Aulas
| Abortar | Gere uma exceção para abortar o processo quando chamado. |
| Abort.Options | Atributos opcionais para Abort |
| Todos | Calcula o "e lógico" dos elementos nas dimensões de um tensor. |
| Todas.Opções | Atributos opcionais para All |
| TodosParaTodos <T> | Uma opção para trocar dados entre réplicas de TPU. |
| AnonymousHashTable | Cria uma tabela hash anônima não inicializada. |
| AnonymousIteratorV2 | Um contêiner para um recurso iterador. |
| AnonymousIteratorV3 | Um contêiner para um recurso iterador. |
| AnonymousMemoryCache | |
| AnonymousMultiDeviceIterator | Um contêiner para um recurso iterador de vários dispositivos. |
| AnonymousMultiDeviceIteratorV3 | Um contêiner para um recurso iterador de vários dispositivos. |
| AnonymousMutableDenseHashTable | Cria uma tabela de hash mutável anônima vazia que usa tensores como armazenamento de apoio. |
| AnonymousMutableDenseHashTable.Options | Atributos opcionais para AnonymousMutableDenseHashTable |
| AnonymousMutableHashTable | Cria uma tabela hash mutável anônima vazia. |
| AnonymousMutableHashTableOfTensors | Cria uma tabela hash mutável anônima vazia de valores vetoriais. |
| AnonymousMutableHashTableOfTensors.Options | Atributos opcionais para AnonymousMutableHashTableOfTensors |
| AnonymousRandomSeedGenerator | |
| AnonymousSeedGenerator | |
| Qualquer | Calcula o "ou lógico" dos elementos nas dimensões de um tensor. |
| Qualquer.Opções | Atributos opcionais para Any |
| AplicarAdagradV2 <T> | Atualize '*var' de acordo com o esquema adagrad. |
| ApplyAdagradV2.Options | Atributos opcionais para ApplyAdagradV2 |
| ApproxTopK <T estende Número> | Retorna os valores min/max k e seus índices do operando de entrada de forma aproximada. |
| ApproxTopK.Options | Atributos opcionais para ApproxTopK |
| AssertCardinalityDataset | |
| AssertNextDataset | Uma transformação que afirma quais transformações acontecerão a seguir. |
| AssertPrevDataset | Uma transformação que afirma quais transformações ocorreram anteriormente. |
| AssertThat | Afirma que a condição fornecida é verdadeira. |
| AssertThat.Options | Atributos opcionais para AssertThat |
| Atribuir <T> | Atualize 'ref' atribuindo 'value' a ele. |
| Atribuir.Opções | Atributos opcionais para Assign |
| Atribuir Adicionar <T> | Atualize 'ref' adicionando 'value' a ele. |
| AssignAdd.Options | Atributos opcionais para AssignAdd |
| AssignAddVariableOp | Adiciona um valor ao valor atual de uma variável. |
| AssignSub <T> | Atualize 'ref' subtraindo 'value' dele. |
| AssignSub.Options | Atributos opcionais para AssignSub |
| AssignSubVariableOp | Subtrai um valor do valor atual de uma variável. |
| AssignVariableOp | Atribui um novo valor a uma variável. |
| AssignVariableOp.Options | Atributos opcionais para AssignVariableOp |
| AtribuirVariávelXlaConcatND | Concatena o tensor de entrada em todas as dimensões. |
| AssignVariableXlaConcatND.Options | Atributos opcionais para AssignVariableXlaConcatND |
| AutoShardDataset | Cria um conjunto de dados que fragmenta o conjunto de dados de entrada. |
| AutoShardDataset.Options | Atributos opcionais para AutoShardDataset |
| BandedTriangularResolve <T> | |
| BandedTriangularSolve.Options | Atributos opcionais para BandedTriangularSolve |
| Barreira | Define uma barreira que persiste em diferentes execuções de gráficos. |
| Barreira.Opções | Atributos opcionais para Barrier |
| Fechar Barreira | Fecha a barreira dada. |
| BarreiraFechar.Opções | Atributos opcionais para BarrierClose |
| Barreira IncompletaTamanho | Calcula o número de elementos incompletos na barreira especificada. |
| BarreiraInserirMuitos | Para cada chave, atribui o respectivo valor ao componente especificado. |
| BarrierReadySize | Calcula o número de elementos completos na barreira especificada. |
| BarreiraTakeMany | Pega o número dado de elementos completos de uma barreira. |
| BarrierTakeMany.Options | Atributos opcionais para BarrierTakeMany |
| Lote | Agrupa todos os tensores de entrada de forma não determinística. |
| Opções de lote | Atributos opcionais para Batch |
| BatchMatMulV2 <T> | Multiplica fatias de dois tensores em lotes. |
| BatchMatMulV2.Options | Atributos opcionais para BatchMatMulV2 |
| BatchMatMulV3 <V> | Multiplica fatias de dois tensores em lotes. |
| BatchMatMulV3.Options | Atributos opcionais para BatchMatMulV3 |
| BatchToSpace <T> | BatchToSpace para tensores 4-D do tipo T. |
| BatchToSpaceNd <T> | BatchToSpace para tensores ND do tipo T. |
| BesselI0 <T estende Número> | |
| BesselI1 <T estende Número> | |
| BesselJ0 <T estende Número> | |
| BesselJ1 <T estende o número> | |
| BesselK0 <T estende Número> | |
| BesselK0e <T estende Número> | |
| BesselK1 <T estende Número> | |
| BesselK1e <T estende Número> | |
| BesselY0 <T estende Número> | |
| BesselY1 <T estende Número> | |
| Bitcast <U> | Bitcasts um tensor de um tipo para outro sem copiar dados. |
| BlockLSTM <T estende o número> | Calcula a propagação direta da célula LSTM para todas as etapas de tempo. |
| BlockLSTM.Options | Atributos opcionais para BlockLSTM |
| BlocoLSTMGrad <T estende Número> | Calcula a propagação inversa da célula LSTM para toda a sequência de tempo. |
| BlockLSTMGradV2 <T extends Number> | Calcula a propagação inversa da célula LSTM para toda a sequência de tempo. |
| BlocoLSTMV2 <T estende o número> | Calcula a propagação direta da célula LSTM para todas as etapas de tempo. |
| BlocoLSTMV2.Options | Atributos opcionais para BlockLSTMV2 |
| BoostedTreesAggregateStats | Agrega o resumo das estatísticas acumuladas para o lote. |
| BoostedTreesBucketize | Organize cada recurso com base nos limites do intervalo. |
| BoostedTreesCalculateBestFeatureSplit | Calcula os ganhos para cada recurso e retorna as melhores informações de divisão possíveis para o recurso. |
| BoostedTreesCalculateBestFeatureSplit.Options | Atributos opcionais para BoostedTreesCalculateBestFeatureSplit |
| BoostedTreesCalculateBestFeatureSplitV2 | Calcula os ganhos para cada recurso e retorna as melhores informações de divisão possíveis para cada nó. |
| BoostedTreesCalculateBestGainsPer Feature | Calcula os ganhos para cada recurso e retorna as melhores informações de divisão possíveis para o recurso. |
| BoostedTreesCenterBias | Calcula o prior a partir dos dados de treinamento (o viés) e preenche o primeiro nó com o logits a priori. |
| BoostedTreesCreateEnsemble | Cria um modelo de conjunto de árvore e retorna um identificador para ele. |
| BoostedTreesCreateQuantileStreamResource | Crie o Recurso para Fluxos Quantile. |
| BoostedTreesCreateQuantileStreamResource.Options | Atributos opcionais para BoostedTreesCreateQuantileStreamResource |
| BoostedTreesDeserializeEnsemble | Desserializa uma configuração de conjunto de árvore serializada e substitui a árvore atual conjunto. |
| BoostedTreesEnsembleResourceHandleOp | Cria um identificador para um BoostedTreesEnsembleResource |
| BoostedTreesEnsembleResourceHandleOp.Options | Atributos opcionais para BoostedTreesEnsembleResourceHandleOp |
| BoostedTreesExampleDebugOutputs | Saídas de interpretabilidade de depuração/modelo para cada exemplo. |
| BoostedTreesFlushQuantileSummaries | Descarregue os resumos de quantil de cada recurso de fluxo de quantil. |
| BoostedTreesGetEnsembleStates | Recupera o token de carimbo de recurso do conjunto de árvores, o número de árvores e as estatísticas de crescimento. |
| BoostedTreesMakeQuantileSummaries | Faz o resumo dos quantis para o lote. |
| BoostedTreesMakeStatsSummary | Faz o resumo das estatísticas acumuladas para o lote. |
| BoostedTreesPredict | Executa vários preditores de conjunto de regressão aditiva em instâncias de entrada e calcula os logits. |
| BoostedTreesQuantileStreamResourceAddSummaries | Adicione os resumos de quantil a cada recurso de fluxo de quantil. |
| BoostedTreesQuantileStreamResourceDeserialize | Desserialize os limites do bucket e o sinalizador pronto no QuantileAccumulator atual. |
| BoostedTreesQuantileStreamResourceFlush | Descarregue os resumos para um recurso de fluxo quantil. |
| BoostedTreesQuantileStreamResourceFlush.Options | Atributos opcionais para BoostedTreesQuantileStreamResourceFlush |
| BoostedTreesQuantileStreamResourceGetBucketBoundaries | Gere os limites do bucket para cada recurso com base nos resumos acumulados. |
| BoostedTreesQuantileStreamResourceHandleOp | Cria um identificador para um BoostedTreesQuantileStreamResource. |
| BoostedTreesQuantileStreamResourceHandleOp.Options | Atributos opcionais para BoostedTreesQuantileStreamResourceHandleOp |
| BoostedTreesSerializeEnsemble | Serializa o conjunto de árvore para um proto. |
| BoostedTreesSparseAggregateStats | Agrega o resumo das estatísticas acumuladas para o lote. |
| BoostedTreesSparseCalculateBestFeatureSplit | Calcula os ganhos para cada recurso e retorna as melhores informações de divisão possíveis para o recurso. |
| BoostedTreesSparseCalculateBestFeatureSplit.Options | Atributos opcionais para BoostedTreesSparseCalculateBestFeatureSplit |
| BoostedTreesTrainingPredict | Executa vários preditores de conjunto de regressão aditiva em instâncias de entrada e calcula a atualização para logits em cache. |
| BoostedTreesUpdateEnsemble | Atualiza o conjunto de árvores adicionando uma camada à última árvore sendo cultivada ou iniciando uma nova árvore. |
| BoostedTreesUpdateEnsembleV2 | Atualiza o conjunto de árvores adicionando uma camada à última árvore que está sendo cultivada ou iniciando uma nova árvore. |
| BoostedTreesUpdateEnsembleV2.Options | Atributos opcionais para BoostedTreesUpdateEnsembleV2 |
| BroadcastDynamicShape <T estende o número> | Retorne a forma de s0 op s1 com broadcast. |
| BroadcastGradientArgs <T extends Number> | Retorne os índices de redução para calcular gradientes de s0 op s1 com transmissão. |
| TransmitirPara <T> | Transmitir uma matriz para uma forma compatível. |
| Balde | Faz intervalos de 'entrada' com base em 'limites'. |
| CacheDatasetV2 | |
| CacheDatasetV2.Options | Atributos opcionais para CacheDatasetV2 |
| CheckNumericsV2 <T estende o número> | Verifica um tensor para valores NaN, -Inf e +Inf. |
| EscolhaFastestDataset | |
| ClipPorValor <T> | Corta os valores do tensor para um mínimo e máximo especificados. |
| CollateTPUEmbeddingMemory | Uma operação que mescla os protos de configuração de memória codificados por string de todos os hosts. |
| CollectiveAllToAllV2 <T extends Number> | Troca mutuamente vários tensores de tipo e forma idênticos. |
| CollectiveAllToAllV2.Options | Atributos opcionais para CollectiveAllToAllV2 |
| CollectiveAllToAllV3 <T extends Number> | Troca mutuamente vários tensores de tipo e forma idênticos. |
| CollectiveAllToAllV3.Options | Atributos opcionais para CollectiveAllToAllV3 |
| CollectiveAssignGroupV2 | Atribua chaves de grupo com base na atribuição de grupo. |
| CollectiveBcastRecvV2 <U> | Recebe um valor de tensor transmitido de outro dispositivo. |
| CollectiveBcastRecvV2.Options | Atributos opcionais para CollectiveBcastRecvV2 |
| CollectiveBcastSendV2 <T> | Transmite um valor de tensor para um ou mais outros dispositivos. |
| CollectiveBcastSendV2.Options | Atributos opcionais para CollectiveBcastSendV2 |
| CollectiveGather <T estende o número> | Acumula mutuamente vários tensores de tipo e forma idênticos. |
| CollectiveGather.Options | Atributos opcionais para CollectiveGather |
| CollectiveGatherV2 <T extends Number> | Acumula mutuamente vários tensores de tipo e forma idênticos. |
| CollectiveGatherV2.Options | Atributos opcionais para CollectiveGatherV2 |
| CollectiveInitializeCommunicator | Inicializa um grupo para operações coletivas. |
| CollectiveInitializeCommunicator.Options | Atributos opcionais para CollectiveInitializeCommunicator |
| ColetivoPermute <T> | Uma opção para permutar tensores em instâncias de TPU replicadas. |
| CollectiveReduceScatterV2 <T extends Number> | Reduz mutuamente vários tensores de tipo e forma idênticos e espalha o resultado. |
| CollectiveReduceScatterV2.Options | Atributos opcionais para CollectiveReduceScatterV2 |
| CollectiveReduceV2 <T extends Number> | Reduz mutuamente vários tensores de tipo e forma idênticos. |
| CollectiveReduceV2.Options | Atributos opcionais para CollectiveReduceV2 |
| CollectiveReduceV3 <T extends Number> | Reduz mutuamente vários tensores de tipo e forma idênticos. |
| CollectiveReduceV3.Options | Atributos opcionais para CollectiveReduceV3 |
| Supressão Não Máxima Combinada | Seleciona avidamente um subconjunto de caixas delimitadoras em ordem decrescente de pontuação, Esta operação executa non_max_suppression nas entradas por lote, em todas as classes. |
| CombinedNonMaxSuppression.Options | Atributos opcionais para CombinedNonMaxSuppression |
| CompositeTensorVariantFromComponents | Codifica um valor `ExtensionType` em um tensor escalar `variant`. |
| CompositeTensorVariantToComponents | Decodifica um Tensor escalar `variante` em um valor `ExtensionType`. |
| CompressElement | Compacta um elemento do conjunto de dados. |
| ComputeBatchSize | Calcula o tamanho do lote estático de um conjunto de dados sem lotes parciais. |
| ComputeDedupDataTupleMask | Um op calcula a máscara de tupla de dados de desduplicação do núcleo de incorporação. |
| Concat <T> | Concatena tensores ao longo de uma dimensão. |
| ConfigureAndInitializeGlobalTPU | Uma operação que configura as estruturas centralizadas para um sistema TPU distribuído. |
| ConfigureAndInitializeGlobalTPU.Options | Atributos opcionais para ConfigureAndInitializeGlobalTPU |
| ConfigurarDistributedTPU | Configura as estruturas centralizadas para um sistema TPU distribuído. |
| ConfigureDistributedTPU.Options | Atributos opcionais para ConfigureDistributedTPU |
| ConfigurarTPUEmbedding | Configura o TPUEmbedding em um sistema TPU distribuído. |
| ConfigureTPUEmbeddingHost | Uma operação que configura o software TPUEmbedding em um host. |
| ConfigureTPUEmbeddingMemory | Uma operação que configura o software TPUEmbedding em um host. |
| ConnectTPUEmbeddingHosts | Uma operação que configura a comunicação entre instâncias de software host TPUEmbedding depois que ConfigureTPUEmbeddingHost foi chamado em cada host. |
| Constante <T> | Um operador que produz um valor constante. |
| ConsumirMutexLock | Esta operação consome um bloqueio criado por `MutexLock`. |
| ControlTrigger | Faz nada. |
| Conv2DBackpropFilterV2 <T extends Number> | Calcula os gradientes de convolução em relação ao filtro. |
| Conv2DBackpropFilterV2.Options | Atributos opcionais para Conv2DBackpropFilterV2 |
| Conv2DBackpropInputV2 <T extends Number> | Calcula os gradientes de convolução em relação à entrada. |
| Conv2DBackpropInputV2.Options | Atributos opcionais para Conv2DBackpropInputV2 |
| Copiar <T> | Copie um tensor de CPU para CPU ou GPU para GPU. |
| Copiar.Opções | Atributos opcionais para Copy |
| CopiarHost <T> | Copie um tensor para hospedar. |
| CopyHost.Options | Atributos opcionais para CopyHost |
| CopyToMesh <T> | |
| CopyToMeshGrad <T> | |
| CopyToMeshGrad.Options | Atributos opcionais para CopyToMeshGrad |
| CountUpTo <T estende o número> | Incrementa 'ref' até atingir 'limite'. |
| CrossReplicaSum <T estende o número> | Uma opção para somar entradas em instâncias de TPU replicadas. |
| CSRSparseMatrixComponents <T> | Lê os componentes CSR no lote `index`. |
| CSRSparseMatrixToDense <T> | Converta um CSRSparseMatrix (possivelmente em lote) em denso. |
| CSRSparseMatrixToSparseTensor <T> | Converte um CSRSparesMatrix (possivelmente em lote) em um SparseTensor. |
| Conjunto de dados CSV | |
| CSVDatasetV2 | |
| CTCLossV2 | Calcula a perda de CTC (probabilidade de log) para cada entrada de lote. |
| CTCLossV2.Options | Atributos opcionais para CTCLossV2 |
| CudnnRNNBackpropV3 <T estende o número> | Etapa de backprop de CudnnRNNV3. |
| CudnnRNNBackpropV3.Options | Atributos opcionais para CudnnRNNBackpropV3 |
| CudnnRNNCanonicalToParamsV2 <T extends Number> | Converte os parâmetros CudnnRNN da forma canônica para a forma utilizável. |
| CudnnRNNCanonicalToParamsV2.Options | Atributos opcionais para CudnnRNNCanonicalToParamsV2 |
| CudnnRNNParamsToCanonicalV2 <T extends Number> | Recupera os parâmetros CudnnRNN na forma canônica. |
| CudnnRNNParamsToCanonicalV2.Options | Atributos opcionais para CudnnRNNParamsToCanonicalV2 |
| CudnnRNNV3 <T estende Número> | Um RNN apoiado por cuDNN. |
| CudnnRNNV3.Options | Atributos opcionais para CudnnRNNV3 |
| CumulativeLogsumexp <T extends Number> | Calcule o produto cumulativo do tensor `x` ao longo do `axis`. |
| CumulativeLogsumexp.Options | Atributos opcionais para CumulativeLogsumexp |
| DataServiceDataset | Cria um conjunto de dados que lê dados do serviço tf.data. |
| DataServiceDataset.Options | Atributos opcionais para DataServiceDataset |
| DataServiceDatasetV2 | Cria um conjunto de dados que lê dados do serviço tf.data. |
| DataServiceDatasetV2.Options | Atributos opcionais para DataServiceDatasetV2 |
| DatasetCardinality | Retorna a cardinalidade de `input_dataset`. |
| DatasetCardinality.Options | Atributos opcionais para DatasetCardinality |
| DatasetFromGraph | Cria um conjunto de dados a partir do `graph_def` fornecido. |
| DatasetToGraphV2 | Retorna um GraphDef serializado representando `input_dataset`. |
| DatasetToGraphV2.Options | Atributos opcionais para DatasetToGraphV2 |
| Dawsn <T estende Número> | |
| DebugGradientIdentity <T> | Operação de identidade para depuração de gradiente. |
| DebugGradientRefIdentity <T> | Operação de identidade para depuração de gradiente. |
| DebugIdentity <T> | Fornece um mapeamento de identidade do tensor de entrada do tipo não Ref para depuração. |
| DebugIdentity.Options | Atributos opcionais para DebugIdentity |
| DebugIdentityV2 <T> | Depurar Identidade V2 Op. |
| DebugIdentityV2.Options | Atributos opcionais para DebugIdentityV2 |
| DebugNanCount | Depurar NaN Value Counter Op. |
| DebugNanCount.Options | Atributos opcionais para DebugNanCount |
| DebugNumericSummary | Op. de resumo numérico de depuração |
| DebugNumericSummary.Options | Atributos opcionais para DebugNumericSummary |
| DebugNumericSummaryV2 <U estende o número> | Resumo numérico de depuração V2 Op. |
| DebugNumericSummaryV2.Options | Atributos opcionais para DebugNumericSummaryV2 |
| DecodeImage <T extends Number> | Função para decode_bmp, decode_gif, decode_jpeg e decode_png. |
| DecodeImage.Options | Atributos opcionais para DecodeImage |
| DecodePaddedRaw <T estende o número> | Reinterprete os bytes de uma string como um vetor de números. |
| DecodePaddedRaw.Options | Atributos opcionais para DecodePaddedRaw |
| DecodeProto | A operação extrai campos de uma mensagem de buffer de protocolo serializado em tensores. |
| DecodeProto.Options | Atributos opcionais para DecodeProto |
| DeepCopy <T> | Faz uma cópia de `x`. |
| DeleteIterator | Um contêiner para um recurso iterador. |
| DeleteMemoryCache | |
| DeleteMultiDeviceIterator | Um contêiner para um recurso iterador. |
| DeleteRandomSeedGenerator | |
| DeleteSeedGenerator | |
| DeleteSessionTensor | Exclua o tensor especificado por seu identificador na sessão. |
| DenseBincount <U estende o número> | Conta o número de ocorrências de cada valor em uma matriz inteira. |
| DenseBincount.Options | Atributos opcionais para DenseBincount |
| DenseCountSparseOutput <U estende o número> | Executa a contagem de compartimentos de saída esparsa para uma entrada tf.tensor. |
| DenseCountSparseOutput.Options | Atributos opcionais para DenseCountSparseOutput |
| DenseToCSRSparseMatrix | Converte um tensor denso em um CSRSparseMatrix (possivelmente agrupado). |
| DestroyResourceOp | Exclui o recurso especificado pelo identificador. |
| DestroyResourceOp.Options | Atributos opcionais para DestroyResourceOp |
| DestroyTemporaryVariable <T> | Destrói a variável temporária e retorna seu valor final. |
| DeviceIndex | Retorna o índice do dispositivo que a operação executa. |
| DirectedInterleaveDataset | Um substituto para `InterleaveDataset` em uma lista fixa de conjuntos de dados `N`. |
| DirectedInterleaveDataset.Options | Atributos opcionais para DirectedInterleaveDataset |
| DisableCopyOnRead | Desativa o modo de cópia na leitura. |
| DistributedSave | |
| DistributedSave.Options | Atributos opcionais para DistributedSave |
| DrawBoundingBoxesV2 <T extends Number> | Desenhe caixas delimitadoras em um lote de imagens. |
| DTensorRestoreV2 | |
| DtensorSetGlobalTPUArray | Uma operação que informa a um host os IDs globais de todas as TPUs no sistema. |
| DummyIterationCounter | |
| DummyMemoryCache | |
| DummySeedGenerator | |
| DynamicEnqueueTPUEmbeddingArbitraryTensorBatch | Facilita a portabilidade do código que usa tf.nn.embedding_lookup_sparse(). |
| DynamicEnqueueTPUEmbeddingArbitraryTensorBatch.Options | Atributos opcionais para DynamicEnqueueTPUEmbeddingArbitraryTensorBatch |
| DynamicPartition <T> | Particiona `data` em tensores `num_partitions` usando índices de `partitions`. |
| Ponto Dinâmico <T> | Intercale os valores dos tensores `data` em um único tensor. |
| EditarDistancia | Calcula a distância de edição de Levenshtein (possivelmente normalizada). |
| EditDistance.Options | Atributos opcionais para EditDistance |
| Eig <u> | Calcula a autodecomposição de uma ou mais matrizes quadradas. |
| Eig.Options | Atributos opcionais para Eig |
| Einsum <T> | Contração do tensor de acordo com a convenção de somatório de Einstein. |
| Vazio <T> | Cria um tensor com a forma dada. |
| Vazio.Opções | Atributos opcionais para Empty |
| EmptyTensorList | Cria e retorna uma lista de tensores vazia. |
| EmptyTensorMap | Cria e retorna um mapa tensor vazio. |
| EncodeProto | O op serializa as mensagens protobuf fornecidas nos tensores de entrada. |
| EncodeProto.Options | Atributos opcionais para EncodeProto |
| EnqueueTPUEmbeddingArbitraryTensorBatch | Facilita a portabilidade do código que usa tf.nn.embedding_lookup_sparse(). |
| EnqueueTPUEmbeddingArbitraryTensorBatch.Options | Atributos opcionais para EnqueueTPUEmbeddingArbitraryTensorBatch |
| EnfileirarTPUEmbeddingBatch | Uma operação que enfileira uma lista de tensores de lote de entrada para TPUEmbedding. |
| EnqueueTPUEmbeddingBatch.Options | Atributos opcionais para EnqueueTPUEmbeddingBatch |
| EnqueueTPUEmbeddingIntegerBatch | Uma operação que enfileira uma lista de tensores de lote de entrada para TPUEmbedding. |
| EnqueueTPUEmbeddingIntegerBatch.Options | Atributos opcionais para EnqueueTPUEmbeddingIntegerBatch |
| EnqueueTPUEmbeddingRaggedTensorBatch | Facilita a portabilidade do código que usa tf.nn.embedding_lookup(). |
| EnqueueTPUEmbeddingRaggedTensorBatch.Options | Atributos opcionais para EnqueueTPUEmbeddingRaggedTensorBatch |
| EnfileirarTPUEmbeddingSparseBatch | Uma operação que enfileira índices de entrada TPUEmbedding de um SparseTensor. |
| EnqueueTPUEmbeddingSparseBatch.Options | Atributos opcionais para EnqueueTPUEmbeddingSparseBatch |
| EnqueueTPUEmbeddingSparseTensorBatch | Facilita a portabilidade do código que usa tf.nn.embedding_lookup_sparse(). |
| EnqueueTPUEmbeddingSparseTensorBatch.Options | Atributos opcionais para EnqueueTPUEmbeddingSparseTensorBatch |
| GarantirForma <T> | Garante que a forma do tensor corresponda à forma esperada. |
| Digite <T> | Cria ou localiza um quadro filho e disponibiliza `dados` para o quadro filho. |
| Enter.Options | Atributos opcionais para Enter |
| Erfinv <T estende Número> | |
| Norma Euclidiana <T> | Calcula a norma euclidiana de elementos nas dimensões de um tensor. |
| EuclideanNorm.Options | Atributos opcionais para EuclideanNorm |
| ExecuteTPUEmbeddingPartitioner | Uma operação que executa o particionador TPUEmbedding na configuração central dispositivo e calcula o tamanho do HBM (em bytes) necessário para a operação TPUEmbedding. |
| Sair <T> | Sai do quadro atual para seu quadro pai. |
| ExpandDims <T> | Insere uma dimensão de 1 na forma de um tensor. |
| ExperimentalAutoShardDataset | Cria um conjunto de dados que fragmenta o conjunto de dados de entrada. |
| ExperimentalAutoShardDataset.Options | Atributos opcionais para ExperimentalAutoShardDataset |
| ExperimentalBytesProposedStatsDataset | Registra o tamanho de bytes de cada elemento de `input_dataset` em um StatsAggregator. |
| ExperimentalChooseFastestDataset | |
| ExperimentalDatasetCardinality | Retorna a cardinalidade de `input_dataset`. |
| ExperimentalDatasetToTFRecord | Grava o conjunto de dados fornecido no arquivo fornecido usando o formato TFRecord. |
| ExperimentalDenseToSparseBatchDataset | Cria um conjunto de dados que agrupa elementos de entrada em um SparseTensor. |
| ExperimentalLatencyStatsDataset | Registra a latência de produção de elementos `input_dataset` em um StatsAggregator. |
| ExperimentalMatchingFilesDataset | |
| ExperimentalMaxIntraOpParallelismDataset | Cria um conjunto de dados que substitui o paralelismo intra-operacional máximo. |
| ExperimentalParseExampleDataset | Transforma `input_dataset` contendo protos `Example` como vetores de DT_STRING em um conjunto de dados de objetos `Tensor` ou `SparseTensor` que representam os recursos analisados. |
| ExperimentalParseExampleDataset.Options | Atributos opcionais para ExperimentalParseExampleDataset |
| ExperimentalPrivateThreadPoolDataset | Cria um conjunto de dados que usa um pool de encadeamento personalizado para calcular `input_dataset`. |
| ExperimentalRandomDataset | Cria um conjunto de dados que retorna números pseudoaleatórios. |
| ExperimentalRebatchDataset | Cria um conjunto de dados que altera o tamanho do lote. |
| ExperimentalRebatchDataset.Options | Atributos opcionais para ExperimentalRebatchDataset |
| ExperimentalSetStatsAggregatorDataset | |
| ExperimentalSlidingWindowDataset | Cria um conjunto de dados que passa uma janela deslizante sobre `input_dataset`. |
| ExperimentalSqlDataset | Cria um conjunto de dados que executa uma consulta SQL e emite linhas do conjunto de resultados. |
| ExperimentalStatsAggregatorHandle | Cria um recurso de gerenciador de estatísticas. |
| ExperimentalStatsAggregatorHandle.Options | Atributos opcionais para ExperimentalStatsAggregatorHandle |
| ExperimentalStatsAggregatorResumo | Produz um resumo de todas as estatísticas registradas pelo gerenciador de estatísticas fornecido. |
| ExperimentalUnbatchDataset | Um conjunto de dados que divide os elementos de sua entrada em vários elementos. |
| Expint <T estende Número> | |
| ExtractGlimpseV2 | Extrai um vislumbre do tensor de entrada. |
| ExtractGlimpseV2.Options | Atributos opcionais para ExtractGlimpseV2 |
| ExtractVolumePatches <T extends Number> | Extraia `patches` de `input` e coloque-os na dimensão de saída `"profundidade"`. |
| FileSystemSetConfiguration | Defina a configuração do sistema de arquivos. |
| Preencher <U> | Cria um tensor preenchido com um valor escalar. |
| FinalizeDataset | Cria um conjunto de dados aplicando tf.data.Options a `input_dataset`. |
| FinalizeDataset.Options | Atributos opcionais para FinalizeDataset |
| FinalizeTPUEmbedding | Uma operação que finaliza a configuração do TPUEmbedding. |
| Impressão digital | Gera valores de impressão digital. |
| FresnelCos <T estende Número> | |
| FresnelSin <T estende o número> | |
| FusedBatchNormGradV3 <T estende o número, U estende o número> | Gradiente para normalização em lote. |
| FusedBatchNormGradV3.Options | Atributos opcionais para FusedBatchNormGradV3 |
| FusedBatchNormV3 <T estende o número, U estende o número> | Normalização de lote. |
| FusedBatchNormV3.Options | Atributos opcionais para FusedBatchNormV3 |
| Reunir <T> | Reúna as fatias do eixo `params` do `eixo` de acordo com os `índices`. |
| Reunir.Opções | Atributos opcionais para Gather |
| Reunir Nd <T> | Reúna fatias de `params` em um tensor com forma especificada por `índices`. |
| Gerar BoundingBoxProposals | Esta operação produz a Região de Interesses de determinadas âncoras wrt codificadas em caixas delimitadoras (bbox_deltas) de acordo com a eq.2 em arXiv:1506.01497 A operação seleciona as principais caixas de pontuação `pre_nms_topn`, decodifica-as em relação às âncoras, aplica supressão não máxima em caixas sobrepostas com valor de interseção sobre união (iou) superior a `nms_threshold`, descartando caixas onde o lado mais curto é menor que ` min_size`. |
| GenerateBoundingBoxProposals.Options | Atributos opcionais para GenerateBoundingBoxProposals |
| GetElementAtIndex | Obtém o elemento no índice especificado em um conjunto de dados. |
| GetOptions | Retorna o tf.data.Options anexado a `input_dataset`. |
| GetSessionHandle | Armazene o tensor de entrada no estado da sessão atual. |
| GetSessionTensor <T> | Obtenha o valor do tensor especificado por seu identificador. |
| Gradientes | Adiciona operações para calcular as derivadas parciais da soma de y s wrt x s, ou seja, d(y_1 + y_2 + ...)/dx_1, d(y_1 + y_2 + ...)/dx_2... Se os valores |
| Gradientes.Opções | Atributos opcionais para Gradients |
| GRUBlockCell <T estende o número> | Calcula a propagação direta da célula GRU para 1 intervalo de tempo. |
| GRUBlockCellGrad <T estende o número> | Calcula a retropropagação da célula GRU para 1 intervalo de tempo. |
| GarantiaConst <T> | Garante ao tempo de execução do TF que o tensor de entrada é uma constante. |
| HashTable | Cria uma tabela de hash não inicializada. |
| HashTable.Options | Atributos opcionais para HashTable |
| HistogramFixedWidth <U estende o número> | Retorna o histograma de valores. |
| Identidade <T> | Retorna um tensor com a mesma forma e conteúdo do tensor ou valor de entrada. |
| Identidade N | Retorna uma lista de tensores com as mesmas formas e conteúdos da entrada tensores. |
| IgnoreErrorsDataset | Cria um conjunto de dados que contém os elementos de `input_dataset` ignorando erros. |
| IgnoreErrorsDataset.Options | Atributos opcionais para IgnoreErrorsDataset |
| ImageProjectiveTransformV2 <T extends Number> | Aplica a transformação fornecida a cada uma das imagens. |
| ImageProjectiveTransformV2.Options | Atributos opcionais para ImageProjectiveTransformV2 |
| ImageProjectiveTransformV3 <T extends Number> | Aplica a transformação fornecida a cada uma das imagens. |
| ImageProjectiveTransformV3.Options | Atributos opcionais para ImageProjectiveTransformV3 |
| ImmutableConst <T> | Retorna o tensor imutável da região da memória. |
| EntradaDefila <T> | Uma opção de espaço reservado para um valor que será inserido na computação. |
| InfeedDequeueTuple | Busca vários valores do feed como uma tupla XLA. |
| EntradaEnfileirar | Uma operação que alimenta um único valor do Tensor na computação. |
| InfeedEnqueue.Options | Atributos opcionais para InfeedEnqueue |
| InfeedEnqueuePrelinearizedBuffer | Uma operação que enfileira o buffer pré-linearizado na alimentação da TPU. |
| InfeedEnqueuePrelinearizedBuffer.Options | Atributos opcionais para InfeedEnqueuePrelinearizedBuffer |
| InfeedEnqueueTuple | Alimenta vários valores do Tensor no cálculo como uma tupla XLA. |
| InfeedEnqueueTuple.Options | Atributos opcionais para InfeedEnqueueTuple |
| InitializeTable | Inicializador de tabela que usa dois tensores para chaves e valores, respectivamente. |
| InitializeTableFromDataset | |
| InitializeTableFromTextFile | Inicializa uma tabela a partir de um arquivo de texto. |
| InitializeTableFromTextFile.Options | Atributos opcionais para InitializeTableFromTextFile |
| InplaceAdd <T> | Adiciona v em linhas especificadas de x. |
| InplaceSub <T> | Subtrai `v` em linhas especificadas de `x`. |
| InplaceUpdate <T> | Atualiza as linhas especificadas 'i' com valores 'v'. |
| IsBoostedTreesEnsembleInitialized | Verifica se um conjunto de árvore foi inicializado. |
| IsBoostedTreesQuantileStreamResourceInitialized | Verifica se um fluxo de quantil foi inicializado. |
| Regressão Isotônica <U estende o Número> | Resolve um lote de problemas de regressão isotônica. |
| IsTPUEmbeddingInitialized | Se a incorporação de TPU foi inicializada em um sistema de TPU distribuído. |
| IsTPUEmbeddingInitialized.Options | Atributos opcionais para IsTPUEmbeddingInitialized |
| ÉVariávelInicializada | Verifica se um tensor foi inicializado. |
| IteratorGetDevice | Retorna o nome do dispositivo no qual o `recurso` foi colocado. |
| KMC2ChainInicialization | Retorna o índice de um ponto de dados que deve ser adicionado ao conjunto de sementes. |
| KmeansPlusPlusInicialization | Seleciona linhas num_to_sample de entrada usando o critério KMeans++. |
| KthOrderStatistic | Calcula a estatística de ordem K de um conjunto de dados. |
| LinSpace <T estende o número> | Gera valores em um intervalo. |
| ListDataset | Cria um conjunto de dados que emite cada um dos `tensores` uma vez. |
| ListDataset.Options | Atributos opcionais para ListDataset |
| Conjunto de dados LMDB | Cria um conjunto de dados que emite os pares chave-valor em um ou mais arquivos LMDB. |
| LoadAllTPUEmbeddingParameters | Uma operação que carrega parâmetros de otimização na memória incorporada. |
| LoadTPUEmbeddingAdadeltaParameters | Carregue os parâmetros de incorporação Adadelta. |
| LoadTPUEmbeddingAdadeltaParameters.Options | Atributos opcionais para LoadTPUEmbeddingAdadeltaParameters |
| LoadTPUEmbeddingAdagradMomentumParameters | Carregue os parâmetros de incorporação do Adagrad Momentum. |
| LoadTPUEmbeddingAdagradMomentumParameters.Options | Atributos opcionais para LoadTPUEmbeddingAdagradMomentumParameters |
| LoadTPUEmbeddingAdagradParameters | Carregue os parâmetros de incorporação do Adagrad. |
| LoadTPUEmbeddingAdagradParameters.Options | Atributos opcionais para LoadTPUEmbeddingAdagradParameters |
| LoadTPUEmbeddingADAMParameters | Carregue os parâmetros de incorporação do ADAM. |
| LoadTPUEmbeddingADAMParameters.Options | Atributos opcionais para LoadTPUEmbeddingADAMParameters |
| LoadTPUEmbeddingCenteredRMSPropParameters | Carregue os parâmetros de incorporação RMSProp centrados. |
| LoadTPUEmbeddingCenteredRMSPropParameters.Options | Atributos opcionais para LoadTPUEmbeddingCenteredRMSPropParameters |
| LoadTPUEmbeddingFrequencyEstimatorParameters | Parâmetros de incorporação do estimador de frequência de carga. |
| LoadTPUEmbeddingFrequencyEstimatorParameters.Options | Atributos opcionais para LoadTPUEmbeddingFrequencyEstimatorParameters |
| LoadTPUEmbeddingFTRLParameters | Carregue os parâmetros de incorporação FTRL. |
| LoadTPUEmbeddingFTRLParameters.Options | Atributos opcionais para LoadTPUEmbeddingFTRLParameters |
| LoadTPUEmbeddingMDLAdagradLightParameters | Carregue os parâmetros de incorporação MDL Adagrad Light. |
| LoadTPUEmbeddingMDLAdagradLightParameters.Options | Atributos opcionais para LoadTPUEmbeddingMDLAdagradLightParameters |
| LoadTPUEmbeddingMomentumParameters | Carregar os parâmetros de incorporação do Momentum. |
| LoadTPUEmbeddingMomentumParameters.Options | Atributos opcionais para LoadTPUEmbeddingMomentumParameters |
| LoadTPUEmbeddingProximalAdagradParameters | Carregue os parâmetros de incorporação proximais do Adagrad. |
| LoadTPUEmbeddingProximalAdagradParameters.Options | Atributos opcionais para LoadTPUEmbeddingProximalAdagradParameters |
| LoadTPUEmbeddingProximalYogiParameters | |
| LoadTPUEmbeddingProximalYogiParameters.Options | Atributos opcionais para LoadTPUEmbeddingProximalYogiParameters |
| LoadTPUEmbeddingRMSPropParameters | Carregue os parâmetros de incorporação RMSProp. |
| LoadTPUEmbeddingRMSPropParameters.Options | Atributos opcionais para LoadTPUEmbeddingRMSPropParameters |
| LoadTPUEmbeddingStochasticGradientDescentParameters | Carregar parâmetros de incorporação SGD. |
| LoadTPUEmbeddingStochasticGradientDescentParameters.Options | Optional attributes for LoadTPUEmbeddingStochasticGradientDescentParameters |
| LookupTableExport <T, U> | Outputs all keys and values in the table. |
| LookupTableFind <U> | 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. |
| LowerBound <U extends Number> | Applies lower_bound(sorted_search_values, values) along each row. |
| LSTMBlockCell <T extends Number> | Computes the LSTM cell forward propagation for 1 time step. |
| LSTMBlockCell.Options | Optional attributes for LSTMBlockCell |
| LSTMBlockCellGrad <T extends Number> | Computes the LSTM cell backward propagation for 1 timestep. |
| Lu <T, U extends Number> | Computes the LU decomposition of one or more square matrices. |
| 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 |
| MapIncompleteSize | Op returns the number of incomplete elements in the underlying container. |
| MapIncompleteSize.Options | Optional attributes for MapIncompleteSize |
| 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 |
| MatrixDiagPartV2 <T> | Returns the batched diagonal part of a batched tensor. |
| MatrixDiagPartV3 <T> | Returns the batched diagonal part of a batched tensor. |
| MatrixDiagPartV3.Options | Optional attributes for MatrixDiagPartV3 |
| MatrixDiagV2 <T> | Returns a batched diagonal tensor with given batched diagonal values. |
| MatrixDiagV3 <T> | Returns a batched diagonal tensor with given batched diagonal values. |
| MatrixDiagV3.Options | Optional attributes for MatrixDiagV3 |
| MatrixSetDiagV2 <T> | Returns a batched matrix tensor with new batched diagonal values. |
| MatrixSetDiagV3 <T> | Returns a batched matrix tensor with new batched diagonal values. |
| MatrixSetDiagV3.Options | Optional attributes for MatrixSetDiagV3 |
| Max <T> | Computes the maximum of elements across dimensions of a tensor. |
| Max.Options | Optional attributes for Max |
| MaxIntraOpParallelismDataset | Creates a dataset that overrides the maximum intra-op parallelism. |
| Merge <T> | Forwards the value of an available tensor from `inputs` to `output`. |
| MergeDedupData | An op merges elements of integer and float tensors into deduplication data as XLA tuple. |
| MergeDedupData.Options | Optional attributes for MergeDedupData |
| Min <T> | Computes the minimum of elements across dimensions of a tensor. |
| Min.Options | Optional attributes for Min |
| MirrorPad <T> | Pads a tensor with mirrored values. |
| MirrorPadGrad <T> | Gradient op for `MirrorPad` op. |
| MlirPassthroughOp | Wraps an arbitrary MLIR computation expressed as a module with a main() function. |
| MulNoNan <T> | Returns x * y element-wise. |
| 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. |
| NcclAllReduce <T extends Number> | Outputs a tensor containing the reduction across all input tensors. |
| NcclBroadcast <T extends Number> | Sends `input` to all devices that are connected to the output. |
| NcclReduce <T extends Number> | Reduces `input` from `num_devices` using `reduction` to a single device. |
| Ndtri <T extends Number> | |
| NearestNeighbors | Selects the k nearest centers for each point. |
| NextAfter <T extends Number> | Returns the next representable value of `x1` in the direction of `x2`, element-wise. |
| NextIteration <T> | Makes its input available to the next iteration. |
| NonDeterministicInts <U> | Non-deterministically generates some integers. |
| NonMaxSuppressionV5 <T extends Number> | 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. |
| NonMaxSuppressionV5.Options | Optional attributes for NonMaxSuppressionV5 |
| NonSerializableDataset | |
| NoOp | Does nothing. |
| OneHot <U> | Returns a one-hot tensor. |
| OneHot.Options | Optional attributes for OneHot |
| OnesLike <T> | Returns a tensor of ones with the same shape and type as x. |
| OptimizeDatasetV2 | Creates a dataset by applying related optimizations to `input_dataset`. |
| OptimizeDatasetV2.Options | Optional attributes for OptimizeDatasetV2 |
| OptionsDataset | Creates a dataset by attaching tf.data.Options to `input_dataset`. |
| OptionsDataset.Options | Optional attributes for OptionsDataset |
| 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 |
| OutfeedDequeue <T> | 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> | 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. |
| Pad <T> | Pads a tensor. |
| ParallelBatchDataset | |
| ParallelBatchDataset.Options | Optional attributes for ParallelBatchDataset |
| ParallelConcat <T> | Concatenates a list of `N` tensors along the first dimension. |
| ParallelDynamicStitch <T> | Interleave the values from the `data` tensors into a single tensor. |
| ParseExampleDatasetV2 | Transforms `input_dataset` containing `Example` protos as vectors of DT_STRING into a dataset of `Tensor` or `SparseTensor` objects representing the parsed features. |
| ParseExampleDatasetV2.Options | Optional attributes for ParseExampleDatasetV2 |
| ParseExampleV2 | Transforms a vector of tf.Example protos (as strings) into typed tensors. |
| ParseSequenceExampleV2 | Transforms a vector of tf.io.SequenceExample protos (as strings) into typed tensors. |
| ParseSequenceExampleV2.Options | Optional attributes for ParseSequenceExampleV2 |
| Placeholder <T> | A placeholder op for a value that will be fed into the computation. |
| Placeholder.Options | Optional attributes for Placeholder |
| PlaceholderWithDefault <T> | A placeholder op that passes through `input` when its output is not fed. |
| 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 |
| Prints a string scalar. | |
| Print.Options | Optional attributes for Print |
| PrivateThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| Prod <T> | Computes the product of elements across dimensions of a tensor. |
| Prod.Options | Optional attributes for Prod |
| QuantizeAndDequantizeV4 <T extends Number> | Quantizes then dequantizes a tensor. |
| QuantizeAndDequantizeV4.Options | Optional attributes for QuantizeAndDequantizeV4 |
| QuantizeAndDequantizeV4Grad <T extends Number> | Returns the gradient of `QuantizeAndDequantizeV4`. |
| QuantizeAndDequantizeV4Grad.Options | Optional attributes for QuantizeAndDequantizeV4Grad |
| QuantizedConcat <T> | Concatenates quantized tensors along one dimension. |
| QuantizedConcatV2 <T> | |
| QuantizedConv2DAndRelu <V> | |
| QuantizedConv2DAndRelu.Options | Optional attributes for QuantizedConv2DAndRelu |
| QuantizedConv2DAndReluAndRequantize <V> | |
| QuantizedConv2DAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DAndReluAndRequantize |
| QuantizedConv2DAndRequantize <V> | |
| QuantizedConv2DAndRequantize.Options | Optional attributes for QuantizedConv2DAndRequantize |
| QuantizedConv2DPerChannel <V> | Computes QuantizedConv2D per channel. |
| QuantizedConv2DPerChannel.Options | Optional attributes for QuantizedConv2DPerChannel |
| QuantizedConv2DWithBias <V> | |
| QuantizedConv2DWithBias.Options | Optional attributes for QuantizedConv2DWithBias |
| QuantizedConv2DWithBiasAndRelu <V> | |
| QuantizedConv2DWithBiasAndRelu.Options | Optional attributes for QuantizedConv2DWithBiasAndRelu |
| QuantizedConv2DWithBiasAndReluAndRequantize <W> | |
| QuantizedConv2DWithBiasAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasAndReluAndRequantize |
| QuantizedConv2DWithBiasAndRequantize <W> | |
| QuantizedConv2DWithBiasAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasAndRequantize |
| QuantizedConv2DWithBiasSignedSumAndReluAndRequantize <X> | |
| QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasSignedSumAndReluAndRequantize |
| QuantizedConv2DWithBiasSumAndRelu <V> | |
| QuantizedConv2DWithBiasSumAndRelu.Options | Optional attributes for QuantizedConv2DWithBiasSumAndRelu |
| QuantizedConv2DWithBiasSumAndReluAndRequantize <X> | |
| QuantizedConv2DWithBiasSumAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasSumAndReluAndRequantize |
| QuantizedDepthwiseConv2D <V> | Computes quantized depthwise Conv2D. |
| QuantizedDepthwiseConv2D.Options | Optional attributes for QuantizedDepthwiseConv2D |
| QuantizedDepthwiseConv2DWithBias <V> | Computes quantized depthwise Conv2D with Bias. |
| QuantizedDepthwiseConv2DWithBias.Options | Optional attributes for QuantizedDepthwiseConv2DWithBias |
| QuantizedDepthwiseConv2DWithBiasAndRelu <V> | Computes quantized depthwise Conv2D with Bias and Relu. |
| QuantizedDepthwiseConv2DWithBiasAndRelu.Options | Optional attributes for QuantizedDepthwiseConv2DWithBiasAndRelu |
| QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize <W> | Computes quantized depthwise Conv2D with Bias, Relu and Requantize. |
| QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.Options | Optional attributes for QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize |
| QuantizedMatMulWithBias <W> | Performs a quantized matrix multiplication of `a` by the matrix `b` with bias add. |
| QuantizedMatMulWithBias.Options | Optional attributes for QuantizedMatMulWithBias |
| QuantizedMatMulWithBiasAndDequantize <W extends Number> | |
| QuantizedMatMulWithBiasAndDequantize.Options | Optional attributes for QuantizedMatMulWithBiasAndDequantize |
| QuantizedMatMulWithBiasAndRelu <V> | 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> | 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> | |
| QuantizedMatMulWithBiasAndRequantize.Options | Optional attributes for QuantizedMatMulWithBiasAndRequantize |
| QuantizedReshape <T> | Reshapes a quantized tensor as per the Reshape op. |
| RaggedBincount <U extends Number> | Counts the number of occurrences of each value in an integer array. |
| RaggedBincount.Options | Optional attributes for RaggedBincount |
| RaggedCountSparseOutput <U extends Number> | Performs sparse-output bin counting for a ragged tensor input. |
| RaggedCountSparseOutput.Options | Optional attributes for RaggedCountSparseOutput |
| RaggedCross <T, U extends Number> | Generates a feature cross from a list of tensors, and returns it as a RaggedTensor. |
| RaggedFillEmptyRows <T> | |
| RaggedFillEmptyRowsGrad <T> | |
| RaggedGather <T extends Number, U> | Gather ragged slices from `params` axis `0` according to `indices`. |
| RaggedRange <U extends Number, T extends Number> | Returns a `RaggedTensor` containing the specified sequences of numbers. |
| RaggedTensorFromVariant <U extends Number, T> | Decodes a `variant` Tensor into a `RaggedTensor`. |
| RaggedTensorToSparse <U> | Converts a `RaggedTensor` into a `SparseTensor` with the same values. |
| RaggedTensorToTensor <U> | Create a dense tensor from a ragged tensor, possibly altering its shape. |
| RaggedTensorToVariant | Encodes a `RaggedTensor` into a `variant` Tensor. |
| RaggedTensorToVariantGradient <U> | Helper used to compute the gradient for `RaggedTensorToVariant`. |
| RandomDatasetV2 | Creates a Dataset that returns pseudorandom numbers. |
| RandomDatasetV2.Options | Optional attributes for RandomDatasetV2 |
| RandomIndexShuffle <T extends Number> | Outputs the position of `value` in a permutation of [0, ..., max_index]. |
| RandomIndexShuffle.Options | Optional attributes for RandomIndexShuffle |
| Range <T extends Number> | Creates a sequence of numbers. |
| Rank | Returns the rank of a tensor. |
| ReadVariableOp <T> | Reads the value of a variable. |
| ReadVariableXlaSplitND <T> | Splits resource variable input tensor across all dimensions. |
| ReadVariableXlaSplitND.Options | Optional attributes for ReadVariableXlaSplitND |
| RebatchDataset | Creates a dataset that changes the batch size. |
| RebatchDataset.Options | Optional attributes for RebatchDataset |
| RebatchDatasetV2 | Creates a dataset that changes the batch size. |
| Recv <T> | Receives the named tensor from send_device on recv_device. |
| Recv.Options | Optional attributes for Recv |
| RecvTPUEmbeddingActivations | An op that receives embedding activations on the TPU. |
| 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 |
| ReduceMax <T> | Computes the maximum of elements across dimensions of a tensor. |
| ReduceMax.Options | Optional attributes for ReduceMax |
| ReduceMin <T> | Computes the minimum of elements across dimensions of a tensor. |
| ReduceMin.Options | Optional attributes for ReduceMin |
| ReduceProd <T> | Computes the product of elements across dimensions of a tensor. |
| ReduceProd.Options | Optional attributes for ReduceProd |
| ReduceSum <T> | Computes the sum of elements across dimensions of a tensor. |
| ReduceSum.Options | Optional attributes for ReduceSum |
| RefEnter <T> | Creates or finds a child frame, and makes `data` available to the child frame. |
| RefEnter.Options | Optional attributes for RefEnter |
| RefExit <T> | Exits the current frame to its parent frame. |
| RefIdentity <T> | Return the same ref tensor as the input ref tensor. |
| RefMerge <T> | Forwards the value of an available tensor from `inputs` to `output`. |
| RefNextIteration <T> | Makes its input available to the next iteration. |
| RefSelect <T> | Forwards the `index`th element of `inputs` to `output`. |
| RefSwitch <T> | Forwards the ref tensor `data` to the output port determined by `pred`. |
| RegisterDataset | Registers a dataset with the tf.data service. |
| RegisterDataset.Options | Optional attributes for RegisterDataset |
| RegisterDatasetV2 | Registers a dataset with the tf.data service. |
| RegisterDatasetV2.Options | Optional attributes for RegisterDatasetV2 |
| Relayout <T> | |
| RelayoutGrad <T> | |
| RequantizationRangePerChannel | Computes requantization range per channel. |
| RequantizePerChannel <U> | Requantizes input with min and max values known per channel. |
| Reshape <T> | Reshapes a tensor. |
| 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> | Extracts the average gradient in the given ConditionalAccumulator. |
| ResourceApplyAdagradV2 | Update '*var' according to the adagrad scheme. |
| ResourceApplyAdagradV2.Options | Optional attributes for ResourceApplyAdagradV2 |
| ResourceApplyAdamWithAmsgrad | Update '*var' according to the Adam algorithm. |
| ResourceApplyAdamWithAmsgrad.Options | Optional attributes for ResourceApplyAdamWithAmsgrad |
| ResourceApplyKerasMomentum | Update '*var' according to the momentum scheme. |
| ResourceApplyKerasMomentum.Options | Optional attributes for ResourceApplyKerasMomentum |
| ResourceConditionalAccumulator | A conditional accumulator for aggregating gradients. |
| ResourceConditionalAccumulator.Options | Optional attributes for ResourceConditionalAccumulator |
| ResourceCountUpTo <T extends Number> | Increments variable pointed to by 'resource' until it reaches 'limit'. |
| ResourceGather <U> | Gather slices from the variable pointed to by `resource` according to `indices`. |
| ResourceGather.Options | Optional attributes for ResourceGather |
| ResourceGatherNd <U> | |
| 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`. |
| ResourceSparseApplyAdagradV2 | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
| ResourceSparseApplyAdagradV2.Options | Optional attributes for ResourceSparseApplyAdagradV2 |
| ResourceSparseApplyKerasMomentum | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
| ResourceSparseApplyKerasMomentum.Options | Optional attributes for ResourceSparseApplyKerasMomentum |
| ResourceStridedSliceAssign | Assign `value` to the sliced l-value reference of `ref`. |
| ResourceStridedSliceAssign.Options | Optional attributes for ResourceStridedSliceAssign |
| RetrieveAllTPUEmbeddingParameters | An op that retrieves optimization parameters from embedding to host memory. |
| RetrieveTPUEmbeddingAdadeltaParameters | Retrieve Adadelta embedding parameters. |
| RetrieveTPUEmbeddingAdadeltaParameters.Options | Optional attributes for RetrieveTPUEmbeddingAdadeltaParameters |
| RetrieveTPUEmbeddingAdagradMomentumParameters | Retrieve Adagrad Momentum embedding parameters. |
| RetrieveTPUEmbeddingAdagradMomentumParameters.Options | Optional attributes for RetrieveTPUEmbeddingAdagradMomentumParameters |
| RetrieveTPUEmbeddingAdagradParameters | Retrieve Adagrad embedding parameters. |
| RetrieveTPUEmbeddingAdagradParameters.Options | Optional attributes for RetrieveTPUEmbeddingAdagradParameters |
| RetrieveTPUEmbeddingADAMParameters | Retrieve ADAM embedding parameters. |
| RetrieveTPUEmbeddingADAMParameters.Options | Optional attributes for RetrieveTPUEmbeddingADAMParameters |
| RetrieveTPUEmbeddingCenteredRMSPropParameters | Retrieve centered RMSProp embedding parameters. |
| RetrieveTPUEmbeddingCenteredRMSPropParameters.Options | Optional attributes for RetrieveTPUEmbeddingCenteredRMSPropParameters |
| RetrieveTPUEmbeddingFrequencyEstimatorParameters | Retrieve frequency estimator embedding parameters. |
| RetrieveTPUEmbeddingFrequencyEstimatorParameters.Options | Optional attributes for RetrieveTPUEmbeddingFrequencyEstimatorParameters |
| RetrieveTPUEmbeddingFTRLParameters | Retrieve FTRL embedding parameters. |
| RetrieveTPUEmbeddingFTRLParameters.Options | Optional attributes for RetrieveTPUEmbeddingFTRLParameters |
| RetrieveTPUEmbeddingMDLAdagradLightParameters | Retrieve MDL Adagrad Light embedding parameters. |
| RetrieveTPUEmbeddingMDLAdagradLightParameters.Options | Optional attributes for RetrieveTPUEmbeddingMDLAdagradLightParameters |
| RetrieveTPUEmbeddingMomentumParameters | Retrieve Momentum embedding parameters. |
| RetrieveTPUEmbeddingMomentumParameters.Options | Optional attributes for RetrieveTPUEmbeddingMomentumParameters |
| RetrieveTPUEmbeddingProximalAdagradParameters | Retrieve proximal Adagrad embedding parameters. |
| RetrieveTPUEmbeddingProximalAdagradParameters.Options | Optional attributes for RetrieveTPUEmbeddingProximalAdagradParameters |
| RetrieveTPUEmbeddingProximalYogiParameters | |
| RetrieveTPUEmbeddingProximalYogiParameters.Options | Optional attributes for RetrieveTPUEmbeddingProximalYogiParameters |
| RetrieveTPUEmbeddingRMSPropParameters | Retrieve RMSProp embedding parameters. |
| RetrieveTPUEmbeddingRMSPropParameters.Options | Optional attributes for RetrieveTPUEmbeddingRMSPropParameters |
| RetrieveTPUEmbeddingStochasticGradientDescentParameters | Retrieve SGD embedding parameters. |
| RetrieveTPUEmbeddingStochasticGradientDescentParameters.Options | Optional attributes for RetrieveTPUEmbeddingStochasticGradientDescentParameters |
| Reverse <T> | Reverses specific dimensions of a tensor. |
| ReverseSequence <T> | Reverses variable length slices. |
| ReverseSequence.Options | Optional attributes for ReverseSequence |
| RewriteDataset | |
| RiscAbs <T extends Number> | |
| RiscAdd <T extends Number> | Returns x + y element-wise. |
| RiscBinaryArithmetic <T extends Number> | |
| RiscBinaryComparison | |
| RiscBitcast <U> | |
| RiscBroadcast <T> | |
| RiscCast <U> | |
| RiscCeil <T extends Number> | |
| RiscCholesky <T extends Number> | |
| RiscConcat <T> | |
| RiscConv <T extends Number> | |
| RiscConv.Options | Optional attributes for RiscConv |
| RiscCos <T extends Number> | |
| RiscDiv <T extends Number> | |
| RiscDot <T extends Number> | |
| RiscDot.Options | Optional attributes for RiscDot |
| RiscExp <T extends Number> | |
| RiscFft <T> | |
| RiscFloor <T extends Number> | |
| RiscGather <T> | |
| RiscGather.Options | Optional attributes for RiscGather |
| RiscImag <U extends Number> | |
| RiscIsFinite | |
| RiscLog <T extends Number> | |
| RiscLogicalAnd | |
| RiscLogicalNot | |
| RiscLogicalOr | |
| RiscMax <T extends Number> | Returns max(x, y) element-wise. |
| RiscMin <T extends Number> | |
| RiscMul <T extends Number> | |
| RiscNeg <T extends Number> | |
| RiscPad <T extends Number> | |
| RiscPool <T extends Number> | |
| RiscPool.Options | Optional attributes for RiscPool |
| RiscPow <T extends Number> | |
| RiscRandomUniform | |
| RiscRandomUniform.Options | Optional attributes for RiscRandomUniform |
| RiscReal <U extends Number> | |
| RiscReduce <T extends Number> | |
| RiscRem <T extends Number> | |
| RiscReshape <T extends Number> | |
| RiscReverse <T extends Number> | |
| RiscScatter <U extends Number> | |
| RiscShape <U extends Number> | |
| RiscSign <T extends Number> | |
| RiscSlice <T extends Number> | |
| RiscSort <T extends Number> | |
| RiscSqueeze <T> | |
| RiscSqueeze.Options | Optional attributes for RiscSqueeze |
| RiscSub <T extends Number> | |
| RiscTranspose <T> | |
| RiscTriangularSolve <T extends Number> | |
| RiscTriangularSolve.Options | Optional attributes for RiscTriangularSolve |
| RiscUnary <T extends Number> | |
| RngReadAndSkip | Advance the counter of a counter-based RNG. |
| RngSkip | Advance the counter of a counter-based RNG. |
| Roll <T> | Rolls the elements of a tensor along an axis. |
| SamplingDataset | Creates a dataset that takes a Bernoulli sample of the contents of another dataset. |
| ScaleAndTranslate | |
| ScaleAndTranslate.Options | Optional attributes for ScaleAndTranslate |
| ScaleAndTranslateGrad <T extends Number> | |
| ScaleAndTranslateGrad.Options | Optional attributes for ScaleAndTranslateGrad |
| ScatterAdd <T> | Adds sparse updates to a variable reference. |
| ScatterAdd.Options | Optional attributes for ScatterAdd |
| ScatterDiv <T> | Divides a variable reference by sparse updates. |
| ScatterDiv.Options | Optional attributes for ScatterDiv |
| ScatterMax <T extends Number> | Reduces sparse updates into a variable reference using the `max` operation. |
| ScatterMax.Options | Optional attributes for ScatterMax |
| ScatterMin <T extends Number> | Reduces sparse updates into a variable reference using the `min` operation. |
| ScatterMin.Options | Optional attributes for ScatterMin |
| ScatterMul <T> | Multiplies sparse updates into a variable reference. |
| ScatterMul.Options | Optional attributes for ScatterMul |
| ScatterNd <U> | Scatters `updates` into a tensor of shape `shape` according to `indices`. |
| ScatterNdAdd <T> | Applies sparse addition to individual values or slices in a Variable. |
| ScatterNdAdd.Options | Optional attributes for ScatterNdAdd |
| ScatterNdMax <T> | Computes element-wise maximum. |
| ScatterNdMax.Options | Optional attributes for ScatterNdMax |
| ScatterNdMin <T> | Computes element-wise minimum. |
| ScatterNdMin.Options | Optional attributes for ScatterNdMin |
| ScatterNdNonAliasingAdd <T> | Applies sparse addition to `input` using individual values or slices from `updates` according to indices `indices`. |
| ScatterNdSub <T> | Applies sparse subtraction to individual values or slices in a Variable. |
| ScatterNdSub.Options | Optional attributes for ScatterNdSub |
| ScatterNdUpdate <T> | Applies sparse `updates` to individual values or slices within a given variable according to `indices`. |
| ScatterNdUpdate.Options | Optional attributes for ScatterNdUpdate |
| ScatterSub <T> | Subtracts sparse updates to a variable reference. |
| ScatterSub.Options | Optional attributes for ScatterSub |
| ScatterUpdate <T> | Applies sparse updates to a variable reference. |
| ScatterUpdate.Options | Optional attributes for ScatterUpdate |
| SegmentMaxV2 <T extends Number> | Computes the maximum along segments of a tensor. |
| SegmentMinV2 <T extends Number> | Computes the minimum along segments of a tensor. |
| SegmentProdV2 <T> | Computes the product along segments of a tensor. |
| SegmentSumV2 <T> | Computes the sum along segments of a tensor. |
| SelectV2 <T> | |
| Send | Sends the named tensor from send_device to recv_device. |
| Send.Options | Optional attributes for Send |
| SendTPUEmbeddingGradients | Performs gradient updates of embedding tables. |
| SetDiff1d <T, U extends Number> | 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 |
| Shape <U extends Number> | Returns the shape of a tensor. |
| ShapeN <U extends Number> | Returns shape of tensors. |
| ShardDataset | Creates a `Dataset` that includes only 1/`num_shards` of this dataset. |
| ShardDataset.Options | Optional attributes for ShardDataset |
| ShuffleAndRepeatDatasetV2 | |
| ShuffleAndRepeatDatasetV2.Options | Optional attributes for ShuffleAndRepeatDatasetV2 |
| ShuffleDatasetV2 | |
| ShuffleDatasetV2.Options | Optional attributes for ShuffleDatasetV2 |
| ShuffleDatasetV3 | |
| ShuffleDatasetV3.Options | Optional attributes for ShuffleDatasetV3 |
| ShutdownDistributedTPU | Shuts down a running distributed TPU system. |
| ShutdownTPUSystem | An op that shuts down the TPU system. |
| Size <U extends Number> | Returns the size of a tensor. |
| Skipgram | Parses a text file and creates a batch of examples. |
| Skipgram.Options | Optional attributes for Skipgram |
| SleepDataset | |
| Slice <T> | Return a slice from 'input'. |
| SlidingWindowDataset | Creates a dataset that passes a sliding window over `input_dataset`. |
| SlidingWindowDataset.Options | Optional attributes for SlidingWindowDataset |
| Snapshot <T> | Returns a copy of the input tensor. |
| SnapshotDataset | Creates a dataset that will write to / read from a snapshot. |
| SnapshotDataset.Options | Optional attributes for SnapshotDataset |
| SnapshotDatasetReader | |
| SnapshotDatasetReader.Options | Optional attributes for SnapshotDatasetReader |
| SnapshotNestedDatasetReader | |
| SobolSample <T extends Number> | Generates points from the Sobol sequence. |
| SpaceToBatchNd <T> | SpaceToBatch for ND tensors of type T. |
| SparseApplyAdagradV2 <T> | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
| SparseApplyAdagradV2.Options | Optional attributes for SparseApplyAdagradV2 |
| SparseBincount <U extends Number> | Counts the number of occurrences of each value in an integer array. |
| SparseBincount.Options | Optional attributes for SparseBincount |
| SparseCountSparseOutput <U extends Number> | Performs sparse-output bin counting for a sparse tensor input. |
| SparseCountSparseOutput.Options | Optional attributes for SparseCountSparseOutput |
| SparseCrossHashed | Generates sparse cross from a list of sparse and dense tensors. |
| SparseCrossV2 | Generates sparse cross from a list of sparse and dense tensors. |
| SparseMatrixAdd | Sparse addition of two CSR matrices, C = alpha * A + beta * B. |
| SparseMatrixMatMul <T> | 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`. |
| SparseSegmentSumGrad <T extends Number> | Computes gradients for SparseSegmentSum. |
| SparseTensorToCSRSparseMatrix | Converts a SparseTensor to a (possibly batched) CSRSparseMatrix. |
| Spence <T extends Number> | |
| Split <T> | Splits a tensor into `num_split` tensors along one dimension. |
| SplitDedupData <T extends Number, U extends Number> | An op splits input deduplication data XLA tuple into integer and floating point tensors. |
| SplitDedupData.Options | Optional attributes for SplitDedupData |
| SplitV <T> | Splits a tensor into `num_split` tensors along one dimension. |
| Squeeze <T> | Removes dimensions of size 1 from the shape of a tensor. |
| Squeeze.Options | Optional attributes for Squeeze |
| Stack <T> | Packs a list of `N` rank-`R` tensors into one rank-`(R+1)` tensor. |
| Stack.Options | Optional attributes for Stack |
| Stage | 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 Number> | |
| StatefulStandardNormal <U> | Outputs random values from a normal distribution. |
| StatefulStandardNormalV2 <U> | Outputs random values from a normal distribution. |
| StatefulTruncatedNormal <U> | Outputs random values from a truncated normal distribution. |
| StatefulUniform <U> | Outputs random values from a uniform distribution. |
| StatefulUniformFullInt <U> | Outputs random integers from a uniform distribution. |
| StatefulUniformInt <U> | Outputs random integers from a uniform distribution. |
| StatelessParameterizedTruncatedNormal <V extends Number> | |
| StatelessRandomBinomial <W extends Number> | Outputs deterministic pseudorandom random numbers from a binomial distribution. |
| StatelessRandomGammaV2 <V extends Number> | Outputs deterministic pseudorandom random numbers from a gamma distribution. |
| StatelessRandomGammaV3 <U extends Number> | Outputs deterministic pseudorandom random numbers from a gamma distribution. |
| StatelessRandomGetAlg | Picks the best counter-based RNG algorithm based on device. |
| StatelessRandomGetKeyCounter | Scrambles seed into key and counter, using the best algorithm based on device. |
| StatelessRandomGetKeyCounterAlg | Picks the best algorithm based on device, and scrambles seed into key and counter. |
| StatelessRandomNormalV2 <U extends Number> | Outputs deterministic pseudorandom values from a normal distribution. |
| StatelessRandomPoisson <W extends Number> | Outputs deterministic pseudorandom random numbers from a Poisson distribution. |
| StatelessRandomUniformFullInt <V extends Number> | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformFullIntV2 <U extends Number> | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformIntV2 <U extends Number> | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformV2 <U extends Number> | Outputs deterministic pseudorandom random values from a uniform distribution. |
| StatelessSampleDistortedBoundingBox <T extends Number> | Generate a randomly distorted bounding box for an image deterministically. |
| StatelessSampleDistortedBoundingBox.Options | Optional attributes for StatelessSampleDistortedBoundingBox |
| StatelessShuffle <T> | Randomly and deterministically shuffles a tensor along its first dimension. |
| StatelessTruncatedNormalV2 <U extends Number> | Outputs deterministic pseudorandom values from a truncated normal distribution. |
| StatsAggregatorHandleV2 | |
| StatsAggregatorHandleV2.Options | Optional attributes for StatsAggregatorHandleV2 |
| StatsAggregatorSetSummaryWriter | Set a summary_writer_interface to record statistics using given stats_aggregator. |
| StopGradient <T> | Stops gradient computation. |
| StridedSlice <T> | Return a strided slice from `input`. |
| StridedSlice.Options | Optional attributes for StridedSlice |
| StridedSliceAssign <T> | Assign `value` to the sliced l-value reference of `ref`. |
| StridedSliceAssign.Options | Optional attributes for StridedSliceAssign |
| StridedSliceGrad <U> | Returns the gradient of `StridedSlice`. |
| StridedSliceGrad.Options | Optional attributes for StridedSliceGrad |
| StringLower | Converts all uppercase characters into their respective lowercase replacements. |
| StringLower.Options | Optional attributes for StringLower |
| StringNGrams <T extends Number> | Creates ngrams from ragged string data. |
| StringUpper | Converts all lowercase characters into their respective uppercase replacements. |
| StringUpper.Options | Optional attributes for StringUpper |
| Sum <T> | Computes the sum of elements across dimensions of a tensor. |
| Sum.Options | Optional attributes for Sum |
| SwitchCond <T> | Forwards `data` to the output port determined by `pred`. |
| SyncDevice | Synchronizes the device this op is run on. |
| TemporaryVariable <T> | Returns a tensor that may be mutated, but only persists within a single step. |
| TemporaryVariable.Options | Optional attributes for TemporaryVariable |
| TensorArray | An array of Tensors of given size. |
| TensorArray.Options | Optional attributes for TensorArray |
| TensorArrayClose | Delete the TensorArray from its resource container. |
| TensorArrayConcat <T> | Concat the elements from the TensorArray into value `value`. |
| TensorArrayConcat.Options | Optional attributes for TensorArrayConcat |
| TensorArrayGather <T> | 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> | |
| TensorArrayPack.Options | Optional attributes for TensorArrayPack |
| TensorArrayRead <T> | 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. |
| TensorListConcat <T> | Concats all tensors in the list along the 0th dimension. |
| TensorListConcat.Options | Optional attributes for TensorListConcat |
| TensorListConcatLists | |
| TensorListConcatV2 <U> | Concats all tensors in the list along the 0th dimension. |
| TensorListElementShape <T extends Number> | 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> | Creates a Tensor by indexing into the TensorList. |
| TensorListGetItem <T> | |
| TensorListLength | Returns the number of tensors in the input tensor list. |
| TensorListPopBack <T> | 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. |
| TensorListScatterV2 | Creates a TensorList by indexing into a Tensor. |
| TensorListSetItem | |
| TensorListSetItem.Options | Optional attributes for TensorListSetItem |
| TensorListSplit | Splits a tensor into a list. |
| TensorListStack <T> | 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> | Returns the value from a given key in a tensor map. |
| TensorMapSize | Returns the number of tensors in the input tensor map. |
| TensorMapStackKeys <T> | Returns a Tensor stack of all keys in a tensor map. |
| TensorScatterAdd <T> | Adds sparse `updates` to an existing tensor according to `indices`. |
| TensorScatterMax <T> | Apply a sparse update to a tensor taking the element-wise maximum. |
| TensorScatterMin <T> | |
| TensorScatterSub <T> | Subtracts sparse `updates` from an existing tensor according to `indices`. |
| TensorScatterUpdate <T> | Scatter `updates` into an existing tensor according to `indices`. |
| TensorStridedSliceUpdate <T> | Assign `value` to the sliced l-value reference of `input`. |
| TensorStridedSliceUpdate.Options | Optional attributes for TensorStridedSliceUpdate |
| 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.Options | Optional attributes for ThreadPoolHandle |
| Tile <T> | Constructs a tensor by tiling a given tensor. |
| Timestamp | Provides the time since epoch in seconds. |
| ToBool | Converts a tensor to a scalar predicate. |
| 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. |
| TPUCompileSucceededAssert | Asserts that compilation succeeded. |
| TPUEmbeddingActivations | An op enabling differentiation of TPU Embeddings. |
| TPUExecute | Op that loads and executes a TPU program on a TPU device. |
| TPUExecuteAndUpdateVariables | Op that executes a program with optional in-place variable updates. |
| TpuHandleToProtoKey | Converts XRT's uid handles to TensorFlow-friendly input format. |
| TPUOrdinalSelector | A TPU core selector Op. |
| TPUPartitionedInput <T> | An op that groups a list of partitioned inputs together. |
| TPUPartitionedInput.Options | Optional attributes for TPUPartitionedInput |
| TPUPartitionedInputV2 <T> | An op that groups a list of partitioned inputs together. |
| TPUPartitionedInputV2.Options | Optional attributes for TPUPartitionedInputV2 |
| TPUPartitionedOutput <T> | An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned outputs outside the XLA computation. |
| TPUPartitionedOutput.Options | Optional attributes for TPUPartitionedOutput |
| TPUPartitionedOutputV2 <T> | An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned outputs outside the XLA computation. |
| TPUReplicatedInput <T> | Connects N inputs to an N-way replicated TPU computation. |
| TPUReplicatedInput.Options | Optional attributes for TPUReplicatedInput |
| TPUReplicatedOutput <T> | 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 |
| TPUReshardVariables | Op that reshards on-device TPU variables to specified state. |
| TPURoundRobin | Round-robin load balancing on TPU cores. |
| TridiagonalMatMul <T> | Calculate product with tridiagonal matrix. |
| TridiagonalSolve <T> | Solves tridiagonal systems of equations. |
| TridiagonalSolve.Options | Optional attributes for TridiagonalSolve |
| Unbatch <T> | Reverses the operation of Batch for a single output Tensor. |
| Unbatch.Options | Optional attributes for Unbatch |
| UnbatchGrad <T> | Gradient of Unbatch. |
| UnbatchGrad.Options | Optional attributes for UnbatchGrad |
| UncompressElement | Uncompresses a compressed dataset element. |
| UnicodeDecode <T extends Number> | Decodes each string in `input` into a sequence of Unicode code points. |
| UnicodeDecode.Options | Optional attributes for UnicodeDecode |
| UnicodeEncode | Encode a tensor of ints into unicode strings. |
| UnicodeEncode.Options | Optional attributes for UnicodeEncode |
| UniformDequantize <U extends Number> | Perform dequantization on the quantized Tensor `input`. |
| UniformDequantize.Options | Optional attributes for UniformDequantize |
| UniformQuantize <U> | Perform quantization on Tensor `input`. |
| UniformQuantize.Options | Optional attributes for UniformQuantize |
| UniformQuantizedAdd <T> | Perform quantized add of quantized Tensor `lhs` and quantized Tensor `rhs` to make quantized `output`. |
| UniformQuantizedAdd.Options | Optional attributes for UniformQuantizedAdd |
| UniformQuantizedClipByValue <T> | Perform clip by value on the quantized Tensor `operand`. |
| UniformQuantizedClipByValue.Options | Optional attributes for UniformQuantizedClipByValue |
| UniformQuantizedConvolution <U> | Perform quantized convolution of quantized Tensor `lhs` and quantized Tensor `rhs`. |
| UniformQuantizedConvolution.Options | Optional attributes for UniformQuantizedConvolution |
| UniformQuantizedConvolutionHybrid <V extends Number> | Perform hybrid quantized convolution of float Tensor `lhs` and quantized Tensor `rhs`. |
| UniformQuantizedConvolutionHybrid.Options | Optional attributes for UniformQuantizedConvolutionHybrid |
| UniformQuantizedDot <U> | Perform quantized dot of quantized Tensor `lhs` and quantized Tensor `rhs` to make quantized `output`. |
| UniformQuantizedDot.Options | Optional attributes for UniformQuantizedDot |
| UniformQuantizedDotHybrid <V extends Number> | Perform hybrid quantized dot of float Tensor `lhs` and quantized Tensor `rhs`. |
| UniformQuantizedDotHybrid.Options | Optional attributes for UniformQuantizedDotHybrid |
| UniformRequantize <U> | Given quantized tensor `input`, requantize it with new quantization parameters. |
| UniformRequantize.Options | Optional attributes for UniformRequantize |
| Unique <T, V extends Number> | Finds unique elements along an axis of a tensor. |
| UniqueDataset | Creates a dataset that contains the unique elements of `input_dataset`. |
| UniqueDataset.Options | Optional attributes for UniqueDataset |
| UniqueWithCounts <T, V extends Number> | Finds unique elements along an axis of a tensor. |
| UnravelIndex <T extends Number> | Converts an array of flat indices into a tuple of coordinate arrays. |
| UnsortedSegmentJoin | |
| UnsortedSegmentJoin.Options | Optional attributes for UnsortedSegmentJoin |
| Unstack <T> | 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 | |
| UpperBound <U extends Number> | Applies upper_bound(sorted_search_values, values) along each row. |
| VarHandleOp | Creates a handle to a Variable resource. |
| VarHandleOp.Options | Optional attributes for VarHandleOp |
| Variable <T> | Holds state in the form of a tensor that persists across steps. |
| Variable.Options | Optional attributes for Variable |
| VariableShape <T extends Number> | Returns the shape of the variable pointed to by `resource`. |
| VarIsInitializedOp | Checks whether a resource handle-based variable has been initialized. |
| Where | Returns locations of nonzero / true values in a tensor. |
| Where3 <T> | Selects elements from `x` or `y`, depending on `condition`. |
| WindowOp | |
| WorkerHeartbeat | Worker heartbeat op. |
| WrapDatasetVariant | |
| WriteRawProtoSummary | Writes a serialized proto summary. |
| XlaConcatND <T> | Concats input tensor across all dimensions. |
| XlaConcatND.Options | Optional attributes for XlaConcatND |
| XlaRecvFromHost <T> | An op to receive a tensor from the host. |
| XlaRecvTPUEmbeddingActivations | An op that receives embedding activations on the TPU. |
| XlaRecvTPUEmbeddingDeduplicationData | Receives deduplication data (indices and weights) from the embedding core. |
| XlaSendToHost | An op to send a tensor to the host. |
| XlaSendTPUEmbeddingGradients | An op that performs gradient updates of embedding tables. |
| XlaSplitND <T> | Splits input tensor across all dimensions. |
| XlaSplitND.Options | Optional attributes for XlaSplitND |
| Xlog1py <T> | Returns 0 if x == 0, and x * log1p(y) otherwise, elementwise. |
| Zeros <T> | An operator creating a constant initialized with zeros of the shape given by `dims`. |
| ZerosLike <T> | Returns a tensor of zeros with the same shape and type as x. |
Classes
| Abort | Raise a exception to abort the process when called. |
| Abort.Options | Optional attributes for Abort |
| All | Computes the "logical and" of elements across dimensions of a tensor. |
| All.Options | Optional attributes for All |
| AllToAll <T> | An Op to exchange data across TPU replicas. |
| AnonymousHashTable | Creates a uninitialized anonymous hash table. |
| AnonymousIteratorV2 | A container for an iterator resource. |
| AnonymousIteratorV3 | A container for an iterator resource. |
| AnonymousMemoryCache | |
| AnonymousMultiDeviceIterator | A container for a multi device iterator resource. |
| AnonymousMultiDeviceIteratorV3 | A container for a multi device iterator resource. |
| AnonymousMutableDenseHashTable | Creates an empty anonymous mutable hash table that uses tensors as the backing store. |
| AnonymousMutableDenseHashTable.Options | Optional attributes for AnonymousMutableDenseHashTable |
| AnonymousMutableHashTable | Creates an empty anonymous mutable hash table. |
| AnonymousMutableHashTableOfTensors | Creates an empty anonymous mutable hash table of vector values. |
| AnonymousMutableHashTableOfTensors.Options | Optional attributes for AnonymousMutableHashTableOfTensors |
| AnonymousRandomSeedGenerator | |
| AnonymousSeedGenerator | |
| Any | Computes the "logical or" of elements across dimensions of a tensor. |
| Any.Options | Optional attributes for Any |
| ApplyAdagradV2 <T> | Update '*var' according to the adagrad scheme. |
| ApplyAdagradV2.Options | Optional attributes for ApplyAdagradV2 |
| ApproxTopK <T extends Number> | Returns min/max k values and their indices of the input operand in an approximate manner. |
| ApproxTopK.Options | Optional attributes for ApproxTopK |
| AssertCardinalityDataset | |
| AssertNextDataset | A transformation that asserts which transformations happen next. |
| AssertPrevDataset | A transformation that asserts which transformations happened previously. |
| AssertThat | Asserts that the given condition is true. |
| AssertThat.Options | Optional attributes for AssertThat |
| Assign <T> | Update 'ref' by assigning 'value' to it. |
| Assign.Options | Optional attributes for Assign |
| AssignAdd <T> | Update 'ref' by adding 'value' to it. |
| AssignAdd.Options | Optional attributes for AssignAdd |
| AssignAddVariableOp | Adds a value to the current value of a variable. |
| AssignSub <T> | Update 'ref' by subtracting 'value' from it. |
| AssignSub.Options | Optional attributes for AssignSub |
| AssignSubVariableOp | Subtracts a value from the current value of a variable. |
| AssignVariableOp | Assigns a new value to a variable. |
| AssignVariableOp.Options | Optional attributes for AssignVariableOp |
| AssignVariableXlaConcatND | Concats input tensor across all dimensions. |
| AssignVariableXlaConcatND.Options | Optional attributes for AssignVariableXlaConcatND |
| AutoShardDataset | Creates a dataset that shards the input dataset. |
| AutoShardDataset.Options | Optional attributes for AutoShardDataset |
| BandedTriangularSolve <T> | |
| BandedTriangularSolve.Options | Optional attributes for BandedTriangularSolve |
| Barrier | Defines a barrier that persists across different graph executions. |
| Barrier.Options | Optional attributes for Barrier |
| BarrierClose | Closes the given barrier. |
| BarrierClose.Options | Optional attributes for BarrierClose |
| BarrierIncompleteSize | Computes the number of incomplete elements in the given barrier. |
| BarrierInsertMany | For each key, assigns the respective value to the specified component. |
| BarrierReadySize | Computes the number of complete elements in the given barrier. |
| BarrierTakeMany | Takes the given number of completed elements from a barrier. |
| BarrierTakeMany.Options | Optional attributes for BarrierTakeMany |
| Batch | Batches all input tensors nondeterministically. |
| Batch.Options | Optional attributes for Batch |
| BatchMatMulV2 <T> | Multiplies slices of two tensors in batches. |
| BatchMatMulV2.Options | Optional attributes for BatchMatMulV2 |
| BatchMatMulV3 <V> | Multiplies slices of two tensors in batches. |
| BatchMatMulV3.Options | Optional attributes for BatchMatMulV3 |
| BatchToSpace <T> | BatchToSpace for 4-D tensors of type T. |
| BatchToSpaceNd <T> | BatchToSpace for ND tensors of type T. |
| BesselI0 <T extends Number> | |
| BesselI1 <T extends Number> | |
| BesselJ0 <T extends Number> | |
| BesselJ1 <T extends Number> | |
| BesselK0 <T extends Number> | |
| BesselK0e <T extends Number> | |
| BesselK1 <T extends Number> | |
| BesselK1e <T extends Number> | |
| BesselY0 <T extends Number> | |
| BesselY1 <T extends Number> | |
| Bitcast <U> | Bitcasts a tensor from one type to another without copying data. |
| BlockLSTM <T extends Number> | Computes the LSTM cell forward propagation for all the time steps. |
| BlockLSTM.Options | Optional attributes for BlockLSTM |
| BlockLSTMGrad <T extends Number> | Computes the LSTM cell backward propagation for the entire time sequence. |
| BlockLSTMGradV2 <T extends Number> | Computes the LSTM cell backward propagation for the entire time sequence. |
| BlockLSTMV2 <T extends Number> | Computes the LSTM cell forward propagation for all the time steps. |
| BlockLSTMV2.Options | Optional attributes for BlockLSTMV2 |
| BoostedTreesAggregateStats | Aggregates the summary of accumulated stats for the batch. |
| BoostedTreesBucketize | Bucketize each feature based on bucket boundaries. |
| BoostedTreesCalculateBestFeatureSplit | Calculates gains for each feature and returns the best possible split information for the feature. |
| BoostedTreesCalculateBestFeatureSplit.Options | Optional attributes for BoostedTreesCalculateBestFeatureSplit |
| BoostedTreesCalculateBestFeatureSplitV2 | Calculates gains for each feature and returns the best possible split information for each node. |
| BoostedTreesCalculateBestGainsPerFeature | Calculates gains for each feature and returns the best possible split information for the feature. |
| BoostedTreesCenterBias | Calculates the prior from the training data (the bias) and fills in the first node with the logits' prior. |
| BoostedTreesCreateEnsemble | Creates a tree ensemble model and returns a handle to it. |
| BoostedTreesCreateQuantileStreamResource | Create the Resource for Quantile Streams. |
| BoostedTreesCreateQuantileStreamResource.Options | Optional attributes for BoostedTreesCreateQuantileStreamResource |
| BoostedTreesDeserializeEnsemble | Deserializes a serialized tree ensemble config and replaces current tree ensemble. |
| BoostedTreesEnsembleResourceHandleOp | Creates a handle to a BoostedTreesEnsembleResource |
| BoostedTreesEnsembleResourceHandleOp.Options | Optional attributes for BoostedTreesEnsembleResourceHandleOp |
| BoostedTreesExampleDebugOutputs | Debugging/model interpretability outputs for each example. |
| BoostedTreesFlushQuantileSummaries | Flush the quantile summaries from each quantile stream resource. |
| BoostedTreesGetEnsembleStates | Retrieves the tree ensemble resource stamp token, number of trees and growing statistics. |
| BoostedTreesMakeQuantileSummaries | Makes the summary of quantiles for the batch. |
| BoostedTreesMakeStatsSummary | Makes the summary of accumulated stats for the batch. |
| BoostedTreesPredict | Runs multiple additive regression ensemble predictors on input instances and computes the logits. |
| BoostedTreesQuantileStreamResourceAddSummaries | Add the quantile summaries to each quantile stream resource. |
| BoostedTreesQuantileStreamResourceDeserialize | Deserialize bucket boundaries and ready flag into current QuantileAccumulator. |
| BoostedTreesQuantileStreamResourceFlush | Flush the summaries for a quantile stream resource. |
| BoostedTreesQuantileStreamResourceFlush.Options | Optional attributes for BoostedTreesQuantileStreamResourceFlush |
| BoostedTreesQuantileStreamResourceGetBucketBoundaries | Generate the bucket boundaries for each feature based on accumulated summaries. |
| BoostedTreesQuantileStreamResourceHandleOp | Creates a handle to a BoostedTreesQuantileStreamResource. |
| BoostedTreesQuantileStreamResourceHandleOp.Options | Optional attributes for BoostedTreesQuantileStreamResourceHandleOp |
| BoostedTreesSerializeEnsemble | Serializes the tree ensemble to a proto. |
| BoostedTreesSparseAggregateStats | Aggregates the summary of accumulated stats for the batch. |
| BoostedTreesSparseCalculateBestFeatureSplit | Calculates gains for each feature and returns the best possible split information for the feature. |
| BoostedTreesSparseCalculateBestFeatureSplit.Options | Optional attributes for BoostedTreesSparseCalculateBestFeatureSplit |
| BoostedTreesTrainingPredict | Runs multiple additive regression ensemble predictors on input instances and computes the update to cached logits. |
| BoostedTreesUpdateEnsemble | Updates the tree ensemble by either adding a layer to the last tree being grown or by starting a new tree. |
| BoostedTreesUpdateEnsembleV2 | Updates the tree ensemble by adding a layer to the last tree being grown or by starting a new tree. |
| BoostedTreesUpdateEnsembleV2.Options | Optional attributes for BoostedTreesUpdateEnsembleV2 |
| BroadcastDynamicShape <T extends Number> | Return the shape of s0 op s1 with broadcast. |
| BroadcastGradientArgs <T extends Number> | Return the reduction indices for computing gradients of s0 op s1 with broadcast. |
| BroadcastTo <T> | Broadcast an array for a compatible shape. |
| Bucketize | Bucketizes 'input' based on 'boundaries'. |
| CacheDatasetV2 | |
| CacheDatasetV2.Options | Optional attributes for CacheDatasetV2 |
| CheckNumericsV2 <T extends Number> | Checks a tensor for NaN, -Inf and +Inf values. |
| ChooseFastestDataset | |
| ClipByValue <T> | Clips tensor values to a specified min and max. |
| CollateTPUEmbeddingMemory | An op that merges the string-encoded memory config protos from all hosts. |
| CollectiveAllToAllV2 <T extends Number> | Mutually exchanges multiple tensors of identical type and shape. |
| CollectiveAllToAllV2.Options | Optional attributes for CollectiveAllToAllV2 |
| CollectiveAllToAllV3 <T extends Number> | Mutually exchanges multiple tensors of identical type and shape. |
| CollectiveAllToAllV3.Options | Optional attributes for CollectiveAllToAllV3 |
| CollectiveAssignGroupV2 | Assign group keys based on group assignment. |
| CollectiveBcastRecvV2 <U> | Receives a tensor value broadcast from another device. |
| CollectiveBcastRecvV2.Options | Optional attributes for CollectiveBcastRecvV2 |
| CollectiveBcastSendV2 <T> | Broadcasts a tensor value to one or more other devices. |
| CollectiveBcastSendV2.Options | Optional attributes for CollectiveBcastSendV2 |
| CollectiveGather <T extends Number> | Mutually accumulates multiple tensors of identical type and shape. |
| CollectiveGather.Options | Optional attributes for CollectiveGather |
| CollectiveGatherV2 <T extends Number> | Mutually accumulates multiple tensors of identical type and shape. |
| CollectiveGatherV2.Options | Optional attributes for CollectiveGatherV2 |
| CollectiveInitializeCommunicator | Initializes a group for collective operations. |
| CollectiveInitializeCommunicator.Options | Optional attributes for CollectiveInitializeCommunicator |
| CollectivePermute <T> | An Op to permute tensors across replicated TPU instances. |
| CollectiveReduceScatterV2 <T extends Number> | Mutually reduces multiple tensors of identical type and shape and scatters the result. |
| CollectiveReduceScatterV2.Options | Optional attributes for CollectiveReduceScatterV2 |
| CollectiveReduceV2 <T extends Number> | Mutually reduces multiple tensors of identical type and shape. |
| CollectiveReduceV2.Options | Optional attributes for CollectiveReduceV2 |
| CollectiveReduceV3 <T extends Number> | Mutually reduces multiple tensors of identical type and shape. |
| CollectiveReduceV3.Options | Optional attributes for CollectiveReduceV3 |
| CombinedNonMaxSuppression | Greedily selects a subset of bounding boxes in descending order of score, This operation performs non_max_suppression on the inputs per batch, across all classes. |
| CombinedNonMaxSuppression.Options | Optional attributes for CombinedNonMaxSuppression |
| CompositeTensorVariantFromComponents | Encodes an `ExtensionType` value into a `variant` scalar Tensor. |
| CompositeTensorVariantToComponents | Decodes a `variant` scalar Tensor into an `ExtensionType` value. |
| CompressElement | Compresses a dataset element. |
| ComputeBatchSize | Computes the static batch size of a dataset sans partial batches. |
| ComputeDedupDataTupleMask | An op computes tuple mask of deduplication data from embedding core. |
| Concat <T> | Concatenates tensors along one dimension. |
| ConfigureAndInitializeGlobalTPU | An op that sets up the centralized structures for a distributed TPU system. |
| ConfigureAndInitializeGlobalTPU.Options | Optional attributes for ConfigureAndInitializeGlobalTPU |
| ConfigureDistributedTPU | Sets up the centralized structures for a distributed TPU system. |
| ConfigureDistributedTPU.Options | Optional attributes for ConfigureDistributedTPU |
| ConfigureTPUEmbedding | Sets up TPUEmbedding in a distributed TPU system. |
| ConfigureTPUEmbeddingHost | An op that configures the TPUEmbedding software on a host. |
| ConfigureTPUEmbeddingMemory | An op that configures the TPUEmbedding software on a host. |
| ConnectTPUEmbeddingHosts | An op that sets up communication between TPUEmbedding host software instances after ConfigureTPUEmbeddingHost has been called on each host. |
| Constant <T> | An operator producing a constant value. |
| ConsumeMutexLock | This op consumes a lock created by `MutexLock`. |
| ControlTrigger | Does nothing. |
| Conv2DBackpropFilterV2 <T extends Number> | Computes the gradients of convolution with respect to the filter. |
| Conv2DBackpropFilterV2.Options | Optional attributes for Conv2DBackpropFilterV2 |
| Conv2DBackpropInputV2 <T extends Number> | Computes the gradients of convolution with respect to the input. |
| Conv2DBackpropInputV2.Options | Optional attributes for Conv2DBackpropInputV2 |
| Copy <T> | Copy a tensor from CPU-to-CPU or GPU-to-GPU. |
| Copy.Options | Optional attributes for Copy |
| CopyHost <T> | Copy a tensor to host. |
| CopyHost.Options | Optional attributes for CopyHost |
| CopyToMesh <T> | |
| CopyToMeshGrad <T> | |
| CopyToMeshGrad.Options | Optional attributes for CopyToMeshGrad |
| CountUpTo <T extends Number> | Increments 'ref' until it reaches 'limit'. |
| CrossReplicaSum <T extends Number> | An Op to sum inputs across replicated TPU instances. |
| CSRSparseMatrixComponents <T> | Reads out the CSR components at batch `index`. |
| CSRSparseMatrixToDense <T> | Convert a (possibly batched) CSRSparseMatrix to dense. |
| CSRSparseMatrixToSparseTensor <T> | Converts a (possibly batched) CSRSparesMatrix to a SparseTensor. |
| CSVDataset | |
| CSVDatasetV2 | |
| CTCLossV2 | Calculates the CTC Loss (log probability) for each batch entry. |
| CTCLossV2.Options | Optional attributes for CTCLossV2 |
| CudnnRNNBackpropV3 <T extends Number> | Backprop step of CudnnRNNV3. |
| CudnnRNNBackpropV3.Options | Optional attributes for CudnnRNNBackpropV3 |
| CudnnRNNCanonicalToParamsV2 <T extends Number> | Converts CudnnRNN params from canonical form to usable form. |
| CudnnRNNCanonicalToParamsV2.Options | Optional attributes for CudnnRNNCanonicalToParamsV2 |
| CudnnRNNParamsToCanonicalV2 <T extends Number> | Retrieves CudnnRNN params in canonical form. |
| CudnnRNNParamsToCanonicalV2.Options | Optional attributes for CudnnRNNParamsToCanonicalV2 |
| CudnnRNNV3 <T extends Number> | A RNN backed by cuDNN. |
| CudnnRNNV3.Options | Optional attributes for CudnnRNNV3 |
| CumulativeLogsumexp <T extends Number> | Compute the cumulative product of the tensor `x` along `axis`. |
| CumulativeLogsumexp.Options | Optional attributes for CumulativeLogsumexp |
| DataServiceDataset | Creates a dataset that reads data from the tf.data service. |
| DataServiceDataset.Options | Optional attributes for DataServiceDataset |
| DataServiceDatasetV2 | Creates a dataset that reads data from the tf.data service. |
| DataServiceDatasetV2.Options | Optional attributes for DataServiceDatasetV2 |
| DatasetCardinality | Returns the cardinality of `input_dataset`. |
| DatasetCardinality.Options | Optional attributes for DatasetCardinality |
| DatasetFromGraph | Creates a dataset from the given `graph_def`. |
| DatasetToGraphV2 | Returns a serialized GraphDef representing `input_dataset`. |
| DatasetToGraphV2.Options | Optional attributes for DatasetToGraphV2 |
| Dawsn <T extends Number> | |
| DebugGradientIdentity <T> | Identity op for gradient debugging. |
| DebugGradientRefIdentity <T> | Identity op for gradient debugging. |
| DebugIdentity <T> | Provides an identity mapping of the non-Ref type input tensor for debugging. |
| DebugIdentity.Options | Optional attributes for DebugIdentity |
| DebugIdentityV2 <T> | Debug Identity V2 Op. |
| DebugIdentityV2.Options | Optional attributes for DebugIdentityV2 |
| DebugNanCount | Debug NaN Value Counter Op. |
| DebugNanCount.Options | Optional attributes for DebugNanCount |
| DebugNumericSummary | Debug Numeric Summary Op. |
| DebugNumericSummary.Options | Optional attributes for DebugNumericSummary |
| DebugNumericSummaryV2 <U extends Number> | Debug Numeric Summary V2 Op. |
| DebugNumericSummaryV2.Options | Optional attributes for DebugNumericSummaryV2 |
| DecodeImage <T extends Number> | Function for decode_bmp, decode_gif, decode_jpeg, and decode_png. |
| DecodeImage.Options | Optional attributes for DecodeImage |
| DecodePaddedRaw <T extends Number> | Reinterpret the bytes of a string as a vector of numbers. |
| DecodePaddedRaw.Options | Optional attributes for DecodePaddedRaw |
| DecodeProto | The op extracts fields from a serialized protocol buffers message into tensors. |
| DecodeProto.Options | Optional attributes for DecodeProto |
| DeepCopy <T> | Makes a copy of `x`. |
| DeleteIterator | A container for an iterator resource. |
| DeleteMemoryCache | |
| DeleteMultiDeviceIterator | A container for an iterator resource. |
| DeleteRandomSeedGenerator | |
| DeleteSeedGenerator | |
| DeleteSessionTensor | Delete the tensor specified by its handle in the session. |
| DenseBincount <U extends Number> | Counts the number of occurrences of each value in an integer array. |
| DenseBincount.Options | Optional attributes for DenseBincount |
| DenseCountSparseOutput <U extends Number> | Performs sparse-output bin counting for a tf.tensor input. |
| DenseCountSparseOutput.Options | Optional attributes for DenseCountSparseOutput |
| DenseToCSRSparseMatrix | Converts a dense tensor to a (possibly batched) CSRSparseMatrix. |
| DestroyResourceOp | Deletes the resource specified by the handle. |
| DestroyResourceOp.Options | Optional attributes for DestroyResourceOp |
| DestroyTemporaryVariable <T> | Destroys the temporary variable and returns its final value. |
| DeviceIndex | Return the index of device the op runs. |
| DirectedInterleaveDataset | A substitute for `InterleaveDataset` on a fixed list of `N` datasets. |
| DirectedInterleaveDataset.Options | Optional attributes for DirectedInterleaveDataset |
| DisableCopyOnRead | Turns off the copy-on-read mode. |
| DistributedSave | |
| DistributedSave.Options | Optional attributes for DistributedSave |
| DrawBoundingBoxesV2 <T extends Number> | Draw bounding boxes on a batch of images. |
| DTensorRestoreV2 | |
| DTensorSetGlobalTPUArray | An op that informs a host of the global ids of all the of TPUs in the system. |
| DummyIterationCounter | |
| DummyMemoryCache | |
| DummySeedGenerator | |
| DynamicEnqueueTPUEmbeddingArbitraryTensorBatch | Eases the porting of code that uses tf.nn.embedding_lookup_sparse(). |
| DynamicEnqueueTPUEmbeddingArbitraryTensorBatch.Options | Optional attributes for DynamicEnqueueTPUEmbeddingArbitraryTensorBatch |
| DynamicPartition <T> | Partitions `data` into `num_partitions` tensors using indices from `partitions`. |
| DynamicStitch <T> | Interleave the values from the `data` tensors into a single tensor. |
| EditDistance | Computes the (possibly normalized) Levenshtein Edit Distance. |
| EditDistance.Options | Optional attributes for EditDistance |
| Eig <U> | Computes the eigen decomposition of one or more square matrices. |
| Eig.Options | Optional attributes for Eig |
| Einsum <T> | Tensor contraction according to Einstein summation convention. |
| Empty <T> | Creates a tensor with the given shape. |
| Empty.Options | Optional attributes for Empty |
| EmptyTensorList | Creates and returns an empty tensor list. |
| EmptyTensorMap | Creates and returns an empty tensor map. |
| EncodeProto | The op serializes protobuf messages provided in the input tensors. |
| EncodeProto.Options | Optional attributes for EncodeProto |
| EnqueueTPUEmbeddingArbitraryTensorBatch | Eases the porting of code that uses tf.nn.embedding_lookup_sparse(). |
| EnqueueTPUEmbeddingArbitraryTensorBatch.Options | Optional attributes for EnqueueTPUEmbeddingArbitraryTensorBatch |
| EnqueueTPUEmbeddingBatch | An op that enqueues a list of input batch tensors to TPUEmbedding. |
| EnqueueTPUEmbeddingBatch.Options | Optional attributes for EnqueueTPUEmbeddingBatch |
| EnqueueTPUEmbeddingIntegerBatch | An op that enqueues a list of input batch tensors to TPUEmbedding. |
| EnqueueTPUEmbeddingIntegerBatch.Options | Optional attributes for EnqueueTPUEmbeddingIntegerBatch |
| EnqueueTPUEmbeddingRaggedTensorBatch | Eases the porting of code that uses tf.nn.embedding_lookup(). |
| EnqueueTPUEmbeddingRaggedTensorBatch.Options | Optional attributes for EnqueueTPUEmbeddingRaggedTensorBatch |
| EnqueueTPUEmbeddingSparseBatch | An op that enqueues TPUEmbedding input indices from a SparseTensor. |
| EnqueueTPUEmbeddingSparseBatch.Options | Optional attributes for EnqueueTPUEmbeddingSparseBatch |
| EnqueueTPUEmbeddingSparseTensorBatch | Eases the porting of code that uses tf.nn.embedding_lookup_sparse(). |
| EnqueueTPUEmbeddingSparseTensorBatch.Options | Optional attributes for EnqueueTPUEmbeddingSparseTensorBatch |
| EnsureShape <T> | Ensures that the tensor's shape matches the expected shape. |
| Enter <T> | Creates or finds a child frame, and makes `data` available to the child frame. |
| Enter.Options | Optional attributes for Enter |
| Erfinv <T extends Number> | |
| EuclideanNorm <T> | Computes the euclidean norm of elements across dimensions of a tensor. |
| EuclideanNorm.Options | Optional attributes for EuclideanNorm |
| ExecuteTPUEmbeddingPartitioner | An op that executes the TPUEmbedding partitioner on the central configuration device and computes the HBM size (in bytes) required for TPUEmbedding operation. |
| Exit <T> | Exits the current frame to its parent frame. |
| ExpandDims <T> | Inserts a dimension of 1 into a tensor's shape. |
| ExperimentalAutoShardDataset | Creates a dataset that shards the input dataset. |
| ExperimentalAutoShardDataset.Options | Optional attributes for ExperimentalAutoShardDataset |
| ExperimentalBytesProducedStatsDataset | Records the bytes size of each element of `input_dataset` in a StatsAggregator. |
| ExperimentalChooseFastestDataset | |
| ExperimentalDatasetCardinality | Returns the cardinality of `input_dataset`. |
| ExperimentalDatasetToTFRecord | Writes the given dataset to the given file using the TFRecord format. |
| ExperimentalDenseToSparseBatchDataset | Creates a dataset that batches input elements into a SparseTensor. |
| ExperimentalLatencyStatsDataset | Records the latency of producing `input_dataset` elements in a StatsAggregator. |
| ExperimentalMatchingFilesDataset | |
| ExperimentalMaxIntraOpParallelismDataset | Creates a dataset that overrides the maximum intra-op parallelism. |
| ExperimentalParseExampleDataset | Transforms `input_dataset` containing `Example` protos as vectors of DT_STRING into a dataset of `Tensor` or `SparseTensor` objects representing the parsed features. |
| ExperimentalParseExampleDataset.Options | Optional attributes for ExperimentalParseExampleDataset |
| ExperimentalPrivateThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| ExperimentalRandomDataset | Creates a Dataset that returns pseudorandom numbers. |
| ExperimentalRebatchDataset | Creates a dataset that changes the batch size. |
| ExperimentalRebatchDataset.Options | Optional attributes for ExperimentalRebatchDataset |
| ExperimentalSetStatsAggregatorDataset | |
| ExperimentalSlidingWindowDataset | Creates a dataset that passes a sliding window over `input_dataset`. |
| ExperimentalSqlDataset | Creates a dataset that executes a SQL query and emits rows of the result set. |
| ExperimentalStatsAggregatorHandle | Creates a statistics manager resource. |
| ExperimentalStatsAggregatorHandle.Options | Optional attributes for ExperimentalStatsAggregatorHandle |
| ExperimentalStatsAggregatorSummary | Produces a summary of any statistics recorded by the given statistics manager. |
| ExperimentalUnbatchDataset | A dataset that splits the elements of its input into multiple elements. |
| Expint <T extends Number> | |
| ExtractGlimpseV2 | Extracts a glimpse from the input tensor. |
| ExtractGlimpseV2.Options | Optional attributes for ExtractGlimpseV2 |
| ExtractVolumePatches <T extends Number> | Extract `patches` from `input` and put them in the `"depth"` output dimension. |
| FileSystemSetConfiguration | Set configuration of the file system. |
| Fill <U> | Creates a tensor filled with a scalar value. |
| FinalizeDataset | Creates a dataset by applying tf.data.Options to `input_dataset`. |
| FinalizeDataset.Options | Optional attributes for FinalizeDataset |
| FinalizeTPUEmbedding | An op that finalizes the TPUEmbedding configuration. |
| Fingerprint | Generates fingerprint values. |
| FresnelCos <T extends Number> | |
| FresnelSin <T extends Number> | |
| FusedBatchNormGradV3 <T extends Number, U extends Number> | Gradient for batch normalization. |
| FusedBatchNormGradV3.Options | Optional attributes for FusedBatchNormGradV3 |
| FusedBatchNormV3 <T extends Number, U extends Number> | Batch normalization. |
| FusedBatchNormV3.Options | Optional attributes for FusedBatchNormV3 |
| Gather <T> | Gather slices from `params` axis `axis` according to `indices`. |
| Gather.Options | Optional attributes for Gather |
| GatherNd <T> | Gather slices from `params` into a Tensor with shape specified by `indices`. |
| GenerateBoundingBoxProposals | This op produces Region of Interests from given bounding boxes(bbox_deltas) encoded wrt anchors according to eq.2 in arXiv:1506.01497 The op selects top `pre_nms_topn` scoring boxes, decodes them with respect to anchors, applies non-maximal suppression on overlapping boxes with higher than `nms_threshold` intersection-over-union (iou) value, discarding boxes where shorter side is less than `min_size`. |
| GenerateBoundingBoxProposals.Options | Optional attributes for GenerateBoundingBoxProposals |
| GetElementAtIndex | Gets the element at the specified index in a dataset. |
| GetOptions | Returns the tf.data.Options attached to `input_dataset`. |
| GetSessionHandle | Store the input tensor in the state of the current session. |
| GetSessionTensor <T> | Get the value of the tensor specified by its handle. |
| Gradients | Adds operations to compute the partial derivatives of sum of y s wrt x s, ie, d(y_1 + y_2 + ...)/dx_1, d(y_1 + y_2 + ...)/dx_2... If |
| Gradients.Options | Optional attributes for Gradients |
| GRUBlockCell <T extends Number> | Computes the GRU cell forward propagation for 1 time step. |
| GRUBlockCellGrad <T extends Number> | Computes the GRU cell back-propagation for 1 time step. |
| GuaranteeConst <T> | Gives a guarantee to the TF runtime that the input tensor is a constant. |
| HashTable | Creates a non-initialized hash table. |
| HashTable.Options | Optional attributes for HashTable |
| HistogramFixedWidth <U extends Number> | Return histogram of values. |
| Identity <T> | Return a tensor with the same shape and contents as the input tensor or value. |
| IdentityN | Returns a list of tensors with the same shapes and contents as the input tensors. |
| IgnoreErrorsDataset | Creates a dataset that contains the elements of `input_dataset` ignoring errors. |
| IgnoreErrorsDataset.Options | Optional attributes for IgnoreErrorsDataset |
| ImageProjectiveTransformV2 <T extends Number> | Applies the given transform to each of the images. |
| ImageProjectiveTransformV2.Options | Optional attributes for ImageProjectiveTransformV2 |
| ImageProjectiveTransformV3 <T extends Number> | Applies the given transform to each of the images. |
| ImageProjectiveTransformV3.Options | Optional attributes for ImageProjectiveTransformV3 |
| ImmutableConst <T> | Returns immutable tensor from memory region. |
| InfeedDequeue <T> | A placeholder op for a value that will be fed into the computation. |
| InfeedDequeueTuple | Fetches multiple values from infeed as an XLA tuple. |
| InfeedEnqueue | An op which feeds a single Tensor value into the computation. |
| InfeedEnqueue.Options | Optional attributes for InfeedEnqueue |
| InfeedEnqueuePrelinearizedBuffer | An op which enqueues prelinearized buffer into TPU infeed. |
| InfeedEnqueuePrelinearizedBuffer.Options | Optional attributes for InfeedEnqueuePrelinearizedBuffer |
| InfeedEnqueueTuple | Feeds multiple Tensor values into the computation as an XLA tuple. |
| InfeedEnqueueTuple.Options | Optional attributes for InfeedEnqueueTuple |
| InitializeTable | Table initializer that takes two tensors for keys and values respectively. |
| InitializeTableFromDataset | |
| InitializeTableFromTextFile | Initializes a table from a text file. |
| InitializeTableFromTextFile.Options | Optional attributes for InitializeTableFromTextFile |
| InplaceAdd <T> | Adds v into specified rows of x. |
| InplaceSub <T> | Subtracts `v` into specified rows of `x`. |
| InplaceUpdate <T> | Updates specified rows 'i' with values 'v'. |
| IsBoostedTreesEnsembleInitialized | Checks whether a tree ensemble has been initialized. |
| IsBoostedTreesQuantileStreamResourceInitialized | Checks whether a quantile stream has been initialized. |
| IsotonicRegression <U extends Number> | Solves a batch of isotonic regression problems. |
| IsTPUEmbeddingInitialized | Whether TPU Embedding is initialized in a distributed TPU system. |
| IsTPUEmbeddingInitialized.Options | Optional attributes for IsTPUEmbeddingInitialized |
| IsVariableInitialized | Checks whether a tensor has been initialized. |
| IteratorGetDevice | Returns the name of the device on which `resource` has been placed. |
| 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. |
| LinSpace <T extends Number> | Generates values in an interval. |
| ListDataset | Creates a dataset that emits each of `tensors` once. |
| ListDataset.Options | Optional attributes for ListDataset |
| LMDBDataset | Creates a dataset that emits the key-value pairs in one or more LMDB files. |
| LoadAllTPUEmbeddingParameters | An op that loads optimization parameters into embedding memory. |
| LoadTPUEmbeddingAdadeltaParameters | Load Adadelta embedding parameters. |
| LoadTPUEmbeddingAdadeltaParameters.Options | Optional attributes for LoadTPUEmbeddingAdadeltaParameters |
| LoadTPUEmbeddingAdagradMomentumParameters | Load Adagrad Momentum embedding parameters. |
| LoadTPUEmbeddingAdagradMomentumParameters.Options | Optional attributes for LoadTPUEmbeddingAdagradMomentumParameters |
| LoadTPUEmbeddingAdagradParameters | Load Adagrad embedding parameters. |
| LoadTPUEmbeddingAdagradParameters.Options | Optional attributes for LoadTPUEmbeddingAdagradParameters |
| LoadTPUEmbeddingADAMParameters | Load ADAM embedding parameters. |
| LoadTPUEmbeddingADAMParameters.Options | Optional attributes for LoadTPUEmbeddingADAMParameters |
| LoadTPUEmbeddingCenteredRMSPropParameters | Load centered RMSProp embedding parameters. |
| LoadTPUEmbeddingCenteredRMSPropParameters.Options | Optional attributes for LoadTPUEmbeddingCenteredRMSPropParameters |
| LoadTPUEmbeddingFrequencyEstimatorParameters | Load frequency estimator embedding parameters. |
| LoadTPUEmbeddingFrequencyEstimatorParameters.Options | Optional attributes for LoadTPUEmbeddingFrequencyEstimatorParameters |
| LoadTPUEmbeddingFTRLParameters | Load FTRL embedding parameters. |
| LoadTPUEmbeddingFTRLParameters.Options | Optional attributes for LoadTPUEmbeddingFTRLParameters |
| LoadTPUEmbeddingMDLAdagradLightParameters | Load MDL Adagrad Light embedding parameters. |
| LoadTPUEmbeddingMDLAdagradLightParameters.Options | Optional attributes for LoadTPUEmbeddingMDLAdagradLightParameters |
| LoadTPUEmbeddingMomentumParameters | Load Momentum embedding parameters. |
| LoadTPUEmbeddingMomentumParameters.Options | Optional attributes for LoadTPUEmbeddingMomentumParameters |
| LoadTPUEmbeddingProximalAdagradParameters | Load proximal Adagrad embedding parameters. |
| LoadTPUEmbeddingProximalAdagradParameters.Options | Optional attributes for LoadTPUEmbeddingProximalAdagradParameters |
| LoadTPUEmbeddingProximalYogiParameters | |
| LoadTPUEmbeddingProximalYogiParameters.Options | Optional attributes for LoadTPUEmbeddingProximalYogiParameters |
| LoadTPUEmbeddingRMSPropParameters | Load RMSProp embedding parameters. |
| LoadTPUEmbeddingRMSPropParameters.Options | Optional attributes for LoadTPUEmbeddingRMSPropParameters |
| LoadTPUEmbeddingStochasticGradientDescentParameters | Load SGD embedding parameters. |
| LoadTPUEmbeddingStochasticGradientDescentParameters.Options | Optional attributes for LoadTPUEmbeddingStochasticGradientDescentParameters |
| LookupTableExport <T, U> | Outputs all keys and values in the table. |
| LookupTableFind <U> | 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. |
| LowerBound <U extends Number> | Applies lower_bound(sorted_search_values, values) along each row. |
| LSTMBlockCell <T extends Number> | Computes the LSTM cell forward propagation for 1 time step. |
| LSTMBlockCell.Options | Optional attributes for LSTMBlockCell |
| LSTMBlockCellGrad <T extends Number> | Computes the LSTM cell backward propagation for 1 timestep. |
| Lu <T, U extends Number> | Computes the LU decomposition of one or more square matrices. |
| 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 |
| MapIncompleteSize | Op returns the number of incomplete elements in the underlying container. |
| MapIncompleteSize.Options | Optional attributes for MapIncompleteSize |
| 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 |
| MatrixDiagPartV2 <T> | Returns the batched diagonal part of a batched tensor. |
| MatrixDiagPartV3 <T> | Returns the batched diagonal part of a batched tensor. |
| MatrixDiagPartV3.Options | Optional attributes for MatrixDiagPartV3 |
| MatrixDiagV2 <T> | Returns a batched diagonal tensor with given batched diagonal values. |
| MatrixDiagV3 <T> | Returns a batched diagonal tensor with given batched diagonal values. |
| MatrixDiagV3.Options | Optional attributes for MatrixDiagV3 |
| MatrixSetDiagV2 <T> | Returns a batched matrix tensor with new batched diagonal values. |
| MatrixSetDiagV3 <T> | Returns a batched matrix tensor with new batched diagonal values. |
| MatrixSetDiagV3.Options | Optional attributes for MatrixSetDiagV3 |
| Max <T> | Computes the maximum of elements across dimensions of a tensor. |
| Max.Options | Optional attributes for Max |
| MaxIntraOpParallelismDataset | Creates a dataset that overrides the maximum intra-op parallelism. |
| Merge <T> | Forwards the value of an available tensor from `inputs` to `output`. |
| MergeDedupData | An op merges elements of integer and float tensors into deduplication data as XLA tuple. |
| MergeDedupData.Options | Optional attributes for MergeDedupData |
| Min <T> | Computes the minimum of elements across dimensions of a tensor. |
| Min.Options | Optional attributes for Min |
| MirrorPad <T> | Pads a tensor with mirrored values. |
| MirrorPadGrad <T> | Gradient op for `MirrorPad` op. |
| MlirPassthroughOp | Wraps an arbitrary MLIR computation expressed as a module with a main() function. |
| MulNoNan <T> | Returns x * y element-wise. |
| 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. |
| NcclAllReduce <T extends Number> | Outputs a tensor containing the reduction across all input tensors. |
| NcclBroadcast <T extends Number> | Sends `input` to all devices that are connected to the output. |
| NcclReduce <T extends Number> | Reduces `input` from `num_devices` using `reduction` to a single device. |
| Ndtri <T extends Number> | |
| NearestNeighbors | Selects the k nearest centers for each point. |
| NextAfter <T extends Number> | Returns the next representable value of `x1` in the direction of `x2`, element-wise. |
| NextIteration <T> | Makes its input available to the next iteration. |
| NonDeterministicInts <U> | Non-deterministically generates some integers. |
| NonMaxSuppressionV5 <T extends Number> | 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. |
| NonMaxSuppressionV5.Options | Optional attributes for NonMaxSuppressionV5 |
| NonSerializableDataset | |
| NoOp | Does nothing. |
| OneHot <U> | Returns a one-hot tensor. |
| OneHot.Options | Optional attributes for OneHot |
| OnesLike <T> | Returns a tensor of ones with the same shape and type as x. |
| OptimizeDatasetV2 | Creates a dataset by applying related optimizations to `input_dataset`. |
| OptimizeDatasetV2.Options | Optional attributes for OptimizeDatasetV2 |
| OptionsDataset | Creates a dataset by attaching tf.data.Options to `input_dataset`. |
| OptionsDataset.Options | Optional attributes for OptionsDataset |
| 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 |
| OutfeedDequeue <T> | 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> | 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. |
| Pad <T> | Pads a tensor. |
| ParallelBatchDataset | |
| ParallelBatchDataset.Options | Optional attributes for ParallelBatchDataset |
| ParallelConcat <T> | Concatenates a list of `N` tensors along the first dimension. |
| ParallelDynamicStitch <T> | Interleave the values from the `data` tensors into a single tensor. |
| ParseExampleDatasetV2 | Transforms `input_dataset` containing `Example` protos as vectors of DT_STRING into a dataset of `Tensor` or `SparseTensor` objects representing the parsed features. |
| ParseExampleDatasetV2.Options | Optional attributes for ParseExampleDatasetV2 |
| ParseExampleV2 | Transforms a vector of tf.Example protos (as strings) into typed tensors. |
| ParseSequenceExampleV2 | Transforms a vector of tf.io.SequenceExample protos (as strings) into typed tensors. |
| ParseSequenceExampleV2.Options | Optional attributes for ParseSequenceExampleV2 |
| Placeholder <T> | A placeholder op for a value that will be fed into the computation. |
| Placeholder.Options | Optional attributes for Placeholder |
| PlaceholderWithDefault <T> | A placeholder op that passes through `input` when its output is not fed. |
| 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 |
| Prints a string scalar. | |
| Print.Options | Optional attributes for Print |
| PrivateThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| Prod <T> | Computes the product of elements across dimensions of a tensor. |
| Prod.Options | Optional attributes for Prod |
| QuantizeAndDequantizeV4 <T extends Number> | Quantizes then dequantizes a tensor. |
| QuantizeAndDequantizeV4.Options | Optional attributes for QuantizeAndDequantizeV4 |
| QuantizeAndDequantizeV4Grad <T extends Number> | Returns the gradient of `QuantizeAndDequantizeV4`. |
| QuantizeAndDequantizeV4Grad.Options | Optional attributes for QuantizeAndDequantizeV4Grad |
| QuantizedConcat <T> | Concatenates quantized tensors along one dimension. |
| QuantizedConcatV2 <T> | |
| QuantizedConv2DAndRelu <V> | |
| QuantizedConv2DAndRelu.Options | Optional attributes for QuantizedConv2DAndRelu |
| QuantizedConv2DAndReluAndRequantize <V> | |
| QuantizedConv2DAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DAndReluAndRequantize |
| QuantizedConv2DAndRequantize <V> | |
| QuantizedConv2DAndRequantize.Options | Optional attributes for QuantizedConv2DAndRequantize |
| QuantizedConv2DPerChannel <V> | Computes QuantizedConv2D per channel. |
| QuantizedConv2DPerChannel.Options | Optional attributes for QuantizedConv2DPerChannel |
| QuantizedConv2DWithBias <V> | |
| QuantizedConv2DWithBias.Options | Optional attributes for QuantizedConv2DWithBias |
| QuantizedConv2DWithBiasAndRelu <V> | |
| QuantizedConv2DWithBiasAndRelu.Options | Optional attributes for QuantizedConv2DWithBiasAndRelu |
| QuantizedConv2DWithBiasAndReluAndRequantize <W> | |
| QuantizedConv2DWithBiasAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasAndReluAndRequantize |
| QuantizedConv2DWithBiasAndRequantize <W> | |
| QuantizedConv2DWithBiasAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasAndRequantize |
| QuantizedConv2DWithBiasSignedSumAndReluAndRequantize <X> | |
| QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasSignedSumAndReluAndRequantize |
| QuantizedConv2DWithBiasSumAndRelu <V> | |
| QuantizedConv2DWithBiasSumAndRelu.Options | Optional attributes for QuantizedConv2DWithBiasSumAndRelu |
| QuantizedConv2DWithBiasSumAndReluAndRequantize <X> | |
| QuantizedConv2DWithBiasSumAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasSumAndReluAndRequantize |
| QuantizedDepthwiseConv2D <V> | Computes quantized depthwise Conv2D. |
| QuantizedDepthwiseConv2D.Options | Optional attributes for QuantizedDepthwiseConv2D |
| QuantizedDepthwiseConv2DWithBias <V> | Computes quantized depthwise Conv2D with Bias. |
| QuantizedDepthwiseConv2DWithBias.Options | Optional attributes for QuantizedDepthwiseConv2DWithBias |
| QuantizedDepthwiseConv2DWithBiasAndRelu <V> | Computes quantized depthwise Conv2D with Bias and Relu. |
| QuantizedDepthwiseConv2DWithBiasAndRelu.Options | Optional attributes for QuantizedDepthwiseConv2DWithBiasAndRelu |
| QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize <W> | Computes quantized depthwise Conv2D with Bias, Relu and Requantize. |
| QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.Options | Optional attributes for QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize |
| QuantizedMatMulWithBias <W> | Performs a quantized matrix multiplication of `a` by the matrix `b` with bias add. |
| QuantizedMatMulWithBias.Options | Optional attributes for QuantizedMatMulWithBias |
| QuantizedMatMulWithBiasAndDequantize <W extends Number> | |
| QuantizedMatMulWithBiasAndDequantize.Options | Optional attributes for QuantizedMatMulWithBiasAndDequantize |
| QuantizedMatMulWithBiasAndRelu <V> | 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> | 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> | |
| QuantizedMatMulWithBiasAndRequantize.Options | Optional attributes for QuantizedMatMulWithBiasAndRequantize |
| QuantizedReshape <T> | Reshapes a quantized tensor as per the Reshape op. |
| RaggedBincount <U extends Number> | Counts the number of occurrences of each value in an integer array. |
| RaggedBincount.Options | Optional attributes for RaggedBincount |
| RaggedCountSparseOutput <U extends Number> | Performs sparse-output bin counting for a ragged tensor input. |
| RaggedCountSparseOutput.Options | Optional attributes for RaggedCountSparseOutput |
| RaggedCross <T, U extends Number> | Generates a feature cross from a list of tensors, and returns it as a RaggedTensor. |
| RaggedFillEmptyRows <T> | |
| RaggedFillEmptyRowsGrad <T> | |
| RaggedGather <T extends Number, U> | Gather ragged slices from `params` axis `0` according to `indices`. |
| RaggedRange <U extends Number, T extends Number> | Returns a `RaggedTensor` containing the specified sequences of numbers. |
| RaggedTensorFromVariant <U extends Number, T> | Decodes a `variant` Tensor into a `RaggedTensor`. |
| RaggedTensorToSparse <U> | Converts a `RaggedTensor` into a `SparseTensor` with the same values. |
| RaggedTensorToTensor <U> | Create a dense tensor from a ragged tensor, possibly altering its shape. |
| RaggedTensorToVariant | Encodes a `RaggedTensor` into a `variant` Tensor. |
| RaggedTensorToVariantGradient <U> | Helper used to compute the gradient for `RaggedTensorToVariant`. |
| RandomDatasetV2 | Creates a Dataset that returns pseudorandom numbers. |
| RandomDatasetV2.Options | Optional attributes for RandomDatasetV2 |
| RandomIndexShuffle <T extends Number> | Outputs the position of `value` in a permutation of [0, ..., max_index]. |
| RandomIndexShuffle.Options | Optional attributes for RandomIndexShuffle |
| Range <T extends Number> | Creates a sequence of numbers. |
| Rank | Returns the rank of a tensor. |
| ReadVariableOp <T> | Reads the value of a variable. |
| ReadVariableXlaSplitND <T> | Splits resource variable input tensor across all dimensions. |
| ReadVariableXlaSplitND.Options | Optional attributes for ReadVariableXlaSplitND |
| RebatchDataset | Creates a dataset that changes the batch size. |
| RebatchDataset.Options | Optional attributes for RebatchDataset |
| RebatchDatasetV2 | Creates a dataset that changes the batch size. |
| Recv <T> | Receives the named tensor from send_device on recv_device. |
| Recv.Options | Optional attributes for Recv |
| RecvTPUEmbeddingActivations | An op that receives embedding activations on the TPU. |
| 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 |
| ReduceMax <T> | Computes the maximum of elements across dimensions of a tensor. |
| ReduceMax.Options | Optional attributes for ReduceMax |
| ReduceMin <T> | Computes the minimum of elements across dimensions of a tensor. |
| ReduceMin.Options | Optional attributes for ReduceMin |
| ReduceProd <T> | Computes the product of elements across dimensions of a tensor. |
| ReduceProd.Options | Optional attributes for ReduceProd |
| ReduceSum <T> | Computes the sum of elements across dimensions of a tensor. |
| ReduceSum.Options | Optional attributes for ReduceSum |
| RefEnter <T> | Creates or finds a child frame, and makes `data` available to the child frame. |
| RefEnter.Options | Optional attributes for RefEnter |
| RefExit <T> | Exits the current frame to its parent frame. |
| RefIdentity <T> | Return the same ref tensor as the input ref tensor. |
| RefMerge <T> | Forwards the value of an available tensor from `inputs` to `output`. |
| RefNextIteration <T> | Makes its input available to the next iteration. |
| RefSelect <T> | Forwards the `index`th element of `inputs` to `output`. |
| RefSwitch <T> | Forwards the ref tensor `data` to the output port determined by `pred`. |
| RegisterDataset | Registers a dataset with the tf.data service. |
| RegisterDataset.Options | Optional attributes for RegisterDataset |
| RegisterDatasetV2 | Registers a dataset with the tf.data service. |
| RegisterDatasetV2.Options | Optional attributes for RegisterDatasetV2 |
| Relayout <T> | |
| RelayoutGrad <T> | |
| RequantizationRangePerChannel | Computes requantization range per channel. |
| RequantizePerChannel <U> | Requantizes input with min and max values known per channel. |
| Reshape <T> | Reshapes a tensor. |
| 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> | Extracts the average gradient in the given ConditionalAccumulator. |
| ResourceApplyAdagradV2 | Update '*var' according to the adagrad scheme. |
| ResourceApplyAdagradV2.Options | Optional attributes for ResourceApplyAdagradV2 |
| ResourceApplyAdamWithAmsgrad | Update '*var' according to the Adam algorithm. |
| ResourceApplyAdamWithAmsgrad.Options | Optional attributes for ResourceApplyAdamWithAmsgrad |
| ResourceApplyKerasMomentum | Update '*var' according to the momentum scheme. |
| ResourceApplyKerasMomentum.Options | Optional attributes for ResourceApplyKerasMomentum |
| ResourceConditionalAccumulator | A conditional accumulator for aggregating gradients. |
| ResourceConditionalAccumulator.Options | Optional attributes for ResourceConditionalAccumulator |
| ResourceCountUpTo <T extends Number> | Increments variable pointed to by 'resource' until it reaches 'limit'. |
| ResourceGather <U> | Gather slices from the variable pointed to by `resource` according to `indices`. |
| ResourceGather.Options | Optional attributes for ResourceGather |
| ResourceGatherNd <U> | |
| 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`. |
| ResourceSparseApplyAdagradV2 | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
| ResourceSparseApplyAdagradV2.Options | Optional attributes for ResourceSparseApplyAdagradV2 |
| ResourceSparseApplyKerasMomentum | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
| ResourceSparseApplyKerasMomentum.Options | Optional attributes for ResourceSparseApplyKerasMomentum |
| ResourceStridedSliceAssign | Assign `value` to the sliced l-value reference of `ref`. |
| ResourceStridedSliceAssign.Options | Optional attributes for ResourceStridedSliceAssign |
| RetrieveAllTPUEmbeddingParameters | An op that retrieves optimization parameters from embedding to host memory. |
| RetrieveTPUEmbeddingAdadeltaParameters | Retrieve Adadelta embedding parameters. |
| RetrieveTPUEmbeddingAdadeltaParameters.Options | Optional attributes for RetrieveTPUEmbeddingAdadeltaParameters |
| RetrieveTPUEmbeddingAdagradMomentumParameters | Retrieve Adagrad Momentum embedding parameters. |
| RetrieveTPUEmbeddingAdagradMomentumParameters.Options | Optional attributes for RetrieveTPUEmbeddingAdagradMomentumParameters |
| RetrieveTPUEmbeddingAdagradParameters | Retrieve Adagrad embedding parameters. |
| RetrieveTPUEmbeddingAdagradParameters.Options | Optional attributes for RetrieveTPUEmbeddingAdagradParameters |
| RetrieveTPUEmbeddingADAMParameters | Retrieve ADAM embedding parameters. |
| RetrieveTPUEmbeddingADAMParameters.Options | Optional attributes for RetrieveTPUEmbeddingADAMParameters |
| RetrieveTPUEmbeddingCenteredRMSPropParameters | Retrieve centered RMSProp embedding parameters. |
| RetrieveTPUEmbeddingCenteredRMSPropParameters.Options | Optional attributes for RetrieveTPUEmbeddingCenteredRMSPropParameters |
| RetrieveTPUEmbeddingFrequencyEstimatorParameters | Retrieve frequency estimator embedding parameters. |
| RetrieveTPUEmbeddingFrequencyEstimatorParameters.Options | Optional attributes for RetrieveTPUEmbeddingFrequencyEstimatorParameters |
| RetrieveTPUEmbeddingFTRLParameters | Retrieve FTRL embedding parameters. |
| RetrieveTPUEmbeddingFTRLParameters.Options | Optional attributes for RetrieveTPUEmbeddingFTRLParameters |
| RetrieveTPUEmbeddingMDLAdagradLightParameters | Retrieve MDL Adagrad Light embedding parameters. |
| RetrieveTPUEmbeddingMDLAdagradLightParameters.Options | Optional attributes for RetrieveTPUEmbeddingMDLAdagradLightParameters |
| RetrieveTPUEmbeddingMomentumParameters | Retrieve Momentum embedding parameters. |
| RetrieveTPUEmbeddingMomentumParameters.Options | Optional attributes for RetrieveTPUEmbeddingMomentumParameters |
| RetrieveTPUEmbeddingProximalAdagradParameters | Retrieve proximal Adagrad embedding parameters. |
| RetrieveTPUEmbeddingProximalAdagradParameters.Options | Optional attributes for RetrieveTPUEmbeddingProximalAdagradParameters |
| RetrieveTPUEmbeddingProximalYogiParameters | |
| RetrieveTPUEmbeddingProximalYogiParameters.Options | Optional attributes for RetrieveTPUEmbeddingProximalYogiParameters |
| RetrieveTPUEmbeddingRMSPropParameters | Retrieve RMSProp embedding parameters. |
| RetrieveTPUEmbeddingRMSPropParameters.Options | Optional attributes for RetrieveTPUEmbeddingRMSPropParameters |
| RetrieveTPUEmbeddingStochasticGradientDescentParameters | Retrieve SGD embedding parameters. |
| RetrieveTPUEmbeddingStochasticGradientDescentParameters.Options | Optional attributes for RetrieveTPUEmbeddingStochasticGradientDescentParameters |
| Reverse <T> | Reverses specific dimensions of a tensor. |
| ReverseSequence <T> | Reverses variable length slices. |
| ReverseSequence.Options | Optional attributes for ReverseSequence |
| RewriteDataset | |
| RiscAbs <T extends Number> | |
| RiscAdd <T extends Number> | Returns x + y element-wise. |
| RiscBinaryArithmetic <T extends Number> | |
| RiscBinaryComparison | |
| RiscBitcast <U> | |
| RiscBroadcast <T> | |
| RiscCast <U> | |
| RiscCeil <T extends Number> | |
| RiscCholesky <T extends Number> | |
| RiscConcat <T> | |
| RiscConv <T extends Number> | |
| RiscConv.Options | Optional attributes for RiscConv |
| RiscCos <T extends Number> | |
| RiscDiv <T extends Number> | |
| RiscDot <T extends Number> | |
| RiscDot.Options | Optional attributes for RiscDot |
| RiscExp <T extends Number> | |
| RiscFft <T> | |
| RiscFloor <T extends Number> | |
| RiscGather <T> | |
| RiscGather.Options | Optional attributes for RiscGather |
| RiscImag <U extends Number> | |
| RiscIsFinite | |
| RiscLog <T extends Number> | |
| RiscLogicalAnd | |
| RiscLogicalNot | |
| RiscLogicalOr | |
| RiscMax <T extends Number> | Returns max(x, y) element-wise. |
| RiscMin <T extends Number> | |
| RiscMul <T extends Number> | |
| RiscNeg <T extends Number> | |
| RiscPad <T extends Number> | |
| RiscPool <T extends Number> | |
| RiscPool.Options | Optional attributes for RiscPool |
| RiscPow <T extends Number> | |
| RiscRandomUniform | |
| RiscRandomUniform.Options | Optional attributes for RiscRandomUniform |
| RiscReal <U extends Number> | |
| RiscReduce <T extends Number> | |
| RiscRem <T extends Number> | |
| RiscReshape <T extends Number> | |
| RiscReverse <T extends Number> | |
| RiscScatter <U extends Number> | |
| RiscShape <U extends Number> | |
| RiscSign <T extends Number> | |
| RiscSlice <T extends Number> | |
| RiscSort <T extends Number> | |
| RiscSqueeze <T> | |
| RiscSqueeze.Options | Optional attributes for RiscSqueeze |
| RiscSub <T extends Number> | |
| RiscTranspose <T> | |
| RiscTriangularSolve <T extends Number> | |
| RiscTriangularSolve.Options | Optional attributes for RiscTriangularSolve |
| RiscUnary <T extends Number> | |
| RngReadAndSkip | Advance the counter of a counter-based RNG. |
| RngSkip | Advance the counter of a counter-based RNG. |
| Roll <T> | Rolls the elements of a tensor along an axis. |
| SamplingDataset | Creates a dataset that takes a Bernoulli sample of the contents of another dataset. |
| ScaleAndTranslate | |
| ScaleAndTranslate.Options | Optional attributes for ScaleAndTranslate |
| ScaleAndTranslateGrad <T extends Number> | |
| ScaleAndTranslateGrad.Options | Optional attributes for ScaleAndTranslateGrad |
| ScatterAdd <T> | Adds sparse updates to a variable reference. |
| ScatterAdd.Options | Optional attributes for ScatterAdd |
| ScatterDiv <T> | Divides a variable reference by sparse updates. |
| ScatterDiv.Options | Optional attributes for ScatterDiv |
| ScatterMax <T extends Number> | Reduces sparse updates into a variable reference using the `max` operation. |
| ScatterMax.Options | Optional attributes for ScatterMax |
| ScatterMin <T extends Number> | Reduces sparse updates into a variable reference using the `min` operation. |
| ScatterMin.Options | Optional attributes for ScatterMin |
| ScatterMul <T> | Multiplies sparse updates into a variable reference. |
| ScatterMul.Options | Optional attributes for ScatterMul |
| ScatterNd <U> | Scatters `updates` into a tensor of shape `shape` according to `indices`. |
| ScatterNdAdd <T> | Applies sparse addition to individual values or slices in a Variable. |
| ScatterNdAdd.Options | Optional attributes for ScatterNdAdd |
| ScatterNdMax <T> | Computes element-wise maximum. |
| ScatterNdMax.Options | Optional attributes for ScatterNdMax |
| ScatterNdMin <T> | Computes element-wise minimum. |
| ScatterNdMin.Options | Optional attributes for ScatterNdMin |
| ScatterNdNonAliasingAdd <T> | Applies sparse addition to `input` using individual values or slices from `updates` according to indices `indices`. |
| ScatterNdSub <T> | Applies sparse subtraction to individual values or slices in a Variable. |
| ScatterNdSub.Options | Optional attributes for ScatterNdSub |
| ScatterNdUpdate <T> | Applies sparse `updates` to individual values or slices within a given variable according to `indices`. |
| ScatterNdUpdate.Options | Optional attributes for ScatterNdUpdate |
| ScatterSub <T> | Subtracts sparse updates to a variable reference. |
| ScatterSub.Options | Optional attributes for ScatterSub |
| ScatterUpdate <T> | Applies sparse updates to a variable reference. |
| ScatterUpdate.Options | Optional attributes for ScatterUpdate |
| SegmentMaxV2 <T extends Number> | Computes the maximum along segments of a tensor. |
| SegmentMinV2 <T extends Number> | Computes the minimum along segments of a tensor. |
| SegmentProdV2 <T> | Computes the product along segments of a tensor. |
| SegmentSumV2 <T> | Computes the sum along segments of a tensor. |
| SelectV2 <T> | |
| Send | Sends the named tensor from send_device to recv_device. |
| Send.Options | Optional attributes for Send |
| SendTPUEmbeddingGradients | Performs gradient updates of embedding tables. |
| SetDiff1d <T, U extends Number> | 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 |
| Shape <U extends Number> | Returns the shape of a tensor. |
| ShapeN <U extends Number> | Returns shape of tensors. |
| ShardDataset | Creates a `Dataset` that includes only 1/`num_shards` of this dataset. |
| ShardDataset.Options | Optional attributes for ShardDataset |
| ShuffleAndRepeatDatasetV2 | |
| ShuffleAndRepeatDatasetV2.Options | Optional attributes for ShuffleAndRepeatDatasetV2 |
| ShuffleDatasetV2 | |
| ShuffleDatasetV2.Options | Optional attributes for ShuffleDatasetV2 |
| ShuffleDatasetV3 | |
| ShuffleDatasetV3.Options | Optional attributes for ShuffleDatasetV3 |
| ShutdownDistributedTPU | Shuts down a running distributed TPU system. |
| ShutdownTPUSystem | An op that shuts down the TPU system. |
| Size <U extends Number> | Returns the size of a tensor. |
| Skipgram | Parses a text file and creates a batch of examples. |
| Skipgram.Options | Optional attributes for Skipgram |
| SleepDataset | |
| Slice <T> | Return a slice from 'input'. |
| SlidingWindowDataset | Creates a dataset that passes a sliding window over `input_dataset`. |
| SlidingWindowDataset.Options | Optional attributes for SlidingWindowDataset |
| Snapshot <T> | Returns a copy of the input tensor. |
| SnapshotDataset | Creates a dataset that will write to / read from a snapshot. |
| SnapshotDataset.Options | Optional attributes for SnapshotDataset |
| SnapshotDatasetReader | |
| SnapshotDatasetReader.Options | Optional attributes for SnapshotDatasetReader |
| SnapshotNestedDatasetReader | |
| SobolSample <T extends Number> | Generates points from the Sobol sequence. |
| SpaceToBatchNd <T> | SpaceToBatch for ND tensors of type T. |
| SparseApplyAdagradV2 <T> | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
| SparseApplyAdagradV2.Options | Optional attributes for SparseApplyAdagradV2 |
| SparseBincount <U extends Number> | Counts the number of occurrences of each value in an integer array. |
| SparseBincount.Options | Optional attributes for SparseBincount |
| SparseCountSparseOutput <U extends Number> | Performs sparse-output bin counting for a sparse tensor input. |
| SparseCountSparseOutput.Options | Optional attributes for SparseCountSparseOutput |
| SparseCrossHashed | Generates sparse cross from a list of sparse and dense tensors. |
| SparseCrossV2 | Generates sparse cross from a list of sparse and dense tensors. |
| SparseMatrixAdd | Sparse addition of two CSR matrices, C = alpha * A + beta * B. |
| SparseMatrixMatMul <T> | 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`. |
| SparseSegmentSumGrad <T extends Number> | Computes gradients for SparseSegmentSum. |
| SparseTensorToCSRSparseMatrix | Converts a SparseTensor to a (possibly batched) CSRSparseMatrix. |
| Spence <T extends Number> | |
| Split <T> | Splits a tensor into `num_split` tensors along one dimension. |
| SplitDedupData <T extends Number, U extends Number> | An op splits input deduplication data XLA tuple into integer and floating point tensors. |
| SplitDedupData.Options | Optional attributes for SplitDedupData |
| SplitV <T> | Splits a tensor into `num_split` tensors along one dimension. |
| Squeeze <T> | Removes dimensions of size 1 from the shape of a tensor. |
| Squeeze.Options | Optional attributes for Squeeze |
| Stack <T> | Packs a list of `N` rank-`R` tensors into one rank-`(R+1)` tensor. |
| Stack.Options | Optional attributes for Stack |
| Stage | 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 Number> | |
| StatefulStandardNormal <U> | Outputs random values from a normal distribution. |
| StatefulStandardNormalV2 <U> | Outputs random values from a normal distribution. |
| StatefulTruncatedNormal <U> | Outputs random values from a truncated normal distribution. |
| StatefulUniform <U> | Outputs random values from a uniform distribution. |
| StatefulUniformFullInt <U> | Outputs random integers from a uniform distribution. |
| StatefulUniformInt <U> | Outputs random integers from a uniform distribution. |
| StatelessParameterizedTruncatedNormal <V extends Number> | |
| StatelessRandomBinomial <W extends Number> | Outputs deterministic pseudorandom random numbers from a binomial distribution. |
| StatelessRandomGammaV2 <V extends Number> | Outputs deterministic pseudorandom random numbers from a gamma distribution. |
| StatelessRandomGammaV3 <U extends Number> | Outputs deterministic pseudorandom random numbers from a gamma distribution. |
| StatelessRandomGetAlg | Picks the best counter-based RNG algorithm based on device. |
| StatelessRandomGetKeyCounter | Scrambles seed into key and counter, using the best algorithm based on device. |
| StatelessRandomGetKeyCounterAlg | Picks the best algorithm based on device, and scrambles seed into key and counter. |
| StatelessRandomNormalV2 <U extends Number> | Outputs deterministic pseudorandom values from a normal distribution. |
| StatelessRandomPoisson <W extends Number> | Outputs deterministic pseudorandom random numbers from a Poisson distribution. |
| StatelessRandomUniformFullInt <V extends Number> | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformFullIntV2 <U extends Number> | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformIntV2 <U extends Number> | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformV2 <U extends Number> | Outputs deterministic pseudorandom random values from a uniform distribution. |
| StatelessSampleDistortedBoundingBox <T extends Number> | Generate a randomly distorted bounding box for an image deterministically. |
| StatelessSampleDistortedBoundingBox.Options | Optional attributes for StatelessSampleDistortedBoundingBox |
| StatelessShuffle <T> | Randomly and deterministically shuffles a tensor along its first dimension. |
| StatelessTruncatedNormalV2 <U extends Number> | Outputs deterministic pseudorandom values from a truncated normal distribution. |
| StatsAggregatorHandleV2 | |
| StatsAggregatorHandleV2.Options | Optional attributes for StatsAggregatorHandleV2 |
| StatsAggregatorSetSummaryWriter | Set a summary_writer_interface to record statistics using given stats_aggregator. |
| StopGradient <T> | Stops gradient computation. |
| StridedSlice <T> | Return a strided slice from `input`. |
| StridedSlice.Options | Optional attributes for StridedSlice |
| StridedSliceAssign <T> | Assign `value` to the sliced l-value reference of `ref`. |
| StridedSliceAssign.Options | Optional attributes for StridedSliceAssign |
| StridedSliceGrad <U> | Returns the gradient of `StridedSlice`. |
| StridedSliceGrad.Options | Optional attributes for StridedSliceGrad |
| StringLower | Converts all uppercase characters into their respective lowercase replacements. |
| StringLower.Options | Optional attributes for StringLower |
| StringNGrams <T extends Number> | Creates ngrams from ragged string data. |
| StringUpper | Converts all lowercase characters into their respective uppercase replacements. |
| StringUpper.Options | Optional attributes for StringUpper |
| Sum <T> | Computes the sum of elements across dimensions of a tensor. |
| Sum.Options | Optional attributes for Sum |
| SwitchCond <T> | Forwards `data` to the output port determined by `pred`. |
| SyncDevice | Synchronizes the device this op is run on. |
| TemporaryVariable <T> | Returns a tensor that may be mutated, but only persists within a single step. |
| TemporaryVariable.Options | Optional attributes for TemporaryVariable |
| TensorArray | An array of Tensors of given size. |
| TensorArray.Options | Optional attributes for TensorArray |
| TensorArrayClose | Delete the TensorArray from its resource container. |
| TensorArrayConcat <T> | Concat the elements from the TensorArray into value `value`. |
| TensorArrayConcat.Options | Optional attributes for TensorArrayConcat |
| TensorArrayGather <T> | 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> | |
| TensorArrayPack.Options | Optional attributes for TensorArrayPack |
| TensorArrayRead <T> | 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. |
| TensorListConcat <T> | Concats all tensors in the list along the 0th dimension. |
| TensorListConcat.Options | Optional attributes for TensorListConcat |
| TensorListConcatLists | |
| TensorListConcatV2 <U> | Concats all tensors in the list along the 0th dimension. |
| TensorListElementShape <T extends Number> | 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> | Creates a Tensor by indexing into the TensorList. |
| TensorListGetItem <T> | |
| TensorListLength | Returns the number of tensors in the input tensor list. |
| TensorListPopBack <T> | 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. |
| TensorListScatterV2 | Creates a TensorList by indexing into a Tensor. |
| TensorListSetItem | |
| TensorListSetItem.Options | Optional attributes for TensorListSetItem |
| TensorListSplit | Splits a tensor into a list. |
| TensorListStack <T> | 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> | Returns the value from a given key in a tensor map. |
| TensorMapSize | Returns the number of tensors in the input tensor map. |
| TensorMapStackKeys <T> | Returns a Tensor stack of all keys in a tensor map. |
| TensorScatterAdd <T> | Adds sparse `updates` to an existing tensor according to `indices`. |
| TensorScatterMax <T> | Apply a sparse update to a tensor taking the element-wise maximum. |
| TensorScatterMin <T> | |
| TensorScatterSub <T> | Subtracts sparse `updates` from an existing tensor according to `indices`. |
| TensorScatterUpdate <T> | Scatter `updates` into an existing tensor according to `indices`. |
| TensorStridedSliceUpdate <T> | Assign `value` to the sliced l-value reference of `input`. |
| TensorStridedSliceUpdate.Options | Optional attributes for TensorStridedSliceUpdate |
| 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.Options | Optional attributes for ThreadPoolHandle |
| Tile <T> | Constructs a tensor by tiling a given tensor. |
| Timestamp | Provides the time since epoch in seconds. |
| ToBool | Converts a tensor to a scalar predicate. |
| 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. |
| TPUCompileSucceededAssert | Asserts that compilation succeeded. |
| TPUEmbeddingActivations | An op enabling differentiation of TPU Embeddings. |
| TPUExecute | Op that loads and executes a TPU program on a TPU device. |
| TPUExecuteAndUpdateVariables | Op that executes a program with optional in-place variable updates. |
| TpuHandleToProtoKey | Converts XRT's uid handles to TensorFlow-friendly input format. |
| TPUOrdinalSelector | A TPU core selector Op. |
| TPUPartitionedInput <T> | An op that groups a list of partitioned inputs together. |
| TPUPartitionedInput.Options | Optional attributes for TPUPartitionedInput |
| TPUPartitionedInputV2 <T> | An op that groups a list of partitioned inputs together. |
| TPUPartitionedInputV2.Options | Optional attributes for TPUPartitionedInputV2 |
| TPUPartitionedOutput <T> | An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned outputs outside the XLA computation. |
| TPUPartitionedOutput.Options | Optional attributes for TPUPartitionedOutput |
| TPUPartitionedOutputV2 <T> | An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned outputs outside the XLA computation. |
| TPUReplicatedInput <T> | Connects N inputs to an N-way replicated TPU computation. |
| TPUReplicatedInput.Options | Optional attributes for TPUReplicatedInput |
| TPUReplicatedOutput <T> | 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 |
| TPUReshardVariables | Op that reshards on-device TPU variables to specified state. |
| TPURoundRobin | Round-robin load balancing on TPU cores. |
| TridiagonalMatMul <T> | Calculate product with tridiagonal matrix. |
| TridiagonalSolve <T> | Solves tridiagonal systems of equations. |
| TridiagonalSolve.Options | Optional attributes for TridiagonalSolve |
| Unbatch <T> | Reverses the operation of Batch for a single output Tensor. |
| Unbatch.Options | Optional attributes for Unbatch |
| UnbatchGrad <T> | Gradient of Unbatch. |
| UnbatchGrad.Options | Optional attributes for UnbatchGrad |
| UncompressElement | Uncompresses a compressed dataset element. |
| UnicodeDecode <T extends Number> | Decodes each string in `input` into a sequence of Unicode code points. |
| UnicodeDecode.Options | Optional attributes for UnicodeDecode |
| UnicodeEncode | Encode a tensor of ints into unicode strings. |
| UnicodeEncode.Options | Optional attributes for UnicodeEncode |
| UniformDequantize <U extends Number> | Perform dequantization on the quantized Tensor `input`. |
| UniformDequantize.Options | Optional attributes for UniformDequantize |
| UniformQuantize <U> | Perform quantization on Tensor `input`. |
| UniformQuantize.Options | Optional attributes for UniformQuantize |
| UniformQuantizedAdd <T> | Perform quantized add of quantized Tensor `lhs` and quantized Tensor `rhs` to make quantized `output`. |
| UniformQuantizedAdd.Options | Optional attributes for UniformQuantizedAdd |
| UniformQuantizedClipByValue <T> | Perform clip by value on the quantized Tensor `operand`. |
| UniformQuantizedClipByValue.Options | Optional attributes for UniformQuantizedClipByValue |
| UniformQuantizedConvolution <U> | Perform quantized convolution of quantized Tensor `lhs` and quantized Tensor `rhs`. |
| UniformQuantizedConvolution.Options | Optional attributes for UniformQuantizedConvolution |
| UniformQuantizedConvolutionHybrid <V extends Number> | Perform hybrid quantized convolution of float Tensor `lhs` and quantized Tensor `rhs`. |
| UniformQuantizedConvolutionHybrid.Options | Optional attributes for UniformQuantizedConvolutionHybrid |
| UniformQuantizedDot <U> | Perform quantized dot of quantized Tensor `lhs` and quantized Tensor `rhs` to make quantized `output`. |
| UniformQuantizedDot.Options | Optional attributes for UniformQuantizedDot |
| UniformQuantizedDotHybrid <V extends Number> | Perform hybrid quantized dot of float Tensor `lhs` and quantized Tensor `rhs`. |
| UniformQuantizedDotHybrid.Options | Optional attributes for UniformQuantizedDotHybrid |
| UniformRequantize <U> | Given quantized tensor `input`, requantize it with new quantization parameters. |
| UniformRequantize.Options | Optional attributes for UniformRequantize |
| Unique <T, V extends Number> | Finds unique elements along an axis of a tensor. |
| UniqueDataset | Creates a dataset that contains the unique elements of `input_dataset`. |
| UniqueDataset.Options | Optional attributes for UniqueDataset |
| UniqueWithCounts <T, V extends Number> | Finds unique elements along an axis of a tensor. |
| UnravelIndex <T extends Number> | Converts an array of flat indices into a tuple of coordinate arrays. |
| UnsortedSegmentJoin | |
| UnsortedSegmentJoin.Options | Optional attributes for UnsortedSegmentJoin |
| Unstack <T> | 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 | |
| UpperBound <U extends Number> | Applies upper_bound(sorted_search_values, values) along each row. |
| VarHandleOp | Creates a handle to a Variable resource. |
| VarHandleOp.Options | Optional attributes for VarHandleOp |
| Variable <T> | Holds state in the form of a tensor that persists across steps. |
| Variable.Options | Optional attributes for Variable |
| VariableShape <T extends Number> | Returns the shape of the variable pointed to by `resource`. |
| VarIsInitializedOp | Checks whether a resource handle-based variable has been initialized. |
| Where | Returns locations of nonzero / true values in a tensor. |
| Where3 <T> | Selects elements from `x` or `y`, depending on `condition`. |
| WindowOp | |
| WorkerHeartbeat | Worker heartbeat op. |
| WrapDatasetVariant | |
| WriteRawProtoSummary | Writes a serialized proto summary. |
| XlaConcatND <T> | Concats input tensor across all dimensions. |
| XlaConcatND.Options | Optional attributes for XlaConcatND |
| XlaRecvFromHost <T> | An op to receive a tensor from the host. |
| XlaRecvTPUEmbeddingActivations | An op that receives embedding activations on the TPU. |
| XlaRecvTPUEmbeddingDeduplicationData | Receives deduplication data (indices and weights) from the embedding core. |
| XlaSendToHost | An op to send a tensor to the host. |
| XlaSendTPUEmbeddingGradients | An op that performs gradient updates of embedding tables. |
| XlaSplitND <T> | Splits input tensor across all dimensions. |
| XlaSplitND.Options | Optional attributes for XlaSplitND |
| Xlog1py <T> | Returns 0 if x == 0, and x * log1p(y) otherwise, elementwise. |
| Zeros <T> | An operator creating a constant initialized with zeros of the shape given by `dims`. |
| ZerosLike <T> | Returns a tensor of zeros with the same shape and type as x. |
Classes
| Abort | Raise a exception to abort the process when called. |
| Abort.Options | Optional attributes for Abort |
| All | Computes the "logical and" of elements across dimensions of a tensor. |
| All.Options | Optional attributes for All |
| AllToAll <T> | An Op to exchange data across TPU replicas. |
| AnonymousHashTable | Creates a uninitialized anonymous hash table. |
| AnonymousIteratorV2 | A container for an iterator resource. |
| AnonymousIteratorV3 | A container for an iterator resource. |
| AnonymousMemoryCache | |
| AnonymousMultiDeviceIterator | A container for a multi device iterator resource. |
| AnonymousMultiDeviceIteratorV3 | A container for a multi device iterator resource. |
| AnonymousMutableDenseHashTable | Creates an empty anonymous mutable hash table that uses tensors as the backing store. |
| AnonymousMutableDenseHashTable.Options | Optional attributes for AnonymousMutableDenseHashTable |
| AnonymousMutableHashTable | Creates an empty anonymous mutable hash table. |
| AnonymousMutableHashTableOfTensors | Creates an empty anonymous mutable hash table of vector values. |
| AnonymousMutableHashTableOfTensors.Options | Optional attributes for AnonymousMutableHashTableOfTensors |
| AnonymousRandomSeedGenerator | |
| AnonymousSeedGenerator | |
| Any | Computes the "logical or" of elements across dimensions of a tensor. |
| Any.Options | Optional attributes for Any |
| ApplyAdagradV2 <T> | Update '*var' according to the adagrad scheme. |
| ApplyAdagradV2.Options | Optional attributes for ApplyAdagradV2 |
| ApproxTopK <T extends Number> | Returns min/max k values and their indices of the input operand in an approximate manner. |
| ApproxTopK.Options | Optional attributes for ApproxTopK |
| AssertCardinalityDataset | |
| AssertNextDataset | A transformation that asserts which transformations happen next. |
| AssertPrevDataset | A transformation that asserts which transformations happened previously. |
| AssertThat | Asserts that the given condition is true. |
| AssertThat.Options | Optional attributes for AssertThat |
| Assign <T> | Update 'ref' by assigning 'value' to it. |
| Assign.Options | Optional attributes for Assign |
| AssignAdd <T> | Update 'ref' by adding 'value' to it. |
| AssignAdd.Options | Optional attributes for AssignAdd |
| AssignAddVariableOp | Adds a value to the current value of a variable. |
| AssignSub <T> | Update 'ref' by subtracting 'value' from it. |
| AssignSub.Options | Optional attributes for AssignSub |
| AssignSubVariableOp | Subtracts a value from the current value of a variable. |
| AssignVariableOp | Assigns a new value to a variable. |
| AssignVariableOp.Options | Optional attributes for AssignVariableOp |
| AssignVariableXlaConcatND | Concats input tensor across all dimensions. |
| AssignVariableXlaConcatND.Options | Optional attributes for AssignVariableXlaConcatND |
| AutoShardDataset | Creates a dataset that shards the input dataset. |
| AutoShardDataset.Options | Optional attributes for AutoShardDataset |
| BandedTriangularSolve <T> | |
| BandedTriangularSolve.Options | Optional attributes for BandedTriangularSolve |
| Barrier | Defines a barrier that persists across different graph executions. |
| Barrier.Options | Optional attributes for Barrier |
| BarrierClose | Closes the given barrier. |
| BarrierClose.Options | Optional attributes for BarrierClose |
| BarrierIncompleteSize | Computes the number of incomplete elements in the given barrier. |
| BarrierInsertMany | For each key, assigns the respective value to the specified component. |
| BarrierReadySize | Computes the number of complete elements in the given barrier. |
| BarrierTakeMany | Takes the given number of completed elements from a barrier. |
| BarrierTakeMany.Options | Optional attributes for BarrierTakeMany |
| Batch | Batches all input tensors nondeterministically. |
| Batch.Options | Optional attributes for Batch |
| BatchMatMulV2 <T> | Multiplies slices of two tensors in batches. |
| BatchMatMulV2.Options | Optional attributes for BatchMatMulV2 |
| BatchMatMulV3 <V> | Multiplies slices of two tensors in batches. |
| BatchMatMulV3.Options | Optional attributes for BatchMatMulV3 |
| BatchToSpace <T> | BatchToSpace for 4-D tensors of type T. |
| BatchToSpaceNd <T> | BatchToSpace for ND tensors of type T. |
| BesselI0 <T extends Number> | |
| BesselI1 <T extends Number> | |
| BesselJ0 <T extends Number> | |
| BesselJ1 <T extends Number> | |
| BesselK0 <T extends Number> | |
| BesselK0e <T extends Number> | |
| BesselK1 <T extends Number> | |
| BesselK1e <T extends Number> | |
| BesselY0 <T extends Number> | |
| BesselY1 <T extends Number> | |
| Bitcast <U> | Bitcasts a tensor from one type to another without copying data. |
| BlockLSTM <T extends Number> | Computes the LSTM cell forward propagation for all the time steps. |
| BlockLSTM.Options | Optional attributes for BlockLSTM |
| BlockLSTMGrad <T extends Number> | Computes the LSTM cell backward propagation for the entire time sequence. |
| BlockLSTMGradV2 <T extends Number> | Computes the LSTM cell backward propagation for the entire time sequence. |
| BlockLSTMV2 <T extends Number> | Computes the LSTM cell forward propagation for all the time steps. |
| BlockLSTMV2.Options | Optional attributes for BlockLSTMV2 |
| BoostedTreesAggregateStats | Aggregates the summary of accumulated stats for the batch. |
| BoostedTreesBucketize | Bucketize each feature based on bucket boundaries. |
| BoostedTreesCalculateBestFeatureSplit | Calculates gains for each feature and returns the best possible split information for the feature. |
| BoostedTreesCalculateBestFeatureSplit.Options | Optional attributes for BoostedTreesCalculateBestFeatureSplit |
| BoostedTreesCalculateBestFeatureSplitV2 | Calculates gains for each feature and returns the best possible split information for each node. |
| BoostedTreesCalculateBestGainsPerFeature | Calculates gains for each feature and returns the best possible split information for the feature. |
| BoostedTreesCenterBias | Calculates the prior from the training data (the bias) and fills in the first node with the logits' prior. |
| BoostedTreesCreateEnsemble | Creates a tree ensemble model and returns a handle to it. |
| BoostedTreesCreateQuantileStreamResource | Create the Resource for Quantile Streams. |
| BoostedTreesCreateQuantileStreamResource.Options | Optional attributes for BoostedTreesCreateQuantileStreamResource |
| BoostedTreesDeserializeEnsemble | Deserializes a serialized tree ensemble config and replaces current tree ensemble. |
| BoostedTreesEnsembleResourceHandleOp | Creates a handle to a BoostedTreesEnsembleResource |
| BoostedTreesEnsembleResourceHandleOp.Options | Optional attributes for BoostedTreesEnsembleResourceHandleOp |
| BoostedTreesExampleDebugOutputs | Debugging/model interpretability outputs for each example. |
| BoostedTreesFlushQuantileSummaries | Flush the quantile summaries from each quantile stream resource. |
| BoostedTreesGetEnsembleStates | Retrieves the tree ensemble resource stamp token, number of trees and growing statistics. |
| BoostedTreesMakeQuantileSummaries | Makes the summary of quantiles for the batch. |
| BoostedTreesMakeStatsSummary | Makes the summary of accumulated stats for the batch. |
| BoostedTreesPredict | Runs multiple additive regression ensemble predictors on input instances and computes the logits. |
| BoostedTreesQuantileStreamResourceAddSummaries | Add the quantile summaries to each quantile stream resource. |
| BoostedTreesQuantileStreamResourceDeserialize | Deserialize bucket boundaries and ready flag into current QuantileAccumulator. |
| BoostedTreesQuantileStreamResourceFlush | Flush the summaries for a quantile stream resource. |
| BoostedTreesQuantileStreamResourceFlush.Options | Optional attributes for BoostedTreesQuantileStreamResourceFlush |
| BoostedTreesQuantileStreamResourceGetBucketBoundaries | Generate the bucket boundaries for each feature based on accumulated summaries. |
| BoostedTreesQuantileStreamResourceHandleOp | Creates a handle to a BoostedTreesQuantileStreamResource. |
| BoostedTreesQuantileStreamResourceHandleOp.Options | Optional attributes for BoostedTreesQuantileStreamResourceHandleOp |
| BoostedTreesSerializeEnsemble | Serializes the tree ensemble to a proto. |
| BoostedTreesSparseAggregateStats | Aggregates the summary of accumulated stats for the batch. |
| BoostedTreesSparseCalculateBestFeatureSplit | Calculates gains for each feature and returns the best possible split information for the feature. |
| BoostedTreesSparseCalculateBestFeatureSplit.Options | Optional attributes for BoostedTreesSparseCalculateBestFeatureSplit |
| BoostedTreesTrainingPredict | Runs multiple additive regression ensemble predictors on input instances and computes the update to cached logits. |
| BoostedTreesUpdateEnsemble | Updates the tree ensemble by either adding a layer to the last tree being grown or by starting a new tree. |
| BoostedTreesUpdateEnsembleV2 | Updates the tree ensemble by adding a layer to the last tree being grown or by starting a new tree. |
| BoostedTreesUpdateEnsembleV2.Options | Optional attributes for BoostedTreesUpdateEnsembleV2 |
| BroadcastDynamicShape <T extends Number> | Return the shape of s0 op s1 with broadcast. |
| BroadcastGradientArgs <T extends Number> | Return the reduction indices for computing gradients of s0 op s1 with broadcast. |
| BroadcastTo <T> | Broadcast an array for a compatible shape. |
| Bucketize | Bucketizes 'input' based on 'boundaries'. |
| CacheDatasetV2 | |
| CacheDatasetV2.Options | Optional attributes for CacheDatasetV2 |
| CheckNumericsV2 <T extends Number> | Checks a tensor for NaN, -Inf and +Inf values. |
| ChooseFastestDataset | |
| ClipByValue <T> | Clips tensor values to a specified min and max. |
| CollateTPUEmbeddingMemory | An op that merges the string-encoded memory config protos from all hosts. |
| CollectiveAllToAllV2 <T extends Number> | Mutually exchanges multiple tensors of identical type and shape. |
| CollectiveAllToAllV2.Options | Optional attributes for CollectiveAllToAllV2 |
| CollectiveAllToAllV3 <T extends Number> | Mutually exchanges multiple tensors of identical type and shape. |
| CollectiveAllToAllV3.Options | Optional attributes for CollectiveAllToAllV3 |
| CollectiveAssignGroupV2 | Assign group keys based on group assignment. |
| CollectiveBcastRecvV2 <U> | Receives a tensor value broadcast from another device. |
| CollectiveBcastRecvV2.Options | Optional attributes for CollectiveBcastRecvV2 |
| CollectiveBcastSendV2 <T> | Broadcasts a tensor value to one or more other devices. |
| CollectiveBcastSendV2.Options | Optional attributes for CollectiveBcastSendV2 |
| CollectiveGather <T extends Number> | Mutually accumulates multiple tensors of identical type and shape. |
| CollectiveGather.Options | Optional attributes for CollectiveGather |
| CollectiveGatherV2 <T extends Number> | Mutually accumulates multiple tensors of identical type and shape. |
| CollectiveGatherV2.Options | Optional attributes for CollectiveGatherV2 |
| CollectiveInitializeCommunicator | Initializes a group for collective operations. |
| CollectiveInitializeCommunicator.Options | Optional attributes for CollectiveInitializeCommunicator |
| CollectivePermute <T> | An Op to permute tensors across replicated TPU instances. |
| CollectiveReduceScatterV2 <T extends Number> | Mutually reduces multiple tensors of identical type and shape and scatters the result. |
| CollectiveReduceScatterV2.Options | Optional attributes for CollectiveReduceScatterV2 |
| CollectiveReduceV2 <T extends Number> | Mutually reduces multiple tensors of identical type and shape. |
| CollectiveReduceV2.Options | Optional attributes for CollectiveReduceV2 |
| CollectiveReduceV3 <T extends Number> | Mutually reduces multiple tensors of identical type and shape. |
| CollectiveReduceV3.Options | Optional attributes for CollectiveReduceV3 |
| CombinedNonMaxSuppression | Greedily selects a subset of bounding boxes in descending order of score, This operation performs non_max_suppression on the inputs per batch, across all classes. |
| CombinedNonMaxSuppression.Options | Optional attributes for CombinedNonMaxSuppression |
| CompositeTensorVariantFromComponents | Encodes an `ExtensionType` value into a `variant` scalar Tensor. |
| CompositeTensorVariantToComponents | Decodes a `variant` scalar Tensor into an `ExtensionType` value. |
| CompressElement | Compresses a dataset element. |
| ComputeBatchSize | Computes the static batch size of a dataset sans partial batches. |
| ComputeDedupDataTupleMask | An op computes tuple mask of deduplication data from embedding core. |
| Concat <T> | Concatenates tensors along one dimension. |
| ConfigureAndInitializeGlobalTPU | An op that sets up the centralized structures for a distributed TPU system. |
| ConfigureAndInitializeGlobalTPU.Options | Optional attributes for ConfigureAndInitializeGlobalTPU |
| ConfigureDistributedTPU | Sets up the centralized structures for a distributed TPU system. |
| ConfigureDistributedTPU.Options | Optional attributes for ConfigureDistributedTPU |
| ConfigureTPUEmbedding | Sets up TPUEmbedding in a distributed TPU system. |
| ConfigureTPUEmbeddingHost | An op that configures the TPUEmbedding software on a host. |
| ConfigureTPUEmbeddingMemory | An op that configures the TPUEmbedding software on a host. |
| ConnectTPUEmbeddingHosts | An op that sets up communication between TPUEmbedding host software instances after ConfigureTPUEmbeddingHost has been called on each host. |
| Constant <T> | An operator producing a constant value. |
| ConsumeMutexLock | This op consumes a lock created by `MutexLock`. |
| ControlTrigger | Does nothing. |
| Conv2DBackpropFilterV2 <T extends Number> | Computes the gradients of convolution with respect to the filter. |
| Conv2DBackpropFilterV2.Options | Optional attributes for Conv2DBackpropFilterV2 |
| Conv2DBackpropInputV2 <T extends Number> | Computes the gradients of convolution with respect to the input. |
| Conv2DBackpropInputV2.Options | Optional attributes for Conv2DBackpropInputV2 |
| Copy <T> | Copy a tensor from CPU-to-CPU or GPU-to-GPU. |
| Copy.Options | Optional attributes for Copy |
| CopyHost <T> | Copy a tensor to host. |
| CopyHost.Options | Optional attributes for CopyHost |
| CopyToMesh <T> | |
| CopyToMeshGrad <T> | |
| CopyToMeshGrad.Options | Optional attributes for CopyToMeshGrad |
| CountUpTo <T extends Number> | Increments 'ref' until it reaches 'limit'. |
| CrossReplicaSum <T extends Number> | An Op to sum inputs across replicated TPU instances. |
| CSRSparseMatrixComponents <T> | Reads out the CSR components at batch `index`. |
| CSRSparseMatrixToDense <T> | Convert a (possibly batched) CSRSparseMatrix to dense. |
| CSRSparseMatrixToSparseTensor <T> | Converts a (possibly batched) CSRSparesMatrix to a SparseTensor. |
| CSVDataset | |
| CSVDatasetV2 | |
| CTCLossV2 | Calculates the CTC Loss (log probability) for each batch entry. |
| CTCLossV2.Options | Optional attributes for CTCLossV2 |
| CudnnRNNBackpropV3 <T extends Number> | Backprop step of CudnnRNNV3. |
| CudnnRNNBackpropV3.Options | Optional attributes for CudnnRNNBackpropV3 |
| CudnnRNNCanonicalToParamsV2 <T extends Number> | Converts CudnnRNN params from canonical form to usable form. |
| CudnnRNNCanonicalToParamsV2.Options | Optional attributes for CudnnRNNCanonicalToParamsV2 |
| CudnnRNNParamsToCanonicalV2 <T extends Number> | Retrieves CudnnRNN params in canonical form. |
| CudnnRNNParamsToCanonicalV2.Options | Optional attributes for CudnnRNNParamsToCanonicalV2 |
| CudnnRNNV3 <T extends Number> | A RNN backed by cuDNN. |
| CudnnRNNV3.Options | Optional attributes for CudnnRNNV3 |
| CumulativeLogsumexp <T extends Number> | Compute the cumulative product of the tensor `x` along `axis`. |
| CumulativeLogsumexp.Options | Optional attributes for CumulativeLogsumexp |
| DataServiceDataset | Creates a dataset that reads data from the tf.data service. |
| DataServiceDataset.Options | Optional attributes for DataServiceDataset |
| DataServiceDatasetV2 | Creates a dataset that reads data from the tf.data service. |
| DataServiceDatasetV2.Options | Optional attributes for DataServiceDatasetV2 |
| DatasetCardinality | Returns the cardinality of `input_dataset`. |
| DatasetCardinality.Options | Optional attributes for DatasetCardinality |
| DatasetFromGraph | Creates a dataset from the given `graph_def`. |
| DatasetToGraphV2 | Returns a serialized GraphDef representing `input_dataset`. |
| DatasetToGraphV2.Options | Optional attributes for DatasetToGraphV2 |
| Dawsn <T extends Number> | |
| DebugGradientIdentity <T> | Identity op for gradient debugging. |
| DebugGradientRefIdentity <T> | Identity op for gradient debugging. |
| DebugIdentity <T> | Provides an identity mapping of the non-Ref type input tensor for debugging. |
| DebugIdentity.Options | Optional attributes for DebugIdentity |
| DebugIdentityV2 <T> | Debug Identity V2 Op. |
| DebugIdentityV2.Options | Optional attributes for DebugIdentityV2 |
| DebugNanCount | Debug NaN Value Counter Op. |
| DebugNanCount.Options | Optional attributes for DebugNanCount |
| DebugNumericSummary | Debug Numeric Summary Op. |
| DebugNumericSummary.Options | Optional attributes for DebugNumericSummary |
| DebugNumericSummaryV2 <U extends Number> | Debug Numeric Summary V2 Op. |
| DebugNumericSummaryV2.Options | Optional attributes for DebugNumericSummaryV2 |
| DecodeImage <T extends Number> | Function for decode_bmp, decode_gif, decode_jpeg, and decode_png. |
| DecodeImage.Options | Optional attributes for DecodeImage |
| DecodePaddedRaw <T extends Number> | Reinterpret the bytes of a string as a vector of numbers. |
| DecodePaddedRaw.Options | Optional attributes for DecodePaddedRaw |
| DecodeProto | The op extracts fields from a serialized protocol buffers message into tensors. |
| DecodeProto.Options | Optional attributes for DecodeProto |
| DeepCopy <T> | Makes a copy of `x`. |
| DeleteIterator | A container for an iterator resource. |
| DeleteMemoryCache | |
| DeleteMultiDeviceIterator | A container for an iterator resource. |
| DeleteRandomSeedGenerator | |
| DeleteSeedGenerator | |
| DeleteSessionTensor | Delete the tensor specified by its handle in the session. |
| DenseBincount <U extends Number> | Counts the number of occurrences of each value in an integer array. |
| DenseBincount.Options | Optional attributes for DenseBincount |
| DenseCountSparseOutput <U extends Number> | Performs sparse-output bin counting for a tf.tensor input. |
| DenseCountSparseOutput.Options | Optional attributes for DenseCountSparseOutput |
| DenseToCSRSparseMatrix | Converts a dense tensor to a (possibly batched) CSRSparseMatrix. |
| DestroyResourceOp | Deletes the resource specified by the handle. |
| DestroyResourceOp.Options | Optional attributes for DestroyResourceOp |
| DestroyTemporaryVariable <T> | Destroys the temporary variable and returns its final value. |
| DeviceIndex | Return the index of device the op runs. |
| DirectedInterleaveDataset | A substitute for `InterleaveDataset` on a fixed list of `N` datasets. |
| DirectedInterleaveDataset.Options | Optional attributes for DirectedInterleaveDataset |
| DisableCopyOnRead | Turns off the copy-on-read mode. |
| DistributedSave | |
| DistributedSave.Options | Optional attributes for DistributedSave |
| DrawBoundingBoxesV2 <T extends Number> | Draw bounding boxes on a batch of images. |
| DTensorRestoreV2 | |
| DTensorSetGlobalTPUArray | An op that informs a host of the global ids of all the of TPUs in the system. |
| DummyIterationCounter | |
| DummyMemoryCache | |
| DummySeedGenerator | |
| DynamicEnqueueTPUEmbeddingArbitraryTensorBatch | Eases the porting of code that uses tf.nn.embedding_lookup_sparse(). |
| DynamicEnqueueTPUEmbeddingArbitraryTensorBatch.Options | Optional attributes for DynamicEnqueueTPUEmbeddingArbitraryTensorBatch |
| DynamicPartition <T> | Partitions `data` into `num_partitions` tensors using indices from `partitions`. |
| DynamicStitch <T> | Interleave the values from the `data` tensors into a single tensor. |
| EditDistance | Computes the (possibly normalized) Levenshtein Edit Distance. |
| EditDistance.Options | Optional attributes for EditDistance |
| Eig <U> | Computes the eigen decomposition of one or more square matrices. |
| Eig.Options | Optional attributes for Eig |
| Einsum <T> | Tensor contraction according to Einstein summation convention. |
| Empty <T> | Creates a tensor with the given shape. |
| Empty.Options | Optional attributes for Empty |
| EmptyTensorList | Creates and returns an empty tensor list. |
| EmptyTensorMap | Creates and returns an empty tensor map. |
| EncodeProto | The op serializes protobuf messages provided in the input tensors. |
| EncodeProto.Options | Optional attributes for EncodeProto |
| EnqueueTPUEmbeddingArbitraryTensorBatch | Eases the porting of code that uses tf.nn.embedding_lookup_sparse(). |
| EnqueueTPUEmbeddingArbitraryTensorBatch.Options | Optional attributes for EnqueueTPUEmbeddingArbitraryTensorBatch |
| EnqueueTPUEmbeddingBatch | An op that enqueues a list of input batch tensors to TPUEmbedding. |
| EnqueueTPUEmbeddingBatch.Options | Optional attributes for EnqueueTPUEmbeddingBatch |
| EnqueueTPUEmbeddingIntegerBatch | An op that enqueues a list of input batch tensors to TPUEmbedding. |
| EnqueueTPUEmbeddingIntegerBatch.Options | Optional attributes for EnqueueTPUEmbeddingIntegerBatch |
| EnqueueTPUEmbeddingRaggedTensorBatch | Eases the porting of code that uses tf.nn.embedding_lookup(). |
| EnqueueTPUEmbeddingRaggedTensorBatch.Options | Optional attributes for EnqueueTPUEmbeddingRaggedTensorBatch |
| EnqueueTPUEmbeddingSparseBatch | An op that enqueues TPUEmbedding input indices from a SparseTensor. |
| EnqueueTPUEmbeddingSparseBatch.Options | Optional attributes for EnqueueTPUEmbeddingSparseBatch |
| EnqueueTPUEmbeddingSparseTensorBatch | Eases the porting of code that uses tf.nn.embedding_lookup_sparse(). |
| EnqueueTPUEmbeddingSparseTensorBatch.Options | Optional attributes for EnqueueTPUEmbeddingSparseTensorBatch |
| EnsureShape <T> | Ensures that the tensor's shape matches the expected shape. |
| Enter <T> | Creates or finds a child frame, and makes `data` available to the child frame. |
| Enter.Options | Optional attributes for Enter |
| Erfinv <T extends Number> | |
| EuclideanNorm <T> | Computes the euclidean norm of elements across dimensions of a tensor. |
| EuclideanNorm.Options | Optional attributes for EuclideanNorm |
| ExecuteTPUEmbeddingPartitioner | An op that executes the TPUEmbedding partitioner on the central configuration device and computes the HBM size (in bytes) required for TPUEmbedding operation. |
| Exit <T> | Exits the current frame to its parent frame. |
| ExpandDims <T> | Inserts a dimension of 1 into a tensor's shape. |
| ExperimentalAutoShardDataset | Creates a dataset that shards the input dataset. |
| ExperimentalAutoShardDataset.Options | Optional attributes for ExperimentalAutoShardDataset |
| ExperimentalBytesProducedStatsDataset | Records the bytes size of each element of `input_dataset` in a StatsAggregator. |
| ExperimentalChooseFastestDataset | |
| ExperimentalDatasetCardinality | Returns the cardinality of `input_dataset`. |
| ExperimentalDatasetToTFRecord | Writes the given dataset to the given file using the TFRecord format. |
| ExperimentalDenseToSparseBatchDataset | Creates a dataset that batches input elements into a SparseTensor. |
| ExperimentalLatencyStatsDataset | Records the latency of producing `input_dataset` elements in a StatsAggregator. |
| ExperimentalMatchingFilesDataset | |
| ExperimentalMaxIntraOpParallelismDataset | Creates a dataset that overrides the maximum intra-op parallelism. |
| ExperimentalParseExampleDataset | Transforms `input_dataset` containing `Example` protos as vectors of DT_STRING into a dataset of `Tensor` or `SparseTensor` objects representing the parsed features. |
| ExperimentalParseExampleDataset.Options | Optional attributes for ExperimentalParseExampleDataset |
| ExperimentalPrivateThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| ExperimentalRandomDataset | Creates a Dataset that returns pseudorandom numbers. |
| ExperimentalRebatchDataset | Creates a dataset that changes the batch size. |
| ExperimentalRebatchDataset.Options | Optional attributes for ExperimentalRebatchDataset |
| ExperimentalSetStatsAggregatorDataset | |
| ExperimentalSlidingWindowDataset | Creates a dataset that passes a sliding window over `input_dataset`. |
| ExperimentalSqlDataset | Creates a dataset that executes a SQL query and emits rows of the result set. |
| ExperimentalStatsAggregatorHandle | Creates a statistics manager resource. |
| ExperimentalStatsAggregatorHandle.Options | Optional attributes for ExperimentalStatsAggregatorHandle |
| ExperimentalStatsAggregatorSummary | Produces a summary of any statistics recorded by the given statistics manager. |
| ExperimentalUnbatchDataset | A dataset that splits the elements of its input into multiple elements. |
| Expint <T extends Number> | |
| ExtractGlimpseV2 | Extracts a glimpse from the input tensor. |
| ExtractGlimpseV2.Options | Optional attributes for ExtractGlimpseV2 |
| ExtractVolumePatches <T extends Number> | Extract `patches` from `input` and put them in the `"depth"` output dimension. |
| FileSystemSetConfiguration | Set configuration of the file system. |
| Fill <U> | Creates a tensor filled with a scalar value. |
| FinalizeDataset | Creates a dataset by applying tf.data.Options to `input_dataset`. |
| FinalizeDataset.Options | Optional attributes for FinalizeDataset |
| FinalizeTPUEmbedding | An op that finalizes the TPUEmbedding configuration. |
| Fingerprint | Generates fingerprint values. |
| FresnelCos <T extends Number> | |
| FresnelSin <T extends Number> | |
| FusedBatchNormGradV3 <T extends Number, U extends Number> | Gradient for batch normalization. |
| FusedBatchNormGradV3.Options | Optional attributes for FusedBatchNormGradV3 |
| FusedBatchNormV3 <T extends Number, U extends Number> | Batch normalization. |
| FusedBatchNormV3.Options | Optional attributes for FusedBatchNormV3 |
| Gather <T> | Gather slices from `params` axis `axis` according to `indices`. |
| Gather.Options | Optional attributes for Gather |
| GatherNd <T> | Gather slices from `params` into a Tensor with shape specified by `indices`. |
| GenerateBoundingBoxProposals | This op produces Region of Interests from given bounding boxes(bbox_deltas) encoded wrt anchors according to eq.2 in arXiv:1506.01497 The op selects top `pre_nms_topn` scoring boxes, decodes them with respect to anchors, applies non-maximal suppression on overlapping boxes with higher than `nms_threshold` intersection-over-union (iou) value, discarding boxes where shorter side is less than `min_size`. |
| GenerateBoundingBoxProposals.Options | Optional attributes for GenerateBoundingBoxProposals |
| GetElementAtIndex | Gets the element at the specified index in a dataset. |
| GetOptions | Returns the tf.data.Options attached to `input_dataset`. |
| GetSessionHandle | Store the input tensor in the state of the current session. |
| GetSessionTensor <T> | Get the value of the tensor specified by its handle. |
| Gradients | Adds operations to compute the partial derivatives of sum of y s wrt x s, ie, d(y_1 + y_2 + ...)/dx_1, d(y_1 + y_2 + ...)/dx_2... If |
| Gradients.Options | Optional attributes for Gradients |
| GRUBlockCell <T extends Number> | Computes the GRU cell forward propagation for 1 time step. |
| GRUBlockCellGrad <T extends Number> | Computes the GRU cell back-propagation for 1 time step. |
| GuaranteeConst <T> | Gives a guarantee to the TF runtime that the input tensor is a constant. |
| HashTable | Creates a non-initialized hash table. |
| HashTable.Options | Optional attributes for HashTable |
| HistogramFixedWidth <U extends Number> | Return histogram of values. |
| Identity <T> | Return a tensor with the same shape and contents as the input tensor or value. |
| IdentityN | Returns a list of tensors with the same shapes and contents as the input tensors. |
| IgnoreErrorsDataset | Creates a dataset that contains the elements of `input_dataset` ignoring errors. |
| IgnoreErrorsDataset.Options | Optional attributes for IgnoreErrorsDataset |
| ImageProjectiveTransformV2 <T extends Number> | Applies the given transform to each of the images. |
| ImageProjectiveTransformV2.Options | Optional attributes for ImageProjectiveTransformV2 |
| ImageProjectiveTransformV3 <T extends Number> | Applies the given transform to each of the images. |
| ImageProjectiveTransformV3.Options | Optional attributes for ImageProjectiveTransformV3 |
| ImmutableConst <T> | Returns immutable tensor from memory region. |
| InfeedDequeue <T> | A placeholder op for a value that will be fed into the computation. |
| InfeedDequeueTuple | Fetches multiple values from infeed as an XLA tuple. |
| InfeedEnqueue | An op which feeds a single Tensor value into the computation. |
| InfeedEnqueue.Options | Optional attributes for InfeedEnqueue |
| InfeedEnqueuePrelinearizedBuffer | An op which enqueues prelinearized buffer into TPU infeed. |
| InfeedEnqueuePrelinearizedBuffer.Options | Optional attributes for InfeedEnqueuePrelinearizedBuffer |
| InfeedEnqueueTuple | Feeds multiple Tensor values into the computation as an XLA tuple. |
| InfeedEnqueueTuple.Options | Optional attributes for InfeedEnqueueTuple |
| InitializeTable | Table initializer that takes two tensors for keys and values respectively. |
| InitializeTableFromDataset | |
| InitializeTableFromTextFile | Initializes a table from a text file. |
| InitializeTableFromTextFile.Options | Optional attributes for InitializeTableFromTextFile |
| InplaceAdd <T> | Adds v into specified rows of x. |
| InplaceSub <T> | Subtracts `v` into specified rows of `x`. |
| InplaceUpdate <T> | Updates specified rows 'i' with values 'v'. |
| IsBoostedTreesEnsembleInitialized | Checks whether a tree ensemble has been initialized. |
| IsBoostedTreesQuantileStreamResourceInitialized | Checks whether a quantile stream has been initialized. |
| IsotonicRegression <U extends Number> | Solves a batch of isotonic regression problems. |
| IsTPUEmbeddingInitialized | Whether TPU Embedding is initialized in a distributed TPU system. |
| IsTPUEmbeddingInitialized.Options | Optional attributes for IsTPUEmbeddingInitialized |
| IsVariableInitialized | Checks whether a tensor has been initialized. |
| IteratorGetDevice | Returns the name of the device on which `resource` has been placed. |
| 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. |
| LinSpace <T extends Number> | Generates values in an interval. |
| ListDataset | Creates a dataset that emits each of `tensors` once. |
| ListDataset.Options | Optional attributes for ListDataset |
| LMDBDataset | Creates a dataset that emits the key-value pairs in one or more LMDB files. |
| LoadAllTPUEmbeddingParameters | An op that loads optimization parameters into embedding memory. |
| LoadTPUEmbeddingAdadeltaParameters | Load Adadelta embedding parameters. |
| LoadTPUEmbeddingAdadeltaParameters.Options | Optional attributes for LoadTPUEmbeddingAdadeltaParameters |
| LoadTPUEmbeddingAdagradMomentumParameters | Load Adagrad Momentum embedding parameters. |
| LoadTPUEmbeddingAdagradMomentumParameters.Options | Optional attributes for LoadTPUEmbeddingAdagradMomentumParameters |
| LoadTPUEmbeddingAdagradParameters | Load Adagrad embedding parameters. |
| LoadTPUEmbeddingAdagradParameters.Options | Optional attributes for LoadTPUEmbeddingAdagradParameters |
| LoadTPUEmbeddingADAMParameters | Load ADAM embedding parameters. |
| LoadTPUEmbeddingADAMParameters.Options | Optional attributes for LoadTPUEmbeddingADAMParameters |
| LoadTPUEmbeddingCenteredRMSPropParameters | Load centered RMSProp embedding parameters. |
| LoadTPUEmbeddingCenteredRMSPropParameters.Options | Optional attributes for LoadTPUEmbeddingCenteredRMSPropParameters |
| LoadTPUEmbeddingFrequencyEstimatorParameters | Load frequency estimator embedding parameters. |
| LoadTPUEmbeddingFrequencyEstimatorParameters.Options | Optional attributes for LoadTPUEmbeddingFrequencyEstimatorParameters |
| LoadTPUEmbeddingFTRLParameters | Load FTRL embedding parameters. |
| LoadTPUEmbeddingFTRLParameters.Options | Optional attributes for LoadTPUEmbeddingFTRLParameters |
| LoadTPUEmbeddingMDLAdagradLightParameters | Load MDL Adagrad Light embedding parameters. |
| LoadTPUEmbeddingMDLAdagradLightParameters.Options | Optional attributes for LoadTPUEmbeddingMDLAdagradLightParameters |
| LoadTPUEmbeddingMomentumParameters | Load Momentum embedding parameters. |
| LoadTPUEmbeddingMomentumParameters.Options | Optional attributes for LoadTPUEmbeddingMomentumParameters |
| LoadTPUEmbeddingProximalAdagradParameters | Load proximal Adagrad embedding parameters. |
| LoadTPUEmbeddingProximalAdagradParameters.Options | Optional attributes for LoadTPUEmbeddingProximalAdagradParameters |
| LoadTPUEmbeddingProximalYogiParameters | |
| LoadTPUEmbeddingProximalYogiParameters.Options | Optional attributes for LoadTPUEmbeddingProximalYogiParameters |
| LoadTPUEmbeddingRMSPropParameters | Load RMSProp embedding parameters. |
| LoadTPUEmbeddingRMSPropParameters.Options | Optional attributes for LoadTPUEmbeddingRMSPropParameters |
| LoadTPUEmbeddingStochasticGradientDescentParameters | Load SGD embedding parameters. |
| LoadTPUEmbeddingStochasticGradientDescentParameters.Options | Optional attributes for LoadTPUEmbeddingStochasticGradientDescentParameters |
| LookupTableExport <T, U> | Outputs all keys and values in the table. |
| LookupTableFind <U> | 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. |
| LowerBound <U extends Number> | Applies lower_bound(sorted_search_values, values) along each row. |
| LSTMBlockCell <T extends Number> | Computes the LSTM cell forward propagation for 1 time step. |
| LSTMBlockCell.Options | Optional attributes for LSTMBlockCell |
| LSTMBlockCellGrad <T extends Number> | Computes the LSTM cell backward propagation for 1 timestep. |
| Lu <T, U extends Number> | Computes the LU decomposition of one or more square matrices. |
| 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 |
| MapIncompleteSize | Op returns the number of incomplete elements in the underlying container. |
| MapIncompleteSize.Options | Optional attributes for MapIncompleteSize |
| 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 |
| MatrixDiagPartV2 <T> | Returns the batched diagonal part of a batched tensor. |
| MatrixDiagPartV3 <T> | Returns the batched diagonal part of a batched tensor. |
| MatrixDiagPartV3.Options | Optional attributes for MatrixDiagPartV3 |
| MatrixDiagV2 <T> | Returns a batched diagonal tensor with given batched diagonal values. |
| MatrixDiagV3 <T> | Returns a batched diagonal tensor with given batched diagonal values. |
| MatrixDiagV3.Options | Optional attributes for MatrixDiagV3 |
| MatrixSetDiagV2 <T> | Returns a batched matrix tensor with new batched diagonal values. |
| MatrixSetDiagV3 <T> | Returns a batched matrix tensor with new batched diagonal values. |
| MatrixSetDiagV3.Options | Optional attributes for MatrixSetDiagV3 |
| Max <T> | Computes the maximum of elements across dimensions of a tensor. |
| Max.Options | Optional attributes for Max |
| MaxIntraOpParallelismDataset | Creates a dataset that overrides the maximum intra-op parallelism. |
| Merge <T> | Forwards the value of an available tensor from `inputs` to `output`. |
| MergeDedupData | An op merges elements of integer and float tensors into deduplication data as XLA tuple. |
| MergeDedupData.Options | Optional attributes for MergeDedupData |
| Min <T> | Computes the minimum of elements across dimensions of a tensor. |
| Min.Options | Optional attributes for Min |
| MirrorPad <T> | Pads a tensor with mirrored values. |
| MirrorPadGrad <T> | Gradient op for `MirrorPad` op. |
| MlirPassthroughOp | Wraps an arbitrary MLIR computation expressed as a module with a main() function. |
| MulNoNan <T> | Returns x * y element-wise. |
| 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. |
| NcclAllReduce <T extends Number> | Outputs a tensor containing the reduction across all input tensors. |
| NcclBroadcast <T extends Number> | Sends `input` to all devices that are connected to the output. |
| NcclReduce <T extends Number> | Reduces `input` from `num_devices` using `reduction` to a single device. |
| Ndtri <T extends Number> | |
| NearestNeighbors | Selects the k nearest centers for each point. |
| NextAfter <T extends Number> | Returns the next representable value of `x1` in the direction of `x2`, element-wise. |
| NextIteration <T> | Makes its input available to the next iteration. |
| NonDeterministicInts <U> | Non-deterministically generates some integers. |
| NonMaxSuppressionV5 <T extends Number> | 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. |
| NonMaxSuppressionV5.Options | Optional attributes for NonMaxSuppressionV5 |
| NonSerializableDataset | |
| NoOp | Does nothing. |
| OneHot <U> | Returns a one-hot tensor. |
| OneHot.Options | Optional attributes for OneHot |
| OnesLike <T> | Returns a tensor of ones with the same shape and type as x. |
| OptimizeDatasetV2 | Creates a dataset by applying related optimizations to `input_dataset`. |
| OptimizeDatasetV2.Options | Optional attributes for OptimizeDatasetV2 |
| OptionsDataset | Creates a dataset by attaching tf.data.Options to `input_dataset`. |
| OptionsDataset.Options | Optional attributes for OptionsDataset |
| 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 |
| OutfeedDequeue <T> | 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> | 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. |
| Pad <T> | Pads a tensor. |
| ParallelBatchDataset | |
| ParallelBatchDataset.Options | Optional attributes for ParallelBatchDataset |
| ParallelConcat <T> | Concatenates a list of `N` tensors along the first dimension. |
| ParallelDynamicStitch <T> | Interleave the values from the `data` tensors into a single tensor. |
| ParseExampleDatasetV2 | Transforms `input_dataset` containing `Example` protos as vectors of DT_STRING into a dataset of `Tensor` or `SparseTensor` objects representing the parsed features. |
| ParseExampleDatasetV2.Options | Optional attributes for ParseExampleDatasetV2 |
| ParseExampleV2 | Transforms a vector of tf.Example protos (as strings) into typed tensors. |
| ParseSequenceExampleV2 | Transforms a vector of tf.io.SequenceExample protos (as strings) into typed tensors. |
| ParseSequenceExampleV2.Options | Optional attributes for ParseSequenceExampleV2 |
| Placeholder <T> | A placeholder op for a value that will be fed into the computation. |
| Placeholder.Options | Optional attributes for Placeholder |
| PlaceholderWithDefault <T> | A placeholder op that passes through `input` when its output is not fed. |
| 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 |
| Prints a string scalar. | |
| Print.Options | Optional attributes for Print |
| PrivateThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| Prod <T> | Computes the product of elements across dimensions of a tensor. |
| Prod.Options | Optional attributes for Prod |
| QuantizeAndDequantizeV4 <T extends Number> | Quantizes then dequantizes a tensor. |
| QuantizeAndDequantizeV4.Options | Optional attributes for QuantizeAndDequantizeV4 |
| QuantizeAndDequantizeV4Grad <T extends Number> | Returns the gradient of `QuantizeAndDequantizeV4`. |
| QuantizeAndDequantizeV4Grad.Options | Optional attributes for QuantizeAndDequantizeV4Grad |
| QuantizedConcat <T> | Concatenates quantized tensors along one dimension. |
| QuantizedConcatV2 <T> | |
| QuantizedConv2DAndRelu <V> | |
| QuantizedConv2DAndRelu.Options | Optional attributes for QuantizedConv2DAndRelu |
| QuantizedConv2DAndReluAndRequantize <V> | |
| QuantizedConv2DAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DAndReluAndRequantize |
| QuantizedConv2DAndRequantize <V> | |
| QuantizedConv2DAndRequantize.Options | Optional attributes for QuantizedConv2DAndRequantize |
| QuantizedConv2DPerChannel <V> | Computes QuantizedConv2D per channel. |
| QuantizedConv2DPerChannel.Options | Optional attributes for QuantizedConv2DPerChannel |
| QuantizedConv2DWithBias <V> | |
| QuantizedConv2DWithBias.Options | Optional attributes for QuantizedConv2DWithBias |
| QuantizedConv2DWithBiasAndRelu <V> | |
| QuantizedConv2DWithBiasAndRelu.Options | Optional attributes for QuantizedConv2DWithBiasAndRelu |
| QuantizedConv2DWithBiasAndReluAndRequantize <W> | |
| QuantizedConv2DWithBiasAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasAndReluAndRequantize |
| QuantizedConv2DWithBiasAndRequantize <W> | |
| QuantizedConv2DWithBiasAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasAndRequantize |
| QuantizedConv2DWithBiasSignedSumAndReluAndRequantize <X> | |
| QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasSignedSumAndReluAndRequantize |
| QuantizedConv2DWithBiasSumAndRelu <V> | |
| QuantizedConv2DWithBiasSumAndRelu.Options | Optional attributes for QuantizedConv2DWithBiasSumAndRelu |
| QuantizedConv2DWithBiasSumAndReluAndRequantize <X> | |
| QuantizedConv2DWithBiasSumAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasSumAndReluAndRequantize |
| QuantizedDepthwiseConv2D <V> | Computes quantized depthwise Conv2D. |
| QuantizedDepthwiseConv2D.Options | Optional attributes for QuantizedDepthwiseConv2D |
| QuantizedDepthwiseConv2DWithBias <V> | Computes quantized depthwise Conv2D with Bias. |
| QuantizedDepthwiseConv2DWithBias.Options | Optional attributes for QuantizedDepthwiseConv2DWithBias |
| QuantizedDepthwiseConv2DWithBiasAndRelu <V> | Computes quantized depthwise Conv2D with Bias and Relu. |
| QuantizedDepthwiseConv2DWithBiasAndRelu.Options | Optional attributes for QuantizedDepthwiseConv2DWithBiasAndRelu |
| QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize <W> | Computes quantized depthwise Conv2D with Bias, Relu and Requantize. |
| QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.Options | Optional attributes for QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize |
| QuantizedMatMulWithBias <W> | Performs a quantized matrix multiplication of `a` by the matrix `b` with bias add. |
| QuantizedMatMulWithBias.Options | Optional attributes for QuantizedMatMulWithBias |
| QuantizedMatMulWithBiasAndDequantize <W extends Number> | |
| QuantizedMatMulWithBiasAndDequantize.Options | Optional attributes for QuantizedMatMulWithBiasAndDequantize |
| QuantizedMatMulWithBiasAndRelu <V> | 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> | 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> | |
| QuantizedMatMulWithBiasAndRequantize.Options | Optional attributes for QuantizedMatMulWithBiasAndRequantize |
| QuantizedReshape <T> | Reshapes a quantized tensor as per the Reshape op. |
| RaggedBincount <U extends Number> | Counts the number of occurrences of each value in an integer array. |
| RaggedBincount.Options | Optional attributes for RaggedBincount |
| RaggedCountSparseOutput <U extends Number> | Performs sparse-output bin counting for a ragged tensor input. |
| RaggedCountSparseOutput.Options | Optional attributes for RaggedCountSparseOutput |
| RaggedCross <T, U extends Number> | Generates a feature cross from a list of tensors, and returns it as a RaggedTensor. |
| RaggedFillEmptyRows <T> | |
| RaggedFillEmptyRowsGrad <T> | |
| RaggedGather <T extends Number, U> | Gather ragged slices from `params` axis `0` according to `indices`. |
| RaggedRange <U extends Number, T extends Number> | Returns a `RaggedTensor` containing the specified sequences of numbers. |
| RaggedTensorFromVariant <U extends Number, T> | Decodes a `variant` Tensor into a `RaggedTensor`. |
| RaggedTensorToSparse <U> | Converts a `RaggedTensor` into a `SparseTensor` with the same values. |
| RaggedTensorToTensor <U> | Create a dense tensor from a ragged tensor, possibly altering its shape. |
| RaggedTensorToVariant | Encodes a `RaggedTensor` into a `variant` Tensor. |
| RaggedTensorToVariantGradient <U> | Helper used to compute the gradient for `RaggedTensorToVariant`. |
| RandomDatasetV2 | Creates a Dataset that returns pseudorandom numbers. |
| RandomDatasetV2.Options | Optional attributes for RandomDatasetV2 |
| RandomIndexShuffle <T extends Number> | Outputs the position of `value` in a permutation of [0, ..., max_index]. |
| RandomIndexShuffle.Options | Optional attributes for RandomIndexShuffle |
| Range <T extends Number> | Creates a sequence of numbers. |
| Rank | Returns the rank of a tensor. |
| ReadVariableOp <T> | Reads the value of a variable. |
| ReadVariableXlaSplitND <T> | Splits resource variable input tensor across all dimensions. |
| ReadVariableXlaSplitND.Options | Optional attributes for ReadVariableXlaSplitND |
| RebatchDataset | Creates a dataset that changes the batch size. |
| RebatchDataset.Options | Optional attributes for RebatchDataset |
| RebatchDatasetV2 | Creates a dataset that changes the batch size. |
| Recv <T> | Receives the named tensor from send_device on recv_device. |
| Recv.Options | Optional attributes for Recv |
| RecvTPUEmbeddingActivations | An op that receives embedding activations on the TPU. |
| 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 |
| ReduceMax <T> | Computes the maximum of elements across dimensions of a tensor. |
| ReduceMax.Options | Optional attributes for ReduceMax |
| ReduceMin <T> | Computes the minimum of elements across dimensions of a tensor. |
| ReduceMin.Options | Optional attributes for ReduceMin |
| ReduceProd <T> | Computes the product of elements across dimensions of a tensor. |
| ReduceProd.Options | Optional attributes for ReduceProd |
| ReduceSum <T> | Computes the sum of elements across dimensions of a tensor. |
| ReduceSum.Options | Optional attributes for ReduceSum |
| RefEnter <T> | Creates or finds a child frame, and makes `data` available to the child frame. |
| RefEnter.Options | Optional attributes for RefEnter |
| RefExit <T> | Exits the current frame to its parent frame. |
| RefIdentity <T> | Return the same ref tensor as the input ref tensor. |
| RefMerge <T> | Forwards the value of an available tensor from `inputs` to `output`. |
| RefNextIteration <T> | Makes its input available to the next iteration. |
| RefSelect <T> | Forwards the `index`th element of `inputs` to `output`. |
| RefSwitch <T> | Forwards the ref tensor `data` to the output port determined by `pred`. |
| RegisterDataset | Registers a dataset with the tf.data service. |
| RegisterDataset.Options | Optional attributes for RegisterDataset |
| RegisterDatasetV2 | Registers a dataset with the tf.data service. |
| RegisterDatasetV2.Options | Optional attributes for RegisterDatasetV2 |
| Relayout <T> | |
| RelayoutGrad <T> | |
| RequantizationRangePerChannel | Computes requantization range per channel. |
| RequantizePerChannel <U> | Requantizes input with min and max values known per channel. |
| Reshape <T> | Reshapes a tensor. |
| 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> | Extracts the average gradient in the given ConditionalAccumulator. |
| ResourceApplyAdagradV2 | Update '*var' according to the adagrad scheme. |
| ResourceApplyAdagradV2.Options | Optional attributes for ResourceApplyAdagradV2 |
| ResourceApplyAdamWithAmsgrad | Update '*var' according to the Adam algorithm. |
| ResourceApplyAdamWithAmsgrad.Options | Optional attributes for ResourceApplyAdamWithAmsgrad |
| ResourceApplyKerasMomentum | Update '*var' according to the momentum scheme. |
| ResourceApplyKerasMomentum.Options | Optional attributes for ResourceApplyKerasMomentum |
| ResourceConditionalAccumulator | A conditional accumulator for aggregating gradients. |
| ResourceConditionalAccumulator.Options | Optional attributes for ResourceConditionalAccumulator |
| ResourceCountUpTo <T extends Number> | Increments variable pointed to by 'resource' until it reaches 'limit'. |
| ResourceGather <U> | Gather slices from the variable pointed to by `resource` according to `indices`. |
| ResourceGather.Options | Optional attributes for ResourceGather |
| ResourceGatherNd <U> | |
| 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`. |
| ResourceSparseApplyAdagradV2 | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
| ResourceSparseApplyAdagradV2.Options | Optional attributes for ResourceSparseApplyAdagradV2 |
| ResourceSparseApplyKerasMomentum | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
| ResourceSparseApplyKerasMomentum.Options | Optional attributes for ResourceSparseApplyKerasMomentum |
| ResourceStridedSliceAssign | Assign `value` to the sliced l-value reference of `ref`. |
| ResourceStridedSliceAssign.Options | Optional attributes for ResourceStridedSliceAssign |
| RetrieveAllTPUEmbeddingParameters | An op that retrieves optimization parameters from embedding to host memory. |
| RetrieveTPUEmbeddingAdadeltaParameters | Retrieve Adadelta embedding parameters. |
| RetrieveTPUEmbeddingAdadeltaParameters.Options | Optional attributes for RetrieveTPUEmbeddingAdadeltaParameters |
| RetrieveTPUEmbeddingAdagradMomentumParameters | Retrieve Adagrad Momentum embedding parameters. |
| RetrieveTPUEmbeddingAdagradMomentumParameters.Options | Optional attributes for RetrieveTPUEmbeddingAdagradMomentumParameters |
| RetrieveTPUEmbeddingAdagradParameters | Retrieve Adagrad embedding parameters. |
| RetrieveTPUEmbeddingAdagradParameters.Options | Optional attributes for RetrieveTPUEmbeddingAdagradParameters |
| RetrieveTPUEmbeddingADAMParameters | Retrieve ADAM embedding parameters. |
| RetrieveTPUEmbeddingADAMParameters.Options | Optional attributes for RetrieveTPUEmbeddingADAMParameters |
| RetrieveTPUEmbeddingCenteredRMSPropParameters | Retrieve centered RMSProp embedding parameters. |
| RetrieveTPUEmbeddingCenteredRMSPropParameters.Options | Optional attributes for RetrieveTPUEmbeddingCenteredRMSPropParameters |
| RetrieveTPUEmbeddingFrequencyEstimatorParameters | Retrieve frequency estimator embedding parameters. |
| RetrieveTPUEmbeddingFrequencyEstimatorParameters.Options | Optional attributes for RetrieveTPUEmbeddingFrequencyEstimatorParameters |
| RetrieveTPUEmbeddingFTRLParameters | Retrieve FTRL embedding parameters. |
| RetrieveTPUEmbeddingFTRLParameters.Options | Optional attributes for RetrieveTPUEmbeddingFTRLParameters |
| RetrieveTPUEmbeddingMDLAdagradLightParameters | Retrieve MDL Adagrad Light embedding parameters. |
| RetrieveTPUEmbeddingMDLAdagradLightParameters.Options | Optional attributes for RetrieveTPUEmbeddingMDLAdagradLightParameters |
| RetrieveTPUEmbeddingMomentumParameters | Retrieve Momentum embedding parameters. |
| RetrieveTPUEmbeddingMomentumParameters.Options | Optional attributes for RetrieveTPUEmbeddingMomentumParameters |
| RetrieveTPUEmbeddingProximalAdagradParameters | Retrieve proximal Adagrad embedding parameters. |
| RetrieveTPUEmbeddingProximalAdagradParameters.Options | Optional attributes for RetrieveTPUEmbeddingProximalAdagradParameters |
| RetrieveTPUEmbeddingProximalYogiParameters | |
| RetrieveTPUEmbeddingProximalYogiParameters.Options | Optional attributes for RetrieveTPUEmbeddingProximalYogiParameters |
| RetrieveTPUEmbeddingRMSPropParameters | Retrieve RMSProp embedding parameters. |
| RetrieveTPUEmbeddingRMSPropParameters.Options | Optional attributes for RetrieveTPUEmbeddingRMSPropParameters |
| RetrieveTPUEmbeddingStochasticGradientDescentParameters | Retrieve SGD embedding parameters. |
| RetrieveTPUEmbeddingStochasticGradientDescentParameters.Options | Optional attributes for RetrieveTPUEmbeddingStochasticGradientDescentParameters |
| Reverse <T> | Reverses specific dimensions of a tensor. |
| ReverseSequence <T> | Reverses variable length slices. |
| ReverseSequence.Options | Optional attributes for ReverseSequence |
| RewriteDataset | |
| RiscAbs <T extends Number> | |
| RiscAdd <T extends Number> | Returns x + y element-wise. |
| RiscBinaryArithmetic <T extends Number> | |
| RiscBinaryComparison | |
| RiscBitcast <U> | |
| RiscBroadcast <T> | |
| RiscCast <U> | |
| RiscCeil <T extends Number> | |
| RiscCholesky <T extends Number> | |
| RiscConcat <T> | |
| RiscConv <T extends Number> | |
| RiscConv.Options | Optional attributes for RiscConv |
| RiscCos <T extends Number> | |
| RiscDiv <T extends Number> | |
| RiscDot <T extends Number> | |
| RiscDot.Options | Optional attributes for RiscDot |
| RiscExp <T extends Number> | |
| RiscFft <T> | |
| RiscFloor <T extends Number> | |
| RiscGather <T> | |
| RiscGather.Options | Optional attributes for RiscGather |
| RiscImag <U extends Number> | |
| RiscIsFinite | |
| RiscLog <T extends Number> | |
| RiscLogicalAnd | |
| RiscLogicalNot | |
| RiscLogicalOr | |
| RiscMax <T extends Number> | Returns max(x, y) element-wise. |
| RiscMin <T extends Number> | |
| RiscMul <T extends Number> | |
| RiscNeg <T extends Number> | |
| RiscPad <T extends Number> | |
| RiscPool <T extends Number> | |
| RiscPool.Options | Optional attributes for RiscPool |
| RiscPow <T extends Number> | |
| RiscRandomUniform | |
| RiscRandomUniform.Options | Optional attributes for RiscRandomUniform |
| RiscReal <U extends Number> | |
| RiscReduce <T extends Number> | |
| RiscRem <T extends Number> | |
| RiscReshape <T extends Number> | |
| RiscReverse <T extends Number> | |
| RiscScatter <U extends Number> | |
| RiscShape <U extends Number> | |
| RiscSign <T extends Number> | |
| RiscSlice <T extends Number> | |
| RiscSort <T extends Number> | |
| RiscSqueeze <T> | |
| RiscSqueeze.Options | Optional attributes for RiscSqueeze |
| RiscSub <T extends Number> | |
| RiscTranspose <T> | |
| RiscTriangularSolve <T extends Number> | |
| RiscTriangularSolve.Options | Optional attributes for RiscTriangularSolve |
| RiscUnary <T extends Number> | |
| RngReadAndSkip | Advance the counter of a counter-based RNG. |
| RngSkip | Advance the counter of a counter-based RNG. |
| Roll <T> | Rolls the elements of a tensor along an axis. |
| SamplingDataset | Creates a dataset that takes a Bernoulli sample of the contents of another dataset. |
| ScaleAndTranslate | |
| ScaleAndTranslate.Options | Optional attributes for ScaleAndTranslate |
| ScaleAndTranslateGrad <T extends Number> | |
| ScaleAndTranslateGrad.Options | Optional attributes for ScaleAndTranslateGrad |
| ScatterAdd <T> | Adds sparse updates to a variable reference. |
| ScatterAdd.Options | Optional attributes for ScatterAdd |
| ScatterDiv <T> | Divides a variable reference by sparse updates. |
| ScatterDiv.Options | Optional attributes for ScatterDiv |
| ScatterMax <T extends Number> | Reduces sparse updates into a variable reference using the `max` operation. |
| ScatterMax.Options | Optional attributes for ScatterMax |
| ScatterMin <T extends Number> | Reduces sparse updates into a variable reference using the `min` operation. |
| ScatterMin.Options | Optional attributes for ScatterMin |
| ScatterMul <T> | Multiplies sparse updates into a variable reference. |
| ScatterMul.Options | Optional attributes for ScatterMul |
| ScatterNd <U> | Scatters `updates` into a tensor of shape `shape` according to `indices`. |
| ScatterNdAdd <T> | Applies sparse addition to individual values or slices in a Variable. |
| ScatterNdAdd.Options | Optional attributes for ScatterNdAdd |
| ScatterNdMax <T> | Computes element-wise maximum. |
| ScatterNdMax.Options | Optional attributes for ScatterNdMax |
| ScatterNdMin <T> | Computes element-wise minimum. |
| ScatterNdMin.Options | Optional attributes for ScatterNdMin |
| ScatterNdNonAliasingAdd <T> | Applies sparse addition to `input` using individual values or slices from `updates` according to indices `indices`. |
| ScatterNdSub <T> | Applies sparse subtraction to individual values or slices in a Variable. |
| ScatterNdSub.Options | Optional attributes for ScatterNdSub |
| ScatterNdUpdate <T> | Applies sparse `updates` to individual values or slices within a given variable according to `indices`. |
| ScatterNdUpdate.Options | Optional attributes for ScatterNdUpdate |
| ScatterSub <T> | Subtracts sparse updates to a variable reference. |
| ScatterSub.Options | Optional attributes for ScatterSub |
| ScatterUpdate <T> | Applies sparse updates to a variable reference. |
| ScatterUpdate.Options | Optional attributes for ScatterUpdate |
| SegmentMaxV2 <T extends Number> | Computes the maximum along segments of a tensor. |
| SegmentMinV2 <T extends Number> | Computes the minimum along segments of a tensor. |
| SegmentProdV2 <T> | Computes the product along segments of a tensor. |
| SegmentSumV2 <T> | Computes the sum along segments of a tensor. |
| SelectV2 <T> | |
| Send | Sends the named tensor from send_device to recv_device. |
| Send.Options | Optional attributes for Send |
| SendTPUEmbeddingGradients | Performs gradient updates of embedding tables. |
| SetDiff1d <T, U extends Number> | 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 |
| Shape <U extends Number> | Returns the shape of a tensor. |
| ShapeN <U extends Number> | Returns shape of tensors. |
| ShardDataset | Creates a `Dataset` that includes only 1/`num_shards` of this dataset. |
| ShardDataset.Options | Optional attributes for ShardDataset |
| ShuffleAndRepeatDatasetV2 | |
| ShuffleAndRepeatDatasetV2.Options | Optional attributes for ShuffleAndRepeatDatasetV2 |
| ShuffleDatasetV2 | |
| ShuffleDatasetV2.Options | Optional attributes for ShuffleDatasetV2 |
| ShuffleDatasetV3 | |
| ShuffleDatasetV3.Options | Optional attributes for ShuffleDatasetV3 |
| ShutdownDistributedTPU | Shuts down a running distributed TPU system. |
| ShutdownTPUSystem | An op that shuts down the TPU system. |
| Size <U extends Number> | Returns the size of a tensor. |
| Skipgram | Parses a text file and creates a batch of examples. |
| Skipgram.Options | Optional attributes for Skipgram |
| SleepDataset | |
| Slice <T> | Return a slice from 'input'. |
| SlidingWindowDataset | Creates a dataset that passes a sliding window over `input_dataset`. |
| SlidingWindowDataset.Options | Optional attributes for SlidingWindowDataset |
| Snapshot <T> | Returns a copy of the input tensor. |
| SnapshotDataset | Creates a dataset that will write to / read from a snapshot. |
| SnapshotDataset.Options | Optional attributes for SnapshotDataset |
| SnapshotDatasetReader | |
| SnapshotDatasetReader.Options | Optional attributes for SnapshotDatasetReader |
| SnapshotNestedDatasetReader | |
| SobolSample <T extends Number> | Generates points from the Sobol sequence. |
| SpaceToBatchNd <T> | SpaceToBatch for ND tensors of type T. |
| SparseApplyAdagradV2 <T> | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
| SparseApplyAdagradV2.Options | Optional attributes for SparseApplyAdagradV2 |
| SparseBincount <U extends Number> | Counts the number of occurrences of each value in an integer array. |
| SparseBincount.Options | Optional attributes for SparseBincount |
| SparseCountSparseOutput <U extends Number> | Performs sparse-output bin counting for a sparse tensor input. |
| SparseCountSparseOutput.Options | Optional attributes for SparseCountSparseOutput |
| SparseCrossHashed | Generates sparse cross from a list of sparse and dense tensors. |
| SparseCrossV2 | Generates sparse cross from a list of sparse and dense tensors. |
| SparseMatrixAdd | Sparse addition of two CSR matrices, C = alpha * A + beta * B. |
| SparseMatrixMatMul <T> | 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`. |
| SparseSegmentSumGrad <T extends Number> | Computes gradients for SparseSegmentSum. |
| SparseTensorToCSRSparseMatrix | Converts a SparseTensor to a (possibly batched) CSRSparseMatrix. |
| Spence <T extends Number> | |
| Split <T> | Splits a tensor into `num_split` tensors along one dimension. |
| SplitDedupData <T extends Number, U extends Number> | An op splits input deduplication data XLA tuple into integer and floating point tensors. |
| SplitDedupData.Options | Optional attributes for SplitDedupData |
| SplitV <T> | Splits a tensor into `num_split` tensors along one dimension. |
| Squeeze <T> | Removes dimensions of size 1 from the shape of a tensor. |
| Squeeze.Options | Optional attributes for Squeeze |
| Stack <T> | Packs a list of `N` rank-`R` tensors into one rank-`(R+1)` tensor. |
| Stack.Options | Optional attributes for Stack |
| Stage | 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 Number> | |
| StatefulStandardNormal <U> | Outputs random values from a normal distribution. |
| StatefulStandardNormalV2 <U> | Outputs random values from a normal distribution. |
| StatefulTruncatedNormal <U> | Outputs random values from a truncated normal distribution. |
| StatefulUniform <U> | Outputs random values from a uniform distribution. |
| StatefulUniformFullInt <U> | Outputs random integers from a uniform distribution. |
| StatefulUniformInt <U> | Outputs random integers from a uniform distribution. |
| StatelessParameterizedTruncatedNormal <V extends Number> | |
| StatelessRandomBinomial <W extends Number> | Outputs deterministic pseudorandom random numbers from a binomial distribution. |
| StatelessRandomGammaV2 <V extends Number> | Outputs deterministic pseudorandom random numbers from a gamma distribution. |
| StatelessRandomGammaV3 <U extends Number> | Outputs deterministic pseudorandom random numbers from a gamma distribution. |
| StatelessRandomGetAlg | Picks the best counter-based RNG algorithm based on device. |
| StatelessRandomGetKeyCounter | Scrambles seed into key and counter, using the best algorithm based on device. |
| StatelessRandomGetKeyCounterAlg | Picks the best algorithm based on device, and scrambles seed into key and counter. |
| StatelessRandomNormalV2 <U extends Number> | Outputs deterministic pseudorandom values from a normal distribution. |
| StatelessRandomPoisson <W extends Number> | Outputs deterministic pseudorandom random numbers from a Poisson distribution. |
| StatelessRandomUniformFullInt <V extends Number> | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformFullIntV2 <U extends Number> | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformIntV2 <U extends Number> | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformV2 <U extends Number> | Outputs deterministic pseudorandom random values from a uniform distribution. |
| StatelessSampleDistortedBoundingBox <T extends Number> | Generate a randomly distorted bounding box for an image deterministically. |
| StatelessSampleDistortedBoundingBox.Options | Optional attributes for StatelessSampleDistortedBoundingBox |
| StatelessShuffle <T> | Randomly and deterministically shuffles a tensor along its first dimension. |
| StatelessTruncatedNormalV2 <U extends Number> | Outputs deterministic pseudorandom values from a truncated normal distribution. |
| StatsAggregatorHandleV2 | |
| StatsAggregatorHandleV2.Options | Optional attributes for StatsAggregatorHandleV2 |
| StatsAggregatorSetSummaryWriter | Set a summary_writer_interface to record statistics using given stats_aggregator. |
| StopGradient <T> | Stops gradient computation. |
| StridedSlice <T> | Return a strided slice from `input`. |
| StridedSlice.Options | Optional attributes for StridedSlice |
| StridedSliceAssign <T> | Assign `value` to the sliced l-value reference of `ref`. |
| StridedSliceAssign.Options | Optional attributes for StridedSliceAssign |
| StridedSliceGrad <U> | Returns the gradient of `StridedSlice`. |
| StridedSliceGrad.Options | Optional attributes for StridedSliceGrad |
| StringLower | Converts all uppercase characters into their respective lowercase replacements. |
| StringLower.Options | Optional attributes for StringLower |
| StringNGrams <T extends Number> | Creates ngrams from ragged string data. |
| StringUpper | Converts all lowercase characters into their respective uppercase replacements. |
| StringUpper.Options | Optional attributes for StringUpper |
| Sum <T> | Computes the sum of elements across dimensions of a tensor. |
| Sum.Options | Optional attributes for Sum |
| SwitchCond <T> | Forwards `data` to the output port determined by `pred`. |
| SyncDevice | Synchronizes the device this op is run on. |
| TemporaryVariable <T> | Returns a tensor that may be mutated, but only persists within a single step. |
| TemporaryVariable.Options | Optional attributes for TemporaryVariable |
| TensorArray | An array of Tensors of given size. |
| TensorArray.Options | Optional attributes for TensorArray |
| TensorArrayClose | Delete the TensorArray from its resource container. |
| TensorArrayConcat <T> | Concat the elements from the TensorArray into value `value`. |
| TensorArrayConcat.Options | Optional attributes for TensorArrayConcat |
| TensorArrayGather <T> | 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> | |
| TensorArrayPack.Options | Optional attributes for TensorArrayPack |
| TensorArrayRead <T> | 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. |
| TensorListConcat <T> | Concats all tensors in the list along the 0th dimension. |
| TensorListConcat.Options | Optional attributes for TensorListConcat |
| TensorListConcatLists | |
| TensorListConcatV2 <U> | Concats all tensors in the list along the 0th dimension. |
| TensorListElementShape <T extends Number> | 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> | Creates a Tensor by indexing into the TensorList. |
| TensorListGetItem <T> | |
| TensorListLength | Returns the number of tensors in the input tensor list. |
| TensorListPopBack <T> | 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. |
| TensorListScatterV2 | Creates a TensorList by indexing into a Tensor. |
| TensorListSetItem | |
| TensorListSetItem.Options | Optional attributes for TensorListSetItem |
| TensorListSplit | Splits a tensor into a list. |
| TensorListStack <T> | 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> | Returns the value from a given key in a tensor map. |
| TensorMapSize | Returns the number of tensors in the input tensor map. |
| TensorMapStackKeys <T> | Returns a Tensor stack of all keys in a tensor map. |
| TensorScatterAdd <T> | Adds sparse `updates` to an existing tensor according to `indices`. |
| TensorScatterMax <T> | Apply a sparse update to a tensor taking the element-wise maximum. |
| TensorScatterMin <T> | |
| TensorScatterSub <T> | Subtracts sparse `updates` from an existing tensor according to `indices`. |
| TensorScatterUpdate <T> | Scatter `updates` into an existing tensor according to `indices`. |
| TensorStridedSliceUpdate <T> | Assign `value` to the sliced l-value reference of `input`. |
| TensorStridedSliceUpdate.Options | Optional attributes for TensorStridedSliceUpdate |
| 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.Options | Optional attributes for ThreadPoolHandle |
| Tile <T> | Constructs a tensor by tiling a given tensor. |
| Timestamp | Provides the time since epoch in seconds. |
| ToBool | Converts a tensor to a scalar predicate. |
| 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. |
| TPUCompileSucceededAssert | Asserts that compilation succeeded. |
| TPUEmbeddingActivations | An op enabling differentiation of TPU Embeddings. |
| TPUExecute | Op that loads and executes a TPU program on a TPU device. |
| TPUExecuteAndUpdateVariables | Op that executes a program with optional in-place variable updates. |
| TpuHandleToProtoKey | Converts XRT's uid handles to TensorFlow-friendly input format. |
| TPUOrdinalSelector | A TPU core selector Op. |
| TPUPartitionedInput <T> | An op that groups a list of partitioned inputs together. |
| TPUPartitionedInput.Options | Optional attributes for TPUPartitionedInput |
| TPUPartitionedInputV2 <T> | An op that groups a list of partitioned inputs together. |
| TPUPartitionedInputV2.Options | Optional attributes for TPUPartitionedInputV2 |
| TPUPartitionedOutput <T> | An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned outputs outside the XLA computation. |
| TPUPartitionedOutput.Options | Optional attributes for TPUPartitionedOutput |
| TPUPartitionedOutputV2 <T> | An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned outputs outside the XLA computation. |
| TPUReplicatedInput <T> | Connects N inputs to an N-way replicated TPU computation. |
| TPUReplicatedInput.Options | Optional attributes for TPUReplicatedInput |
| TPUReplicatedOutput <T> | 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 |
| TPUReshardVariables | Op that reshards on-device TPU variables to specified state. |
| TPURoundRobin | Round-robin load balancing on TPU cores. |
| TridiagonalMatMul <T> | Calculate product with tridiagonal matrix. |
| TridiagonalSolve <T> | Solves tridiagonal systems of equations. |
| TridiagonalSolve.Options | Optional attributes for TridiagonalSolve |
| Unbatch <T> | Reverses the operation of Batch for a single output Tensor. |
| Unbatch.Options | Optional attributes for Unbatch |
| UnbatchGrad <T> | Gradient of Unbatch. |
| UnbatchGrad.Options | Optional attributes for UnbatchGrad |
| UncompressElement | Uncompresses a compressed dataset element. |
| UnicodeDecode <T extends Number> | Decodes each string in `input` into a sequence of Unicode code points. |
| UnicodeDecode.Options | Optional attributes for UnicodeDecode |
| UnicodeEncode | Encode a tensor of ints into unicode strings. |
| UnicodeEncode.Options | Optional attributes for UnicodeEncode |
| UniformDequantize <U extends Number> | Perform dequantization on the quantized Tensor `input`. |
| UniformDequantize.Options | Optional attributes for UniformDequantize |
| UniformQuantize <U> | Perform quantization on Tensor `input`. |
| UniformQuantize.Options | Optional attributes for UniformQuantize |
| UniformQuantizedAdd <T> | Perform quantized add of quantized Tensor `lhs` and quantized Tensor `rhs` to make quantized `output`. |
| UniformQuantizedAdd.Options | Optional attributes for UniformQuantizedAdd |
| UniformQuantizedClipByValue <T> | Perform clip by value on the quantized Tensor `operand`. |
| UniformQuantizedClipByValue.Options | Optional attributes for UniformQuantizedClipByValue |
| UniformQuantizedConvolution <U> | Perform quantized convolution of quantized Tensor `lhs` and quantized Tensor `rhs`. |
| UniformQuantizedConvolution.Options | Optional attributes for UniformQuantizedConvolution |
| UniformQuantizedConvolutionHybrid <V extends Number> | Perform hybrid quantized convolution of float Tensor `lhs` and quantized Tensor `rhs`. |
| UniformQuantizedConvolutionHybrid.Options | Optional attributes for UniformQuantizedConvolutionHybrid |
| UniformQuantizedDot <U> | Perform quantized dot of quantized Tensor `lhs` and quantized Tensor `rhs` to make quantized `output`. |
| UniformQuantizedDot.Options | Optional attributes for UniformQuantizedDot |
| UniformQuantizedDotHybrid <V extends Number> | Perform hybrid quantized dot of float Tensor `lhs` and quantized Tensor `rhs`. |
| UniformQuantizedDotHybrid.Options | Optional attributes for UniformQuantizedDotHybrid |
| UniformRequantize <U> | Given quantized tensor `input`, requantize it with new quantization parameters. |
| UniformRequantize.Options | Optional attributes for UniformRequantize |
| Unique <T, V extends Number> | Finds unique elements along an axis of a tensor. |
| UniqueDataset | Creates a dataset that contains the unique elements of `input_dataset`. |
| UniqueDataset.Options | Optional attributes for UniqueDataset |
| UniqueWithCounts <T, V extends Number> | Finds unique elements along an axis of a tensor. |
| UnravelIndex <T extends Number> | Converts an array of flat indices into a tuple of coordinate arrays. |
| UnsortedSegmentJoin | |
| UnsortedSegmentJoin.Options | Optional attributes for UnsortedSegmentJoin |
| Unstack <T> | 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 | |
| UpperBound <U extends Number> | Applies upper_bound(sorted_search_values, values) along each row. |
| VarHandleOp | Creates a handle to a Variable resource. |
| VarHandleOp.Options | Optional attributes for VarHandleOp |
| Variable <T> | Holds state in the form of a tensor that persists across steps. |
| Variable.Options | Optional attributes for Variable |
| VariableShape <T extends Number> | Returns the shape of the variable pointed to by `resource`. |
| VarIsInitializedOp | Checks whether a resource handle-based variable has been initialized. |
| Where | Returns locations of nonzero / true values in a tensor. |
| Where3 <T> | Selects elements from `x` or `y`, depending on `condition`. |
| WindowOp | |
| WorkerHeartbeat | Worker heartbeat op. |
| WrapDatasetVariant | |
| WriteRawProtoSummary | Writes a serialized proto summary. |
| XlaConcatND <T> | Concats input tensor across all dimensions. |
| XlaConcatND.Options | Optional attributes for XlaConcatND |
| XlaRecvFromHost <T> | An op to receive a tensor from the host. |
| XlaRecvTPUEmbeddingActivations | An op that receives embedding activations on the TPU. |
| XlaRecvTPUEmbeddingDeduplicationData | Receives deduplication data (indices and weights) from the embedding core. |
| XlaSendToHost | An op to send a tensor to the host. |
| XlaSendTPUEmbeddingGradients | An op that performs gradient updates of embedding tables. |
| XlaSplitND <T> | Splits input tensor across all dimensions. |
| XlaSplitND.Options | Optional attributes for XlaSplitND |
| Xlog1py <T> | Returns 0 if x == 0, and x * log1p(y) otherwise, elementwise. |
| Zeros <T> | An operator creating a constant initialized with zeros of the shape given by `dims`. |
| ZerosLike <T> | Returns a tensor of zeros with the same shape and type as x. |