UN
Avorter | Déclenchez une exception pour abandonner le processus lorsqu'il est appelé. |
Abandonner.Options | Attributs facultatifs pour Abort |
Abs <T étend TNumber > | Calcule la valeur absolue d'un tenseur. |
AbstractDataBuffer <T> | |
AbstractDataBufferWindow <B étend DataBuffer <?>> | |
AbstractDenseNdArray <T, U étend NdArray <T>> | |
AbstractNdArray <T, U étend NdArray <T>> | |
RésuméTF_Buffer | |
RésuméTF_Graph | |
RésuméTF_ImportGraphDefOptions | |
RésuméTF_Session | |
RésuméTF_SessionOptions | |
RésuméTF_Status | |
RésuméTF_Tensor | |
RésuméTFE_Context | |
RésuméTFE_ContextOptions | |
RésuméTFE_Op | |
RésuméTFE_TensorHandle | |
AccumulateN <T étend TType > | Renvoie la somme par éléments d'une liste de tenseurs. |
AccumulateurApplyGradient | Applique un dégradé à un accumulateur donné. |
AccumulateurNumAccumulé | Renvoie le nombre de gradients agrégés dans les accumulateurs donnés. |
AccumulatorSetGlobalStep | Met à jour l'accumulateur avec une nouvelle valeur pour global_step. |
AccumulatorTakeGradient <T étend TType > | Extrait le gradient moyen dans le ConditionalAccumulator donné. |
Acos <T étend TType > | Calcule l'acos de x par élément. |
Acosh <T étend TType > | Calcule le cosinus hyperbolique inverse de x par élément. |
Activation <T étend TNumber > | Classe de base abstraite pour les activations Remarque : L'attribut |
AdaDelta | Optimiseur qui implémente l'algorithme Adadelta. |
AdaGrad | Optimiseur qui implémente l'algorithme d'Adagrad. |
AdaGradDA | Optimiseur qui implémente l'algorithme Adagrad Dual-Averaging. |
Adam | Optimiseur qui implémente l'algorithme d'Adam. |
Adamax | Optimiseur qui implémente l'algorithme Adamax. |
Ajouter <T étend TType > | Renvoie x + y par élément. |
AddManySparseToTensorsMap | Ajoutez un `N`-minibatch `SparseTensor` à un `SparseTensorsMap`, renvoyez les handles `N`. |
AddManySparseToTensorsMap.Options | Attributs facultatifs pour AddManySparseToTensorsMap |
AddN <T étend TType > | Ajoutez tous les tenseurs d'entrée par élément. |
AddSparseToTensorsMap | Ajoutez un `SparseTensor` à un `SparseTensorsMap` et renvoyez son handle. |
AddSparseToTensorsMap.Options | Attributs facultatifs pour AddSparseToTensorsMap |
AjusterContrast <T étend TNumber > | Ajustez le contraste d’une ou plusieurs images. |
AjusterHue <T étend TNumber > | Ajustez la teinte d’une ou plusieurs images. |
AjusterSaturation <T étend TNumber > | Ajustez la saturation d’une ou plusieurs images. |
Tous | Calcule le « et logique » des éléments sur les dimensions d'un tenseur. |
Toutes.Options | Attributs facultatifs pour All |
Tous les candidats | Génère des étiquettes pour l'échantillonnage des candidats avec une distribution d'unigramme apprise. |
AllCandidateSampler.Options | Attributs facultatifs pour AllCandidateSampler |
Description de l'allocation | tensorflow.AllocationDescription de type Protobuf.AllocationDescription |
AllocationDescription.Builder | tensorflow.AllocationDescription de type Protobuf.AllocationDescription |
AllocationDescriptionOuBuilder | |
AllocationDescriptionProtos | |
Enregistrement d'allocation | An allocation/de-allocation operation performed by the allocator. |
AllocationRecord.Builder | An allocation/de-allocation operation performed by the allocator. |
AllocationRecordOrBuilder | |
AllocateurMémoireUtilisée | tensorflow.AllocatorMemoryUsed de type Protobuf.AllocatorMemoryUsed |
AllocatorMemoryUsed.Builder | tensorflow.AllocatorMemoryUsed de type Protobuf.AllocatorMemoryUsed |
AllocatorMemoryUsedOrBuilder | |
AllReduce <T étend TNumber > | Réduit mutuellement plusieurs tenseurs de type et de forme identiques. |
AllReduce.Options | Attributs facultatifs pour AllReduce |
AllToAll <T étend TType > | Une opération pour échanger des données entre les répliques TPU. |
Angle <U étend TNombre > | Renvoie l'argument d'un nombre complexe. |
AnonymeItérateur | Un conteneur pour une ressource itérateur. |
AnonymeMemoryCache | |
AnonymousMultiDeviceIterator | Un conteneur pour une ressource itérateur multi-périphérique. |
Générateur de graines aléatoires anonymes | |
Générateur de graines anonyme | |
N'importe lequel | Calcule le « ou logique » des éléments sur les dimensions d'un tenseur. |
Any.Options | Attributs facultatifs pour 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 | tensorflow.ApiDef.Arg de type Protobuf |
ApiDef.Arg.Builder | tensorflow.ApiDef.Arg de type Protobuf |
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.Visibilité | Protobuf enum tensorflow.ApiDef.Visibility |
ApiDefOrBuilder | |
ApiDefProtos | |
APIDefs | tensorflow.ApiDefs de type Protobuf.ApiDefs |
ApiDefs.Builder | tensorflow.ApiDefs de type Protobuf.ApiDefs |
ApiDefsOrBuilder | |
ApplyAdadelta <T étend TType > | Mettez à jour '*var' selon le schéma adadelta. |
AppliquerAdadelta.Options | Attributs facultatifs pour ApplyAdadelta |
ApplyAdagrad <T étend TType > | Mettez à jour '*var' selon le schéma adagrad. |
AppliquerAdagrad.Options | Attributs facultatifs pour ApplyAdagrad |
ApplyAdagradDa <T étend TType > | Mettez à jour '*var' selon le schéma adagrad proximal. |
AppliquerAdagradDa.Options | Attributs facultatifs pour ApplyAdagradDa |
ApplyAdagradV2 <T étend TType > | Mettez à jour '*var' selon le schéma adagrad. |
AppliquerAdagradV2.Options | Attributs facultatifs pour ApplyAdagradV2 |
ApplyAdam <T étend TType > | Mettez à jour '*var' selon l'algorithme d'Adam. |
AppliquerAdam.Options | Attributs facultatifs pour ApplyAdam |
ApplyAdaMax <T étend TType > | Mettez à jour '*var' selon l'algorithme AdaMax. |
AppliquerAdaMax.Options | Attributs facultatifs pour ApplyAdaMax |
ApplyAddSign <T étend TType > | Mettez à jour '*var' selon la mise à jour AddSign. |
ApplyAddSign.Options | Attributs facultatifs pour ApplyAddSign |
ApplyCenteredRmsProp <T étend TType > | Mettez à jour '*var' selon l'algorithme RMSProp centré. |
ApplyCenteredRmsProp.Options | Attributs facultatifs pour ApplyCenteredRmsProp |
ApplyFtrl <T étend TType > | Mettez à jour '*var' selon le schéma Ftrl-proximal. |
AppliquerFtrl.Options | Attributs facultatifs pour ApplyFtrl |
ApplyGradientDescent <T étend TType > | Mettez à jour '*var' en soustrayant 'alpha' * 'delta'. |
ApplyGradientDescent.Options | Attributs facultatifs pour ApplyGradientDescent |
ApplyMomentum <T étend TType > | Mettez à jour '*var' selon le schéma momentum. |
AppliquerMomentum.Options | Attributs facultatifs pour ApplyMomentum |
ApplyPowerSign <T étend TType > | Mettez à jour '*var' selon la mise à jour AddSign. |
ApplyPowerSign.Options | Attributs facultatifs pour ApplyPowerSign |
ApplyProximalAdagrad <T étend TType > | Mettez à jour '*var' et '*accum' selon FOBOS avec le taux d'apprentissage d'Adagrad. |
AppliquerProximalAdagrad.Options | Attributs facultatifs pour ApplyProximalAdagrad |
ApplyProximalGradientDescent <T étend TType > | Mettez à jour '*var' en tant qu'algorithme FOBOS avec un taux d'apprentissage fixe. |
ApplyProximalGradientDescent.Options | Attributs facultatifs pour ApplyProximalGradientDescent |
ApplyRmsProp <T étend TType > | Mettez à jour '*var' selon l'algorithme RMSProp. |
AppliquerRmsProp.Options | Attributs facultatifs pour ApplyRmsProp |
Égal approximatif | Renvoie la valeur de vérité de abs(xy) < tolérance par élément. |
ApproximateEqual.Options | Attributs facultatifs pour ApproximateEqual |
ArgMax <V étend TNumber > | Renvoie l'index avec la plus grande valeur sur toutes les dimensions d'un tenseur. |
ArgMin <V étend TNumber > | Renvoie l'index avec la plus petite valeur sur les dimensions d'un tenseur. |
Asin <T étend TType > | Calcule le sinus inverse trignométrique de x par élément. |
Asinh <T étend TType > | Calcule le sinus hyperbolique inverse de x par élément. |
AssertCardinalityDataset | |
AssertNextDataset | Une transformation qui affirme quelles transformations se produiront ensuite. |
AssertNextDataset | |
Affirmer que | Affirme que la condition donnée est vraie. |
AssertThat.Options | Attributs facultatifs pour 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 | |
Attribuer <T étend TType > | Mettez à jour « ref » en lui attribuant une « valeur ». |
Attribuer.Options | Attributs facultatifs pour Assign |
AssignAdd <T étend TType > | Mettez à jour 'ref' en y ajoutant 'value'. |
AssignAdd.Options | Attributs facultatifs pour AssignAdd |
AssignAddVariableOp | Ajoute une valeur à la valeur actuelle d'une variable. |
AssignSub <T étend TType > | Mettez à jour « ref » en soustrayant « valeur ». |
AssignSub.Options | Attributs facultatifs pour AssignSub |
AssignSubVariableOp | Soustrait une valeur de la valeur actuelle d'une variable. |
AssignVariableOp | Attribue une nouvelle valeur à une variable. |
CommeChaîne | Convertit chaque entrée du tenseur donné en chaînes. |
AsString.Options | Attributs facultatifs pour AsString |
Atan <T étend TType > | Calcule la tangente inverse trignométrique de x par élément. |
Atan2 <T étend TNumber > | Calcule l'arctangente de `y/x` par élément, en respectant les signes des arguments. |
Atanh <T étend TType > | Calcule la tangente hyperbolique inverse de x par élément. |
Valeur d'attribut | 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.IfChange tensorflow.AttrValue.ListValue de type Protobuf |
AttrValue.ListValue.Builder | LINT.IfChange tensorflow.AttrValue.ListValue de type Protobuf |
AttrValue.ListValueOrBuilder | |
AttrValue.ValueCase | |
AttrValueOrBuilder | |
AttrValueProtos | |
AudioSpectrogramme | Produit une visualisation des données audio au fil du temps. |
AudioSpectrogram.Options | Attributs facultatifs pour AudioSpectrogram |
Résumé audio | Produit un tampon de protocole « Résumé » avec audio. |
RésuméAudio.Options | Attributs facultatifs pour AudioSummary |
OptionsParallèleAuto | tensorflow.AutoParallelOptions de type Protobuf.AutoParallelOptions |
AutoParallelOptions.Builder | tensorflow.AutoParallelOptions de type Protobuf.AutoParallelOptions |
AutoParallelOptionsOrBuilder | |
Ensemble de données AutoShard | Crée un ensemble de données qui fragmente l'ensemble de données d'entrée. |
Ensemble de données AutoShard | Crée un ensemble de données qui fragmente l'ensemble de données d'entrée. |
AutoShardDataset.Options | Attributs facultatifs pour AutoShardDataset |
AutoShardDataset.Options | Attributs facultatifs pour AutoShardDataset |
Informations sur le périphérique disponible | Matches DeviceAttributes tensorflow.AvailableDeviceInfo de type Protobuf.AvailableDeviceInfo |
AvailableDeviceInfo.Builder | Matches DeviceAttributes tensorflow.AvailableDeviceInfo de type Protobuf.AvailableDeviceInfo |
AvailableDeviceInfoOrBuilder | |
AvgPool <T étend TNumber > | Effectue un pooling moyen sur l’entrée. |
AvgPool.Options | Attributs facultatifs pour AvgPool |
AvgPool3d <T étend TNumber > | Effectue un pooling moyen 3D sur l’entrée. |
AvgPool3d.Options | Attributs facultatifs pour AvgPool3d |
AvgPool3dGrad <T étend TNumber > | Calcule les gradients de la fonction de pooling moyenne. |
AvgPool3dGrad.Options | Attributs facultatifs pour AvgPool3dGrad |
AvgPoolGrad <T étend TNumber > | Calcule les gradients de la fonction de pooling moyenne. |
AvgPoolGrad.Options | Attributs facultatifs pour AvgPoolGrad |
B
BandedTriangularSolve <T étend TType > | |
BandedTriangularSolve.Options | Attributs facultatifs pour BandedTriangularSolve |
BandPart <T étend TType > | Copiez un tenseur mettant à zéro tout ce qui se trouve en dehors d'une bande centrale dans chaque matrice la plus interne. |
Barrière | Définit une barrière qui persiste dans différentes exécutions de graphiques. |
Barrière.Options | Attributs facultatifs pour Barrier |
BarrièreFermer | Ferme la barrière donnée. |
BarrièreFerme.Options | Attributs facultatifs pour BarrierClose |
BarrièreIncompleteSize | Calcule le nombre d'éléments incomplets dans la barrière donnée. |
BarrièreInsérerBeaucoup | Pour chaque clé, attribue la valeur respective au composant spécifié. |
TailleBarrièrePrêt | Calcule le nombre d'éléments complets dans la barrière donnée. |
BarrièrePrendreBeaucoup | Prend le nombre donné d'éléments terminés d'une barrière. |
BarrièreTakeMany.Options | Attributs facultatifs pour BarrierTakeMany |
BaseInitializer <T étend TType > | Classe de base abstraite pour tous les initialiseurs |
Lot | Regroupe tous les tenseurs d'entrée de manière non déterministe. |
Batch.Options | Attributs facultatifs pour Batch |
BatchCholesky <T étend TNumber > | |
BatchCholeskyGrad <T étend TNumber > | |
Ensemble de données par lots | |
Ensemble de données par lots | Crée un ensemble de données qui regroupe les éléments `batch_size` à partir de `input_dataset`. |
BatchDataset.Options | Attributs facultatifs pour BatchDataset |
BatchFft | |
LotFft2d | |
LotFft3d | |
BatchIfft | |
BatchIfft2d | |
BatchIfft3d | |
BatchMatMul <T étend TType > | Multiplie les tranches de deux tenseurs par lots. |
BatchMatMul.Options | Attributs facultatifs pour BatchMatMul |
BatchMatrixBandPart <T étend TType > | |
BatchMatrixDeterminant <T étend TType > | |
BatchMatrixDiag <T étend TType > | |
BatchMatrixDiagPart <T étend TType > | |
BatchMatrixInverse <T étend TNumber > | |
BatchMatrixInverse.Options | Attributs facultatifs pour BatchMatrixInverse |
BatchMatrixSetDiag <T étend TType > | |
BatchMatrixSolve <T étend TNumber > | |
BatchMatrixSolve.Options | Attributs facultatifs pour BatchMatrixSolve |
BatchMatrixSolveLs <T étend TNumber > | |
BatchMatrixSolveLs.Options | Attributs facultatifs pour BatchMatrixSolveLs |
BatchMatrixTriangularSolve <T étend TNumber > | |
BatchMatrixTriangularSolve.Options | Attributs facultatifs pour BatchMatrixTriangularSolve |
BatchNormWithGlobalNormalization <T étend TType > | Normalisation des lots. |
BatchNormWithGlobalNormalizationGrad <T étend TType > | Dégradés pour la normalisation par lots. |
BatchSelfAdjointEig <T étend TNumber > | |
BatchSelfAdjointEig.Options | Attributs facultatifs pour BatchSelfAdjointEig |
BatchSvd <T étend TType > | |
BatchSvd.Options | Attributs facultatifs pour BatchSvd |
BatchToSpace <T étend TType > | BatchToSpace pour les tenseurs 4-D de type T. |
BatchToSpaceNd <T étend TType > | BatchToSpace pour les tenseurs ND de type T. |
Entrées de référence | tensorflow.BenchmarkEntries de type Protobuf.BenchmarkEntries |
BenchmarkEntries.Builder | tensorflow.BenchmarkEntries de type Protobuf.BenchmarkEntries |
BenchmarkEntriesOrBuilder | |
Entrée de référence | 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 étend TNumber > | |
BesselI0e <T étend TNumber > | |
BesselI1 <T étend TNumber > | |
BesselI1e <T étend TNumber > | |
BesselJ0 <T étend TNumber > | |
BesselJ1 <T étend TNumber > | |
BesselK0 <T étend TNumber > | |
BesselK0e <T étend TNumber > | |
BesselK1 <T étend TNumber > | |
BesselK1e <T étend TNumber > | |
BesselY0 <T étend TNumber > | |
BesselY1 <T étend TNumber > | |
Betainc <T étend TNumber > | Calculer l’intégrale bêta incomplète régularisée \\(I_x(a, b)\\). |
BfcMemoryMapProtos | |
Bfloat16Mise en page | Disposition des données qui convertit les flottants 32 bits de/vers 16 bits, tronquant leur mantisse à 7 bits mais préservant l'exposant 8 bits avec le même biais. |
BiasAdd <T étend TType > | Ajoute un « biais » à une « valeur ». |
BiasAdd.Options | Attributs facultatifs pour BiasAdd |
BiasAddGrad <T étend TType > | L'opération inverse pour "BiasAdd" sur le tenseur "bias". |
BiasAddGrad.Options | Attributs facultatifs pour BiasAddGrad |
BinaireCrossentropie | Calcule la perte d'entropie croisée entre les étiquettes réelles et les étiquettes prédites. |
BinaryCrossentropy <T étend TNumber > | Une métrique qui calcule la perte d'entropie croisée binaire entre les étiquettes réelles et les étiquettes prédites. |
Bincount <T étend TNumber > | Compte le nombre d'occurrences de chaque valeur dans un tableau d'entiers. |
BinRésumé | tensorflow.BinSummary de type Protobuf.BinSummary |
BinSummary.Builder | tensorflow.BinSummary de type Protobuf.BinSummary |
BinRésuméOuBuilder | |
Bitcast <U étend TType > | Bitcaste un tenseur d'un type à un autre sans copier les données. |
BitwiseAnd <T étend TNumber > | Elementwise calcule le ET au niveau du bit de « x » et « y ». |
BitwiseOr <T étend TNumber > | Elementwise calcule le OU au niveau du bit de « x » et « y ». |
BitwiseXor <T étend TNumber > | Elementwise calcule le XOR au niveau du bit de « x » et « y ». |
BlockLSTM <T étend TNumber > | Calcule la propagation des cellules LSTM pour tous les pas de temps. |
BlockLSTM.Options | Attributs facultatifs pour BlockLSTM |
BlockLSTMGrad <T étend TNumber > | Calcule la propagation vers l'arrière de la cellule LSTM pour toute la séquence temporelle. |
BooleanDataBuffer | Un DataBuffer de booléens. |
BooleanDataLayout <S étend DataBuffer <?>> | Un DataLayout qui convertit les données stockées dans un tampon en booléens. |
BooléenDenseNdArray | |
Masque booléen | |
BooleanMask.Options | Attributs facultatifs pour BooleanMask |
BooleanMaskUpdate | |
BooleanMaskUpdate.Options | Attributs facultatifs pour BooleanMaskUpdate |
BooléenNdArray | Un NdArray de booléens. |
BoolLayout | Disposition des données qui convertit les booléens de/en octets. |
BoostedTreesAggregateStats | Agrége le résumé des statistiques accumulées pour le lot. |
BoostedTreesBucketiser | Répartir chaque fonctionnalité en compartiments en fonction des limites du compartiment. |
BoostedTreesCalculateBestFeatureSplit | Calcule les gains pour chaque fonctionnalité et renvoie les meilleures informations de répartition possibles pour la fonctionnalité. |
BoostedTreesCalculateBestFeatureSplit.Options | Attributs facultatifs pour BoostedTreesCalculateBestFeatureSplit |
BoostedTreesCalculateBestFeatureSplitV2 | Calcule les gains pour chaque fonctionnalité et renvoie les meilleures informations de répartition possibles pour chaque nœud. |
Arbres boostésCalculer les meilleurs gains par fonctionnalité | Calcule les gains pour chaque fonctionnalité et renvoie les meilleures informations de répartition possibles pour la fonctionnalité. |
BoostedTreesCenterBias | Calcule le prior à partir des données d'entraînement (le biais) et remplit le premier nœud avec le prior des logits. |
BoostedTreesCreateEnsemble | Crée un modèle d'ensemble d'arbres et lui renvoie un handle. |
BoostedTreesCreateQuantileStreamResource | Créez la ressource pour les flux quantiles. |
BoostedTreesCreateQuantileStreamResource.Options | Attributs facultatifs pour BoostedTreesCreateQuantileStreamResource |
BoostedTreesDeserializeEnsemble | Désérialise une configuration d'ensemble d'arbres sérialisés et remplace l'arborescence actuelle ensemble. |
BoostedTreesEnsembleResourceHandleOp | Crée un handle vers un BoostedTreesEnsembleResource |
BoostedTreesEnsembleResourceHandleOp.Options | Attributs facultatifs pour BoostedTreesEnsembleResourceHandleOp |
BoostedTreesExampleDebugOutputs | Sorties de débogage/interprétabilité du modèle pour chaque exemple. |
BoostedTreesFlushQuantileRésumés | Videz les résumés de quantile de chaque ressource de flux de quantile. |
BoostedTreesGetEnsembleStates | Récupère le jeton de tampon de ressource de l’ensemble d’arbres, le nombre d’arbres et les statistiques de croissance. |
BoostedTreesMakeQuantileSummaries | Fait le résumé des quantiles pour le lot. |
BoostedTreesMakeStatsRésumé | Fait le résumé des statistiques accumulées pour le lot. |
BoostedTreesPredict | Exécute plusieurs prédicteurs d'ensemble de régression additive sur les instances d'entrée et calcule les logits. |
BoostedTreesQuantileStreamResourceAddSummaries | Ajoutez les résumés de quantile à chaque ressource de flux quantile. |
BoostedTreesQuantileStreamResourceDeserialize | Désérialisez les limites du bucket et signalez-le dans le QuantileAccumulator actuel. |
BoostedTreesQuantileStreamResourceFlush | Videz les résumés d’une ressource de flux quantile. |
BoostedTreesQuantileStreamResourceFlush.Options | Attributs facultatifs pour BoostedTreesQuantileStreamResourceFlush |
BoostedTreesQuantileStreamResourceGetBucketBoundaries | Générez les limites du compartiment pour chaque fonctionnalité en fonction des résumés accumulés. |
BoostedTreesQuantileStreamResourceHandleOp | Crée un handle vers un BoostedTreesQuantileStreamResource. |
BoostedTreesQuantileStreamResourceHandleOp.Options | Attributs facultatifs pour BoostedTreesQuantileStreamResourceHandleOp |
BoostedTreesSerializeEnsemble | Sérialise l'ensemble d'arbres en un proto. |
BoostedTreesSparseAggregateStats | Agrége le résumé des statistiques accumulées pour le lot. |
BoostedTreesSparseCalculateBestFeatureSplit | Calcule les gains pour chaque fonctionnalité et renvoie les meilleures informations de répartition possibles pour la fonctionnalité. |
BoostedTreesSparseCalculateBestFeatureSplit.Options | Attributs facultatifs pour BoostedTreesSparseCalculateBestFeatureSplit |
BoostedTreesTrainingPredict | Exécute plusieurs prédicteurs d'ensemble de régression additive sur les instances d'entrée et calcule la mise à jour des logits mis en cache. |
BoostedTreesUpdateEnsemble | Met à jour l'ensemble d'arbres en ajoutant une couche au dernier arbre en croissance ou en démarrant un nouvel arbre. |
BoostedTreesUpdateEnsembleV2 | Met à jour l'ensemble d'arbres en ajoutant une couche au dernier arbre en croissance ou en démarrant un nouvel arbre. |
BoostedTreesUpdateEnsembleV2.Options | Attributs facultatifs pour BoostedTreesUpdateEnsembleV2 |
BoundedTensorSpecProto | A protobuf to represent tf.BoundedTensorSpec. |
BoundedTensorSpecProto.Builder | A protobuf to represent tf.BoundedTensorSpec. |
BoundedTensorSpecProtoOrBuilder | |
BroadcastDynamicShape <T étend TNumber > | Renvoie la forme de s0 op s1 avec diffusion. |
BroadcastGradientArgs <T étend TNumber > | Renvoie les indices de réduction pour le calcul des gradients de s0 op s1 avec diffusion. |
BroadcastHelper <T étend TType > | Opérateur assistant pour effectuer des diffusions de style XLA Diffuse `lhs` et `rhs` au même rang, en ajoutant des dimensions de taille 1 à celui de `lhs` et `rhs` ayant le rang inférieur, en utilisant les règles de diffusion de XLA pour les opérateurs binaires. |
BroadcastRecv <T étend TType > | Reçoit une valeur tensorielle diffusée depuis un autre appareil. |
BroadcastRecv.Options | Attributs facultatifs pour BroadcastRecv |
BroadcastSend <T étend TType > | Diffuse une valeur tensorielle à un ou plusieurs autres appareils. |
BroadcastSend.Options | Attributs facultatifs pour BroadcastSend |
BroadcastTo <T étend TType > | Diffusez un tableau pour une forme compatible. |
Bucketiser | Bucketise les « entrées » en fonction des « limites ». |
ConstruireConfiguration | tensorflow.BuildConfiguration de type Protobuf.BuildConfiguration |
BuildConfiguration.Builder | tensorflow.BuildConfiguration de type Protobuf.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 | |
OctetDataBuffer | Un DataBuffer d'octets. |
ByteDataLayout <S étend DataBuffer <?>> | Un DataLayout qui convertit les données stockées dans un tampon en octets. |
OctetDenseNdArray | |
OctetNdArray | Un NdArray d'octets. |
OctetSequenceProvider <T> | Produit une séquence d'octets à stocker dans un ByteSequenceTensorBuffer . |
ByteSequenceTensorBuffer | Tampon pour stocker les données du tenseur de chaîne. |
Liste d'octets | Containers to hold repeated fundamental values. |
BytesList.Builder | Containers to hold repeated fundamental values. |
BytesListOrBuilder | |
BytesProducedStatsDataset | Enregistre la taille en octets de chaque élément de `input_dataset` dans un StatsAggregator. |
BytesProducedStatsDataset | Enregistre la taille en octets de chaque élément de `input_dataset` dans un StatsAggregator. |
C
CacheDataset | Crée un ensemble de données qui met en cache les éléments de « input_dataset ». |
CacheDatasetV2 | |
Optionsappelables | 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 étend TType > | Convertissez x de type SrcT en y de DstT. |
Cast.Options | Attributs facultatifs pour Cast |
Aide à la diffusion | Une classe d'assistance pour lancer un opérande |
CatégoriqueCrossentropie | Calcule la perte d'entropie croisée entre les étiquettes et les prédictions. |
CategoricalCrossentropy <T étend TNumber > | Une métrique qui calcule la perte d'entropie croisée catégorielle entre les étiquettes réelles et les étiquettes prédites. |
Charnière catégorique | Calcule la perte de charnière catégorielle entre les étiquettes et les prédictions. |
CategoricalHinge <T étend TNumber > | Une métrique qui calcule la métrique de perte de charnière catégorielle entre les étiquettes et les prédictions. |
Ceil <T étend TNumber > | Renvoie le plus petit entier élément par élément non inférieur à x. |
CheckNumerics <T étend TNumber > | Vérifie un tenseur pour les valeurs NaN, -Inf et +Inf. |
Cholesky <T étend TType > | Calcule la décomposition de Cholesky d'une ou plusieurs matrices carrées. |
CholeskyGrad <T étend TNumber > | Calcule le gradient rétropropagé en mode inverse de l'algorithme de Cholesky. |
ChoisirFastestDataset | |
ChoisirFastestDataset | |
ClipByValue <T étend TType > | Coupe les valeurs du tenseur à un min et un max spécifiés. |
FermerRédacteur de résumé | |
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 étend TType > | Opérateur qui connecte la sortie d'un calcul XLA à d'autres nœuds de graphe consommateur. |
ClusterProtos | |
Code | The canonical error codes for TensorFlow APIs. |
CodeEmplacement | Code location information: A stack trace with host-name information. |
CodeLocation.Builder | Code location information: A stack trace with host-name information. |
CodeEmplacementOuBuilder | |
CollectionDef | 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 | |
CollectionDef.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 | |
CollectionDef.KindCase | |
CollectionDef.NodeList | NodeList is used for collecting nodes in graph. |
CollectionDef.NodeList.Builder | NodeList is used for collecting nodes in graph. |
CollectionDef.NodeListOrBuilder | |
CollectionDefOrBuilder | |
CollectiveGather <T étend TNumber > | Accumule mutuellement plusieurs tenseurs de type et de forme identiques. |
CollectiveGather.Options | Attributs facultatifs pour CollectiveGather |
CollectivePermute <T étend TType > | Une opération pour permuter les tenseurs sur les instances TPU répliquées. |
CombinedNonMaxSuppression | Sélectionne goulûment un sous-ensemble de boîtes englobantes par ordre décroissant de score, Cette opération effectue non_max_suppression sur les entrées par lot, dans toutes les classes. |
CombinedNonMaxSuppression.Options | Attributs facultatifs pour CombinedNonMaxSuppression |
ID de validation | tensorflow.CommitId de type Protobuf.CommitId |
CommitId.Builder | tensorflow.CommitId de type Protobuf.CommitId |
CommitId.KindCase | |
CommitIdOrBuilder | |
ComparerEtBitpack | Comparez les valeurs de « input » à « threshold » et regroupez les bits résultants dans un « uint8 ». |
Résultat de la compilation | Renvoie le résultat d'une compilation TPU. |
CompileSucceededAssert | Affirme que la compilation a réussi. |
Complexe <U étend TType > | Convertit deux nombres réels en un nombre complexe. |
ComplexAbs <U étend TNumber > | Calcule la valeur absolue complexe d'un tenseur. |
CompressElement | Compresse un élément d'ensemble de données. |
Compute_func_Pointer_TF_OpKernelContext | |
CalculerAccès Accidentels | Calcule les identifiants des postes dans sampled_candidates qui correspondent à true_labels. |
ComputeAccidentalHits.Options | Attributs facultatifs pour ComputeAccidentalHits |
Taille du lot de calcul | Calcule la taille de lot statique d'un ensemble de données sans lots partiels. |
Concat <T étend TType > | Concatène les tenseurs selon une dimension. |
Concaténer un ensemble de données | Crée un ensemble de données qui concatène « input_dataset » avec « another_dataset ». |
Fonction Béton | Un graphique qui peut être invoqué comme une fonction unique, avec une signature d'entrée et de sortie. |
CondContextDef | Protocol buffer representing a CondContext object. |
CondContextDef.Builder | Protocol buffer representing a CondContext object. |
CondContextDefOrBuilder | |
Accumulateur conditionnel | Un accumulateur conditionnel pour agréger les gradients. |
ConditionalAccumulator.Options | Attributs facultatifs pour ConditionalAccumulator |
ConfigProto | Session configuration parameters. |
ConfigProto.Builder | Session configuration parameters. |
ConfigProto.Expérimental | 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 | |
ConfigurerDistributedTPU | Configure les structures centralisées pour un système TPU distribué. |
ConfigurerDistributedTPU.Options | Attributs facultatifs pour ConfigureDistributedTPU |
ConfigurerTPUEmbedding | Configure TPUEmbedding dans un système TPU distribué. |
Conj <T étend TType > | Renvoie le conjugué complexe d'un nombre complexe. |
ConjugateTranspose <T étend TType > | Mélangez les dimensions de x selon une permutation et conjuguez le résultat. |
Constante <T étend TType > | Initialiseur qui génère des tenseurs avec une valeur constante. |
Constante <T étend TType > | Un opérateur produisant une valeur constante. |
Contrainte | Classe de base pour les contraintes. |
ConsommerMutexLock | Cette opération consomme un verrou créé par `MutexLock`. |
ControlFlowContextDef | Container for any kind of control flow context. |
ControlFlowContextDef.Builder | Container for any kind of control flow context. |
ControlFlowContextDef.CtxtCase | |
ControlFlowContextDefOrBuilder | |
ContrôleFlowProtos | |
Déclencheur de contrôle | Ne fait rien. |
Conv <T étend TType > | Encapsule l'opérateur XLA ConvGeneralDilated, documenté dans https://www.tensorflow.org/performance/xla/operation_semantics#conv_convolution . |
Conv2d <T étend TNumber > | Calcule une convolution 2D à partir des tenseurs 4-D « entrée » et « filtre ». |
Conv2d.Options | Attributs facultatifs pour Conv2d |
Conv2dBackpropFilter <T étend TNumber > | Calcule les gradients de convolution par rapport au filtre. |
Conv2dBackpropFilter.Options | Attributs facultatifs pour Conv2dBackpropFilter |
Conv2dBackpropInput <T étend TNumber > | Calcule les gradients de convolution par rapport à l'entrée. |
Conv2dBackpropInput.Options | Attributs facultatifs pour Conv2dBackpropInput |
Conv3d <T étend TNumber > | Calcule une convolution 3D à partir des tenseurs « entrée » et « filtre » 5-D. |
Conv3d.Options | Attributs facultatifs pour Conv3d |
Conv3dBackpropFilter <T étend TNumber > | Calcule les gradients de convolution 3D par rapport au filtre. |
Conv3dBackpropFilter.Options | Attributs facultatifs pour Conv3dBackpropFilter |
Conv3dBackpropInput <U étend TNumber > | Calcule les gradients de convolution 3D par rapport à l'entrée. |
Conv3dBackpropInput.Options | Attributs facultatifs pour Conv3dBackpropInput |
Copier <T étend TType > | Copiez un tenseur de CPU à CPU ou de GPU à GPU. |
Copier.Options | Attributs facultatifs pour Copy |
CopyHost <T étend TType > | Copiez un tenseur sur l'hôte. |
CopierHost.Options | Attributs facultatifs pour CopyHost |
Cos <T étend TType > | Calcule le cos de x par élément. |
Cosh <T étend TType > | Calcule le cosinus hyperbolique de x par élément. |
CosinusSimilarité | Calcule la similarité cosinusoïdale entre les étiquettes et les prédictions. |
CosineSimilarity <T étend TNumber > | Métrique qui calcule la métrique de similarité cosinus entre les étiquettes et les prédictions. |
CoûtGraphDef | tensorflow.CostGraphDef de type Protobuf.CostGraphDef |
CostGraphDef.AggregatedCost | 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 | tensorflow.CostGraphDef de type Protobuf.CostGraphDef |
CostGraphDef.Node | tensorflow.CostGraphDef.Node de type Protobuf.CostGraphDef.Node |
CostGraphDef.Node.Builder | tensorflow.CostGraphDef.Node de type Protobuf.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 | |
CoûtGraphProtos | |
CountUpTo <T étend TNumber > | Incrémente « ref » jusqu'à ce qu'il atteigne « limite ». |
Informations CPU | tensorflow.CPUInfo de type Protobuf.CPUInfo |
CPUInfo.Builder | tensorflow.CPUInfo de type Protobuf.CPUInfo |
CPUInfoOuBuilder | |
Create_func_TF_OpKernelConstruction | |
CreateSummaryDbWriter | |
CreateSummaryFileWriter | |
RecadrerEtRedimensionner | Extrait les recadrages du tenseur de l'image d'entrée et les redimensionne. |
CropAndResize.Options | Attributs facultatifs pour CropAndResize |
CropAndResizeGradBoxes | Calcule le dégradé de l'opération crop_and_resize par rapport au tenseur des zones de saisie. |
CropAndResizeGradBoxes.Options | Attributs facultatifs pour CropAndResizeGradBoxes |
CropAndResizeGradImage <T étend TNumber > | Calcule le dégradé de l'opération crop_and_resize par rapport au tenseur de l'image d'entrée. |
CropAndResizeGradImage.Options | Attributs facultatifs pour CropAndResizeGradImage |
Croix <T étend TNumber > | Calculez le produit croisé par paire. |
CrossReplicaSum <T étend TNumber > | Une opération pour additionner les entrées sur les instances TPU répliquées. |
CSRSparseMatrixComponents <T étend TType > | Lit les composants CSR au lot `index`. |
CSRSparseMatrixToDense <T étend TType > | Convertissez un CSRSparseMatrix (éventuellement par lots) en dense. |
CSRSparseMatrixToSparseTensor <T étend TType > | Convertit un CSRSparesMatrix (éventuellement par lots) en SparseTensor. |
Ensemble de données CSV | |
Ensemble de données CSV | |
CSVDatasetV2 | |
CtcBeamSearchDecoder <T étend TNumber > | Effectue le décodage de la recherche de faisceau sur les logits donnés en entrée. |
CtcBeamSearchDecoder.Options | Attributs facultatifs pour CtcBeamSearchDecoder |
CtcGreedyDecoder <T étend TNumber > | Effectue un décodage gourmand sur les logits donnés en entrées. |
CtcGreedyDecoder.Options | Attributs facultatifs pour CtcGreedyDecoder |
CtcLoss <T étend TNumber > | Calcule la perte CTC (probabilité logarithmique) pour chaque entrée de lot. |
CtcLoss.Options | Attributs facultatifs pour CtcLoss |
CTCPerteV2 | Calcule la perte CTC (probabilité logarithmique) pour chaque entrée de lot. |
CTCLossV2.Options | Attributs facultatifs pour CTCLossV2 |
CudnnRNN <T étend TNumber > | Un RNN soutenu par cuDNN. |
CudnnRNN.Options | Attributs facultatifs pour CudnnRNN |
CudnnRNNBackprop <T étend TNumber > | Étape de backprop de CudnnRNNV3. |
CudnnRNNBackprop.Options | Attributs facultatifs pour CudnnRNNBackprop |
CudnnRNNCanonicalToParams <T étend TNumber > | Convertit les paramètres CudnnRNN de la forme canonique en forme utilisable. |
CudnnRNNCanonicalToParams.Options | Attributs facultatifs pour CudnnRNNCanonicalToParams |
CudnnRnnParamsSize <U étend TNumber > | Calcule la taille des poids qui peuvent être utilisés par un modèle Cudnn RNN. |
CudnnRnnParamsSize.Options | Attributs facultatifs pour CudnnRnnParamsSize |
CudnnRNNParamsToCanonical <T étend TNumber > | Récupère les paramètres CudnnRNN sous forme canonique. |
CudnnRNNParamsToCanonical.Options | Attributs facultatifs pour CudnnRNNParamsToCanonical |
Cumprod <T étend TType > | Calculez le produit cumulé du tenseur « x » le long de « l'axe ». |
Cumprod.Options | Attributs facultatifs pour Cumprod |
Cumsum <T étend TType > | Calculez la somme cumulée du tenseur « x » le long de « l'axe ». |
Cumsum.Options | Attributs facultatifs pour Cumsum |
CumulativeLogsumexp <T étend TNumber > | Calculez le produit cumulé du tenseur « x » le long de « l'axe ». |
CumulativeLogsumexp.Options | Attributs facultatifs pour CumulativeLogsumexp |
D
Tampon de données <T> | Un conteneur de données d'un type spécifique. |
DataBufferAdapterFactory | Usine d'adaptateurs de tampon de données. |
Tampons de données | Classe d'assistance pour créer des instances DataBuffer . |
DataBufferWindow <B étend DataBuffer <?>> | Un conteneur mutable pour afficher une partie d'un DataBuffer . |
Classe de données | Protobuf enum tensorflow.DataClass |
DataFormatDimMap <T étend TNumber > | Renvoie l'index de dimension dans le format de données de destination étant donné celui de le format des données sources. |
DataFormatDimMap.Options | Attributs facultatifs pour DataFormatDimMap |
DataFormatVecPermute <T étend TNumber > | Permutez le tenseur d'entrée de `src_format` à `dst_format`. |
DataFormatVecPermute.Options | Attributs facultatifs pour DataFormatVecPermute |
Datalayout <S étend Databuffer <?>, T> | Convertit les données stockées dans un tampon en un type donné. |
Datalayouts | Expose les instances DataLayout de formats de données fréquemment utilisés dans le calcul de l'algèbre linéaire. |
DataServicedAtaset | |
DataServicedataset.options | Attributs facultatifs pour DataServiceDataset |
Ensemble de données | Représente une liste potentiellement importante d'éléments indépendants (échantillons) et permet de réaliser l'itération et les transformations sur ces éléments. |
DataSetCardinality | Renvoie la cardinalité de `input_dataset`. |
DataSetCardinality | Renvoie la cardinalité de `input_dataset`. |
Ensemble de données | Crée un ensemble de données à partir du `Graph_def` donné. |
DataSeTiterator | Représente l'état d'une itération via un ensemble de données tf.data. |
DataSeTOptional | Une option représente le résultat d'une opération GetNext de jeu de données qui peut échouer, lorsque la fin de l'ensemble de données a été atteinte. |
DataSettograph | Renvoie un GraphDef sérialisé représentant `input_dataset`. |
DataSettograph.options | Attributs facultatifs pour DatasetToGraph |
DataSettosingLeElement | Sorte l'élément unique de l'ensemble de données donné. |
DataSettotfrecord | Écrit l'ensemble de données donné au fichier donné à l'aide du format tfrecord. |
DataSettotfrecord | Écrit l'ensemble de données donné au fichier donné à l'aide du format tfrecord. |
DataStorageVisitor <R> | Visitez le stockage du stockage des instances DataBuffer . |
Type de données | (== suppress_warning documentation-presence ==) LINT.IfChangeProtobuf enum tensorflow.DataType |
Dawsn <t étend 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 | |
Débogage | 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. |
Débogueddeviceorbuilder | |
Débogue | A debugger-instrumented graph. |
Déboguedgraph.builder | A debugger-instrumented graph. |
Débogue | |
Débogue | Type protobuf tensorflow.DebuggedSourceFile |
DebuggedSourcefile.builder | Type protobuf tensorflow.DebuggedSourceFile |
Débogue | |
Débogue | Type protobuf tensorflow.DebuggedSourceFiles |
Déboguesourcefiles.builder | Type protobuf tensorflow.DebuggedSourceFiles |
Déboguedsourcefilesorbuilder | |
DebuggradIentIdentity <T étend Ttype > | Identité OP pour le débogage de gradient. |
DebuggradIentRefidentity <T étend Ttype > | Identité OP pour le débogage de gradient. |
DebugIdentity <T étend Ttype > | Debug Identity v2 op. |
DebugIdentity.options | Attributs facultatifs pour DebugIdentity |
Debugmetadata | Metadata about the debugger and the debugged TensorFlow program. |
Debugmetadata.builder | Metadata about the debugger and the debugged TensorFlow program. |
Debugmetadataorbuilder | |
Debugncount | Débogage du compteur de valeur nan op. |
Debugnanccount.options | Attributs facultatifs pour DebugNanCount |
DebugnumericsSummary <u étend Tnumber > | Débogage Résumé numérique V2 Op. |
DebugnumericsSummary.options | Attributs facultatifs pour DebugNumericsSummary |
Debugoptions | 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 | |
Décodcropjpeg | Décoder et recadrer une image codée par JPEG à un tenseur Uint8. |
Decodeandcropjpeg.options | Attributs facultatifs pour DecodeAndCropJpeg |
DecodeBase64 | Décode les chaînes codées en base de base Web. |
Décodebmp | Décodez la première image d'une image codée BMP vers un tenseur Uint8. |
Décodebmp.options | Attributs facultatifs pour DecodeBmp |
Décodé compressé | Décompressez les cordes. |
DecodeCompress.options | Attributs facultatifs pour DecodeCompressed |
Decodecsv | Convertir les enregistrements CSV en tenseurs. |
Decodecsv.options | Attributs facultatifs pour DecodeCsv |
Décodergif | Décodez le (s) cadre (s) d'une image codée GIF à un tenseur Uint8. |
Du décodeimage <t étend tNumber > | Fonction pour decode_bmp, decode_gif, decode_jpeg et decode_png. |
Décodeimage.options | Attributs facultatifs pour DecodeImage |
Décoderjpeg | Décodez une image codée JPEG à un tenseur Uint8. |
Décodejpeg.options | Attributs facultatifs pour DecodeJpeg |
Dudejsonexample | Convertir des exemples d'exemples codés par JSON en chaînes de tampon de protocole binaire. |
Decodepaddedraw <t étend tNumber > | Réinterprétez les octets d'une chaîne comme vecteur de nombres. |
Decodepaddedraw.options | Attributs facultatifs pour DecodePaddedRaw |
Decodepng <T étend tNumber > | Décodez une image codée par PNG vers un tenseur UInt8 ou Uint16. |
Décodepng.options | Attributs facultatifs pour DecodePng |
Décodeproto | L'OP extrait les champs d'un message de protocole sérialisé le message dans les tenseurs. |
Decodeproto.options | Attributs facultatifs pour DecodeProto |
Decoderaw <T étend Ttype > | Réinterprétez les octets d'une chaîne comme vecteur de nombres. |
Decoderaw.options | Attributs facultatifs pour DecodeRaw |
Decodewav | Décodez un fichier WAV PCM 16 bits dans un tenseur de flotteur. |
Decodewav.options | Attributs facultatifs pour DecodeWav |
Deepcopy <T étend Ttype > | Fait une copie de `x`. |
Delete_func_pointer | |
Deleteiterator | Un conteneur pour une ressource itérateur. |
DeletememoryCache | |
DeleteMultideviceiterator | Un conteneur pour une ressource itérateur. |
Délai | |
Deleteeseenerator | |
DeleteSessiontenSor | Supprimez le tenseur spécifié par sa poignée dans la session. |
Densebincount <u étend tNumber > | Compte le nombre d'occurrences de chaque valeur dans un tableau entier. |
Densebincount.options | Attributs facultatifs pour DenseBincount |
DenseCountsParseOutput <u étend tNumber > | Effectue un comptage de bacs à sortie clairsemée pour une entrée tf.tensor. |
DenseCountsParseoutput.options | Attributs facultatifs pour DenseCountSparseOutput |
DendendArray <T> | |
Densetocsrsparsematrix | Convertit un tenseur dense en un CSRSParsematrix (éventuellement lot). |
DensetodensensetOperation <T étend Ttype > | Applique un fonctionnement de réglage le long de la dernière dimension de 2 entrées «tensor». |
DensetodensensetOperation.Options | Attributs facultatifs pour DenseToDenseSetOperation |
Densetosparsebatchdataset | Crée un ensemble de données qui lance des éléments d'entrée dans un sparsetensor. |
Densetosparsebatchdataset | Crée un ensemble de données qui lance des éléments d'entrée dans un sparsetensor. |
DensetOsParsesetOperation <T étend Ttype > | Applique le fonctionnement de la dernière dimension de la dernière dimension de «Tensor» et «Sparsetentensor». |
DensetOsparseSetOperation.Options | Attributs facultatifs pour DenseToSparseSetOperation |
DepthTospace <T étend Ttype > | Depthtospace pour les tenseurs de type T. |
DepthtOspace.options | Attributs facultatifs pour DepthToSpace |
DepthwiseConv2Dnative <T étend Tnumber > | Calcule une convolution 2D dans le sens de la profondeur compte tenu des tenseurs 4-D «entrée» et «filtre». |
DepthwiseConv2dnative.options | Attributs facultatifs pour DepthwiseConv2dNative |
DepthWiseConv2DnativeBackPropFilter <T étend Tnumber > | Calcule les gradients de la convolution dans le sens de la profondeur par rapport au filtre. |
DepthwiseConv2DnativeBackPropFilter.options | Attributs facultatifs pour DepthwiseConv2dNativeBackpropFilter |
DepthWiseConv2DnativeBackPropInput <T étend Tnumber > | Calcule les gradients de la convolution dans le sens de la profondeur par rapport à l'entrée. |
DepthWiseConv2DnativeBackPropInput.options | Attributs facultatifs pour DepthwiseConv2dNativeBackpropInput |
Déquantiser <u étend tNumber > | Débantisez le tenseur «d'entrée» dans un tenseur de flotteur ou de bfloat16. |
Désactiver | Prend l'entrée uint32 emballée et déballait l'entrée à uint8 pour faire Débantisation sur l'appareil. |
Déshabiller les options | Attributs facultatifs pour Dequantize |
Désérialiser | Convertit le tenseur variant donné en un itérateur et le stocke dans la ressource donnée. |
Deserialisemanysparse <T étend Ttype > | Désérialiser et concaténer des «sparsettenseurs» d'un minibatch sérialisé. |
Désérializsparse <u étend ttype > | Désérialiser les objets «sparsetentensor». |
Détruire | Supprime la ressource spécifiée par la poignée. |
Destrustresourceop.options | Attributs facultatifs pour DestroyResourceOp |
DestroyTemporaryVariable <T étend Ttype > | Détruit la variable temporaire et renvoie sa valeur finale. |
Det <t étend Ttype > | Calcule le déterminant d'une ou plusieurs matrices carrées. |
Deviceatributes | tensorflow.DeviceAttributes de type protobuf.DeviceAttributes |
DeviceAttributes.builder | tensorflow.DeviceAttributes de type protobuf.DeviceAttributes |
DeviceAttributesorbuilder | |
DeviceAttributesprotos | |
Devicefiltersprotos | |
Device Index | Renvoie l'index de l'appareil que l'OP s'exécute. |
Déviation | tensorflow.DeviceLocality de type protobuf.devicelocalité |
Devicelocality.builder | tensorflow.DeviceLocality de type protobuf.devicelocalité |
Devicelocalicyorbuilder | |
DeviceProperties | Type protobuf tensorflow.DeviceProperties |
DeviceProperties.builder | Type protobuf tensorflow.DeviceProperties |
DevicePropertiesorBuilder | |
DevicePropertiesProtos | |
Dispositif | Représente une spécification (peut-être partielle) pour un dispositif TensorFlow. |
Dispositifpe.builder | Une classe de constructeur pour construire DeviceSpec . |
Disciplepec.deviceType | |
DeviceStatstats | tensorflow.DeviceStepStats de type protobuf.DeviceStEpstats |
DeviceStepstats.builder | tensorflow.DeviceStepStats de type protobuf.DeviceStEpstats |
DeviceStatsorbuilder | |
Dicton | Represents a Python dict keyed by `str`. |
DictValue.builder | Represents a Python dict keyed by `str`. |
Dictvalueorbuilder | |
Digamma <t étend tNumber > | Calcule psi, la dérivée de LGAMMA (le journal de la valeur absolue de `Gamma (x) '), en termes d'élément. |
Dilation2d <t étend tNumber > | Calcule la dilatation en niveaux de gris des tenseurs 4-D «entrée» et «filtre» 3-d. |
Dilation2dbackpropfilter <t étend tNumber > | Calcule le gradient de la dilatation morphologique 2-D par rapport au filtre. |
Dilation2dbackpropInput <t étend tNumber > | Calcule le gradient de la dilatation morphologique 2-D par rapport à l'entrée. |
Dimension | |
DIMENDENALSPACE | |
Direction InterleveVedataset | Un substitut pour «interleavevedataset» sur une liste fixe des ensembles de données `n». |
Direction InterleveVedataset | Un substitut pour «interleavevedataset» sur une liste fixe des ensembles de données `n». |
Div <t étend ttype > | Renvoie X / Y sur le plan des éléments. |
Divnonan <t étend ttype > | Renvoie 0 si le dénominateur est nul. |
Dot <T étend Ttype > | Enveloppe l'opérateur de dotgénique XLA, documenté à https://www.tensorflow.org/performance/xla/operation_semitics#dotgeneral. |
Doublé | Un DataBuffer de doubles. |
DoubleDatalayout <S étend Databuffer <? >> | Un DataLayout qui convertit les données stockées dans un tampon en double. |
DoubledensrendArray | |
Doubler. | Un NdArray de doubles. |
Drawboundingboxes <T étend tNumber > | Dessinez des boîtes de délimitation sur un lot d'images. |
Mât | |
Mâle | |
Ingénieur muet | |
DynamicPartition <T étend Ttype > | Partitions «Données» dans les tenseurs «num_partitions» utilisant des indices de «partitions». |
Dynamicslice <T étend Ttype > | Enveloppe l'opérateur XLA Dynamicslice, documenté à https://www.tensorflow.org/performance/xla/operation_semantics#dynamicslice. |
DynamicSttitch <T étend Ttype > | Entrelacez les valeurs des tenseurs de «données» en un seul tenseur. |
DynamicUpDateslice <T étend Ttype > | Enveloppe l'opérateur XLA DynamicUpDatesLice, documenté à https://www.tensorflow.org/performance/xla/operation_semantics#damicupdateslice. |
E
EAGERSESSESSE | Un environnement pour exécuter des opérations Tensorflow avec impatience. |
EAGERSESSESSE.DEVICEplacementPolicy | Contrôle comment agir lorsque nous essayons d'exécuter une opération sur un périphérique donné, mais certains tenseurs d'entrée ne sont pas sur cet appareil. |
EagerSession.options | |
Édition | Calcule la distance d'édition (éventuellement normalisée) de Levenshtein. |
EditDistance.options | Attributs facultatifs pour EditDistance |
Eig <u étend ttype > | Calcule la décomposition propre d'une ou plusieurs matrices carrées. |
Options eig. | Attributs facultatifs pour Eig |
Einsum <t étend ttype > | Contraction du tenseur selon la convention de sommation d'Einstein. |
Einsum <t étend ttype > | Un OP qui prend en charge l'OP de base Einsum avec 2 entrées et 1 sortie. |
Elu <t étend tnumber > | Calcule Exponential Linear: `EXP (fonctionnalités) - 1` si <0,` Fonctionnalités »sinon. |
Elu <t étend tfloating > | Unité linéaire exponentielle. |
Elugrad <T étend Tnumber > | Calcule les gradients de l'opération linéaire exponentielle (ELU). |
Enclatement | Une option de différenciation permettant des incorporations TPU. |
Vide <t étend ttype > | Crée un tenseur avec la forme donnée. |
Options vides | Attributs facultatifs pour Empty |
Videtensorlist | Crée et renvoie une liste de tenseur vide. |
Vide-tempête | Crée et renvoie une carte du tenseur vide. |
Encodébase64 | Encoder les chaînes au format Base64 en service Web. |
EncodeBase64. Options | Attributs facultatifs pour EncodeBase64 |
Encodejpeg | JPEG-Encode une image. |
Encodejpeg.options | Attributs facultatifs pour EncodeJpeg |
Encodejpegvariablequality | JPEG Encode l'image d'entrée avec une qualité de compression fournie. |
Encoder | PNG-Encode une image. |
Encodepng.options | Attributs facultatifs pour EncodePng |
Encodéproto | L'OP sérialise les messages Protobuf fournis dans les tenseurs d'entrée. |
Encodéproto.options | Attributs facultatifs pour EncodeProto |
Encodewav | Encoder les données audio à l'aide du format de fichier WAV. |
Point final | Annotation utilisée pour marquer une méthode d'une classe annotée avec @Operator qui devrait générer un point de terminaison en ERROR(Ops/org.tensorflow.op.Ops Ops) ou l'un de ses groupes. |
EnqueUetpueMeddingIntegerBatch | Un OP qui entend une liste de tenseurs de lot d'entrée à tpuembedding. |
EnqueUetpueMeddingIntegerBatch.options | Attributs facultatifs pour EnqueueTPUEmbeddingIntegerBatch |
EnqueUetpueMeddingraggedtenSorbatch | Soutient le portage du code qui utilise tf.nn.embedding_lookup (). |
EnqueUetpueMeddingraggedtenSorBatch.options | Attributs facultatifs pour EnqueueTPUEmbeddingRaggedTensorBatch |
EnqueUetPuembeddingSparsebatch | Un OP qui en file les indices d'entrée tpuembedding d'un sparsetensor. |
EnqueUetPuembeddingsParseBatch.options | Attributs facultatifs pour EnqueueTPUEmbeddingSparseBatch |
EnqueUetpueMeddingsPaSetenSorbatch | Soutient le portage du code qui utilise tf.nn.embedding_lookup_sparse (). |
EnqueUetPuembeddingsParsetenSorbatch.options | Attributs facultatifs pour EnqueueTPUEmbeddingSparseTensorBatch |
Assure lachère <T étend Ttype > | S'assure que la forme du tenseur correspond à la forme attendue. |
Entrée <T étend Ttype > | Crée ou trouve un cadre enfant et rend les «données» à la disposition du cadre enfant. |
Enter.options | Attributs facultatifs pour Enter |
Entrée | Type protobuf tensorflow.EntryValue |
EntryValue.builder | Type protobuf tensorflow.EntryValue |
EntryValue.kindCase | |
EntryValueorBuilder | |
Égal | Renvoie la valeur de vérité de (x == y) sur le plan des éléments. |
Options égales | Attributs facultatifs pour Equal |
Erf <t étend tnumber > | Calcule la fonction d'erreur Gauss de l'élément `x`. |
ERFC <T étend Tnumber > | Calcule la fonction d'erreur complémentaire des éléments `x`. |
Erfinv <T étend tNumber > | |
Codes d'erreur | |
Errorcodesprotos | |
Euclideannorm <t étend ttype > | Calcule la norme euclidienne des éléments à travers les dimensions d'un tenseur. |
Euclideannorm.options | Attributs facultatifs pour EuclideanNorm |
Événement | 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. |
Événement.Whatcase | |
Eventorbuilder | |
Eventprotos | |
Exemple | tensorflow.Example de type protobuf.exemple |
Exemple.builder | tensorflow.Example de type protobuf.exemple |
ExempleorBuilder | |
ExemplePaSerConfiguration | Type protobuf tensorflow.ExampleParserConfiguration |
ExempleParserConfiguration.builder | Type protobuf tensorflow.ExampleParserConfiguration |
ExempleParSerConfigurationorbuilder | |
ExempleParSerConfigurationProtos | |
Exemples deprotos | |
Exécuter | OP qui charge et exécute un programme TPU sur un périphérique TPU. |
Exécution | OP qui exécute un programme avec des mises à jour de variables en place facultatives. |
Exécution | Data relating to the eager execution of an op or a Graph. |
Exécution.builder | Data relating to the eager execution of an op or a Graph. |
Exécution de l'environnement | Définit un environnement pour créer et exécuter Operation TensorFlow s. |
Executionenvironment.Types | |
Exécution | |
L'exit <t étend Ttype > | Quitte le cadre actuel de son cadre parent. |
Exp <T étend Ttype > | Calcule exponentiel de x élément. |
Extenddims <T étend Ttype > | Insère une dimension de 1 dans la forme d'un tenseur. |
Expint <T étend tNumber > | |
Expm1 <T étend Ttype > | Calcule `EXP (x) - 1` par élément. |
Exponentiel <T étend tfloating > | Fonction d'activation exponentielle. |
Extracter | Extrait un aperçu du tenseur d'entrée. |
ExtractGLIMPSE.options | Attributs facultatifs pour ExtractGlimpse |
ExtractimagePatches <T étend Ttype > | Extrairez des «correctifs» à partir de «images» et placez-les dans la dimension de sortie «profondeur». |
ExtractJpegShape <T étend Tnumber > | Extraire les informations de forme d'une image codée JPEG. |
ExtractVolumePatches <T étend Tnumber > | Extraire les «correctifs» de «entrée» et les mettre dans la dimension de sortie «profondeur» «profondeur». |
F
Fait | Sortie un fait sur les factoriels. |
FakeQuant avec | Faux-quantification du tenseur «Entrées», typez flotter sur le tenseur «sorties» du même type. |
FakeQuant withminMaxargs.options | Attributs facultatifs pour FakeQuantWithMinMaxArgs |
FakeQuant avec le cycle | Calculez les gradients pour une fausse fonctionnalité avec une opération de maxargs. |
FakeQuantwithminMaxargsgradient.options | Attributs facultatifs pour FakeQuantWithMinMaxArgsGradient |
FakeQuant avec | Faux-quantification du tenseur des «entrées» du flotteur de type via les scalaires de flottants mondiaux Fake-Quantifie le tenseur `` Entrée 'du Float de type via des scalaires de flottants mondiaux `min` et` max »à` `sorties' tenseur de même forme que les« entrées ». |
FakeQuant withminmaxvars.options | Attributs facultatifs pour FakeQuantWithMinMaxVars |
FakeQuant avec | Calculez les gradients pour un faux fonctionnement avec l'opération de maxvars. |
FakeQuantwithminMaxVarsgradient.options | Attributs facultatifs pour FakeQuantWithMinMaxVarsGradient |
FakeQuantwithminmaxvarsperChannel | Faux-quantification du tenseur «entrées» de type flotteur via des flotteurs par canal Fake-Quantize le tenseur `` Entrée 'du flotteur de type par canal et l'une des formes: `[d]`, `[b, d]` `[b, h, w, d]` via les flotteurs par canal ` Min` et «Max» de forme `[d]« à «sort» tenseur de même forme que «entrées». |
FakeQuantwithminmaxvarsperChannel.options | Attributs facultatifs pour FakeQuantWithMinMaxVarsPerChannel |
FakeQuant withinMaxvarsperChannelgradient | Calculez les gradients pour un faux point de surface en fonction de l'opération. |
FakeQuantwithminMaxvarsperChannelgradient.options | Attributs facultatifs pour FakeQuantWithMinMaxVarsPerChannelGradient |
FastElementSequence <t, u étend ndarray <T>> | Une séquence recyclant la même instance NdArray lors de l'itération de ses éléments |
Fonctionnalité | Containers for non-sequential data. |
Caractéristique.builder | Containers for non-sequential data. |
Caractéristique.kindcase | |
FeatureConfiguration | Type protobuf tensorflow.FeatureConfiguration |
FeatConfiguration.builder | Type protobuf tensorflow.FeatureConfiguration |
FeatureConfiguration.configcase | |
FeatConfigurationorbuilder | |
Enterré | Containers for sequential data. |
FeatList.builder | Containers for sequential data. |
FeatRelistorbuilder | |
Featurs | tensorflow.FeatureLists de type protobuf. |
Featlates.builder | tensorflow.FeatureLists de type protobuf. |
FeatRelistsorbuilder | |
Caractéristique | |
Caractéristiqueprotos | |
Caractéristiques | tensorflow.Features de type protobuf. |
Fonctionnalités.builder | tensorflow.Features de type protobuf. |
Fonctionnalités | |
FFT <T étend Ttype > | Transformée de Fourier rapide. |
Fft2d <T étend Ttype > | Transformée de Fourier rapide 2D. |
Fft3d <T étend Ttype > | Transformée de Fourier rapide 3D. |
Fifroqueue | Une file d'attente qui produit des éléments dans le premier ordre du premier coup. |
FIFOQUEUE.OPTIONS | Attributs facultatifs pour FifoQueue |
Remplir <u étend Ttype > | Crée un tenseur rempli d'une valeur scalaire. |
FilterBylastComponentDataset | Crée un ensemble de données contenant des éléments du premier composant de «input_dataset» ayant vrai dans le dernier composant. |
Empreinte digitale | Génère des valeurs d'empreintes digitales. |
FixedLenFeatureProto | Type protobuf tensorflow.FixedLenFeatureProto |
FixedLenFeatureProto.Builder | Type protobuf tensorflow.FixedLenFeatureProto |
FixedLenFeatureProtoorBuilder | |
FixeLengthRecordDataset | |
FixeLengthRecOrDreader | Un lecteur qui publie des enregistrements de longueur fixe à partir d'un fichier. |
FIXTLENGTHRECORDREADER.OPTIONS | Attributs facultatifs pour FixedLengthRecordReader |
FixenigramcanDidatesampler | Génère des étiquettes pour l'échantillonnage des candidats avec une distribution d'apprentissage en unigramme. |
FIXTUGRAMADIDADADADAMPLER.OPTIONS | Attributs facultatifs pour FixedUnigramCandidateSampler |
Float16layout | Disposition des données qui convertit 32 bits flotte de / à 16 bits, en conséquence de la spécification du point flottant de la demi-précision IEEE-754. |
Floatadatabuffer | Un DataBuffer de flotteurs. |
FloatDatalayout <S étend Databuffer <? >> | Un DataLayout qui convertit les données stockées dans un tampon en flotteurs. |
FloatdensendArray | |
Flotlist | Type protobuf tensorflow.FloatList |
Floatlist.builder | Type protobuf tensorflow.FloatList |
Floatlistorbuilder | |
Floatndarray | Un NdArray de flotteurs. |
Le sol <t étend tNumber > | Renvoie un entier le plus grand des éléments pas supérieur à x. |
Floordiv <T étend Ttype > | Renvoie x // y élément par élément. |
Floormod <T étend tNumber > | Renvoie le reste des éléments de division. |
Rédacteur | |
FractionalaVgpool <t étend tNumber > | Effectue un regroupement moyen fractionnaire sur l'entrée. |
Fractionalavgpool.options | Attributs facultatifs pour FractionalAvgPool |
FractionalaVgpoolgrad <t étend tNumber > | Calcule le gradient de la fonction FractionalAvgpool. |
Fractionalavgpoolgrad.options | Attributs facultatifs pour FractionalAvgPoolGrad |
Fractionalmaxpool <t étend tNumber > | Effectue une regroupement max fractionnaire sur l'entrée. |
Fractionalmaxpool.options | Attributs facultatifs pour FractionalMaxPool |
Fractionalmaxpoolgrad <t étend tNumber > | Calcule le gradient de la fonction Fractionalmaxpool. |
Fractionalmaxpoolgrad.options | Attributs facultatifs pour FractionalMaxPoolGrad |
Fresnelcos <T étend tNumber > | |
Fresnelsin <T étend tNumber > | |
Ftrl | Optimiseur qui implémente l'algorithme FTRL. |
Functiondef | A function can be instantiated when the runtime can bind every attr with a value. |
Functiondef.argattrs | Attributes for function arguments. |
Functiondef.argattrs.builder | Attributes for function arguments. |
Functiondef.argattrsorbuilder | |
Functiondef.builder | A function can be instantiated when the runtime can bind every attr with a value. |
Fundeflibrary | A library is a set of named functions. |
Functiondeflibrary.builder | A library is a set of named functions. |
Functiondeflibraryorbuilder | |
Functiondeforbuilder | |
Fonctionprotos | |
FunctionSpec | Represents `FunctionSpec` used in `Function`. |
FunctionSpec.builder | Represents `FunctionSpec` used in `Function`. |
Functionspe.experimentalcompile | Whether the function should be compiled by XLA. |
Fonction de fonction | |
FusedBatchNorm <T étend tNumber , u étend tNumber > | Normalisation par lots. |
FusedBatchNorm.Options | Attributs facultatifs pour FusedBatchNorm |
FusedBatchNormgrad <T étend tNumber , u étend tNumber > | Gradient pour la normalisation par lots. |
FusedBatchNormgrad.options | Attributs facultatifs pour FusedBatchNormGrad |
FusedPadconv2d <T étend Tnumber > | Effectue un rembourrage en tant que prétraitement lors d'une convolution. |
FusedResizEndpadconv2d <T étend Tnumber > | Effectue un redimensionnement et un rembourrage en tant que prétraitement lors d'une convolution. |
FusedResizEndpadconv2d.options | Attributs facultatifs pour FusedResizeAndPadConv2d |
G
Rassemble <T étend tNumber > | Accumule mutuellement plusieurs tenseurs de type et de forme identiques. |
Rassemble <T étend Ttype > | Rassemblez des tranches à partir de `` params 'de l'axe «axe» en fonction des «indices». |
Rassemble <T étend Ttype > | Enveloppe l'opérateur XLA Gather documenté à https://www.tensorflow.org/xla/operation_semantics#gather |
Rassembler des options | Attributs facultatifs pour Gather |
Rassembler des options | Attributs facultatifs pour Gather |
Gathernd <T étend Ttype > | Rassemblez des tranches de «params» dans un tenseur avec une forme spécifiée par «Indices». |
GATHERV2 <T étend Tnumber > | Accumule mutuellement plusieurs tenseurs de type et de forme identiques. |
GATHERV2. OPTIONS | Attributs facultatifs pour GatherV2 |
Générer desProposals debound | Cet OP produit une région d'intérêts à partir d'ancrages WRT codés en codés en codés conformes à l'eq.2 dans ArXIV: 1506.01497. L'OP sélectionne les boîtes de notation `pre_nms_topn` les décode par rapport aux ancres, applique la suppression non maximale sur les boîtes de chevauchement avec des boîtes d'intersection plus élevées que` NMS_THRESHOLD` min_size`. |
Générer laBoundingBoxProposals.options | Attributs facultatifs pour GenerateBoundingBoxProposals |
Générer unvocabremapping | Étant donné un chemin vers des fichiers de vocabulaire nouveaux et anciens, renvoie un tenseur de remappage de longueur `num_new_vocab`, où` remappage [i] `contient le numéro de ligne dans l'ancien vocabulaire qui correspond à la ligne` i` dans le nouveau vocabulaire (commençant à la ligne `new_vocab_offset` et jusqu'à` num_new_vocab` entités), ou `- et jusqu'à` num_new_vocab` entités), ou `- 1 'Si l'entrée «Je» dans le nouveau vocabulaire n'est pas dans l'ancien vocabulaire. |
Générervocabremapping.options | Attributs facultatifs pour GenerateVocabRemapping |
GetSessionhandle | Stockez le tenseur d'entrée dans l'état de la session en cours. |
GetSessiontensor <T étend ttype > | Obtenez la valeur du tenseur spécifié par sa poignée. |
Glorot <T étend tfloating > | L'initialisateur de Glorot, également appelé initialiseur Xavier. |
Gpuinfo | Type protobuf tensorflow.GPUInfo |
Gpuinfo.builder | Type protobuf tensorflow.GPUInfo |
Gpuinfoorbuilder | |
Gpuoptions | Type protobuf tensorflow.GPUOptions |
Gpuoptions.builder | Type protobuf tensorflow.GPUOptions |
Gpuoptions.Experimental | Type protobuf tensorflow.GPUOptions.Experimental |
Gpuoptions.experimental.builder | Type protobuf tensorflow.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. | |
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 | |
Gradientdecent | Optimiseur de descente de gradient stochastique de base. |
Dégradés | Ajoute des opérations pour calculer les dérivés partiels de la somme de y s wrt x s, ie, d(y_1 + y_2 + ...)/dx_1, d(y_1 + y_2 + ...)/dx_2... Si les valeurs |
Gradients. | Attributs facultatifs pour Gradients |
Graphique | Un graphique de flux de données représentant un calcul tenorflow. |
Graphique | Utilisé pour instancier une classe abstraite qui remplace la méthode BuildSubgraph pour construire un sous-graphe conditionnel ou corporel pendant une boucle de temps. |
Graphdebuginfo | Type protobuf tensorflow.GraphDebugInfo |
Graphdebuginfo.builder | Type protobuf tensorflow.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 operationsType protobuf tensorflow.GraphDef |
Graphdef.builder | Represents the graph of operationsType protobuf tensorflow.GraphDef |
Graphdeforbuilder | |
GraphExEcutionTrace | Data relating to an execution of a Graph (e.g., an eager execution of a FuncGraph). |
GraphExecutionTrace.builder | Data relating to an execution of a Graph (e.g., an eager execution of a FuncGraph). |
GraphExecutionTraceorBuilder | |
Graphopcrition | The creation of an op in a TensorFlow Graph (e.g., FuncGraph in TF2). |
Graphopcreation.builder | The creation of an op in a TensorFlow Graph (e.g., FuncGraph in TF2). |
Graphopcreationorbuilder | |
Graphopération | Implémentation pour une Operation ajoutée comme nœud à un Graph . |
Graphoperationbuilder | Un OperationBuilder pour l'ajout GraphOperation à un Graph . |
Graphoptions | tensorflow.GraphOptions de type protobuf.Graphoptions |
Graphoptions.builder | tensorflow.GraphOptions de type protobuf.Graphoptions |
Graphoptionsorbuilder | |
Graphprotos | |
Graphtransferconstnodeinfo | Type protobuf tensorflow.GraphTransferConstNodeInfo |
Graphtransferconstnodeinfo.builder | Type protobuf tensorflow.GraphTransferConstNodeInfo |
Graphtransferconstnodeinfoorbuilder | |
Graphtransfergraphinputnodeinfo | Type protobuf tensorflow.GraphTransferGraphInputNodeInfo |
Graphtransfergraphinputnodeinfo.builder | Type protobuf tensorflow.GraphTransferGraphInputNodeInfo |
Graphtransfergraphinputnodeinfoorbuilder | |
Graphtransfergraphoutputnodeinfo | Type protobuf tensorflow.GraphTransferGraphOutputNodeInfo |
Graphtransfergraphoutputnodeinfo.builder | Type protobuf tensorflow.GraphTransferGraphOutputNodeInfo |
Graphtransfergraphoutputnodeinfoorbuilder | |
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 | |
Graphtransférinfoproto | |
Graphtransfernodeinfo | Type protobuf tensorflow.GraphTransferNodeInfo |
Graphtransfernodeinfo.builder | Type protobuf tensorflow.GraphTransferNodeInfo |
Graphtransfernodeinfoorbuilder | |
GraphtransferNodeInput | Type protobuf tensorflow.GraphTransferNodeInput |
GraphtransferNodeInput.builder | Type protobuf tensorflow.GraphTransferNodeInput |
GraphtransferNodeInputinfo | Type protobuf tensorflow.GraphTransferNodeInputInfo |
Graphtransfernodeinputinfo.builder | Type protobuf tensorflow.GraphTransferNodeInputInfo |
Graphtransfernodeinputinfoorbuilder | |
GraphtransferNodeInputorBuilder | |
GraphtransferNodeoutUtinfo | Type protobuf tensorflow.GraphTransferNodeOutputInfo |
GraphtransferNodeOutputinfo.builder | Type protobuf tensorflow.GraphTransferNodeOutputInfo |
GraphtransferNodeOutputinfoorBuilder | |
Plus grand | Renvoie la valeur de vérité de (x> y) en termes d'élément. |
Plus grand | Renvoie la valeur de vérité de (x> = y) sur le plan des éléments. |
Grubockcell <T étend tNumber > | Calcule la propagation vers l'avant de la cellule GRU pendant un pas de temps. |
GrublockCellgrad <t étend tNumber > | Calculez le rétro-propagation de la cellule GRU pendant un pas de temps. |
GuaralineConst <T étend Ttype > | Donne une garantie à l'exécution TF que le tenseur d'entrée est une constante. |
H
Hardsigmoïd <t étend tfloating > | Activation du sigmoïde dur. |
Hachage | Crée une table de hachage non initialisée. |
Hashtable.options | Attributs facultatifs pour HashTable |
Il <T étend tfloating > | Il initialiseur. |
Assistants | Classe de conteneurs pour les méthodes de base qui ajoutent ou effectuent plusieurs opérations et renvoient l'une d'entre elles. |
Charnière | Calcule la perte de charnière entre les étiquettes et les prédictions. |
Hinge <t étend tNumber > | Une métrique qui calcule la métrique de la perte de charnière entre les étiquettes et les prédictions. |
HistogramFixedWidth <u étend tNumber > | Histogramme de retour des valeurs. |
Histogramproto | Serialization format for histogram module in core/lib/histogram/histogram.hType protobuf tensorflow.HistogramProto |
Histogramproto.builder | Serialization format for histogram module in core/lib/histogram/histogram.hType protobuf tensorflow.HistogramProto |
Histogramprotoorbuilder | |
Histogrammaire | Sorte un tampon de protocole «Résumé» avec un histogramme. |
Hsvtorgb <t étend tNumber > | Convertissez une ou plusieurs images de HSV en RVB. |
Huber | Calcule la perte de Huber entre les étiquettes et les prédictions. |
je
Identité <t étend tfloating > | Initialiseur qui génère la matrice d'identité. |
Identité <T étend Ttype > | Renvoyez un tenseur avec la même forme et le même contenu que le tenseur d'entrée ou la valeur. |
Identité | Renvoie une liste de tenseurs avec les mêmes formes et contenus que l'entrée tenseurs. |
IdentityReader | Un lecteur qui publie la file d'attente fonctionne à la fois comme la clé et la valeur. |
IdentityReader.options | Attributs facultatifs pour IdentityReader |
IFFT <T étend Ttype > | Transformée de Fourier rapide inverse. |
Ifft2d <T étend Ttype > | Transformée de Fourier rapide 2D inverse. |
Ifft3d <T étend Ttype > | Transformée de Fourier rapide 3D inverse. |
Igamma <t étend tNumber > | Calculez la fonction gamma incomplète régularisée inférieure `p (a, x)`. |
Igammac <t étend tNumber > | Calculez la fonction gamma incomplète régularisée supérieure `q (a, x)`. |
Igammagrada <t étend tNumber > | Calcule le gradient de `igamma (a, x)` wrt `a`. |
IgnoreErrorsdataset | Crée un ensemble de données qui contient les éléments d'erreurs d'ignorance `input_dataset». |
IgnoreErrorsdataset | Crée un ensemble de données qui contient les éléments d'erreurs d'ignorance `input_dataset». |
Ignoreerrorsdataset.options | Attributs facultatifs pour IgnoreErrorsDataset |
Ignoreerrorsdataset.options | Attributs facultatifs pour IgnoreErrorsDataset |
Illégalrankexception | Exception lancée lorsqu'une opération ne peut pas être terminée en raison du rang du tableau ciblé. |
Imag <u étend tNumber > | Renvoie la partie imaginaire d'un nombre complexe. |
ImageProjectiveTransformv2 <T étend tNumber > | Applique la transformation donnée à chacune des images. |
ImageProjectiveTransformv2.options | Attributs facultatifs pour ImageProjectiveTransformV2 |
ImageProjectiveTransformv3 <T étend Tnumber > | Applique la transformation donnée à chacune des images. |
ImageProjectiveTransformv3.options | Attributs facultatifs pour ImageProjectiveTransformV3 |
Images | Sorte un tampon de protocole «Résumé» avec des images. |
Imagesummary.options | Attributs facultatifs pour ImageSummary |
ImmutableConst <T étend Ttype > | Renvoie le tenseur immuable de la région de la mémoire. |
Importation | |
Indice | Un index utilisé pour découper une vue d'un tableau à n dimensions. |
Indexéiterator | |
IndexEdPoseterator.CoordslongConsumer | |
Indices | Classe d'assistance pour instanciation des objets Index . |
Infeeddequeue <t étend ttype > | Un Payholder OP pour une valeur qui sera introduite dans le calcul. |
Feeddequeuetuple | Répondance à plusieurs valeurs de l'infeed comme un tuple XLA. |
Infeeddenqueue | Un OP qui alimente une seule valeur de tenseur dans le calcul. |
Infeedenqueue.options | Attributs facultatifs pour InfeedEnqueue |
Infeedenqueueprelinearisonbuffer | Un OP qui en file des tampons prélinéarisés dans une infeed TPU. |
Infeedenqueueprelinearisonbuffer.options | Attributs facultatifs pour InfeedEnqueuePrelinearizedBuffer |
Infeedenqueuetuple | Alimente plusieurs valeurs de tenseur dans le calcul sous forme de tuple XLA. |
Infeedenqueuetuple.options | Attributs facultatifs pour InfeedEnqueueTuple |
Init | |
L'initialisateur <T étend Ttype > | Une interface pour les initialiseurs |
Initialable | Tableau initialiseur qui prend respectivement deux tenseurs pour les clés et les valeurs. |
Initializetable à partir de | |
Initialisetablefromtextfile | Initialise une table à partir d'un fichier texte. |
InitialisetablefromTextFile.options | Attributs facultatifs pour InitializeTableFromTextFile |
Inplaceadd <t étend ttype > | Ajoute V dans des lignes spécifiées de x. |
Inplacesub <t étend ttype > | Soustrait `V` en lignes spécifiées de` x`. |
Inplaceupdate <t étend ttype > | Mises à jour des lignes spécifiées «i» avec des valeurs «v». |
Int64list | Type protobuf tensorflow.Int64List |
Int64list.builder | Type protobuf tensorflow.Int64List |
Int64ListorBuilder | |
Intdatabuffer | Un DataBuffer d'INTS. |
IntDatalayout <S étend Databuffer <? >> | Un DataLayout qui convertit les données stockées dans un tampon en INTS. |
IntdesenSendArray | |
Interconnexion | Type protobuf tensorflow.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. |
Itérateur | |
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 | |
Rejoindre | 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`. |
Moins | 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. |
Perte | |
Pertes | 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 |
Inférieur | 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 |
Métrique | 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 |
Élan | 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 | Ne fait rien. |
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 |
Ô
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. |
Opération | 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. |
Opération | Performs computation on Tensors. |
OperationBuilder | A builder for Operation s. |
Opérateur | 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 |
Optimiseur | 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 |
Imprimer | 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. |
Rang | 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 |
Réduction | 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 |
Restaurer | 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. |
Sauvegarder | 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 |
Portée | 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. |
Envoyer | Sends the named tensor from send_device to recv_device. |
Envoyer | 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. |
Serveur | 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 | |
Session | 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 | |
Forme | 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. |
Formes | 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. |
Signature | 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. |
Instantané | 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 | |
Scène | 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 |
Bande | 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 |
Résumé | 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 |
Tensor | A statically typed multi-dimensional array. |
Tensor | |
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. |
flux tensoriel | |
flux tensoriel | |
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`. |
Horodatage | 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 | Type de chaîne. |
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 > | Recherche des éléments uniques le long d'un axe d'un tenseur. |
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 > | Recherche des éléments uniques le long d'un axe d'un tenseur. |
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 | |
Supérieur | 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. |
Où | 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`. |