computes the minimum of elements across dimensions of a tensor. |
| Min.Options | Optional attributes for Min |
| Minimum <T extends TNumber > | Returns the min of x and y (ie |
| MinMaxNorm | Constrains the weights to have the norm between a lower bound and an upper bound. |
| MirrorPad <T extends TType > | Pads a tensor with mirrored values. |
| MirrorPadGrad <T extends TType > | Gradient op for `MirrorPad` op. |
| MiscDataBufferFactory | Factory of miscellaneous data buffers |
| MlirPassthroughOp | Wraps an arbitrary MLIR computation expressed as a module with a main() function. |
| Mod <T extends TNumber > | Returns element-wise remainder of division. |
| ModelDataset | Identity transformation that models performance. |
| ModelDataset.Options | Optional attributes for ModelDataset |
| Slancio | Stochastic gradient descent plus momentum, either nesterov or traditional. |
| Mul <T extends TType > | Returns x * y element-wise. |
| MulNoNan <T extends TType > | Returns x * y element-wise. |
| MultiDeviceIterator | Creates a MultiDeviceIterator resource. |
| MultiDeviceIteratorFromStringHandle | Generates a MultiDeviceIterator resource from its provided string handle. |
| MultiDeviceIteratorFromStringHandle.Options | Optional attributes for MultiDeviceIteratorFromStringHandle |
| MultiDeviceIteratorGetNextFromShard | Gets next element for the provided shard number. |
| MultiDeviceIteratorInit | Initializes the multi device iterator with the given dataset. |
| MultiDeviceIteratorToStringHandle | Produces a string handle for the given MultiDeviceIterator. |
| Multinomial <U extends TNumber > | Draws samples from a multinomial distribution. |
| Multinomial.Options | Optional attributes for Multinomial |
| MutableDenseHashTable | Creates an empty hash table that uses tensors as the backing store. |
| MutableDenseHashTable.Options | Optional attributes for MutableDenseHashTable |
| MutableHashTable | Creates an empty hash table. |
| MutableHashTable.Options | Optional attributes for MutableHashTable |
| MutableHashTableOfTensors | Creates an empty hash table. |
| MutableHashTableOfTensors.Options | Optional attributes for MutableHashTableOfTensors |
| Mutex | Creates a Mutex resource that can be locked by `MutexLock`. |
| Mutex.Options | Optional attributes for Mutex |
| MutexLock | Locks a mutex resource. |
N
| Nadam | Nadam Optimizer that implements the NAdam algorithm. |
| NameAttrList | A list of attr names and their values. |
| NameAttrList.Builder | A list of attr names and their values. |
| NameAttrListOrBuilder | |
| NamedDevice | Protobuf type tensorflow.NamedDevice |
| NamedDevice.Builder | Protobuf type tensorflow.NamedDevice |
| NamedDeviceOrBuilder | |
| NamedTensorProto | A pair of tensor name and tensor values. |
| NamedTensorProto.Builder | A pair of tensor name and tensor values. |
| NamedTensorProtoOrBuilder | |
| NamedTensorProtos | |
| NamedTupleValue | Represents Python's namedtuple. |
| NamedTupleValue.Builder | Represents Python's namedtuple. |
| NamedTupleValueOrBuilder | |
| NcclAllReduce <T extends TNumber > | Outputs a tensor containing the reduction across all input tensors. |
| NcclAllReduce <T extends TNumber > | Outputs a tensor containing the reduction across all input tensors. |
| NcclBroadcast <T extends TNumber > | Sends `input` to all devices that are connected to the output. |
| NcclBroadcast <T extends TNumber > | Sends `input` to all devices that are connected to the output. |
| NcclReduce <T extends TNumber > | Reduces `input` from `num_devices` using `reduction` to a single device. |
| NcclReduce <T extends TNumber > | Reduces `input` from `num_devices` using `reduction` to a single device. |
| NdArray <T> | A data structure of N-dimensions. |
| NdArrays | Utility class for instantiating NdArray objects. |
| NdArraySequence <T extends NdArray <?>> | A sequence of elements of an N-dimensional array. |
| Ndtri <T extends TNumber > | |
| NearestNeighbors | Selects the k nearest centers for each point. |
| Neg <T extends TType > | Computes numerical negative value element-wise. |
| NegTrain | Training via negative sampling. |
| NextAfter <T extends TNumber > | Returns the next representable value of `x1` in the direction of `x2`, element-wise. |
| NextIteration <T extends TType > | Makes its input available to the next iteration. |
| NioDataBufferFactory | Factory of JDK NIO-based data buffers |
| NodeDef | Protobuf type tensorflow.NodeDef |
| NodeDef.Builder | Protobuf type tensorflow.NodeDef |
| NodeDef.ExperimentalDebugInfo | Protobuf type tensorflow.NodeDef.ExperimentalDebugInfo |
| NodeDef.ExperimentalDebugInfo.Builder | Protobuf type tensorflow.NodeDef.ExperimentalDebugInfo |
| NodeDef.ExperimentalDebugInfoOrBuilder | |
| NodeDefOrBuilder | |
| NodeExecStats | Time/size stats recorded for a single execution of a graph node. |
| NodeExecStats.Builder | Time/size stats recorded for a single execution of a graph node. |
| NodeExecStatsOrBuilder | |
| NodeOutput | Output sizes recorded for a single execution of a graph node. |
| NodeOutput.Builder | Output sizes recorded for a single execution of a graph node. |
| NodeOutputOrBuilder | |
| NodeProto | |
| NonDeterministicInts <U extends TType > | Non-deterministically generates some integers. |
| NoneValue | Represents None. |
| NoneValue.Builder | Represents None. |
| NoneValueOrBuilder | |
| NonMaxSuppression <T extends TNumber > | Greedily selects a subset of bounding boxes in descending order of score, pruning away boxes that have high intersection-over-union (IOU) overlap with previously selected boxes. |
| NonMaxSuppression.Options | Optional attributes for NonMaxSuppression |
| NonMaxSuppressionWithOverlaps | Greedily selects a subset of bounding boxes in descending order of score, pruning away boxes that have high overlaps with previously selected boxes. |
| NonNeg | Constrains the weights to be non-negative. |
| NonSerializableDataset | |
| NonSerializableDataset | |
| NoOp | Does nothing. |
| NotBroadcastableException | Exception that indicates that static shapes are not able to broadcast among each other during arithmetic operations. |
| NotEqual | Returns the truth value of (x != y) element-wise. |
| NotEqual.Options | Optional attributes for NotEqual |
| NthElement <T extends TNumber > | Finds values of the `n`-th order statistic for the last dimension. |
| NthElement.Options | Optional attributes for NthElement |
O
| OneHot <U extends TType > | Returns a one-hot tensor. |
| OneHot.Options | Optional attributes for OneHot |
| Ones <T extends TType > | Initializer that generates tensors initialized to 1. |
| Ones <T extends TType > | An operator creating a constant initialized with ones of the shape given by `dims`. |
| OnesLike <T extends TType > | Returns a tensor of ones with the same shape and type as x. |
| Op | A logical unit of computation. |
| OpDef | Defines an operation. |
| OpDef.ArgDef | For describing inputs and outputs. |
| OpDef.ArgDef.Builder | For describing inputs and outputs. |
| OpDef.ArgDefOrBuilder | |
| OpDef.AttrDef | Description of the graph-construction-time configuration of this Op. |
| OpDef.AttrDef.Builder | Description of the graph-construction-time configuration of this Op. |
| OpDef.AttrDefOrBuilder | |
| OpDef.Builder | Defines an operation. |
| OpDefOrBuilder | |
| OpDefProtos | |
| OpDeprecation | Information about version-dependent deprecation of an opProtobuf type tensorflow.OpDeprecation |
| OpDeprecation.Builder | Information about version-dependent deprecation of an opProtobuf type tensorflow.OpDeprecation |
| OpDeprecationOrBuilder | |
| Operand <T extends TType > | Interface implemented by operands of a TensorFlow operation. |
| Operands | Utilities for manipulating operand related types and lists. |
| Operazione | Performs computation on Tensors. |
| OperationBuilder | A builder for Operation s. |
| Operatore | Annotation used by classes to make TensorFlow operations conveniently accessible via org.tensorflow.op.Ops or one of its groups. |
| OpList | A collection of OpDefsProtobuf type tensorflow.OpList |
| OpList.Builder | A collection of OpDefsProtobuf type tensorflow.OpList |
| OpListOrBuilder | |
| OptimizeDataset | Creates a dataset by applying optimizations to `input_dataset`. |
| OptimizeDataset.Options | Optional attributes for OptimizeDataset |
| OptimizeDatasetV2 | Creates a dataset by applying related optimizations to `input_dataset`. |
| OptimizeDatasetV2.Options | Optional attributes for OptimizeDatasetV2 |
| Optimizer | Base class for gradient optimizers. |
| Optimizer.GradAndVar <T extends TType > | A class that holds a paired gradient and variable. |
| Optimizer.Options | Optional attributes for Optimizer |
| OptimizerOptions | Options passed to the graph optimizerProtobuf type tensorflow.OptimizerOptions |
| OptimizerOptions.Builder | Options passed to the graph optimizerProtobuf type tensorflow.OptimizerOptions |
| OptimizerOptions.GlobalJitLevel | Control the use of the compiler/jit. |
| OptimizerOptions.Level | Optimization levelProtobuf enum tensorflow.OptimizerOptions.Level |
| OptimizerOptionsOrBuilder | |
| Optimizers | Enumerator used to create a new Optimizer with default parameters. |
| OptionalFromValue | Constructs an Optional variant from a tuple of tensors. |
| OptionalGetValue | Returns the value stored in an Optional variant or raises an error if none exists. |
| OptionalHasValue | Returns true if and only if the given Optional variant has a value. |
| OptionalNone | Creates an Optional variant with no value. |
| OrderedMapClear | Op removes all elements in the underlying container. |
| OrderedMapClear.Options | Optional attributes for OrderedMapClear |
| OrderedMapIncompleteSize | Op returns the number of incomplete elements in the underlying container. |
| OrderedMapIncompleteSize.Options | Optional attributes for OrderedMapIncompleteSize |
| OrderedMapPeek | Op peeks at the values at the specified key. |
| OrderedMapPeek.Options | Optional attributes for OrderedMapPeek |
| OrderedMapSize | Op returns the number of elements in the underlying container. |
| OrderedMapSize.Options | Optional attributes for OrderedMapSize |
| OrderedMapStage | Stage (key, values) in the underlying container which behaves like a ordered associative container. |
| OrderedMapStage.Options | Optional attributes for OrderedMapStage |
| OrderedMapUnstage | Op removes and returns the values associated with the key from the underlying container. |
| OrderedMapUnstage.Options | Optional attributes for OrderedMapUnstage |
| OrderedMapUnstageNoKey | Op removes and returns the (key, value) element with the smallest key from the underlying container. |
| OrderedMapUnstageNoKey.Options | Optional attributes for OrderedMapUnstageNoKey |
| OrdinalSelector | A TPU core selector Op. |
| Orthogonal <T extends TFloating > | Initializer that generates an orthogonal matrix. |
| OutfeedDequeue <T extends TType > | Retrieves a single tensor from the computation outfeed. |
| OutfeedDequeue.Options | Optional attributes for OutfeedDequeue |
| OutfeedDequeueTuple | Retrieve multiple values from the computation outfeed. |
| OutfeedDequeueTuple.Options | Optional attributes for OutfeedDequeueTuple |
| OutfeedDequeueTupleV2 | Retrieve multiple values from the computation outfeed. |
| OutfeedDequeueV2 <T extends TType > | Retrieves a single tensor from the computation outfeed. |
| OutfeedEnqueue | Enqueue a Tensor on the computation outfeed. |
| OutfeedEnqueueTuple | Enqueue multiple Tensor values on the computation outfeed. |
| Output <T extends TType > | A symbolic handle to a tensor produced by an Operation . |
P
| Pad <T extends TType > | Pads a tensor. |
| Pad <T extends TType > | Wraps the XLA Pad operator, documented at https://www.tensorflow.org/performance/xla/operation_semantics#pad . |
| PaddedBatchDataset | Creates a dataset that batches and pads `batch_size` elements from the input. |
| PaddedBatchDataset.Options | Optional attributes for PaddedBatchDataset |
| PaddingFifoQueue | A queue that produces elements in first-in first-out order. |
| PaddingFifoQueue.Options | Optional attributes for PaddingFifoQueue |
| PairValue | Represents a (key, value) pair. |
| PairValue.Builder | Represents a (key, value) pair. |
| PairValueOrBuilder | |
| ParallelConcat <T extends TType > | Concatenates a list of `N` tensors along the first dimension. |
| ParallelDynamicStitch <T extends TType > | Interleave the values from the `data` tensors into a single tensor. |
| ParameterizedTruncatedNormal <U extends TNumber > | Outputs random values from a normal distribution. |
| ParameterizedTruncatedNormal.Options | Optional attributes for ParameterizedTruncatedNormal |
| ParseExample | Transforms a vector of tf.Example protos (as strings) into typed tensors. |
| ParseExampleDataset | Transforms `input_dataset` containing `Example` protos as vectors of DT_STRING into a dataset of `Tensor` or `SparseTensor` objects representing the parsed features. |
| ParseExampleDataset.Options | Optional attributes for ParseExampleDataset |
| ParseSequenceExample | Transforms a vector of tf.io.SequenceExample protos (as strings) into typed tensors. |
| ParseSequenceExample.Options | Optional attributes for ParseSequenceExample |
| ParseSingleExample | Transforms a tf.Example proto (as a string) into typed tensors. |
| ParseSingleSequenceExample | Transforms a scalar brain.SequenceExample proto (as strings) into typed tensors. |
| ParseSingleSequenceExample.Options | Optional attributes for ParseSingleSequenceExample |
| ParseTensor <T extends TType > | Transforms a serialized tensorflow.TensorProto proto into a Tensor. |
| PartitionedInput <T extends TType > | An op that groups a list of partitioned inputs together. |
| PartitionedInput.Options | Optional attributes for PartitionedInput |
| PartitionedOutput <T extends TType > | An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned outputs outside the XLA computation. |
| PartitionedOutput.Options | Optional attributes for PartitionedOutput |
| Placeholder <T extends TType > | A placeholder op for a value that will be fed into the computation. |
| Placeholder.Options | Optional attributes for Placeholder |
| PlaceholderWithDefault <T extends TType > | A placeholder op that passes through `input` when its output is not fed. |
| PlatformInfo | Protobuf type tensorflow.PlatformInfo |
| PlatformInfo.Builder | Protobuf type tensorflow.PlatformInfo |
| PlatformInfoOrBuilder | |
| Poisson | Computes the Poisson loss between labels and predictions. |
| Poisson <T extends TNumber > | A metric that computes the poisson loss metric between labels and predictions. |
| Polygamma <T extends TNumber > | Compute the polygamma function \\(\psi^{(n)}(x)\\). |
| PopulationCount | Computes element-wise population count (aka |
| PositionIterator | |
| Pow <T extends TType > | Computes the power of one value to another. |
| PrefetchDataset | Creates a dataset that asynchronously prefetches elements from `input_dataset`. |
| PrefetchDataset.Options | Optional attributes for PrefetchDataset |
| Prelinearize | An op which linearizes one Tensor value to an opaque variant tensor. |
| Prelinearize.Options | Optional attributes for Prelinearize |
| PrelinearizeTuple | An op which linearizes multiple Tensor values to an opaque variant tensor. |
| PrelinearizeTuple.Options | Optional attributes for PrelinearizeTuple |
| PreventGradient <T extends TType > | An identity op that triggers an error if a gradient is requested. |
| PreventGradient.Options | Optional attributes for PreventGradient |
| Stampa | Prints a string scalar. |
| Print.Options | Optional attributes for Print |
| PriorityQueue | A queue that produces elements sorted by the first component value. |
| PriorityQueue.Options | Optional attributes for PriorityQueue |
| PrivateThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| PrivateThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| Prod <T extends TType > | Computes the product of elements across dimensions of a tensor. |
| Prod.Options | Optional attributes for Prod |
| ProfileOptions | Next ID: 11Protobuf type tensorflow.ProfileOptions |
| ProfileOptions.Builder | Next ID: 11Protobuf type tensorflow.ProfileOptions |
| ProfileOptions.DeviceType | Protobuf enum tensorflow.ProfileOptions.DeviceType |
| ProfileOptionsOrBuilder | |
| ProfilerOptionsProtos |
Q
| Qr <T extends TType > | Computes the QR decompositions of one or more matrices. |
| Qr.Options | Optional attributes for Qr |
| Quantize <T extends TType > | Quantize the 'input' tensor of type float to 'output' tensor of type 'T'. |
| Quantize.Options | Optional attributes for Quantize |
| QuantizeAndDequantize <T extends TNumber > | Quantizes then dequantizes a tensor. |
| QuantizeAndDequantize.Options | Optional attributes for QuantizeAndDequantize |
| QuantizeAndDequantizeV3 <T extends TNumber > | Quantizes then dequantizes a tensor. |
| QuantizeAndDequantizeV3.Options | Optional attributes for QuantizeAndDequantizeV3 |
| QuantizeAndDequantizeV4 <T extends TNumber > | Returns the gradient of `quantization.QuantizeAndDequantizeV4`. |
| QuantizeAndDequantizeV4.Options | Optional attributes for QuantizeAndDequantizeV4 |
| QuantizeAndDequantizeV4Grad <T extends TNumber > | Returns the gradient of `QuantizeAndDequantizeV4`. |
| QuantizeAndDequantizeV4Grad.Options | Optional attributes for QuantizeAndDequantizeV4Grad |
| QuantizedAdd <V extends TType > | Returns x + y element-wise, working on quantized buffers. |
| QuantizedAvgPool <T extends TType > | Produces the average pool of the input tensor for quantized types. |
| QuantizedBatchNormWithGlobalNormalization <U extends TType > | Quantized Batch normalization. |
| QuantizedBiasAdd <V extends TType > | Adds Tensor 'bias' to Tensor 'input' for Quantized types. |
| QuantizedConcat <T extends TType > | Concatenates quantized tensors along one dimension. |
| QuantizedConv2d <V extends TType > | Computes a 2D convolution given quantized 4D input and filter tensors. |
| QuantizedConv2d.Options | Optional attributes for QuantizedConv2d |
| QuantizedConv2DAndRelu <V extends TType > | |
| QuantizedConv2DAndRelu.Options | Optional attributes for QuantizedConv2DAndRelu |
| QuantizedConv2DAndReluAndRequantize <V extends TType > | |
| QuantizedConv2DAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DAndReluAndRequantize |
| QuantizedConv2DAndRequantize <V extends TType > | |
| QuantizedConv2DAndRequantize.Options | Optional attributes for QuantizedConv2DAndRequantize |
| QuantizedConv2DPerChannel <V extends TType > | Computes QuantizedConv2D per channel. |
| QuantizedConv2DPerChannel.Options | Optional attributes for QuantizedConv2DPerChannel |
| QuantizedConv2DWithBias <V extends TType > | |
| QuantizedConv2DWithBias.Options | Optional attributes for QuantizedConv2DWithBias |
| QuantizedConv2DWithBiasAndRelu <V extends TType > | |
| QuantizedConv2DWithBiasAndRelu.Options | Optional attributes for QuantizedConv2DWithBiasAndRelu |
| QuantizedConv2DWithBiasAndReluAndRequantize <W extends TType > | |
| QuantizedConv2DWithBiasAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasAndReluAndRequantize |
| QuantizedConv2DWithBiasAndRequantize <W extends TType > | |
| QuantizedConv2DWithBiasAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasAndRequantize |
| QuantizedConv2DWithBiasSignedSumAndReluAndRequantize <X extends TType > | |
| QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasSignedSumAndReluAndRequantize |
| QuantizedConv2DWithBiasSumAndRelu <V extends TType > | |
| QuantizedConv2DWithBiasSumAndRelu.Options | Optional attributes for QuantizedConv2DWithBiasSumAndRelu |
| QuantizedConv2DWithBiasSumAndReluAndRequantize <X extends TType > | |
| QuantizedConv2DWithBiasSumAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasSumAndReluAndRequantize |
| QuantizedDepthwiseConv2D <V extends TType > | Computes quantized depthwise Conv2D. |
| QuantizedDepthwiseConv2D.Options | Optional attributes for QuantizedDepthwiseConv2D |
| QuantizedDepthwiseConv2DWithBias <V extends TType > | Computes quantized depthwise Conv2D with Bias. |
| QuantizedDepthwiseConv2DWithBias.Options | Optional attributes for QuantizedDepthwiseConv2DWithBias |
| QuantizedDepthwiseConv2DWithBiasAndRelu <V extends TType > | Computes quantized depthwise Conv2D with Bias and Relu. |
| QuantizedDepthwiseConv2DWithBiasAndRelu.Options | Optional attributes for QuantizedDepthwiseConv2DWithBiasAndRelu |
| QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize <W extends TType > | Computes quantized depthwise Conv2D with Bias, Relu and Requantize. |
| QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.Options | Optional attributes for QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize |
| QuantizedInstanceNorm <T extends TType > | Quantized Instance normalization. |
| QuantizedInstanceNorm.Options | Optional attributes for QuantizedInstanceNorm |
| QuantizedMatMul <V extends TType > | Perform a quantized matrix multiplication of `a` by the matrix `b`. |
| QuantizedMatMul.Options | Optional attributes for QuantizedMatMul |
| QuantizedMatMulWithBias <W extends TType > | Performs a quantized matrix multiplication of `a` by the matrix `b` with bias add. |
| QuantizedMatMulWithBias.Options | Optional attributes for QuantizedMatMulWithBias |
| QuantizedMatMulWithBiasAndDequantize <W extends TNumber > | |
| QuantizedMatMulWithBiasAndDequantize.Options | Optional attributes for QuantizedMatMulWithBiasAndDequantize |
| QuantizedMatMulWithBiasAndRelu <V extends TType > | Perform a quantized matrix multiplication of `a` by the matrix `b` with bias add and relu fusion. |
| QuantizedMatMulWithBiasAndRelu.Options | Optional attributes for QuantizedMatMulWithBiasAndRelu |
| QuantizedMatMulWithBiasAndReluAndRequantize <W extends TType > | Perform a quantized matrix multiplication of `a` by the matrix `b` with bias add and relu and requantize fusion. |
| QuantizedMatMulWithBiasAndReluAndRequantize.Options | Optional attributes for QuantizedMatMulWithBiasAndReluAndRequantize |
| QuantizedMatMulWithBiasAndRequantize <W extends TType > | |
| QuantizedMatMulWithBiasAndRequantize.Options | Optional attributes for QuantizedMatMulWithBiasAndRequantize |
| QuantizedMaxPool <T extends TType > | Produces the max pool of the input tensor for quantized types. |
| QuantizedMul <V extends TType > | Returns x * y element-wise, working on quantized buffers. |
| QuantizeDownAndShrinkRange <U extends TType > | Convert the quantized 'input' tensor into a lower-precision 'output', using the actual distribution of the values to maximize the usage of the lower bit depth and adjusting the output min and max ranges accordingly. |
| QuantizedRelu <U extends TType > | Computes Quantized Rectified Linear: `max(features, 0)` |
| QuantizedRelu6 <U extends TType > | Computes Quantized Rectified Linear 6: `min(max(features, 0), 6)` |
| QuantizedReluX <U extends TType > | Computes Quantized Rectified Linear X: `min(max(features, 0), max_value)` |
| QuantizedReshape <T extends TType > | Reshapes a quantized tensor as per the Reshape op. |
| QuantizedResizeBilinear <T extends TType > | Resize quantized `images` to `size` using quantized bilinear interpolation. |
| QuantizedResizeBilinear.Options | Optional attributes for QuantizedResizeBilinear |
| QueueClose | Closes the given queue. |
| QueueClose.Options | Optional attributes for QueueClose |
| QueueDequeue | Dequeues a tuple of one or more tensors from the given queue. |
| QueueDequeue.Options | Optional attributes for QueueDequeue |
| QueueDequeueMany | Dequeues `n` tuples of one or more tensors from the given queue. |
| QueueDequeueMany.Options | Optional attributes for QueueDequeueMany |
| QueueDequeueUpTo | Dequeues `n` tuples of one or more tensors from the given queue. |
| QueueDequeueUpTo.Options | Optional attributes for QueueDequeueUpTo |
| QueueEnqueue | Enqueues a tuple of one or more tensors in the given queue. |
| QueueEnqueue.Options | Optional attributes for QueueEnqueue |
| QueueEnqueueMany | Enqueues zero or more tuples of one or more tensors in the given queue. |
| QueueEnqueueMany.Options | Optional attributes for QueueEnqueueMany |
| QueueIsClosed | Returns true if queue is closed. |
| QueueRunnerDef | Protocol buffer representing a QueueRunner. |
| QueueRunnerDef.Builder | Protocol buffer representing a QueueRunner. |
| QueueRunnerDefOrBuilder | |
| QueueRunnerProtos | |
| QueueSize | Computes the number of elements in the given queue. |
R
| RaggedBincount <U extends TNumber > | Counts the number of occurrences of each value in an integer array. |
| RaggedBincount.Options | Optional attributes for RaggedBincount |
| RaggedCountSparseOutput <U extends TNumber > | Performs sparse-output bin counting for a ragged tensor input. |
| RaggedCountSparseOutput.Options | Optional attributes for RaggedCountSparseOutput |
| RaggedCross <T extends TType , U extends TNumber > | Generates a feature cross from a list of tensors, and returns it as a RaggedTensor. |
| RaggedGather <T extends TNumber , U extends TType > | Gather ragged slices from `params` axis `0` according to `indices`. |
| RaggedRange <U extends TNumber , T extends TNumber > | Returns a `RaggedTensor` containing the specified sequences of numbers. |
| RaggedTensorFromVariant <U extends TNumber , T extends TType > | Decodes a `variant` Tensor into a `RaggedTensor`. |
| RaggedTensorToSparse <U extends TType > | Converts a `RaggedTensor` into a `SparseTensor` with the same values. |
| RaggedTensorToTensor <U extends TType > | Create a dense tensor from a ragged tensor, possibly altering its shape. |
| RaggedTensorToVariant | Encodes a `RaggedTensor` into a `variant` Tensor. |
| RaggedTensorToVariantGradient <U extends TType > | Helper used to compute the gradient for `RaggedTensorToVariant`. |
| RandomCrop <T extends TNumber > | Randomly crop `image`. |
| RandomCrop.Options | Optional attributes for RandomCrop |
| RandomDataset | Creates a Dataset that returns pseudorandom numbers. |
| RandomDataset | Creates a Dataset that returns pseudorandom numbers. |
| RandomGamma <U extends TNumber > | Outputs random values from the Gamma distribution(s) described by alpha. |
| RandomGamma.Options | Optional attributes for RandomGamma |
| RandomGammaGrad <T extends TNumber > | Computes the derivative of a Gamma random sample wrt |
| RandomNormal <T extends TFloating > | Initializer that generates tensors with a normal distribution. |
| RandomPoisson <V extends TNumber > | Outputs random values from the Poisson distribution(s) described by rate. |
| RandomPoisson.Options | Optional attributes for RandomPoisson |
| RandomShuffle <T extends TType > | Randomly shuffles a tensor along its first dimension. |
| RandomShuffle.Options | Optional attributes for RandomShuffle |
| RandomShuffleQueue | A queue that randomizes the order of elements. |
| RandomShuffleQueue.Options | Optional attributes for RandomShuffleQueue |
| RandomStandardNormal <U extends TNumber > | Outputs random values from a normal distribution. |
| RandomStandardNormal.Options | Optional attributes for RandomStandardNormal |
| RandomUniform <T extends TNumber > | Initializer that generates tensors with a uniform distribution. |
| RandomUniform <U extends TNumber > | Outputs random values from a uniform distribution. |
| RandomUniform.Options | Optional attributes for RandomUniform |
| RandomUniformInt <U extends TNumber > | Outputs random integers from a uniform distribution. |
| RandomUniformInt.Options | Optional attributes for RandomUniformInt |
| Range <T extends TNumber > | Creates a sequence of numbers. |
| RangeDataset | Creates a dataset with a range of values. |
| Rango | Returns the rank of a tensor. |
| RawDataBufferFactory | Factory of raw data buffers |
| RawOp | A base class for Op implementations that are backed by a single Operation . |
| RawTensor | A tensor which memory has not been mapped to a data space directly accessible from the JVM. |
| ReaderBaseProtos | |
| ReaderBaseState | For serializing and restoring the state of ReaderBase, see reader_base.h for details. |
| ReaderBaseState.Builder | For serializing and restoring the state of ReaderBase, see reader_base.h for details. |
| ReaderBaseStateOrBuilder | |
| ReaderNumRecordsProduced | Returns the number of records this Reader has produced. |
| ReaderNumWorkUnitsCompleted | Returns the number of work units this Reader has finished processing. |
| ReaderRead | Returns the next record (key, value pair) produced by a Reader. |
| ReaderReadUpTo | Returns up to `num_records` (key, value) pairs produced by a Reader. |
| ReaderReset | Restore a Reader to its initial clean state. |
| ReaderRestoreState | Restore a reader to a previously saved state. |
| ReaderSerializeState | Produce a string tensor that encodes the state of a Reader. |
| ReadFile | Reads and outputs the entire contents of the input filename. |
| ReadVariableOp <T extends TType > | Reads the value of a variable. |
| Real <U extends TNumber > | Returns the real part of a complex number. |
| RealDiv <T extends TType > | Returns x / y element-wise for real types. |
| RebatchDataset | Creates a dataset that changes the batch size. |
| RebatchDataset | Creates a dataset that changes the batch size. |
| RebatchDataset.Options | Optional attributes for RebatchDataset |
| RebatchDataset.Options | Optional attributes for RebatchDataset |
| RebatchDatasetV2 | Creates a dataset that changes the batch size. |
| Reciprocal <T extends TType > | Computes the reciprocal of x element-wise. |
| ReciprocalGrad <T extends TType > | Computes the gradient for the inverse of `x` wrt its input. |
| RecordInput | Emits randomized records. |
| RecordInput.Options | Optional attributes for RecordInput |
| Recv <T extends TType > | Receives the named tensor from send_device on recv_device. |
| Recv <T extends TType > | Receives the named tensor from another XLA computation. |
| Recv.Options | Optional attributes for Recv |
| RecvTPUEmbeddingActivations | An op that receives embedding activations on the TPU. |
| Reduce <T extends TNumber > | Encapsulates metrics that perform a reduce operation on the metric values. |
| Reduce <T extends TNumber > | Mutually reduces multiple tensors of identical type and shape. |
| Reduce.Options | Optional attributes for Reduce |
| ReduceAll | Computes the "logical and" of elements across dimensions of a tensor. |
| ReduceAll.Options | Optional attributes for ReduceAll |
| ReduceAny | Computes the "logical or" of elements across dimensions of a tensor. |
| ReduceAny.Options | Optional attributes for ReduceAny |
| ReduceJoin | Joins a string Tensor across the given dimensions. |
| ReduceJoin.Options | Optional attributes for ReduceJoin |
| ReduceMax <T extends TType > | Computes the maximum of elements across dimensions of a tensor. |
| ReduceMax.Options | Optional attributes for ReduceMax |
| ReduceMin <T extends TType > | Computes the minimum of elements across dimensions of a tensor. |
| ReduceMin.Options | Optional attributes for ReduceMin |
| ReduceProd <T extends TType > | Computes the product of elements across dimensions of a tensor. |
| ReduceProd.Options | Optional attributes for ReduceProd |
| ReduceSum <T extends TType > | Computes the sum of elements across dimensions of a tensor. |
| ReduceSum.Options | Optional attributes for ReduceSum |
| ReduceV2 <T extends TNumber > | Mutually reduces multiple tensors of identical type and shape. |
| ReduceV2.Options | Optional attributes for ReduceV2 |
| Riduzione | Type of Loss Reduction |
| RefEnter <T extends TType > | Creates or finds a child frame, and makes `data` available to the child frame. |
| RefEnter.Options | Optional attributes for RefEnter |
| RefExit <T extends TType > | Exits the current frame to its parent frame. |
| RefIdentity <T extends TType > | Return the same ref tensor as the input ref tensor. |
| RefMerge <T extends TType > | Forwards the value of an available tensor from `inputs` to `output`. |
| RefNextIteration <T extends TType > | Makes its input available to the next iteration. |
| RefSelect <T extends TType > | Forwards the `index`th element of `inputs` to `output`. |
| RefSwitch <T extends TType > | Forwards the ref tensor `data` to the output port determined by `pred`. |
| RegexFullMatch | Check if the input matches the regex pattern. |
| RegexReplace | Replaces matches of the `pattern` regular expression in `input` with the replacement string provided in `rewrite`. |
| RegexReplace.Options | Optional attributes for RegexReplace |
| RegisterDataset | Registers a dataset with the tf.data service. |
| RelativeDimensionalSpace | |
| Relu <T extends TType > | Computes rectified linear: `max(features, 0)`. |
| ReLU <T extends TNumber > | Rectified Linear Unit(ReLU) activation. |
| Relu6 <T extends TNumber > | Computes rectified linear 6: `min(max(features, 0), 6)`. |
| Relu6Grad <T extends TNumber > | Computes rectified linear 6 gradients for a Relu6 operation. |
| ReluGrad <T extends TNumber > | Computes rectified linear gradients for a Relu operation. |
| RemoteFusedGraphExecute | Execute a sub graph on a remote processor. |
| RemoteFusedGraphExecuteInfo | Protocol buffer representing a handle to a tensorflow resource. |
| RemoteFusedGraphExecuteInfo.Builder | Protocol buffer representing a handle to a tensorflow resource. |
| RemoteFusedGraphExecuteInfo.TensorShapeTypeProto | Protobuf type tensorflow.RemoteFusedGraphExecuteInfo.TensorShapeTypeProto |
| RemoteFusedGraphExecuteInfo.TensorShapeTypeProto.Builder | Protobuf type tensorflow.RemoteFusedGraphExecuteInfo.TensorShapeTypeProto |
| RemoteFusedGraphExecuteInfo.TensorShapeTypeProtoOrBuilder | |
| RemoteFusedGraphExecuteInfoOrBuilder | |
| RemoteFusedGraphExecuteInfoProto | |
| RemoteProfilerSessionManagerOptions | Options for remote profiler session manager. |
| RemoteProfilerSessionManagerOptions.Builder | Options for remote profiler session manager. |
| RemoteProfilerSessionManagerOptionsOrBuilder | |
| RemoteTensorHandle | Protobuf type tensorflow.eager.RemoteTensorHandle |
| RemoteTensorHandle.Builder | Protobuf type tensorflow.eager.RemoteTensorHandle |
| RemoteTensorHandleOrBuilder | |
| RemoteTensorHandleProtos | |
| RepeatDataset | Creates a dataset that emits the outputs of `input_dataset` `count` times. |
| ReplicaId | Replica ID. |
| ReplicatedInput <T extends TType > | Connects N inputs to an N-way replicated TPU computation. |
| ReplicatedInput.Options | Optional attributes for ReplicatedInput |
| ReplicatedOutput <T extends TType > | Connects N outputs from an N-way replicated TPU computation. |
| ReplicateMetadata | Metadata indicating how the TPU computation should be replicated. |
| ReplicateMetadata.Options | Optional attributes for ReplicateMetadata |
| RequantizationRange | Computes a range that covers the actual values present in a quantized tensor. |
| RequantizationRangePerChannel | Computes requantization range per channel. |
| Requantize <U extends TType > | Converts the quantized `input` tensor into a lower-precision `output`. |
| RequantizePerChannel <U extends TType > | Requantizes input with min and max values known per channel. |
| RequestedExitCode | Protobuf type tensorflow.RequestedExitCode |
| RequestedExitCode.Builder | Protobuf type tensorflow.RequestedExitCode |
| RequestedExitCodeOrBuilder | |
| Reshape <T extends TType > | Reshapes a tensor. |
| ResizeArea | Resize `images` to `size` using area interpolation. |
| ResizeArea.Options | Optional attributes for ResizeArea |
| ResizeBicubic | Resize `images` to `size` using bicubic interpolation. |
| ResizeBicubic.Options | Optional attributes for ResizeBicubic |
| ResizeBicubicGrad <T extends TNumber > | Computes the gradient of bicubic interpolation. |
| ResizeBicubicGrad.Options | Optional attributes for ResizeBicubicGrad |
| ResizeBilinear | Resize `images` to `size` using bilinear interpolation. |
| ResizeBilinear.Options | Optional attributes for ResizeBilinear |
| ResizeBilinearGrad <T extends TNumber > | Computes the gradient of bilinear interpolation. |
| ResizeBilinearGrad.Options | Optional attributes for ResizeBilinearGrad |
| ResizeNearestNeighbor <T extends TNumber > | Resize `images` to `size` using nearest neighbor interpolation. |
| ResizeNearestNeighbor.Options | Optional attributes for ResizeNearestNeighbor |
| ResizeNearestNeighborGrad <T extends TNumber > | Computes the gradient of nearest neighbor interpolation. |
| ResizeNearestNeighborGrad.Options | Optional attributes for ResizeNearestNeighborGrad |
| ResourceAccumulatorApplyGradient | Applies a gradient to a given accumulator. |
| ResourceAccumulatorNumAccumulated | Returns the number of gradients aggregated in the given accumulators. |
| ResourceAccumulatorSetGlobalStep | Updates the accumulator with a new value for global_step. |
| ResourceAccumulatorTakeGradient <T extends TType > | Extracts the average gradient in the given ConditionalAccumulator. |
| ResourceApplyAdadelta | Update '*var' according to the adadelta scheme. |
| ResourceApplyAdadelta.Options | Optional attributes for ResourceApplyAdadelta |
| ResourceApplyAdagrad | Update '*var' according to the adagrad scheme. |
| ResourceApplyAdagrad.Options | Optional attributes for ResourceApplyAdagrad |
| ResourceApplyAdagradDa | Update '*var' according to the proximal adagrad scheme. |
| ResourceApplyAdagradDa.Options | Optional attributes for ResourceApplyAdagradDa |
| ResourceApplyAdam | Update '*var' according to the Adam algorithm. |
| ResourceApplyAdam.Options | Optional attributes for ResourceApplyAdam |
| ResourceApplyAdaMax | Update '*var' according to the AdaMax algorithm. |
| ResourceApplyAdaMax.Options | Optional attributes for ResourceApplyAdaMax |
| ResourceApplyAdamWithAmsgrad | Update '*var' according to the Adam algorithm. |
| ResourceApplyAdamWithAmsgrad.Options | Optional attributes for ResourceApplyAdamWithAmsgrad |
| ResourceApplyAddSign | Update '*var' according to the AddSign update. |
| ResourceApplyAddSign.Options | Optional attributes for ResourceApplyAddSign |
| ResourceApplyCenteredRmsProp | Update '*var' according to the centered RMSProp algorithm. |
| ResourceApplyCenteredRmsProp.Options | Optional attributes for ResourceApplyCenteredRmsProp |
| ResourceApplyFtrl | Update '*var' according to the Ftrl-proximal scheme. |
| ResourceApplyFtrl.Options | Optional attributes for ResourceApplyFtrl |
| ResourceApplyGradientDescent | Update '*var' by subtracting 'alpha' * 'delta' from it. |
| ResourceApplyGradientDescent.Options | Optional attributes for ResourceApplyGradientDescent |
| ResourceApplyKerasMomentum | Update '*var' according to the momentum scheme. |
| ResourceApplyKerasMomentum.Options | Optional attributes for ResourceApplyKerasMomentum |
| ResourceApplyMomentum | Update '*var' according to the momentum scheme. |
| ResourceApplyMomentum.Options | Optional attributes for ResourceApplyMomentum |
| ResourceApplyPowerSign | Update '*var' according to the AddSign update. |
| ResourceApplyPowerSign.Options | Optional attributes for ResourceApplyPowerSign |
| ResourceApplyProximalAdagrad | Update '*var' and '*accum' according to FOBOS with Adagrad learning rate. |
| ResourceApplyProximalAdagrad.Options | Optional attributes for ResourceApplyProximalAdagrad |
| ResourceApplyProximalGradientDescent | Update '*var' as FOBOS algorithm with fixed learning rate. |
| ResourceApplyProximalGradientDescent.Options | Optional attributes for ResourceApplyProximalGradientDescent |
| ResourceApplyRmsProp | Update '*var' according to the RMSProp algorithm. |
| ResourceApplyRmsProp.Options | Optional attributes for ResourceApplyRmsProp |
| ResourceConditionalAccumulator | A conditional accumulator for aggregating gradients. |
| ResourceConditionalAccumulator.Options | Optional attributes for ResourceConditionalAccumulator |
| ResourceCountUpTo <T extends TNumber > | Increments variable pointed to by 'resource' until it reaches 'limit'. |
| ResourceDtypeAndShape | Protobuf type tensorflow.eager.ResourceDtypeAndShape |
| ResourceDtypeAndShape.Builder | Protobuf type tensorflow.eager.ResourceDtypeAndShape |
| ResourceDtypeAndShapeOrBuilder | |
| ResourceGather <U extends TType > | Gather slices from the variable pointed to by `resource` according to `indices`. |
| ResourceGather.Options | Optional attributes for ResourceGather |
| ResourceGatherNd <U extends TType > | |
| ResourceHandle | |
| ResourceHandleProto | Protocol buffer representing a handle to a tensorflow resource. |
| ResourceHandleProto.Builder | Protocol buffer representing a handle to a tensorflow resource. |
| ResourceHandleProto.DtypeAndShape | Protocol buffer representing a pair of (data type, tensor shape). |
| ResourceHandleProto.DtypeAndShape.Builder | Protocol buffer representing a pair of (data type, tensor shape). |
| ResourceHandleProto.DtypeAndShapeOrBuilder | |
| ResourceHandleProtoOrBuilder | |
| ResourceScatterAdd | Adds sparse updates to the variable referenced by `resource`. |
| ResourceScatterDiv | Divides sparse updates into the variable referenced by `resource`. |
| ResourceScatterMax | Reduces sparse updates into the variable referenced by `resource` using the `max` operation. |
| ResourceScatterMin | Reduces sparse updates into the variable referenced by `resource` using the `min` operation. |
| ResourceScatterMul | Multiplies sparse updates into the variable referenced by `resource`. |
| ResourceScatterNdAdd | Applies sparse addition to individual values or slices in a Variable. |
| ResourceScatterNdAdd.Options | Optional attributes for ResourceScatterNdAdd |
| ResourceScatterNdMax | |
| ResourceScatterNdMax.Options | Optional attributes for ResourceScatterNdMax |
| ResourceScatterNdMin | |
| ResourceScatterNdMin.Options | Optional attributes for ResourceScatterNdMin |
| ResourceScatterNdSub | Applies sparse subtraction to individual values or slices in a Variable. |
| ResourceScatterNdSub.Options | Optional attributes for ResourceScatterNdSub |
| ResourceScatterNdUpdate | Applies sparse `updates` to individual values or slices within a given variable according to `indices`. |
| ResourceScatterNdUpdate.Options | Optional attributes for ResourceScatterNdUpdate |
| ResourceScatterSub | Subtracts sparse updates from the variable referenced by `resource`. |
| ResourceScatterUpdate | Assigns sparse updates to the variable referenced by `resource`. |
| ResourceSparseApplyAdadelta | var: Should be from a Variable(). |
| ResourceSparseApplyAdadelta.Options | Optional attributes for ResourceSparseApplyAdadelta |
| ResourceSparseApplyAdagrad | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
| ResourceSparseApplyAdagrad.Options | Optional attributes for ResourceSparseApplyAdagrad |
| ResourceSparseApplyAdagradDa | Update entries in '*var' and '*accum' according to the proximal adagrad scheme. |
| ResourceSparseApplyAdagradDa.Options | Optional attributes for ResourceSparseApplyAdagradDa |
| ResourceSparseApplyAdagradV2 | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
| ResourceSparseApplyAdagradV2.Options | Optional attributes for ResourceSparseApplyAdagradV2 |
| ResourceSparseApplyCenteredRmsProp | Update '*var' according to the centered RMSProp algorithm. |
| ResourceSparseApplyCenteredRmsProp.Options | Optional attributes for ResourceSparseApplyCenteredRmsProp |
| ResourceSparseApplyFtrl | Update relevant entries in '*var' according to the Ftrl-proximal scheme. |
| ResourceSparseApplyFtrl.Options | Optional attributes for ResourceSparseApplyFtrl |
| ResourceSparseApplyKerasMomentum | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
| ResourceSparseApplyKerasMomentum.Options | Optional attributes for ResourceSparseApplyKerasMomentum |
| ResourceSparseApplyMomentum | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
| ResourceSparseApplyMomentum.Options | Optional attributes for ResourceSparseApplyMomentum |
| ResourceSparseApplyProximalAdagrad | Sparse update entries in '*var' and '*accum' according to FOBOS algorithm. |
| ResourceSparseApplyProximalAdagrad.Options | Optional attributes for ResourceSparseApplyProximalAdagrad |
| ResourceSparseApplyProximalGradientDescent | Sparse update '*var' as FOBOS algorithm with fixed learning rate. |
| ResourceSparseApplyProximalGradientDescent.Options | Optional attributes for ResourceSparseApplyProximalGradientDescent |
| ResourceSparseApplyRmsProp | Update '*var' according to the RMSProp algorithm. |
| ResourceSparseApplyRmsProp.Options | Optional attributes for ResourceSparseApplyRmsProp |
| ResourceStridedSliceAssign | Assign `value` to the sliced l-value reference of `ref`. |
| ResourceStridedSliceAssign.Options | Optional attributes for ResourceStridedSliceAssign |
| Ripristinare | Restores tensors from a V2 checkpoint. |
| RestoreSlice <T extends TType > | Restores a tensor from checkpoint files. |
| RestoreSlice.Options | Optional attributes for RestoreSlice |
| RetrieveTPUEmbeddingAdadeltaParameters | Retrieve Adadelta embedding parameters. |
| RetrieveTPUEmbeddingAdadeltaParameters.Options | Optional attributes for RetrieveTPUEmbeddingAdadeltaParameters |
| RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug | Retrieve Adadelta embedding parameters with debug support. |
| RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug |
| RetrieveTPUEmbeddingAdagradParameters | Retrieve Adagrad embedding parameters. |
| RetrieveTPUEmbeddingAdagradParameters.Options | Optional attributes for RetrieveTPUEmbeddingAdagradParameters |
| RetrieveTPUEmbeddingAdagradParametersGradAccumDebug | Retrieve Adagrad embedding parameters with debug support. |
| RetrieveTPUEmbeddingAdagradParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingAdagradParametersGradAccumDebug |
| RetrieveTPUEmbeddingADAMParameters | Retrieve ADAM embedding parameters. |
| RetrieveTPUEmbeddingADAMParameters.Options | Optional attributes for RetrieveTPUEmbeddingADAMParameters |
| RetrieveTPUEmbeddingADAMParametersGradAccumDebug | Retrieve ADAM embedding parameters with debug support. |
| RetrieveTPUEmbeddingADAMParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingADAMParametersGradAccumDebug |
| RetrieveTPUEmbeddingCenteredRMSPropParameters | Retrieve centered RMSProp embedding parameters. |
| RetrieveTPUEmbeddingCenteredRMSPropParameters.Options | Optional attributes for RetrieveTPUEmbeddingCenteredRMSPropParameters |
| RetrieveTPUEmbeddingFTRLParameters | Retrieve FTRL embedding parameters. |
| RetrieveTPUEmbeddingFTRLParameters.Options | Optional attributes for RetrieveTPUEmbeddingFTRLParameters |
| RetrieveTPUEmbeddingFTRLParametersGradAccumDebug | Retrieve FTRL embedding parameters with debug support. |
| RetrieveTPUEmbeddingFTRLParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingFTRLParametersGradAccumDebug |
| RetrieveTPUEmbeddingMDLAdagradLightParameters | Retrieve MDL Adagrad Light embedding parameters. |
| RetrieveTPUEmbeddingMDLAdagradLightParameters.Options | Optional attributes for RetrieveTPUEmbeddingMDLAdagradLightParameters |
| RetrieveTPUEmbeddingMomentumParameters | Retrieve Momentum embedding parameters. |
| RetrieveTPUEmbeddingMomentumParameters.Options | Optional attributes for RetrieveTPUEmbeddingMomentumParameters |
| RetrieveTPUEmbeddingMomentumParametersGradAccumDebug | Retrieve Momentum embedding parameters with debug support. |
| RetrieveTPUEmbeddingMomentumParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingMomentumParametersGradAccumDebug |
| RetrieveTPUEmbeddingProximalAdagradParameters | Retrieve proximal Adagrad embedding parameters. |
| RetrieveTPUEmbeddingProximalAdagradParameters.Options | Optional attributes for RetrieveTPUEmbeddingProximalAdagradParameters |
| RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug | Retrieve proximal Adagrad embedding parameters with debug support. |
| RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug |
| RetrieveTPUEmbeddingProximalYogiParameters | |
| RetrieveTPUEmbeddingProximalYogiParameters.Options | Optional attributes for RetrieveTPUEmbeddingProximalYogiParameters |
| RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug | |
| RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug |
| RetrieveTPUEmbeddingRMSPropParameters | Retrieve RMSProp embedding parameters. |
| RetrieveTPUEmbeddingRMSPropParameters.Options | Optional attributes for RetrieveTPUEmbeddingRMSPropParameters |
| RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug | Retrieve RMSProp embedding parameters with debug support. |
| RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug |
| RetrieveTPUEmbeddingStochasticGradientDescentParameters | Retrieve SGD embedding parameters. |
| RetrieveTPUEmbeddingStochasticGradientDescentParameters.Options | Optional attributes for RetrieveTPUEmbeddingStochasticGradientDescentParameters |
| RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug | Retrieve SGD embedding parameters with debug support. |
| RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug |
| Reverse <T extends TType > | Reverses specific dimensions of a tensor. |
| ReverseSequence <T extends TType > | Reverses variable length slices. |
| ReverseSequence.Options | Optional attributes for ReverseSequence |
| RewriterConfig | Graph rewriting is experimental and subject to change, not covered by any API stability guarantees. |
| RewriterConfig.Builder | Graph rewriting is experimental and subject to change, not covered by any API stability guarantees. |
| RewriterConfig.CpuLayout | Enum for layout conversion between NCHW and NHWC on CPU. |
| RewriterConfig.CustomGraphOptimizer | Message to describe custom graph optimizer and its parametersProtobuf type tensorflow.RewriterConfig.CustomGraphOptimizer |
| RewriterConfig.CustomGraphOptimizer.Builder | Message to describe custom graph optimizer and its parametersProtobuf type tensorflow.RewriterConfig.CustomGraphOptimizer |
| RewriterConfig.CustomGraphOptimizerOrBuilder | |
| RewriterConfig.MemOptType | Protobuf enum tensorflow.RewriterConfig.MemOptType |
| RewriterConfig.NumIterationsType | Enum controlling the number of times to run optimizers. |
| RewriterConfig.Toggle | Protobuf enum tensorflow.RewriterConfig.Toggle |
| RewriterConfigOrBuilder | |
| RewriterConfigProtos | |
| Rfft <U extends TType > | Real-valued fast Fourier transform. |
| Rfft2d <U extends TType > | 2D real-valued fast Fourier transform. |
| Rfft3d <U extends TType > | 3D real-valued fast Fourier transform. |
| RgbToHsv <T extends TNumber > | Converts one or more images from RGB to HSV. |
| RightShift <T extends TNumber > | Elementwise computes the bitwise right-shift of `x` and `y`. |
| Rint <T extends TNumber > | Returns element-wise integer closest to x. |
| RMSProp | Optimizer that implements the RMSProp algorithm. |
| RngReadAndSkip | Advance the counter of a counter-based RNG. |
| RngSkip | Advance the counter of a counter-based RNG. |
| Roll <T extends TType > | Rolls the elements of a tensor along an axis. |
| Round <T extends TType > | Rounds the values of a tensor to the nearest integer, element-wise. |
| Rpc | Perform batches of RPC requests. |
| Rpc.Options | Optional attributes for Rpc |
| RPCOptions | Protobuf type tensorflow.RPCOptions |
| RPCOptions.Builder | Protobuf type tensorflow.RPCOptions |
| RPCOptionsOrBuilder | |
| Rsqrt <T extends TType > | Computes reciprocal of square root of x element-wise. |
| RsqrtGrad <T extends TType > | Computes the gradient for the rsqrt of `x` wrt its input. |
| RunConfiguration | Run-specific items such as arguments to the test / benchmark. |
| RunConfiguration.Builder | Run-specific items such as arguments to the test / benchmark. |
| RunConfigurationOrBuilder | |
| RunMetadata | Metadata output (i.e., non-Tensor) for a single Run() call. |
| RunMetadata.Builder | Metadata output (i.e., non-Tensor) for a single Run() call. |
| RunMetadata.FunctionGraphs | Protobuf type tensorflow.RunMetadata.FunctionGraphs |
| RunMetadata.FunctionGraphs.Builder | Protobuf type tensorflow.RunMetadata.FunctionGraphs |
| RunMetadata.FunctionGraphsOrBuilder | |
| RunMetadataOrBuilder | |
| RunOptions | Options for a single Run() call. |
| RunOptions.Builder | Options for a single Run() call. |
| RunOptions.Experimental | Everything inside Experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat. |
| RunOptions.Experimental.Builder | Everything inside Experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat. |
| RunOptions.Experimental.RunHandlerPoolOptions | Options for run handler thread pool. |
| RunOptions.Experimental.RunHandlerPoolOptions.Builder | Options for run handler thread pool. |
| RunOptions.Experimental.RunHandlerPoolOptionsOrBuilder | |
| RunOptions.ExperimentalOrBuilder | |
| RunOptions.TraceLevel | TODO(pbar) Turn this into a TraceOptions proto which allows tracing to be controlled in a more orthogonal manner?Protobuf enum tensorflow.RunOptions.TraceLevel |
| RunOptionsOrBuilder |
S
| SampleDistortedBoundingBox <T extends TNumber > | Generate a single randomly distorted bounding box for an image. |
| SampleDistortedBoundingBox.Options | Optional attributes for SampleDistortedBoundingBox |
| SamplingDataset | Creates a dataset that takes a Bernoulli sample of the contents of another dataset. |
| Salva | Saves tensors in V2 checkpoint format. |
| SaveableObject | Protobuf type tensorflow.SaveableObject |
| SaveableObject.Builder | Protobuf type tensorflow.SaveableObject |
| SaveableObjectOrBuilder | |
| SavedAsset | A SavedAsset points to an asset in the MetaGraph. |
| SavedAsset.Builder | A SavedAsset points to an asset in the MetaGraph. |
| SavedAssetOrBuilder | |
| SavedBareConcreteFunction | Protobuf type tensorflow.SavedBareConcreteFunction |
| SavedBareConcreteFunction.Builder | Protobuf type tensorflow.SavedBareConcreteFunction |
| SavedBareConcreteFunctionOrBuilder | |
| SavedConcreteFunction | Stores low-level information about a concrete function. |
| SavedConcreteFunction.Builder | Stores low-level information about a concrete function. |
| SavedConcreteFunctionOrBuilder | |
| SavedConstant | Protobuf type tensorflow.SavedConstant |
| SavedConstant.Builder | Protobuf type tensorflow.SavedConstant |
| SavedConstantOrBuilder | |
| SavedFunction | A function with multiple signatures, possibly with non-Tensor arguments. |
| SavedFunction.Builder | A function with multiple signatures, possibly with non-Tensor arguments. |
| SavedFunctionOrBuilder | |
| SavedModel | SavedModel is the high level serialization format for TensorFlow Models. |
| SavedModel.Builder | SavedModel is the high level serialization format for TensorFlow Models. |
| SavedModelBundle | SavedModelBundle represents a model loaded from storage. |
| SavedModelBundle.Exporter | Options for exporting a SavedModel. |
| SavedModelBundle.Loader | Options for loading a SavedModel. |
| SavedModelOrBuilder | |
| SavedModelProtos | |
| SavedObject | Protobuf type tensorflow.SavedObject |
| SavedObject.Builder | Protobuf type tensorflow.SavedObject |
| SavedObject.KindCase | |
| SavedObjectGraph | Protobuf type tensorflow.SavedObjectGraph |
| SavedObjectGraph.Builder | Protobuf type tensorflow.SavedObjectGraph |
| SavedObjectGraphOrBuilder | |
| SavedObjectGraphProtos | |
| SavedObjectOrBuilder | |
| SavedResource | A SavedResource represents a TF object that holds state during its lifetime. |
| SavedResource.Builder | A SavedResource represents a TF object that holds state during its lifetime. |
| SavedResourceOrBuilder | |
| SavedSlice | Saved tensor slice: it stores the name of the tensors, the slice, and the raw data. |
| SavedSlice.Builder | Saved tensor slice: it stores the name of the tensors, the slice, and the raw data. |
| SavedSliceMeta | Metadata describing the set of slices of the same tensor saved in a checkpoint file. |
| SavedSliceMeta.Builder | Metadata describing the set of slices of the same tensor saved in a checkpoint file. |
| SavedSliceMetaOrBuilder | |
| SavedSliceOrBuilder | |
| SavedTensorSliceMeta | Metadata describing the set of tensor slices saved in a checkpoint file. |
| SavedTensorSliceMeta.Builder | Metadata describing the set of tensor slices saved in a checkpoint file. |
| SavedTensorSliceMetaOrBuilder | |
| SavedTensorSliceProtos | |
| SavedTensorSlices | Each record in a v3 checkpoint file is a serialized SavedTensorSlices message. |
| SavedTensorSlices.Builder | Each record in a v3 checkpoint file is a serialized SavedTensorSlices message. |
| SavedTensorSlicesOrBuilder | |
| SavedUserObject | A SavedUserObject is an object (in the object-oriented language of the TensorFlow program) of some user- or framework-defined class other than those handled specifically by the other kinds of SavedObjects. |
| SavedUserObject.Builder | A SavedUserObject is an object (in the object-oriented language of the TensorFlow program) of some user- or framework-defined class other than those handled specifically by the other kinds of SavedObjects. |
| SavedUserObjectOrBuilder | |
| SavedVariable | Represents a Variable that is initialized by loading the contents from the checkpoint. |
| SavedVariable.Builder | Represents a Variable that is initialized by loading the contents from the checkpoint. |
| SavedVariableOrBuilder | |
| SaverDef | Protocol buffer representing the configuration of a Saver. |
| SaverDef.Builder | Protocol buffer representing the configuration of a Saver. |
| SaverDef.CheckpointFormatVersion | A version number that identifies a different on-disk checkpoint format. |
| SaverDefOrBuilder | |
| SaverProtos | |
| SaveSliceInfoDef | Protobuf type tensorflow.SaveSliceInfoDef |
| SaveSliceInfoDef.Builder | Protobuf type tensorflow.SaveSliceInfoDef |
| SaveSliceInfoDefOrBuilder | |
| SaveSlices | Saves input tensors slices to disk. |
| ScalarSummary | Outputs a `Summary` protocol buffer with scalar values. |
| ScaleAndTranslate | |
| ScaleAndTranslate.Options | Optional attributes for ScaleAndTranslate |
| ScaleAndTranslateGrad <T extends TNumber > | |
| ScaleAndTranslateGrad.Options | Optional attributes for ScaleAndTranslateGrad |
| ScatterAdd <T extends TType > | Adds sparse updates to a variable reference. |
| ScatterAdd.Options | Optional attributes for ScatterAdd |
| ScatterDiv <T extends TType > | Divides a variable reference by sparse updates. |
| ScatterDiv.Options | Optional attributes for ScatterDiv |
| ScatterMax <T extends TNumber > | Reduces sparse updates into a variable reference using the `max` operation. |
| ScatterMax.Options | Optional attributes for ScatterMax |
| ScatterMin <T extends TNumber > | Reduces sparse updates into a variable reference using the `min` operation. |
| ScatterMin.Options | Optional attributes for ScatterMin |
| ScatterMul <T extends TType > | Multiplies sparse updates into a variable reference. |
| ScatterMul.Options | Optional attributes for ScatterMul |
| ScatterNd <U extends TType > | Scatter `updates` into a new tensor according to `indices`. |
| ScatterNdAdd <T extends TType > | Applies sparse addition to individual values or slices in a Variable. |
| ScatterNdAdd.Options | Optional attributes for ScatterNdAdd |
| ScatterNdMax <T extends TType > | Computes element-wise maximum. |
| ScatterNdMax.Options | Optional attributes for ScatterNdMax |
| ScatterNdMin <T extends TType > | Computes element-wise minimum. |
| ScatterNdMin.Options | Optional attributes for ScatterNdMin |
| ScatterNdNonAliasingAdd <T extends TType > | Applies sparse addition to `input` using individual values or slices from `updates` according to indices `indices`. |
| ScatterNdSub <T extends TType > | Applies sparse subtraction to individual values or slices in a Variable. |
| ScatterNdSub.Options | Optional attributes for ScatterNdSub |
| ScatterNdUpdate <T extends TType > | Applies sparse `updates` to individual values or slices within a given variable according to `indices`. |
| ScatterNdUpdate.Options | Optional attributes for ScatterNdUpdate |
| ScatterSub <T extends TType > | Subtracts sparse updates to a variable reference. |
| ScatterSub.Options | Optional attributes for ScatterSub |
| ScatterUpdate <T extends TType > | Applies sparse updates to a variable reference. |
| ScatterUpdate.Options | Optional attributes for ScatterUpdate |
| Ambito | Manages groups of related properties when creating Tensorflow Operations, such as a common name prefix. |
| ScopedAllocatorOptions | Protobuf type tensorflow.ScopedAllocatorOptions |
| ScopedAllocatorOptions.Builder | Protobuf type tensorflow.ScopedAllocatorOptions |
| ScopedAllocatorOptionsOrBuilder | |
| SdcaFprint | Computes fingerprints of the input strings. |
| SdcaOptimizer | Distributed version of Stochastic Dual Coordinate Ascent (SDCA) optimizer for linear models with L1 + L2 regularization. |
| SdcaOptimizer.Options | Optional attributes for SdcaOptimizer |
| SdcaShrinkL1 | Applies L1 regularization shrink step on the parameters. |
| SegmentMax <T extends TNumber > | Computes the maximum along segments of a tensor. |
| SegmentMean <T extends TType > | Computes the mean along segments of a tensor. |
| SegmentMin <T extends TNumber > | Computes the minimum along segments of a tensor. |
| SegmentProd <T extends TType > | Computes the product along segments of a tensor. |
| SegmentSum <T extends TType > | Computes the sum along segments of a tensor. |
| Select <T extends TType > | |
| SelfAdjointEig <T extends TType > | Computes the eigen decomposition of one or more square self-adjoint matrices. |
| SelfAdjointEig <T extends TType > | Computes the eigen decomposition of a batch of self-adjoint matrices (Note: Only real inputs are supported). |
| SelfAdjointEig.Options | Optional attributes for SelfAdjointEig |
| Selu <T extends TNumber > | Computes scaled exponential linear: `scale * alpha * (exp(features) - 1)` if < 0, `scale * features` otherwise. |
| SELU <T extends TFloating > | Scaled Exponential Linear Unit (SELU). |
| SeluGrad <T extends TNumber > | Computes gradients for the scaled exponential linear (Selu) operation. |
| Inviare | Sends the named tensor from send_device to recv_device. |
| Inviare | Sends the named tensor to another XLA computation. |
| Send.Options | Optional attributes for Send |
| SendTPUEmbeddingGradients | Performs gradient updates of embedding tables. |
| SequenceExample | Protobuf type tensorflow.SequenceExample |
| SequenceExample.Builder | Protobuf type tensorflow.SequenceExample |
| SequenceExampleOrBuilder | |
| SerializeIterator | Converts the given `resource_handle` representing an iterator to a variant tensor. |
| SerializeIterator.Options | Optional attributes for SerializeIterator |
| SerializeManySparse <U extends TType > | Serialize an `N`-minibatch `SparseTensor` into an `[N, 3]` `Tensor` object. |
| SerializeSparse <U extends TType > | Serialize a `SparseTensor` into a `[3]` `Tensor` object. |
| SerializeTensor | Transforms a Tensor into a serialized TensorProto proto. |
| Server | An in-process TensorFlow server, for use in distributed training. |
| ServerDef | Defines the configuration of a single TensorFlow server. |
| ServerDef.Builder | Defines the configuration of a single TensorFlow server. |
| ServerDefOrBuilder | |
| ServerProtos | |
| ServiceConfig | |
| ServiceConfig.DispatcherConfig | Configuration for a tf.data service DispatchServer. |
| ServiceConfig.DispatcherConfig.Builder | Configuration for a tf.data service DispatchServer. |
| ServiceConfig.DispatcherConfigOrBuilder | |
| ServiceConfig.WorkerConfig | Configuration for a tf.data service WorkerServer. |
| ServiceConfig.WorkerConfig.Builder | Configuration for a tf.data service WorkerServer. |
| ServiceConfig.WorkerConfigOrBuilder | |
| Sessione | Driver for Graph execution. |
| Session.Run | Output tensors and metadata obtained when executing a session. |
| Session.Runner | Run Operation s and evaluate Tensors . |
| SessionLog | Protocol buffer used for logging session state. |
| SessionLog.Builder | Protocol buffer used for logging session state. |
| SessionLog.SessionStatus | Protobuf enum tensorflow.SessionLog.SessionStatus |
| SessionLogOrBuilder | |
| SessionMetadata | Metadata about the session. |
| SessionMetadata.Builder | Metadata about the session. |
| SessionMetadataOrBuilder | |
| SetDiff1d <T extends TType , U extends TNumber > | Computes the difference between two lists of numbers or strings. |
| SetSize | Number of unique elements along last dimension of input `set`. |
| SetSize.Options | Optional attributes for SetSize |
| SetsOps | Implementation of set operations |
| SetsOps.Operation | Enumeration containing the string operation values to be passed to the TensorFlow Sparse Ops function ERROR(/SparseOps#denseToDenseSetOperation) |
| SetStatsAggregatorDataset | |
| SetStatsAggregatorDataset | |
| Forma | The shape of a Tensor or NdArray . |
| Shape <U extends TNumber > | Returns the shape of a tensor. |
| Shape_inference_func_TF_ShapeInferenceContext_TF_Status | |
| Shaped | Any data container with a given Shape . |
| ShapeN <U extends TNumber > | Returns shape of tensors. |
| Forme | An operator providing methods on org.tensorflow.op.core.Shape tensors and 1d operands that represent the dimensions of a shape. |
| ShapeUtils | Various methods for processing with Shapes and Operands |
| ShardDataset | Creates a `Dataset` that includes only 1/`num_shards` of this dataset. |
| ShardDataset.Options | Optional attributes for ShardDataset |
| ShardedFilename | Generate a sharded filename. |
| ShardedFilespec | Generate a glob pattern matching all sharded file names. |
| Sharding <T extends TType > | An op which shards the input based on the given sharding attribute. |
| ShortDataBuffer | A DataBuffer of shorts. |
| ShortDataLayout <S extends DataBuffer <?>> | A DataLayout that converts data stored in a buffer to shorts. |
| ShortDenseNdArray | |
| ShortNdArray | An NdArray of shorts. |
| ShuffleAndRepeatDataset | |
| ShuffleAndRepeatDataset.Options | Optional attributes for ShuffleAndRepeatDataset |
| ShuffleDataset | |
| ShuffleDataset.Options | Optional attributes for ShuffleDataset |
| ShutdownDistributedTPU | Shuts down a running distributed TPU system. |
| Sigmoid <T extends TFloating > | Sigmoid activation. |
| Sigmoid <T extends TType > | Computes sigmoid of `x` element-wise. |
| SigmoidCrossEntropyWithLogits | |
| SigmoidGrad <T extends TType > | Computes the gradient of the sigmoid of `x` wrt its input. |
| Sign <T extends TType > | Returns an element-wise indication of the sign of a number. |
| Firma | Describe the inputs and outputs of an executable entity, such as a ConcreteFunction , among other useful metadata. |
| Signature.Builder | Builds a new function signature. |
| Signature.TensorDescription | |
| SignatureDef | SignatureDef defines the signature of a computation supported by a TensorFlow graph. |
| SignatureDef.Builder | SignatureDef defines the signature of a computation supported by a TensorFlow graph. |
| SignatureDefOrBuilder | |
| Sin <T extends TType > | Computes sine of x element-wise. |
| SingleElementSequence <T, U extends NdArray <T>> | A sequence of one single element |
| Sinh <T extends TType > | Computes hyperbolic sine of x element-wise. |
| Size <U extends TNumber > | Returns the size of a tensor. |
| SkipDataset | |
| SkipDataset | Creates a dataset that skips `count` elements from the `input_dataset`. |
| Skipgram | Parses a text file and creates a batch of examples. |
| Skipgram.Options | Optional attributes for Skipgram |
| SleepDataset | |
| SleepDataset | |
| Slice <T extends TType > | Return a slice from 'input'. |
| SlicingElementSequence <T, U extends NdArray <T>> | A sequence creating a new NdArray instance (slice) for each element of an iteration |
| SlidingWindowDataset | Creates a dataset that passes a sliding window over `input_dataset`. |
| SlidingWindowDataset | Creates a dataset that passes a sliding window over `input_dataset`. |
| Snapshot <T extends TType > | Returns a copy of the input tensor. |
| Istantanea | Protobuf type tensorflow.SnapShot |
| SnapShot.Builder | Protobuf type tensorflow.SnapShot |
| SnapshotMetadataRecord | This stores the metadata information present in each snapshot record. |
| SnapshotMetadataRecord.Builder | This stores the metadata information present in each snapshot record. |
| SnapshotMetadataRecordOrBuilder | |
| SnapShotOrBuilder | |
| SnapshotProtos | |
| SnapshotRecord | Each SnapshotRecord represents one batch of pre-processed input data. |
| SnapshotRecord.Builder | Each SnapshotRecord represents one batch of pre-processed input data. |
| SnapshotRecordOrBuilder | |
| SnapshotTensorMetadata | Metadata for all the tensors in a Snapshot Record. |
| SnapshotTensorMetadata.Builder | Metadata for all the tensors in a Snapshot Record. |
| SnapshotTensorMetadataOrBuilder | |
| SobolSample <T extends TNumber > | Generates points from the Sobol sequence. |
| Softmax <T extends TFloating > | Softmax converts a real vector to a vector of categorical probabilities. |
| Softmax <T extends TNumber > | Computes softmax activations. |
| SoftmaxCrossEntropyWithLogits | |
| SoftmaxCrossEntropyWithLogits <T extends TNumber > | Computes softmax cross entropy cost and gradients to backpropagate. |
| Softplus <T extends TFloating > | Softplus activation function, softplus(x) = log(exp(x) + 1) . |
| Softplus <T extends TNumber > | Computes softplus: `log(exp(features) + 1)`. |
| SoftplusGrad <T extends TNumber > | Computes softplus gradients for a softplus operation. |
| Softsign <T extends TFloating > | Softsign activation function, softsign(x) = x / (abs(x) + 1) . |
| Softsign <T extends TNumber > | Computes softsign: `features / (abs(features) + 1)`. |
| SoftsignGrad <T extends TNumber > | Computes softsign gradients for a softsign operation. |
| Solve <T extends TType > | Solves systems of linear equations. |
| Solve.Options | Optional attributes for Solve |
| Sort <T extends TType > | Wraps the XLA Sort operator, documented at https://www.tensorflow.org/performance/xla/operation_semantics#sort . |
| SourceFile | Content of a source file involved in the execution of the debugged TensorFlow program. |
| SourceFile.Builder | Content of a source file involved in the execution of the debugged TensorFlow program. |
| SourceFileOrBuilder | |
| SpaceToBatch <T extends TType > | SpaceToBatch for 4-D tensors of type T. |
| SpaceToBatchNd <T extends TType > | SpaceToBatch for ND tensors of type T. |
| SpaceToDepth <T extends TType > | SpaceToDepth for tensors of type T. |
| SpaceToDepth.Options | Optional attributes for SpaceToDepth |
| SparseAccumulatorApplyGradient | Applies a sparse gradient to a given accumulator. |
| SparseAccumulatorTakeGradient <T extends TType > | Extracts the average sparse gradient in a SparseConditionalAccumulator. |
| SparseAdd <T extends TType > | Adds two `SparseTensor` objects to produce another `SparseTensor`. |
| SparseAddGrad <T extends TType > | The gradient operator for the SparseAdd op. |
| SparseApplyAdadelta <T extends TType > | var: Should be from a Variable(). |
| SparseApplyAdadelta.Options | Optional attributes for SparseApplyAdadelta |
| SparseApplyAdagrad <T extends TType > | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
| SparseApplyAdagrad.Options | Optional attributes for SparseApplyAdagrad |
| SparseApplyAdagradDa <T extends TType > | Update entries in '*var' and '*accum' according to the proximal adagrad scheme. |
| SparseApplyAdagradDa.Options | Optional attributes for SparseApplyAdagradDa |
| SparseApplyCenteredRmsProp <T extends TType > | Update '*var' according to the centered RMSProp algorithm. |
| SparseApplyCenteredRmsProp.Options | Optional attributes for SparseApplyCenteredRmsProp |
| SparseApplyFtrl <T extends TType > | Update relevant entries in '*var' according to the Ftrl-proximal scheme. |
| SparseApplyFtrl.Options | Optional attributes for SparseApplyFtrl |
| SparseApplyMomentum <T extends TType > | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
| SparseApplyMomentum.Options | Optional attributes for SparseApplyMomentum |
| SparseApplyProximalAdagrad <T extends TType > | Sparse update entries in '*var' and '*accum' according to FOBOS algorithm. |
| SparseApplyProximalAdagrad.Options | Optional attributes for SparseApplyProximalAdagrad |
| SparseApplyProximalGradientDescent <T extends TType > | Sparse update '*var' as FOBOS algorithm with fixed learning rate. |
| SparseApplyProximalGradientDescent.Options | Optional attributes for SparseApplyProximalGradientDescent |
| SparseApplyRmsProp <T extends TType > | Update '*var' according to the RMSProp algorithm. |
| SparseApplyRmsProp.Options | Optional attributes for SparseApplyRmsProp |
| SparseBincount <U extends TNumber > | Counts the number of occurrences of each value in an integer array. |
| SparseBincount.Options | Optional attributes for SparseBincount |
| SparseCategoricalCrossentropy | Computes the crossentropy loss between labels and predictions. |
| SparseCategoricalCrossentropy <T extends TNumber > | A metric that computes the sparse categorical cross-entropy loss between true labels and predicted labels. |
| SparseConcat <T extends TType > | Concatenates a list of `SparseTensor` along the specified dimension. |
| SparseConditionalAccumulator | A conditional accumulator for aggregating sparse gradients. |
| SparseConditionalAccumulator.Options | Optional attributes for SparseConditionalAccumulator |
| SparseCountSparseOutput <U extends TNumber > | Performs sparse-output bin counting for a sparse tensor input. |
| SparseCountSparseOutput.Options | Optional attributes for SparseCountSparseOutput |
| SparseCross | Generates sparse cross from a list of sparse and dense tensors. |
| SparseCrossHashed | Generates sparse cross from a list of sparse and dense tensors. |
| SparseDenseCwiseAdd <T extends TType > | Adds up a SparseTensor and a dense Tensor, using these special rules: (1) Broadcasts the dense side to have the same shape as the sparse side, if eligible; (2) Then, only the dense values pointed to by the indices of the SparseTensor participate in the cwise addition. |
| SparseDenseCwiseDiv <T extends TType > | Component-wise divides a SparseTensor by a dense Tensor. |
| SparseDenseCwiseMul <T extends TType > | Component-wise multiplies a SparseTensor by a dense Tensor. |
| SparseFillEmptyRows <T extends TType > | Fills empty rows in the input 2-D `SparseTensor` with a default value. |
| SparseFillEmptyRowsGrad <T extends TType > | The gradient of SparseFillEmptyRows. |
| SparseMatMul | Multiply matrix "a" by matrix "b". |
| SparseMatMul.Options | Optional attributes for SparseMatMul |
| SparseMatrixAdd | Sparse addition of two CSR matrices, C = alpha * A + beta * B. |
| SparseMatrixMatMul <T extends TType > | Matrix-multiplies a sparse matrix with a dense matrix. |
| SparseMatrixMatMul.Options | Optional attributes for SparseMatrixMatMul |
| SparseMatrixMul | Element-wise multiplication of a sparse matrix with a dense tensor. |
| SparseMatrixNNZ | Returns the number of nonzeroes of `sparse_matrix`. |
| SparseMatrixOrderingAMD | Computes the Approximate Minimum Degree (AMD) ordering of `input`. |
| SparseMatrixSoftmax | Calculates the softmax of a CSRSparseMatrix. |
| SparseMatrixSoftmaxGrad | Calculates the gradient of the SparseMatrixSoftmax op. |
| SparseMatrixSparseCholesky | Computes the sparse Cholesky decomposition of `input`. |
| SparseMatrixSparseMatMul | Sparse-matrix-multiplies two CSR matrices `a` and `b`. |
| SparseMatrixSparseMatMul.Options | Optional attributes for SparseMatrixSparseMatMul |
| SparseMatrixTranspose | Transposes the inner (matrix) dimensions of a CSRSparseMatrix. |
| SparseMatrixTranspose.Options | Optional attributes for SparseMatrixTranspose |
| SparseMatrixZeros | Creates an all-zeros CSRSparseMatrix with shape `dense_shape`. |
| SparseReduceMax <T extends TNumber > | Computes the max of elements across dimensions of a SparseTensor. |
| SparseReduceMax.Options | Optional attributes for SparseReduceMax |
| SparseReduceMaxSparse <T extends TNumber > | Computes the max of elements across dimensions of a SparseTensor. |
| SparseReduceMaxSparse.Options | Optional attributes for SparseReduceMaxSparse |
| SparseReduceSum <T extends TType > | Computes the sum of elements across dimensions of a SparseTensor. |
| SparseReduceSum.Options | Optional attributes for SparseReduceSum |
| SparseReduceSumSparse <T extends TType > | Computes the sum of elements across dimensions of a SparseTensor. |
| SparseReduceSumSparse.Options | Optional attributes for SparseReduceSumSparse |
| SparseReorder <T extends TType > | Reorders a SparseTensor into the canonical, row-major ordering. |
| SparseReshape | Reshapes a SparseTensor to represent values in a new dense shape. |
| SparseSegmentMean <T extends TNumber > | Computes the mean along sparse segments of a tensor. |
| SparseSegmentMeanGrad <T extends TNumber > | Computes gradients for SparseSegmentMean. |
| SparseSegmentMeanWithNumSegments <T extends TNumber > | Computes the mean along sparse segments of a tensor. |
| SparseSegmentSqrtN <T extends TNumber > | Computes the sum along sparse segments of a tensor divided by the sqrt of N. |
| SparseSegmentSqrtNGrad <T extends TNumber > | Computes gradients for SparseSegmentSqrtN. |
| SparseSegmentSqrtNWithNumSegments <T extends TNumber > | Computes the sum along sparse segments of a tensor divided by the sqrt of N. |
| SparseSegmentSum <T extends TNumber > | Computes the sum along sparse segments of a tensor. |
| SparseSegmentSumWithNumSegments <T extends TNumber > | Computes the sum along sparse segments of a tensor. |
| SparseSlice <T extends TType > | Slice a `SparseTensor` based on the `start` and `size`. |
| SparseSliceGrad <T extends TType > | The gradient operator for the SparseSlice op. |
| SparseSoftmax <T extends TNumber > | Applies softmax to a batched ND `SparseTensor`. |
| SparseSoftmaxCrossEntropyWithLogits | |
| SparseSoftmaxCrossEntropyWithLogits <T extends TNumber > | Computes softmax cross entropy cost and gradients to backpropagate. |
| SparseSparseMaximum <T extends TNumber > | Returns the element-wise max of two SparseTensors. |
| SparseSparseMinimum <T extends TType > | Returns the element-wise min of two SparseTensors. |
| SparseSplit <T extends TType > | Split a `SparseTensor` into `num_split` tensors along one dimension. |
| SparseTensorDenseAdd <U extends TType > | Adds up a `SparseTensor` and a dense `Tensor`, producing a dense `Tensor`. |
| SparseTensorDenseMatMul <U extends TType > | Multiply SparseTensor (of rank 2) "A" by dense matrix "B". |
| SparseTensorDenseMatMul.Options | Optional attributes for SparseTensorDenseMatMul |
| SparseTensorSliceDataset | Creates a dataset that splits a SparseTensor into elements row-wise. |
| SparseTensorToCSRSparseMatrix | Converts a SparseTensor to a (possibly batched) CSRSparseMatrix. |
| SparseToDense <U extends TType > | Converts a sparse representation into a dense tensor. |
| SparseToDense.Options | Optional attributes for SparseToDense |
| SparseToSparseSetOperation <T extends TType > | Applies set operation along last dimension of 2 `SparseTensor` inputs. |
| SparseToSparseSetOperation.Options | Optional attributes for SparseToSparseSetOperation |
| SpecializedType | For identifying the underlying type of a variant. |
| Spence <T extends TNumber > | |
| Split <T extends TType > | Splits a tensor into `num_split` tensors along one dimension. |
| SplitV <T extends TType > | Splits a tensor into `num_split` tensors along one dimension. |
| SqlDataset | Creates a dataset that executes a SQL query and emits rows of the result set. |
| SqlDataset | Creates a dataset that executes a SQL query and emits rows of the result set. |
| Sqrt <T extends TType > | Computes square root of x element-wise. |
| SqrtGrad <T extends TType > | Computes the gradient for the sqrt of `x` wrt its input. |
| Sqrtm <T extends TType > | Computes the matrix square root of one or more square matrices: matmul(sqrtm(A), sqrtm(A)) = A The input matrix should be invertible. |
| Square <T extends TType > | Computes square of x element-wise. |
| SquaredDifference <T extends TType > | Returns conj(x - y)(x - y) element-wise. |
| SquaredHinge | Computes the squared hinge loss between labels and predictions. |
| SquaredHinge <T extends TNumber > | A metric that computes the squared hinge loss metric between labels and predictions. |
| Squeeze <T extends TType > | Removes dimensions of size 1 from the shape of a tensor. |
| Squeeze.Options | Optional attributes for Squeeze |
| Stack <T extends TType > | Packs a list of `N` rank-`R` tensors into one rank-`(R+1)` tensor. |
| Stack.Options | Optional attributes for Stack |
| StackFrameWithId | A stack frame with ID. |
| StackFrameWithId.Builder | A stack frame with ID. |
| StackFrameWithIdOrBuilder | |
| Palcoscenico | Stage values similar to a lightweight Enqueue. |
| Stage.Options | Optional attributes for Stage |
| StageClear | Op removes all elements in the underlying container. |
| StageClear.Options | Optional attributes for StageClear |
| StagePeek | Op peeks at the values at the specified index. |
| StagePeek.Options | Optional attributes for StagePeek |
| StageSize | Op returns the number of elements in the underlying container. |
| StageSize.Options | Optional attributes for StageSize |
| StatefulRandomBinomial <V extends TNumber > | |
| StatefulStandardNormal <U extends TType > | Outputs random values from a normal distribution. |
| StatefulTruncatedNormal <U extends TType > | Outputs random values from a truncated normal distribution. |
| StatefulUniform <U extends TType > | Outputs random values from a uniform distribution. |
| StatefulUniformFullInt <U extends TType > | Outputs random integers from a uniform distribution. |
| StatefulUniformInt <U extends TType > | Outputs random integers from a uniform distribution. |
| StatelessMultinomial <V extends TNumber > | Draws samples from a multinomial distribution. |
| StatelessParameterizedTruncatedNormal <V extends TNumber > | |
| StatelessRandomBinomial <W extends TNumber > | Outputs deterministic pseudorandom random numbers from a binomial distribution. |
| StatelessRandomGamma <V extends TNumber > | Outputs deterministic pseudorandom random numbers from a gamma distribution. |
| StatelessRandomGetKeyCounterAlg | Picks the best algorithm based on device, and scrambles seed into key and counter. |
| StatelessRandomNormal <V extends TNumber > | Outputs deterministic pseudorandom values from a normal distribution. |
| StatelessRandomNormalV2 <U extends TNumber > | Outputs deterministic pseudorandom values from a normal distribution. |
| StatelessRandomPoisson <W extends TNumber > | Outputs deterministic pseudorandom random numbers from a Poisson distribution. |
| StatelessRandomUniform <V extends TNumber > | Outputs deterministic pseudorandom random values from a uniform distribution. |
| StatelessRandomUniformFullInt <V extends TNumber > | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformFullIntV2 <U extends TNumber > | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformInt <V extends TNumber > | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformIntV2 <U extends TNumber > | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformV2 <U extends TNumber > | Outputs deterministic pseudorandom random values from a uniform distribution. |
| StatelessSampleDistortedBoundingBox <T extends TNumber > | Generate a randomly distorted bounding box for an image deterministically. |
| StatelessSampleDistortedBoundingBox.Options | Optional attributes for StatelessSampleDistortedBoundingBox |
| StatelessTruncatedNormal <V extends TNumber > | Outputs deterministic pseudorandom values from a truncated normal distribution. |
| StatelessTruncatedNormalV2 <U extends TNumber > | Outputs deterministic pseudorandom values from a truncated normal distribution. |
| StaticRegexFullMatch | Check if the input matches the regex pattern. |
| StaticRegexReplace | Replaces the match of pattern in input with rewrite. |
| StaticRegexReplace.Options | Optional attributes for StaticRegexReplace |
| StatsAggregatorHandle | Creates a statistics manager resource. |
| StatsAggregatorHandle | |
| StatsAggregatorHandle.Options | Optional attributes for StatsAggregatorHandle |
| StatsAggregatorHandle.Options | Optional attributes for StatsAggregatorHandle |
| StatsAggregatorSetSummaryWriter | Set a summary_writer_interface to record statistics using given stats_aggregator. |
| StatsAggregatorSummary | Produces a summary of any statistics recorded by the given statistics manager. |
| StatsAggregatorSummary | Produces a summary of any statistics recorded by the given statistics manager. |
| StdArrays | Utility class for working with NdArray instances mixed with standard Java arrays. |
| StepStats | Protobuf type tensorflow.StepStats |
| StepStats.Builder | Protobuf type tensorflow.StepStats |
| StepStatsOrBuilder | |
| StepStatsProtos | |
| StopGradient <T extends TType > | Stops gradient computation. |
| StridedSlice <T extends TType > | Return a strided slice from `input`. |
| StridedSlice.Options | Optional attributes for StridedSlice |
| StridedSliceAssign <T extends TType > | Assign `value` to the sliced l-value reference of `ref`. |
| StridedSliceAssign.Options | Optional attributes for StridedSliceAssign |
| StridedSliceGrad <U extends TType > | Returns the gradient of `StridedSlice`. |
| StridedSliceGrad.Options | Optional attributes for StridedSliceGrad |
| StridedSliceHelper | Helper endpoint methods for Python like indexing. |
| StringFormat | Formats a string template using a list of tensors. |
| StringFormat.Options | Optional attributes for StringFormat |
| StringLayout | Data layout that converts a String to/from a sequence of bytes applying a given charset. |
| StringLength | String lengths of `input`. |
| StringLength.Options | Optional attributes for StringLength |
| StringNGrams <T extends TNumber > | Creates ngrams from ragged string data. |
| StringSplit | Split elements of `source` based on `sep` into a `SparseTensor`. |
| StringSplit.Options | Optional attributes for StringSplit |
| Striscia | Strip leading and trailing whitespaces from the Tensor. |
| StructProtos | |
| StructuredValue | `StructuredValue` represents a dynamically typed value representing various data structures that are inspired by Python data structures typically used in TensorFlow functions as inputs and outputs. |
| StructuredValue.Builder | `StructuredValue` represents a dynamically typed value representing various data structures that are inspired by Python data structures typically used in TensorFlow functions as inputs and outputs. |
| StructuredValue.KindCase | |
| StructuredValueOrBuilder | |
| Sub <T extends TType > | Returns x - y element-wise. |
| Substr | Return substrings from `Tensor` of strings. |
| Substr.Options | Optional attributes for Substr |
| Sum <T extends TType > | Computes the sum of elements across dimensions of a tensor. |
| Sum.Options | Optional attributes for Sum |
| Riepilogo | A Summary is a set of named values to be displayed by the visualizer. |
| Summary.Audio | Protobuf type tensorflow.Summary.Audio |
| Summary.Audio.Builder | Protobuf type tensorflow.Summary.Audio |
| Summary.AudioOrBuilder | |
| Summary.Builder | A Summary is a set of named values to be displayed by the visualizer. |
| Summary.Image | Protobuf type tensorflow.Summary.Image |
| Summary.Image.Builder | Protobuf type tensorflow.Summary.Image |
| Summary.ImageOrBuilder | |
| Summary.Value | Protobuf type tensorflow.Summary.Value |
| Summary.Value.Builder | Protobuf type tensorflow.Summary.Value |
| Summary.Value.ValueCase | |
| Summary.ValueOrBuilder | |
| SummaryDescription | Metadata associated with a series of Summary dataProtobuf type tensorflow.SummaryDescription |
| SummaryDescription.Builder | Metadata associated with a series of Summary dataProtobuf type tensorflow.SummaryDescription |
| SummaryDescriptionOrBuilder | |
| SummaryMetadata | A SummaryMetadata encapsulates information on which plugins are able to make use of a certain summary value. |
| SummaryMetadata.Builder | A SummaryMetadata encapsulates information on which plugins are able to make use of a certain summary value. |
| SummaryMetadata.PluginData | Protobuf type tensorflow.SummaryMetadata.PluginData |
| SummaryMetadata.PluginData.Builder | Protobuf type tensorflow.SummaryMetadata.PluginData |
| SummaryMetadata.PluginDataOrBuilder | |
| SummaryMetadataOrBuilder | |
| SummaryOrBuilder | |
| SummaryProtos | |
| SummaryWriter | |
| SummaryWriter.Options | Optional attributes for SummaryWriter |
| Svd <T extends TType > | Computes the singular value decompositions of one or more matrices. |
| Svd <T extends TType > | Computes the eigen decomposition of a batch of self-adjoint matrices (Note: Only real inputs are supported). |
| Svd.Options | Optional attributes for Svd |
| Swish <T extends TFloating > | Swish activation function. |
| SwitchCond <T extends TType > | Forwards `data` to the output port determined by `pred`. |
T
| TaggedRunMetadata | For logging the metadata output for a single session.run() call. |
| TaggedRunMetadata.Builder | For logging the metadata output for a single session.run() call. |
| TaggedRunMetadataOrBuilder | |
| TakeDataset | |
| TakeDataset | Creates a dataset that contains `count` elements from the `input_dataset`. |
| TakeManySparseFromTensorsMap <T extends TType > | Read `SparseTensors` from a `SparseTensorsMap` and concatenate them. |
| TakeManySparseFromTensorsMap.Options | Optional attributes for TakeManySparseFromTensorsMap |
| Tan <T extends TType > | Computes tan of x element-wise. |
| Tanh <T extends TFloating > | Hyperbolic tangent activation function. |
| Tanh <T extends TType > | Computes hyperbolic tangent of `x` element-wise. |
| TanhGrad <T extends TType > | Computes the gradient for the tanh of `x` wrt its input. |
| TaskDeviceFilters | Defines the device filters for a remote task. |
| TaskDeviceFilters.Builder | Defines the device filters for a remote task. |
| TaskDeviceFiltersOrBuilder | |
| TBfloat16 | Brain 16-bit float tensor type. |
| TBfloat16Mapper | Maps memory of DT_BFLOAT16 tensors to a n-dimensional data space. |
| TBool | Boolean tensor type. |
| TBoolMapper | Maps memory of DT_BOOL tensors to a n-dimensional data space. |
| TemporaryVariable <T extends TType > | Returns a tensor that may be mutated, but only persists within a single step. |
| TemporaryVariable.Options | Optional attributes for TemporaryVariable |
| Tensore | A statically typed multi-dimensional array. |
| Tensore | |
| TensorArray | An array of Tensors of given size. |
| TensorArray.Options | Optional attributes for TensorArray |
| TensorArrayClose | Delete the TensorArray from its resource container. |
| TensorArrayConcat <T extends TType > | Concat the elements from the TensorArray into value `value`. |
| TensorArrayConcat.Options | Optional attributes for TensorArrayConcat |
| TensorArrayGather <T extends TType > | Gather specific elements from the TensorArray into output `value`. |
| TensorArrayGather.Options | Optional attributes for TensorArrayGather |
| TensorArrayGrad | Creates a TensorArray for storing the gradients of values in the given handle. |
| TensorArrayGradWithShape | Creates a TensorArray for storing multiple gradients of values in the given handle. |
| TensorArrayPack <T extends TType > | |
| TensorArrayPack.Options | Optional attributes for TensorArrayPack |
| TensorArrayRead <T extends TType > | Read an element from the TensorArray into output `value`. |
| TensorArrayScatter | Scatter the data from the input value into specific TensorArray elements. |
| TensorArraySize | Get the current size of the TensorArray. |
| TensorArraySplit | Split the data from the input value into TensorArray elements. |
| TensorArrayUnpack | |
| TensorArrayWrite | Push an element onto the tensor_array. |
| TensorBuffers | Maps native tensor memory into DataBuffers , allowing I/O operations from the JVM. |
| TensorBundleProtos | |
| TensorConnection | Defines a connection between two tensors in a `GraphDef`. |
| TensorConnection.Builder | Defines a connection between two tensors in a `GraphDef`. |
| TensorConnectionOrBuilder | |
| TensorDataset | Creates a dataset that emits `components` as a tuple of tensors once. |
| TensorDebugMode | Available modes for extracting debugging information from a Tensor. |
| TensorDescription | Protobuf type tensorflow.TensorDescription |
| TensorDescription.Builder | Protobuf type tensorflow.TensorDescription |
| TensorDescriptionOrBuilder | |
| TensorDescriptionProtos | |
| TensorDiag <T extends TType > | Returns a diagonal tensor with a given diagonal values. |
| TensorDiagPart <T extends TType > | Returns the diagonal part of the tensor. |
| TensorFlow | Static utility methods describing the TensorFlow runtime. |
| tensorflow | |
| tensorflow | |
| TensorFlowException | Unchecked exception thrown by TensorFlow core classes |
| TensorForestCreateTreeVariable | Creates a tree resource and returns a handle to it. |
| TensorForestTreeDeserialize | Deserializes a proto into the tree handle |
| TensorForestTreeIsInitializedOp | Checks whether a tree has been initialized. |
| TensorForestTreePredict | Output the logits for the given input data |
| TensorForestTreeResourceHandleOp | Creates a handle to a TensorForestTreeResource |
| TensorForestTreeResourceHandleOp.Options | Optional attributes for TensorForestTreeResourceHandleOp |
| TensorForestTreeSerialize | Serializes the tree handle to a proto |
| TensorForestTreeSize | Get the number of nodes in a tree |
| TensorInfo | Information about a Tensor necessary for feeding or retrieval. |
| TensorInfo.Builder | Information about a Tensor necessary for feeding or retrieval. |
| TensorInfo.CompositeTensor | Generic encoding for composite tensors. |
| TensorInfo.CompositeTensor.Builder | Generic encoding for composite tensors. |
| TensorInfo.CompositeTensorOrBuilder | |
| TensorInfo.CooSparse | For sparse tensors, The COO encoding stores a triple of values, indices, and shape. |
| TensorInfo.CooSparse.Builder | For sparse tensors, The COO encoding stores a triple of values, indices, and shape. |
| TensorInfo.CooSparseOrBuilder | |
| TensorInfo.EncodingCase | |
| TensorInfoOrBuilder | |
| TensorListConcat <U extends TType > | Concats all tensors in the list along the 0th dimension. |
| TensorListConcatLists | |
| TensorListElementShape <T extends TNumber > | The shape of the elements of the given list, as a tensor. |
| TensorListFromTensor | Creates a TensorList which, when stacked, has the value of `tensor`. |
| TensorListGather <T extends TType > | Creates a Tensor by indexing into the TensorList. |
| TensorListGetItem <T extends TType > | |
| TensorListLength | Returns the number of tensors in the input tensor list. |
| TensorListPopBack <T extends TType > | Returns the last element of the input list as well as a list with all but that element. |
| TensorListPushBack | Returns a list which has the passed-in `Tensor` as last element and the other elements of the given list in `input_handle`. |
| TensorListPushBackBatch | |
| TensorListReserve | List of the given size with empty elements. |
| TensorListResize | Resizes the list. |
| TensorListScatter | Creates a TensorList by indexing into a Tensor. |
| TensorListScatterIntoExistingList | Scatters tensor at indices in an input list. |
| TensorListSetItem | |
| TensorListSplit | Splits a tensor into a list. |
| TensorListStack <T extends TType > | Stacks all tensors in the list. |
| TensorListStack.Options | Optional attributes for TensorListStack |
| TensorMapErase | Returns a tensor map with item from given key erased. |
| TensorMapHasKey | Returns whether the given key exists in the map. |
| TensorMapInsert | Returns a map that is the 'input_handle' with the given key-value pair inserted. |
| TensorMapLookup <U extends TType > | Returns the value from a given key in a tensor map. |
| TensorMapper <T extends TType > | Maps the native memory of a RawTensor to a n-dimensional typed data space accessible from the JVM. |
| TensorMapSize | Returns the number of tensors in the input tensor map. |
| TensorMapStackKeys <T extends TType > | Returns a Tensor stack of all keys in a tensor map. |
| TensorMetadata | Metadata for a single tensor in the Snapshot Record. |
| TensorMetadata.Builder | Metadata for a single tensor in the Snapshot Record. |
| TensorMetadataOrBuilder | |
| TensorProto | Protocol buffer representing a tensor. |
| TensorProto.Builder | Protocol buffer representing a tensor. |
| TensorProtoOrBuilder | |
| TensorProtos | |
| TensorScatterNdAdd <T extends TType > | Adds sparse `updates` to an existing tensor according to `indices`. |
| TensorScatterNdMax <T extends TType > | |
| TensorScatterNdMin <T extends TType > | |
| TensorScatterNdSub <T extends TType > | Subtracts sparse `updates` from an existing tensor according to `indices`. |
| TensorScatterNdUpdate <T extends TType > | Scatter `updates` into an existing tensor according to `indices`. |
| TensorShapeProto | Dimensions of a tensor. |
| TensorShapeProto.Builder | Dimensions of a tensor. |
| TensorShapeProto.Dim | One dimension of the tensor. |
| TensorShapeProto.Dim.Builder | One dimension of the tensor. |
| TensorShapeProto.DimOrBuilder | |
| TensorShapeProtoOrBuilder | |
| TensorShapeProtos | |
| TensorSliceDataset | |
| TensorSliceDataset | Creates a dataset that emits each dim-0 slice of `components` once. |
| TensorSliceProto | Can only be interpreted if you know the corresponding TensorShape. |
| TensorSliceProto.Builder | Can only be interpreted if you know the corresponding TensorShape. |
| TensorSliceProto.Extent | Extent of the slice in one dimension. |
| TensorSliceProto.Extent.Builder | Extent of the slice in one dimension. |
| TensorSliceProto.Extent.HasLengthCase | |
| TensorSliceProto.ExtentOrBuilder | |
| TensorSliceProtoOrBuilder | |
| TensorSliceProtos | |
| TensorSpecProto | A protobuf to represent tf.TensorSpec. |
| TensorSpecProto.Builder | A protobuf to represent tf.TensorSpec. |
| TensorSpecProtoOrBuilder | |
| TensorStridedSliceUpdate <T extends TType > | Assign `value` to the sliced l-value reference of `input`. |
| TensorStridedSliceUpdate.Options | Optional attributes for TensorStridedSliceUpdate |
| TensorSummary | Outputs a `Summary` protocol buffer with a tensor and per-plugin data. |
| TensorType | Annotation for all tensor types. |
| TensorTypeInfo <T extends TType > | Registered information about a tensor type. |
| TensorTypeRegistry | Repository of all registered tensor types. |
| TestLogProtos | |
| TestResults | The output of one benchmark / test run. |
| TestResults.BenchmarkType | The type of benchmark. |
| TestResults.Builder | The output of one benchmark / test run. |
| TestResultsOrBuilder | |
| TextLineDataset | |
| TextLineDataset | Creates a dataset that emits the lines of one or more text files. |
| TextLineReader | A Reader that outputs the lines of a file delimited by '\n'. |
| TextLineReader.Options | Optional attributes for TextLineReader |
| TF_AllocatorAttributes | |
| TF_ApiDefMap | |
| TF_AttrMetadata | |
| TF_Buffer | |
| TF_Buffer.Data_deallocator_Pointer_long | |
| TF_DeprecatedSession | |
| TF_DeviceList | |
| TF_DimensionHandle | |
| TF_Function | |
| TF_FunctionOptions | |
| TF_Graph | |
| TF_ImportGraphDefOptions | |
| TF_ImportGraphDefResults | |
| TF_Input | |
| TF_KernelBuilder | |
| TF_Library | |
| TF_OpDefinitionBuilder | |
| TF_Operation | |
| TF_OperationDescription | |
| TF_OpKernelConstruction | |
| TF_OpKernelContext | |
| TF_Output | |
| TF_Server | |
| TF_Session | |
| TF_SessionOptions | |
| TF_ShapeHandle | |
| TF_ShapeInferenceContext | |
| TF_Status | |
| TF_StringView | |
| TF_Tensor | |
| TF_TString | |
| TF_TString_Large | |
| TF_TString_Offset | |
| TF_TString_Raw | |
| TF_TString_Small | |
| TF_TString_Union | |
| TF_TString_View | |
| TF_WhileParams | |
| TFE_Context | |
| TFE_ContextOptions | |
| TFE_Op | |
| TFE_TensorDebugInfo | |
| TFE_TensorHandle | |
| TFFailedPreconditionException | |
| TFInvalidArgumentException | |
| TFloat16 | IEEE-754 half-precision 16-bit float tensor type. |
| TFloat16Mapper | Maps memory of DT_HALF tensors to a n-dimensional data space. |
| TFloat32 | IEEE-754 single-precision 32-bit float tensor type. |
| TFloat32Mapper | Maps memory of DT_FLOAT tensors to a n-dimensional data space. |
| TFloat64 | IEEE-754 double-precision 64-bit float tensor type. |
| TFloat64Mapper | Maps memory of DT_DOUBLE tensors to a n-dimensional data space. |
| TFloating | Common interface for all floating point tensors. |
| TFOutOfRangeException | |
| TFPermissionDeniedException | |
| TfRecordDataset | Creates a dataset that emits the records from one or more TFRecord files. |
| TFRecordDataset | |
| TfRecordReader | A Reader that outputs the records from a TensorFlow Records file. |
| TfRecordReader.Options | Optional attributes for TfRecordReader |
| TFResourceExhaustedException | |
| TFUnauthenticatedException | |
| TFUnimplementedException | |
| ThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| ThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| ThreadPoolHandle | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| ThreadPoolHandle | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| ThreadPoolHandle.Options | Optional attributes for ThreadPoolHandle |
| ThreadPoolHandle.Options | Optional attributes for ThreadPoolHandle |
| ThreadPoolOptionProto | Protobuf type tensorflow.ThreadPoolOptionProto |
| ThreadPoolOptionProto.Builder | Protobuf type tensorflow.ThreadPoolOptionProto |
| ThreadPoolOptionProtoOrBuilder | |
| Tile <T extends TType > | Constructs a tensor by tiling a given tensor. |
| TileGrad <T extends TType > | Returns the gradient of `Tile`. |
| Timestamp | Provides the time since epoch in seconds. |
| TInt32 | 32-bit signed integer tensor type. |
| TInt32Mapper | Maps memory of DT_INT32 tensors to a n-dimensional data space. |
| TInt64 | 64-bit signed integer tensor type. |
| TInt64Mapper | Maps memory of DT_INT64 tensors to a n-dimensional data space. |
| TIntegral | Common interface for all integral numeric tensors. |
| TNumber | Common interface for all numeric tensors. |
| ToBool | Converts a tensor to a scalar predicate. |
| ToHashBucket | Converts each string in the input Tensor to its hash mod by a number of buckets. |
| ToHashBucketFast | Converts each string in the input Tensor to its hash mod by a number of buckets. |
| ToHashBucketStrong | Converts each string in the input Tensor to its hash mod by a number of buckets. |
| ToNumber <T extends TNumber > | Converts each string in the input Tensor to the specified numeric type. |
| TopK <T extends TNumber > | Finds values and indices of the `k` largest elements for the last dimension. |
| TopK.Options | Optional attributes for TopK |
| TopKUnique | Returns the TopK unique values in the array in sorted order. |
| TopKWithUnique | Returns the TopK values in the array in sorted order. |
| TPUCompilationResult | Returns the result of a TPU compilation. |
| TPUEmbeddingActivations | An op enabling differentiation of TPU Embeddings. |
| TPUReplicatedInput <T extends TType > | Connects N inputs to an N-way replicated TPU computation. |
| TPUReplicatedInput.Options | Optional attributes for TPUReplicatedInput |
| TPUReplicatedOutput <T extends TType > | Connects N outputs from an N-way replicated TPU computation. |
| TPUReplicateMetadata | Metadata indicating how the TPU computation should be replicated. |
| TPUReplicateMetadata.Options | Optional attributes for TPUReplicateMetadata |
| TrackableObjectGraph | Protobuf type tensorflow.TrackableObjectGraph |
| TrackableObjectGraph.Builder | Protobuf type tensorflow.TrackableObjectGraph |
| TrackableObjectGraph.TrackableObject | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject |
| TrackableObjectGraph.TrackableObject.Builder | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject |
| TrackableObjectGraph.TrackableObject.ObjectReference | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference |
| TrackableObjectGraph.TrackableObject.ObjectReference.Builder | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference |
| TrackableObjectGraph.TrackableObject.ObjectReferenceOrBuilder | |
| TrackableObjectGraph.TrackableObject.SerializedTensor | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.SerializedTensor |
| TrackableObjectGraph.TrackableObject.SerializedTensor.Builder | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.SerializedTensor |
| TrackableObjectGraph.TrackableObject.SerializedTensorOrBuilder | |
| TrackableObjectGraph.TrackableObject.SlotVariableReference | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference |
| TrackableObjectGraph.TrackableObject.SlotVariableReference.Builder | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference |
| TrackableObjectGraph.TrackableObject.SlotVariableReferenceOrBuilder | |
| TrackableObjectGraph.TrackableObjectOrBuilder | |
| TrackableObjectGraphOrBuilder | |
| TrackableObjectGraphProtos | |
| TransportOptions | |
| TransportOptions.RecvBufRespExtra | Extra data needed on a non-RDMA RecvBufResponse. |
| TransportOptions.RecvBufRespExtra.Builder | Extra data needed on a non-RDMA RecvBufResponse. |
| TransportOptions.RecvBufRespExtraOrBuilder | |
| Transpose <T extends TType > | Shuffle dimensions of x according to a permutation. |
| TriangularSolve <T extends TType > | Solves systems of linear equations with upper or lower triangular matrices by backsubstitution. |
| TriangularSolve.Options | Optional attributes for TriangularSolve |
| TridiagonalMatMul <T extends TType > | Calculate product with tridiagonal matrix. |
| TridiagonalSolve <T extends TType > | Solves tridiagonal systems of equations. |
| TridiagonalSolve.Options | Optional attributes for TridiagonalSolve |
| TruncateDiv <T extends TType > | Returns x / y element-wise for integer types. |
| TruncatedNormal <T extends TFloating > | Initializer that generates a truncated normal distribution. |
| TruncatedNormal <U extends TNumber > | Outputs random values from a truncated normal distribution. |
| TruncatedNormal.Options | Optional attributes for TruncatedNormal |
| TruncateMod <T extends TNumber > | Returns element-wise remainder of division. |
| TryRpc | Perform batches of RPC requests. |
| TryRpc.Options | Optional attributes for TryRpc |
| TString | String type. |
| TStringInitializer <T> | Helper class for initializing a TString tensor. |
| TStringMapper | Maps memory of DT_STRING tensors to a n-dimensional data space. |
| TType | Common interface for all typed tensors. |
| TUint8 | 8-bit unsigned integer tensor type. |
| TUint8Mapper | Maps memory of DT_UINT8 tensors to a n-dimensional data space. |
| TupleValue | Represents a Python tuple. |
| TupleValue.Builder | Represents a Python tuple. |
| TupleValueOrBuilder | |
| TypeSpecProto | Represents a tf.TypeSpecProtobuf type tensorflow.TypeSpecProto |
| TypeSpecProto.Builder | Represents a tf.TypeSpecProtobuf type tensorflow.TypeSpecProto |
| TypeSpecProto.TypeSpecClass | Protobuf enum tensorflow.TypeSpecProto.TypeSpecClass |
| TypeSpecProtoOrBuilder | |
| TypesProtos |
U
| Unbatch <T extends TType > | Reverses the operation of Batch for a single output Tensor. |
| Unbatch.Options | Optional attributes for Unbatch |
| UnbatchDataset | A dataset that splits the elements of its input into multiple elements. |
| UnbatchDataset | A dataset that splits the elements of its input into multiple elements. |
| UnbatchGrad <T extends TType > | Gradient of Unbatch. |
| UnbatchGrad.Options | Optional attributes for UnbatchGrad |
| UncompressElement | Uncompresses a compressed dataset element. |
| UnicodeDecode <T extends TNumber > | Decodes each string in `input` into a sequence of Unicode code points. |
| UnicodeDecode.Options | Optional attributes for UnicodeDecode |
| UnicodeDecodeWithOffsets <T extends TNumber > | Decodes each string in `input` into a sequence of Unicode code points. |
| UnicodeDecodeWithOffsets.Options | Optional attributes for UnicodeDecodeWithOffsets |
| UnicodeEncode | Encode a tensor of ints into unicode strings. |
| UnicodeEncode.Options | Optional attributes for UnicodeEncode |
| UnicodeScript | Determine the script codes of a given tensor of Unicode integer code points. |
| UnicodeTranscode | Transcode the input text from a source encoding to a destination encoding. |
| UnicodeTranscode.Options | Optional attributes for UnicodeTranscode |
| UniformCandidateSampler | Generates labels for candidate sampling with a uniform distribution. |
| UniformCandidateSampler.Options | Optional attributes for UniformCandidateSampler |
| Unique <T extends TType , V extends TNumber > | Trova elementi unici lungo un asse di un tensore. |
| UniqueDataset | Creates a dataset that contains the unique elements of `input_dataset`. |
| UniqueDataset | Creates a dataset that contains the unique elements of `input_dataset`. |
| UniqueWithCounts <T extends TType , V extends TNumber > | Trova elementi unici lungo un asse di un tensore. |
| UnitNorm | Constrains the weights to have unit norm. |
| UnravelIndex <T extends TNumber > | Converts an array of flat indices into a tuple of coordinate arrays. |
| UnsortedSegmentJoin | Joins the elements of `inputs` based on `segment_ids`. |
| UnsortedSegmentJoin.Options | Optional attributes for UnsortedSegmentJoin |
| UnsortedSegmentMax <T extends TNumber > | Computes the maximum along segments of a tensor. |
| UnsortedSegmentMin <T extends TNumber > | Computes the minimum along segments of a tensor. |
| UnsortedSegmentProd <T extends TType > | Computes the product along segments of a tensor. |
| UnsortedSegmentSum <T extends TType > | Computes the sum along segments of a tensor. |
| Unstack <T extends TType > | Unpacks a given dimension of a rank-`R` tensor into `num` rank-`(R-1)` tensors. |
| Unstack.Options | Optional attributes for Unstack |
| Unstage | Op is similar to a lightweight Dequeue. |
| Unstage.Options | Optional attributes for Unstage |
| UnwrapDatasetVariant | |
| Superiore | Converts all lowercase characters into their respective uppercase replacements. |
| Upper.Options | Optional attributes for Upper |
| UpperBound <U extends TNumber > | Applies upper_bound(sorted_search_values, values) along each row. |
V
| Validator | |
| Validator | |
| ValuesDef | Protocol buffer representing the values in ControlFlowContext. |
| ValuesDef.Builder | Protocol buffer representing the values in ControlFlowContext. |
| ValuesDefOrBuilder | |
| VarHandleOp | Creates a handle to a Variable resource. |
| VarHandleOp.Options | Optional attributes for VarHandleOp |
| Variable <T extends TType > | Holds state in the form of a tensor that persists across steps. |
| Variable.Options | Optional attributes for Variable |
| VariableAggregation | Indicates how a distributed variable will be aggregated. |
| VariableDef | Protocol buffer representing a Variable. |
| VariableDef.Builder | Protocol buffer representing a Variable. |
| VariableDefOrBuilder | |
| VariableProtos | |
| VariableShape <T extends TNumber > | Returns the shape of the variable pointed to by `resource`. |
| VariableSynchronization | Indicates when a distributed variable will be synced. |
| VarianceScaling <T extends TFloating > | Initializer capable of adapting its scale to the shape of weights tensors. |
| VarianceScaling.Distribution | The random distribution to use when initializing the values. |
| VarianceScaling.Mode | The mode to use for calculating the fan values. |
| VariantTensorDataProto | Protocol buffer representing the serialization format of DT_VARIANT tensors. |
| VariantTensorDataProto.Builder | Protocol buffer representing the serialization format of DT_VARIANT tensors. |
| VariantTensorDataProtoOrBuilder | |
| VarIsInitializedOp | Checks whether a resource handle-based variable has been initialized. |
| VarLenFeatureProto | Protobuf type tensorflow.VarLenFeatureProto |
| VarLenFeatureProto.Builder | Protobuf type tensorflow.VarLenFeatureProto |
| VarLenFeatureProtoOrBuilder | |
| VerifierConfig | The config for graph verifiers. |
| VerifierConfig.Builder | The config for graph verifiers. |
| VerifierConfig.Toggle | Protobuf enum tensorflow.VerifierConfig.Toggle |
| VerifierConfigOrBuilder | |
| VerifierConfigProtos | |
| VersionDef | Version information for a piece of serialized data There are different types of versions for each type of data (GraphDef, etc.), but they all have the same common shape described here. |
| VersionDef.Builder | Version information for a piece of serialized data There are different types of versions for each type of data (GraphDef, etc.), but they all have the same common shape described here. |
| VersionDefOrBuilder | |
| VersionsProtos |
W
| WatchdogConfig | Protobuf type tensorflow.WatchdogConfig |
| WatchdogConfig.Builder | Protobuf type tensorflow.WatchdogConfig |
| WatchdogConfigOrBuilder | |
| WeakPointerScope | A minimalist pointer scope only keeping weak references to its elements. |
| Dove | Returns locations of nonzero / true values in a tensor. |
| WhileContextDef | Protocol buffer representing a WhileContext object. |
| WhileContextDef.Builder | Protocol buffer representing a WhileContext object. |
| WhileContextDefOrBuilder | |
| WholeFileReader | A Reader that outputs the entire contents of a file as a value. |
| WholeFileReader.Options | Optional attributes for WholeFileReader |
| WindowDataset | Combines (nests of) input elements into a dataset of (nests of) windows. |
| WorkerHealth | Current health status of a worker. |
| WorkerHeartbeat | Worker heartbeat op. |
| WorkerHeartbeatRequest | Protobuf type tensorflow.WorkerHeartbeatRequest |
| WorkerHeartbeatRequest.Builder | Protobuf type tensorflow.WorkerHeartbeatRequest |
| WorkerHeartbeatRequestOrBuilder | |
| WorkerHeartbeatResponse | Protobuf type tensorflow.WorkerHeartbeatResponse |
| WorkerHeartbeatResponse.Builder | Protobuf type tensorflow.WorkerHeartbeatResponse |
| WorkerHeartbeatResponseOrBuilder | |
| WorkerShutdownMode | Indicates the behavior of the worker when an internal error or shutdown signal is received. |
| WrapDatasetVariant | |
| WriteAudioSummary | Writes an audio summary. |
| WriteAudioSummary.Options | Optional attributes for WriteAudioSummary |
| WriteFile | Writes contents to the file at input filename. |
| WriteGraphSummary | Writes a graph summary. |
| WriteHistogramSummary | Writes a histogram summary. |
| WriteImageSummary | Writes an image summary. |
| WriteImageSummary.Options | Optional attributes for WriteImageSummary |
| WriteRawProtoSummary | Writes a serialized proto summary. |
| WriteScalarSummary | Writes a scalar summary. |
| WriteSummary | Writes a tensor summary. |
X
| Xdivy <T extends TType > | Returns 0 if x == 0, and x / y otherwise, elementwise. |
| XEvent | An XEvent is a trace event, optionally annotated with XStats. |
| XEvent.Builder | An XEvent is a trace event, optionally annotated with XStats. |
| XEvent.DataCase | |
| XEventMetadata | Metadata for an XEvent, corresponds to an event type and is shared by all XEvents with the same metadata_id. |
| XEventMetadata.Builder | Metadata for an XEvent, corresponds to an event type and is shared by all XEvents with the same metadata_id. |
| XEventMetadataOrBuilder | |
| XEventOrBuilder | |
| XlaRecvFromHost <T extends TType > | An op to receive a tensor from the host. |
| XlaSendToHost | An op to send a tensor to the host. |
| XlaSetBound | Set a bound for the given input value as a hint to Xla compiler, returns the same value. |
| XlaSpmdFullToShardShape <T extends TType > | An op used by XLA SPMD partitioner to switch from automatic partitioning to manual partitioning. |
| XlaSpmdShardToFullShape <T extends TType > | An op used by XLA SPMD partitioner to switch from manual partitioning to automatic partitioning. |
| XLine | An XLine is a timeline of trace events (XEvents). |
| XLine.Builder | An XLine is a timeline of trace events (XEvents). |
| XLineOrBuilder | |
| Xlog1py <T extends TType > | Returns 0 if x == 0, and x * log1p(y) otherwise, elementwise. |
| Xlogy <T extends TType > | Returns 0 if x == 0, and x * log(y) otherwise, elementwise. |
| XPlane | An XPlane is a container of parallel timelines (XLines), generated by a profiling source or by post-processing one or more XPlanes. |
| XPlane.Builder | An XPlane is a container of parallel timelines (XLines), generated by a profiling source or by post-processing one or more XPlanes. |
| XPlaneOrBuilder | |
| XPlaneProtos | |
| XSpace | A container of parallel XPlanes, generated by one or more profiling sources. |
| XSpace.Builder | A container of parallel XPlanes, generated by one or more profiling sources. |
| XSpaceOrBuilder | |
| XStat | An XStat is a named value associated with an XEvent, e.g., a performance counter value, a metric computed by a formula applied over nested XEvents and XStats. |
| XStat.Builder | An XStat is a named value associated with an XEvent, e.g., a performance counter value, a metric computed by a formula applied over nested XEvents and XStats. |
| XStat.ValueCase | |
| XStatMetadata | Metadata for an XStat, corresponds to a stat type and is shared by all XStats with the same metadata_id. |
| XStatMetadata.Builder | Metadata for an XStat, corresponds to a stat type and is shared by all XStats with the same metadata_id. |
| XStatMetadataOrBuilder | |
| XStatOrBuilder |
Z
| Zeros <T extends TType > | Creates an Initializer that sets all values to zero. |
| Zeros <T extends TType > | An operator creating a constant initialized with zeros of the shape given by `dims`. |
| ZerosLike <T extends TType > | Returns a tensor of zeros with the same shape and type as x. |
| Zeta <T extends TNumber > | Compute the Hurwitz zeta function \\(\zeta(x, q)\\). |
| ZipDataset | Creates a dataset that zips together `input_datasets`. |