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Op

Op de interfaz pública

Subclases indirectas conocidas

Abort , All , AllToAll <T> , AnonymousHashTable , AnonymousIteratorV2 , AnonymousIteratorV3 , AnonymousMemoryCache , AnonymousMultiDeviceIterator , AnonymousMultiDeviceIteratorV3 , AnonymousMutableDenseHashTable , AnonymousMutableHashTable , AnonymousMutableHashTableOfTensors , AnonymousRandomSeed 5 otros, AnonymousRandomSeed Generator 5 y otros .

Abortar	Genera una excepción para abortar el proceso cuando se llama.
Todo	Calcula el "y" lógico de los elementos a través de las dimensiones de un tensor.
De todos a todos <T>	Una opción para intercambiar datos entre réplicas de TPU.
AnónimoHashTable	Crea una tabla hash anónima no inicializada.
AnónimoIteratorV2	Un contenedor para un recurso de iterador.
AnónimoIteratorV3	Un contenedor para un recurso de iterador.
AnónimoMemoryCache
AnónimoMultiDeviceIterator	Un contenedor para un recurso de iterador de varios dispositivos.
AnónimoMultiDeviceIteratorV3	Un contenedor para un recurso de iterador de varios dispositivos.
AnónimoMutableDenseHashTable	Crea una tabla hash mutable anónima vacía que usa tensores como almacén de respaldo.
AnónimoMutableHashTable	Crea una tabla hash mutable anónima vacía.
AnónimoMutableHashTableOfTensors	Crea una tabla hash mutable anónima vacía de valores vectoriales.
AnónimoRandomSeedGenerator
AnónimoSeedGenerator
Cualquier	Calcula el "o lógico" de los elementos a través de las dimensiones de un tensor.
AplicarAdagradV2 <T>	Actualice '*var' de acuerdo con el esquema adagrad.
ApproxTopK <T extiende Número>	Devuelve los valores min/max k y sus índices del operando de entrada de forma aproximada.
AssertCardinalityDataset
AssertNextDataset	Una transformación que afirma qué transformaciones suceden a continuación.
AssertPrevDataset	Una transformación que afirma qué transformaciones ocurrieron previamente.
afirmar que	Afirma que la condición dada es verdadera.
Asignar <T>	Actualice 'ref' asignándole 'valor'.
Asignar Agregar <T>	Actualice 'ref' agregándole 'value'.
AsignarAñadirVariableOp	Agrega un valor al valor actual de una variable.
Asignar Sub <T>	Actualice 'ref' restando 'value' de él.
AsignarOpSubVariable	Resta un valor del valor actual de una variable.
AsignarOpVariable	Asigna un nuevo valor a una variable.
AsignarVariableXlaConcatND	Concatena el tensor de entrada en todas las dimensiones.
AutoShardDatasetAutoShardDataset	Crea un conjunto de datos que fragmenta el conjunto de datos de entrada.
BandedTriangularResolver <T>
Barrera	Define una barrera que persiste en diferentes ejecuciones de gráficos.
BarreraCerrar	Cierra la barrera dada.
BarreraIncompletaTamaño	Calcula el número de elementos incompletos en la barrera dada.
BarreraInsertarMuchos	Para cada tecla, asigna el valor respectivo al componente especificado.
BarreraListoTamaño	Calcula el número de elementos completos en la barrera dada.
BarreraTomarMuchos	Toma el número dado de elementos completos de una barrera.
Lote	Distribuye por lotes todos los tensores de entrada de forma no determinista.
BatchMatMulV2 <T>	Multiplica rebanadas de dos tensores en lotes.
BatchMatMulV3 <V>	Multiplica rebanadas de dos tensores en lotes.
LoteAEspacio <T>	BatchToSpace para tensores 4-D de tipo T.
LoteAEspacioNd <T>	BatchToSpace para tensores ND de tipo T.
BesselI0 <T extiende Número>
BesselI1 <T extiende Número>
BesselJ0 <T extiende Número>
BesselJ1 <T extiende Número>
BesselK0 <T extiende Número>
BesselK0e <T extiende Número>
BesselK1 <T extiende Número>
BesselK1e <T extiende Número>
BesselY0 <T extiende Número>
BesselY1 <T extiende Número>
Transmisión de bits <U>	Bitcasts un tensor de un tipo a otro sin copiar datos.
BlockLSTM <T extiende Número>	Calcula la propagación hacia adelante de la celda LSTM para todos los pasos de tiempo.
BlockLSTMGrad <T extiende Número>	Calcula la propagación hacia atrás de la celda LSTM para toda la secuencia de tiempo.
BlockLSTMGradV2 <T extiende Número>	Calcula la propagación hacia atrás de la celda LSTM para toda la secuencia de tiempo.
BlockLSTMV2 <T extiende Número>	Calcula la propagación hacia adelante de la celda LSTM para todos los pasos de tiempo.
BoostedTreesAgregateStats	Agrega el resumen de estadísticas acumuladas para el lote.
BoostedTreesBucketize	Organice en cubos cada función en función de los límites de los cubos.
ImpulsadoÁrbolesCalcularMejorCaracterísticaDividir	Calcula las ganancias para cada función y devuelve la mejor información de división posible para la función.
ImpulsadoÁrbolesCalcularMejorCaracterísticaDividirV2	Calcula las ganancias para cada función y devuelve la mejor información dividida posible para cada nodo.
ImpulsadoÁrbolesCalcularMejorGananciasPorCaracterística	Calcula las ganancias para cada función y devuelve la mejor información de división posible para la función.
BoostedTreesCenterBias	Calcula el previo a partir de los datos de entrenamiento (el sesgo) y completa el primer nodo con el previo de los logits.
BoostedTreesCreateEnsemble	Crea un modelo de conjunto de árboles y le devuelve un identificador.
BoostedTreesCreateQuantileStreamResource	Cree el recurso para flujos cuantiles.
BoostedTreesDeserializeEnsemble	Deserializa una configuración de conjunto de árbol serializado y reemplaza el árbol actual conjunto.
ImpulsadoÁrbolesConjuntoRecursoHandleOp	Crea un identificador para un BoostedTreesEnsembleResource
BoostedTreesExampleDebugOutputs	Salidas de interpretabilidad de depuración/modelo para cada ejemplo.
BoostedTreesFlushQuantilResúmenes	Vacíe los resúmenes de cuantiles de cada recurso de flujo de cuantiles.
BoostedTreesGetEnsembleStates	Recupera el token de sello de recursos del conjunto de árboles, el número de árboles y las estadísticas de crecimiento.
BoostedTreesMakeQuantileResúmenes	Hace el resumen de cuantiles para el lote.
BoostedTreesMakeStatsResumen	Hace el resumen de las estadísticas acumuladas para el lote.
BoostedTreesPredict	Ejecuta múltiples predictores de conjunto de regresión aditiva en instancias de entrada y calcula los logits.
BoostedTreesQuantileStreamResourceAddSummaries	Agregue los resúmenes de cuantiles a cada recurso de flujo de cuantiles.
BoostedTreesQuantileStreamResourceDeserialize	Deserialice los límites del depósito y el indicador listo en el QuantileAccumulator actual.
BoostedTreesQuantileStreamResourceFlush	Vacíe los resúmenes de un recurso de secuencia de cuantiles.
BoostedTreesQuantileStreamResourceGetBucketBoundaries	Genere los límites de la cubeta para cada función en función de los resúmenes acumulados.
BoostedTreesQuantileStreamResourceHandleOp	Crea un identificador para BoostedTreesQuantileStreamResource.
BoostedTreesSerializeEnsemble	Serializa el conjunto de árboles en un proto.
BoostedTreesSparseAgregateStats	Agrega el resumen de estadísticas acumuladas para el lote.
ImpulsadoÁrbolesEscasoCalcularMejorCaracterísticaDividir	Calcula las ganancias para cada función y devuelve la mejor información de división posible para la función.
ImpulsadoÁrbolesEntrenamientoPredecir	Ejecuta múltiples predictores de conjunto de regresión aditiva en instancias de entrada y calcula la actualización de los registros almacenados en caché.
BoostedTreesUpdateEnsemble	Actualiza el conjunto de árboles agregando una capa al último árbol que se está cultivando o comenzando un nuevo árbol.
BoostedTreesUpdateEnsembleV2	Actualiza el conjunto de árboles agregando una capa al último árbol que se está cultivando o comenzando un nuevo árbol.
BroadcastDynamicShape <T extiende Número>	Devuelve la forma de s0 op s1 con transmisión.
BroadcastGradientArgs <T extiende Número>	Devuelva los índices de reducción para calcular gradientes de s0 op s1 con transmisión.
Difundir a <T>	Transmita una matriz para una forma compatible.
Cubitear	Divide en cubos la 'entrada' en función de los 'límites'.
CSRSparseMatrixComponents <T>	Lee los componentes de CSR en el `índice` del lote.
CSRSparseMatrixToDense <T>	Convierta un CSRSparseMatrix (posiblemente por lotes) en denso.
CSRSparseMatrixToSparseTensor <T>	Convierte un CSRSparesMatrix (posiblemente por lotes) en un SparseTensor.
CSVConjunto de datos
CSVDatasetV2
CTCLossV2	Calcula la pérdida de CTC (probabilidad de registro) para cada entrada de lote.
CacheDatasetV2
CheckNumericsV2 <T extiende Número>	Comprueba un tensor para los valores de NaN, -Inf y +Inf.
Elija el conjunto de datos más rápido
ClipPorValor <T>	Recorta los valores de tensor a un mínimo y máximo especificado.
IntercalarTPUEmbeddingMemory	Una operación que fusiona los prototipos de configuración de memoria codificada en cadena de todos los hosts.
CollectiveAllToAllV2 <T extiende Número>	Intercambia mutuamente múltiples tensores de tipo y forma idénticos.
CollectiveAllToAllV3 <T extiende Número>	Intercambia mutuamente múltiples tensores de tipo y forma idénticos.
CollectiveAssignGroupV2	Asigne teclas de grupo según la asignación de grupo.
CollectiveBcastRecvV2 <U>	Recibe una transmisión de valor de tensor desde otro dispositivo.
CollectiveBcastSendV2 <T>	Transmite un valor de tensor a uno o más dispositivos.
CollectiveGather <T extiende Número>	Acumula mutuamente múltiples tensores de idéntico tipo y forma.
CollectiveGatherV2 <T extiende Número>	Acumula mutuamente múltiples tensores de idéntico tipo y forma.
CollectiveInitializeCommunicator	Inicializa un grupo para operaciones colectivas.
Permutación colectiva <T>	Op para permutar tensores en instancias de TPU replicadas.
CollectiveReduceScatterV2 <T extiende Número>	Reduce mutuamente múltiples tensores de tipo y forma idénticos y dispersa el resultado.
CollectiveReduceV2 <T extiende Número>	Reduce mutuamente múltiples tensores de tipo y forma idénticos.
CollectiveReduceV3 <T extiende Número>	Reduce mutuamente múltiples tensores de tipo y forma idénticos.
Supresión no máx. combinada	Selecciona con avidez un subconjunto de cuadros delimitadores en orden descendente de puntuación, Esta operación realiza non_max_suppression en las entradas por lote, en todas las clases.
CompuestoTensorVariantFromComponents	Codifica un valor `ExtensionType` en un tensor escalar `variant`.
CompositeTensorVariantToComponents	Decodifica un tensor escalar `variant` en un valor `ExtensionType`.
CompressElement	Comprime un elemento del conjunto de datos.
Calcular tamaño de lote	Calcula el tamaño de lote estático de un conjunto de datos sin lotes parciales.
ComputeDedupDataTupleMask	Una operación calcula la máscara de tupla de los datos de deduplicación del núcleo integrado.
Concatenar <T>	Concatena tensores a lo largo de una dimensión.
ConfigureAndInitializeGlobalTPU	Una operación que configura las estructuras centralizadas para un sistema de TPU distribuido.
ConfigureDistributedTPU	Configura las estructuras centralizadas para un sistema de TPU distribuido.
ConfigurarTPUEincrustación	Configura TPUEmbedding en un sistema de TPU distribuido.
ConfigureTPUEmbeddingHost	Una operación que configura el software TPUEmbedding en un host.
ConfigurarTPUEmbeddingMemory	Una operación que configura el software TPUEmbedding en un host.
ConnectTPUEembeddingHosts	Una operación que configura la comunicación entre las instancias de software host de TPUEmbedding después de llamar a ConfigureTPUEmbeddingHost en cada host.
<T> constante	Un operador que produce un valor constante.
ConsumirMutexLock	Esta operación consume un bloqueo creado por `MutexLock`.
Disparador de control	No hace nada.
Conv2DBackpropFilterV2 <T extiende Número>	Calcula los gradientes de convolución con respecto al filtro.
Conv2DBackpropInputV2 <T extiende Número>	Calcula los gradientes de convolución con respecto a la entrada.
Copiar <T>	Copie un tensor de CPU a CPU o de GPU a GPU.
Copiar host <T>	Copia un tensor a host.
Copiar a malla <T>
Copiar a gradiente de malla <T>
CountUpTo <T extiende Número>	Incrementa 'ref' hasta que alcanza el 'límite'.
CrossReplicaSum <T extiende Número>	Op para sumar entradas en instancias de TPU replicadas.
CudnnRNNBackpropV3 <T extiende Número>	Paso de apoyo trasero de CudnnRNNV3.
CudnnRNNCanonicalToParamsV2 <T extiende Número>	Convierte parámetros CudnnRNN de forma canónica a forma utilizable.
CudnnRNNParamsToCanonicalV2 <T extiende Número>	Recupera parámetros de CudnnRNN en forma canónica.
CudnnRNNV3 <T extiende Número>	Un RNN respaldado por cuDNN.
CumulativeLogsumexp <T extiende Número>	Calcule el producto acumulativo del tensor `x` a lo largo del `eje`.
DTensorRestoreV2
DTensorSetGlobalTPUArray	Una operación que informa a un host de los ID globales de todas las TPU del sistema.
DataServiceDataset	Crea un conjunto de datos que lee datos del servicio tf.data.
DataServiceDatasetV2	Crea un conjunto de datos que lee datos del servicio tf.data.
Conjunto de datosCardinalidad	Devuelve la cardinalidad de `input_dataset`.
DatasetFromGraph	Crea un conjunto de datos a partir del `graph_def` dado.
DatasetToGraphV2	Devuelve un GraphDef serializado que representa `input_dataset`.
Dawsn <T extiende Número>
DebugGradientIdentity <T>	Operación de identidad para la depuración de gradientes.
DebugGradientRefIdentity <T>	Operación de identidad para la depuración de gradientes.
Identidad de depuración <T>	Proporciona una asignación de identidad del tensor de entrada de tipo no Ref para la depuración.
DepurarIdentidadV2 <T>	Op. de depuración de identidad V2.
DebugNanCount	Contador de valor NaN de depuración Op.
DebugNumericSummary	Resumen numérico de depuración Op.
DebugNumericSummaryV2 <U extiende Número>	Resumen numérico de depuración V2 Op.
DecodeImage <T extiende Número>	Función para decode_bmp, decode_gif, decode_jpeg y decode_png.
DecodePaddedRaw <T extiende Número>	Reinterpreta los bytes de una cadena como un vector de números.
DecodeProto	El op extrae campos de un mensaje de búfer de protocolo serializado en tensores.
Copia profunda <T>	Hace una copia de `x`.
Eliminar iterador	Un contenedor para un recurso de iterador.
EliminarMemoryCache
DeleteMultiDeviceIterator	Un contenedor para un recurso de iterador.
DeleteRandomSeedGenerator
DeleteSeedGenerator
DeleteSessionTensor	Elimina el tensor especificado por su identificador en la sesión.
DenseBincount <U extiende Número>	Cuenta el número de ocurrencias de cada valor en una matriz de enteros.
DenseCountSparseOutput <Número de extensión U>	Realiza el conteo de contenedores de salida dispersa para una entrada tf.tensor.
DenseToCSRSparseMatrix	Convierte un tensor denso en un CSRSparseMatrix (posiblemente por lotes).
DestruirRecursoOp	Elimina el recurso especificado por el identificador.
Destruir Variable Temporal <T>	Destruye la variable temporal y devuelve su valor final.
Índice de dispositivo	Devuelve el índice del dispositivo que ejecuta la operación.
DirectedInterleaveDataset	Un sustituto de `InterleaveDataset` en una lista fija de conjuntos de datos `N`.
DeshabilitarCopiarEnLectura	Desactiva el modo de copia en lectura.
DistribuidoGuardar
DrawBoundingBoxesV2 <T extiende Número>	Dibuje cuadros delimitadores en un lote de imágenes.
DummyIterationCounter
DummyMemoryCache
DummySeedGenerator
DynamicEnqueueTPUEmbeddingArbitraryTensorBatch	Facilita la transferencia de código que utiliza tf.nn.embedding_lookup_sparse().
Partición dinámica <T>	Divide `data` en tensores `num_partitions` utilizando índices de `partitions`.
Puntada Dinámica <T>	Intercala los valores de los tensores `datos` en un solo tensor.
Editar distancia	Calcula la distancia de edición de Levenshtein (posiblemente normalizada).
Eig <U>	Calcula la descomposición propia de una o más matrices cuadradas.
Einsum <T>	Contracción tensorial según la convención de suma de Einstein.
Vacío <T>	Crea un tensor con la forma dada.
EmptyTensorList	Crea y devuelve una lista de tensores vacía.
VacíoTensorMapa	Crea y devuelve un mapa de tensor vacío.
EncodeProto	La operación serializa los mensajes protobuf proporcionados en los tensores de entrada.
EnqueueTPUEmbeddingArbitraryTensorBatch	Facilita la transferencia de código que utiliza tf.nn.embedding_lookup_sparse().
Poner en colaTPUEmbeddingBatch	Una operación que pone en cola una lista de tensores por lotes de entrada para TPUEmbedding.
EnqueueTPUEmbeddingIntegerBatch	Una operación que pone en cola una lista de tensores por lotes de entrada para TPUEmbedding.
EnqueueTPUEmbeddingRaggedTensorBatch	Facilita la transferencia de código que utiliza tf.nn.embedding_lookup().
EnqueueTPUEmbeddingSparseBatch	Una operación que pone en cola los índices de entrada de TPUEmbedding de un SparseTensor.
EnqueueTPUEmbeddingSparseTensorBatch	Facilita la transferencia de código que utiliza tf.nn.embedding_lookup_sparse().
Asegurar forma <T>	Garantiza que la forma del tensor coincida con la forma esperada.
Introduzca <T>	Crea o encuentra un marco secundario y hace que los "datos" estén disponibles para el marco secundario.
Erfinv <T extiende Número>
Norma euclidiana <T>	Calcula la norma euclidiana de los elementos a través de las dimensiones de un tensor.
EjecutarTPUEmbeddingPartitioner	Una operación que ejecuta el particionador TPUEmbedding en la configuración central dispositivo y calcula el tamaño HBM (en bytes) necesario para la operación TPUEmbedding.
Salir <T>	Sale del marco actual a su marco principal.
ExpandirDims <T>	Inserta una dimensión de 1 en la forma de un tensor.
ExperimentalAutoShardDatasetExperimentalAutoShardDataset	Crea un conjunto de datos que fragmenta el conjunto de datos de entrada.
ExperimentalBytesProducedStatsDataset	Registra el tamaño en bytes de cada elemento de `input_dataset` en un StatsAggregator.
ExperimentalChooseFastestDataset
ExperimentalDatasetCardinalidad	Devuelve la cardinalidad de `input_dataset`.
ExperimentalDatasetToTFRecord	Escribe el conjunto de datos dado en el archivo dado usando el formato TFRecord.
ExperimentalDenseToSparseBatchDataset	Crea un conjunto de datos que agrupa elementos de entrada en un SparseTensor.
ExperimentalLatencyStatsDataset	Registra la latencia de producir elementos `input_dataset` en un StatsAggregator.
ExperimentalMatchingFilesDatasetExperimentalMatchingFilesDataset
ExperimentalMaxIntraOpParallelismDataset	Crea un conjunto de datos que anula el paralelismo intraoperatorio máximo.
ExperimentalParseExampleDatasetExperimentalParseExampleDataset	Transforma `input_dataset` que contiene prototipos de `Ejemplo` como vectores de DT_STRING en un conjunto de datos de objetos `Tensor` o `SparseTensor` que representan las características analizadas.
ExperimentalPrivateThreadPoolDataset	Crea un conjunto de datos que utiliza un grupo de subprocesos personalizado para calcular `conjunto_de_datos_de_entrada`.
ExperimentalRandomDataset	Crea un conjunto de datos que devuelve números pseudoaleatorios.
ExperimentalRebatchDataset	Crea un conjunto de datos que cambia el tamaño del lote.
ExperimentalSetStatsAggregatorDataset
Conjunto de datos de ventana deslizante experimental	Crea un conjunto de datos que pasa una ventana deslizante sobre `input_dataset`.
ExperimentalSqlDatasetExperimentalSqlDatasetExperimentalSqlDataset	Crea un conjunto de datos que ejecuta una consulta SQL y emite filas del conjunto de resultados.
ExperimentalStatsAggregatorHandle	Crea un recurso de administrador de estadísticas.
ExperimentalStatsAgregatorSummary	Produce un resumen de las estadísticas registradas por el administrador de estadísticas determinado.
ExperimentalUnbatchDatasetExperimentalUnbatchDataset	Un conjunto de datos que divide los elementos de su entrada en varios elementos.
Expint <T extiende Número>
ExtraerGlimpseV2	Extrae un vistazo del tensor de entrada.
ExtractVolumePatches <T extiende Número>	Extraiga `parches` de `entrada` y colóquelos en la dimensión de salida `"profundidad"`.
FileSystemSetConfigurationFileSystemSetConfiguration	Establecer la configuración del sistema de archivos.
Rellenar <U>	Crea un tensor relleno con un valor escalar.
FinalizeDataset	Crea un conjunto de datos aplicando `tf.data.Options` a `input_dataset`.
FinalizarTPUEmbedding	Una operación que finaliza la configuración de TPUEmbedding.
Huella dactilar	Genera valores de huellas dactilares.
FresnelCos <T extiende Número>
FresnelSin <T extiende Número>
FusedBatchNormGradV3 <T extiende Número, U extiende Número>	Gradiente para la normalización de lotes.
FusedBatchNormV3 <T extiende el número, U extiende el número>	Normalización de lotes.
GRUBlockCell <T extiende Número>	Calcula la propagación hacia adelante de la celda GRU para 1 paso de tiempo.
GRUBlockCellGrad <T extiende Número>	Calcula la propagación hacia atrás de la celda GRU para 1 paso de tiempo.
Reunir <T>	Reúna cortes del eje `params` `eje` de acuerdo con `índices`.
Reunir y <T>	Reúne segmentos de `params` en un tensor con la forma especificada por `indices`.
GenerarBoundingBoxProposals	Esta operación produce Regiones de interés a partir de cuadros delimitadores dados (bbox_deltas) codificados WRT anclas de acuerdo con eq.2 en arXiv: 1506.01497 El operador selecciona los cuadros de puntuación superiores `pre_nms_topn`, los decodifica con respecto a los anclajes, aplica una supresión no máxima en los cuadros superpuestos con un valor de intersección sobre unión (iou) superior a `nms_threshold` y descarta los cuadros donde el lado más corto es menor que ` min_size`.
ObtenerElementoEnIndice	Obtiene el elemento en el índice especificado en un conjunto de datos.
ObtenerOpciones	Devuelve las `tf.data.Options` adjuntas a `input_dataset`.
ObtenerSessionHandle	Almacene el tensor de entrada en el estado de la sesión actual.
ObtenerTensor de Sesión <T>	Obtenga el valor del tensor especificado por su identificador.
Gradientes	Agrega operaciones para calcular las derivadas parciales de la suma de `y` s con `x` s, es decir, `d(y_1 + y_2 + ...)/dx_1, d(y_1 + y_2 + ...)/dx_2...` Si se establecen los valores `Options.dx()` , son como las derivadas parciales simbólicas iniciales de alguna función de pérdida `L` wrt
GarantíaConst <T>	Da una garantía al tiempo de ejecución de TF de que el tensor de entrada es una constante.
Tabla de picadillo	Crea una tabla hash no inicializada.
HistogramFixedWidth <U extiende Número>	Devolver histograma de valores.
Identidad <T>	Devuelve un tensor con la misma forma y contenido que el tensor o valor de entrada.
IdentidadN	Devuelve una lista de tensores con las mismas formas y contenidos que la entrada tensores.
IgnorarErrorsDatasetIgnoreErrorsDataset	Crea un conjunto de datos que contiene los elementos de `input_dataset` ignorando los errores.
ImageProjectiveTransformV2 <T extiende Número>	Aplica la transformación dada a cada una de las imágenes.
ImageProjectiveTransformV3 <T extiende Número>	Aplica la transformación dada a cada una de las imágenes.
Constante inmutable <T>	Devuelve el tensor inmutable de la región de memoria.
InfeedDequeue <T>	Un marcador de posición para un valor que se incluirá en el cálculo.
InfeedDequeueTuple	Obtiene múltiples valores de la entrada como una tupla XLA.
InfeedEnqueue	Una operación que alimenta un solo valor de Tensor en el cálculo.
InfeedEnqueuePrelinearizedBuffer	Una operación que pone en cola el búfer prelinealizado en la entrada de TPU.
InfeedEnqueueTuple	Alimenta varios valores de tensor en el cálculo como una tupla XLA.
InitializeTable	Inicializador de tabla que toma dos tensores para claves y valores respectivamente.
InitializeTableFromDataset
InitializeTableFromTextFile	Inicializa una tabla a partir de un archivo de texto.
InplaceAdd <T>	Agrega v en filas especificadas de x.
InplaceSub <T>	Resta `v` en filas especificadas de `x`.
InplaceUpdate <T>	Actualiza las filas especificadas 'i' con los valores 'v'.
IsBoostedTreesEnsembleInicializado	Comprueba si se ha inicializado un conjunto de árbol.
IsBoostedTreesQuantileStreamResourceInitialized	Comprueba si se ha inicializado un flujo de cuantiles.
IsTPUEmbeddingInicializado	Si TPU Embedding se inicializa en un sistema de TPU distribuido.
EsVariableInicializado	Comprueba si se ha inicializado un tensor.
IsotonicRegression <U extiende Número>	Resuelve un lote de problemas de regresión isotónica.
IteradorObtenerDispositivo	Devuelve el nombre del dispositivo en el que se ha colocado el `recurso`.
KMC2ChainInitialization	Devuelve el índice de un punto de datos que debe agregarse al conjunto semilla.
KmeansPlusPlusInicialización	Selecciona num_to_sample filas de entrada usando el criterio KMeans++.
KthOrderStatistic	Calcula la estadística de orden K de un conjunto de datos.
Conjunto de datos LMDB	Crea un conjunto de datos que emite los pares clave-valor en uno o más archivos LMDB.
LSTMBlockCell <T extiende Número>	Calcula la propagación directa de la celda LSTM para 1 paso de tiempo.
LSTMBlockCellGrad <T extiende Número>	Calcula la propagación hacia atrás de la celda LSTM para 1 paso de tiempo.
LinSpace <T extiende Número>	Genera valores en un intervalo.
ListDataset	Crea un conjunto de datos que emite cada uno de los `tensores` una vez.
CargartodoslosTPUEmbeddingParameters	Una operación que carga parámetros de optimización en la memoria integrada.
LoadTPUEmbeddingADAMParameters	Cargue los parámetros de incrustación de ADAM.
CargarTPUEmbeddingAdadeltaParameters	Cargue los parámetros de incrustación de Adadelta.
LoadTPUEmbeddingAdagradMomentumParameters	Cargue los parámetros de incrustación de Adagrad Momentum.
CargarTPUEmbeddingAdagradParameters	Cargue los parámetros de incrustación de Adagrad.
LoadTPUEmbeddingCenteredRMSPropParameters	Parámetros de incrustación de RMSProp centrados en la carga.
CargarTPUEmbeddingFTRLParameters	Cargue los parámetros de incrustación de FTRL.
LoadTPUEmbeddingFrequencyEstimatorParameters	Parámetros de incrustación del estimador de frecuencia de carga.
CargarTPUEmbeddingMDLAdagradLightParameters	Cargue los parámetros de incrustación de MDL Adagrad Light.
LoadTPUEmbeddingMomentumParameters	Cargue los parámetros de incrustación de Momentum.
CargarTPUEmbeddingProximalAdagradParameters	Cargue los parámetros de incrustación de Adagrad proximal.
CargarTPUEmbeddingProximalYogiParameters
CargarTPUEmbeddingRMSPropParameters	Cargue los parámetros de incrustación de RMSProp.
LoadTPUEmbeddingStochasticGradientDescentParameters	Cargue los parámetros de incrustación de SGD.
Exportación de tabla de búsqueda <T, U>	Muestra todas las claves y valores de la tabla.
BuscarTablaBuscar <U>	Busca claves en una tabla, genera los valores correspondientes.
LookupTableImport	Reemplaza el contenido de la tabla con las claves y valores especificados.
BuscarTablaInsertar	Actualiza la tabla para asociar claves con valores.
LookupTableRemove	Elimina claves y sus valores asociados de una tabla.
LookupTableSize	Calcula el número de elementos en la tabla dada.
LoopCond	Reenvía la entrada a la salida.
Límite Inferior <U extiende Número>	Aplica lower_bound(sorted_search_values, valores) a lo largo de cada fila.
Lu <T, U extiende Número>	Calcula la descomposición LU de una o más matrices cuadradas.
hacer único	Haga que todos los elementos en la dimensión que no sea de lote sean únicos, pero \"cercanos\" a su valor inicial.
MapaLimpiar	Op elimina todos los elementos del contenedor subyacente.
MapIncompleteSize	Op devuelve el número de elementos incompletos en el contenedor subyacente.
MapaPeek	Op mira los valores en la clave especificada.
Tamaño de mapa	Op devuelve el número de elementos en el contenedor subyacente.
MapStage	Etapa (clave, valores) en el contenedor subyacente que se comporta como una tabla hash.
MapaUnstage	Op elimina y devuelve los valores asociados con la clave del contenedor subyacente.
MapaUnstageNoKey	Op elimina y devuelve un aleatorio (clave, valor) del contenedor subyacente.
MatrixDiagPartV2 <T>	Devuelve la parte diagonal por lotes de un tensor por lotes.
MatrixDiagPartV3 <T>	Devuelve la parte diagonal por lotes de un tensor por lotes.
MatrixDiagV2 <T>	Devuelve un tensor diagonal por lotes con valores diagonales por lotes dados.
MatrixDiagV3 <T>	Devuelve un tensor diagonal por lotes con valores diagonales por lotes dados.
MatrixSetDiagV2 <T>	Devuelve un tensor de matriz por lotes con nuevos valores diagonales por lotes.
MatrixSetDiagV3 <T>	Devuelve un tensor de matriz por lotes con nuevos valores diagonales por lotes.
Máximo <T>	Calcula el máximo de elementos a través de las dimensiones de un tensor.
MaxIntraOpParallelismDataset	Crea un conjunto de datos que anula el paralelismo intraoperatorio máximo.
Combinar <T>	Reenvía el valor de un tensor disponible de `entradas` a `salida`.
MergeDedupData	Una operación combina elementos de tensores enteros y flotantes en datos de deduplicación como tupla XLA.
Min <T>	Calcula el mínimo de elementos a través de las dimensiones de un tensor.
Almohadilla de espejo <T>	Rellena un tensor con valores reflejados.
MirrorPadGrad <T>	Opción de gradiente para op `MirrorPad`.
MlirPassthroughOp	Envuelve un cálculo MLIR arbitrario expresado como un módulo con una función main().
MulNoNan <T>	Devuelve x * y por elemento.
MutableDenseHashTable	Crea una tabla hash vacía que usa tensores como almacén de respaldo.
MutableHashTable	Crea una tabla hash vacía.
MutableHashTableOfTensors	Crea una tabla hash vacía.
exclusión mutua	Crea un recurso Mutex que puede ser bloqueado por `MutexLock`.
MutexLock	Bloquea un recurso mutex.
NcclAllReduce <T extiende Número>	Produce un tensor que contiene la reducción en todos los tensores de entrada.
NcclBroadcast <T extiende Número>	Envía `entrada` a todos los dispositivos que están conectados a la salida.
NcclReduce <T extiende Número>	Reduce `input` de `num_devices` usando `reduction` a un solo dispositivo.
Ndtri <T extiende Número>
Vecinos más cercanos	Selecciona los k centros más cercanos para cada punto.
SiguienteDespués de <T extiende Número>	Devuelve el siguiente valor representable de `x1` en la dirección de `x2`, por elementos.
Siguiente iteración <T>	Hace que su entrada esté disponible para la próxima iteración.
NoOp	No hace nada.
Enteros no deterministas <U>	Genera de forma no determinista algunos números enteros.
NonMaxSuppressionV5 <T extiende Número>	Selecciona con avidez un subconjunto de cuadros delimitadores en orden descendente de puntuación, podar las cajas que tienen una gran superposición de intersección sobre unión (IOU) con las cajas previamente seleccionadas.
Conjunto de datos no serializable
UnoCaliente <U>	Devuelve un tensor one-hot.
UnosComo <T>	Devuelve un tensor de unos con la misma forma y tipo que x.
OptimizeDatasetV2	Crea un conjunto de datos aplicando optimizaciones relacionadas a `input_dataset`.
OpcionesConjunto de datos	Crea un conjunto de datos adjuntando tf.data.Options a `input_dataset`.
OrdenadoMapaLimpiar	Op elimina todos los elementos del contenedor subyacente.
OrderedMapIncompleteSize	Op devuelve el número de elementos incompletos en el contenedor subyacente.
OrdenadoMapaPeek	Op mira los valores en la clave especificada.
OrderedMapSize	Op devuelve el número de elementos en el contenedor subyacente.
Etapa de mapa ordenada	Etapa (clave, valores) en el contenedor subyacente que se comporta como un ordenado contenedor asociativo.
OrdenadoMapaUnstage	Op elimina y devuelve los valores asociados con la clave del contenedor subyacente.
OrdenadoMapaUnstageNoKey	Op elimina y devuelve el elemento (clave, valor) con el menor clave del contenedor subyacente.
Desencolado de salida <T>	Recupera un solo tensor de la salida de cálculo.
OutfeedDequeueTuple	Recupere múltiples valores de la salida de cálculo.
SalidaDequeueTupleV2	Recupere múltiples valores de la salida de cálculo.
SalidaDequeueV2 <T>	Recupera un solo tensor de la salida de cálculo.
OutfeedEnqueue	Ponga en cola un tensor en la salida de cálculo.
OutfeedEnqueueTuple	Ponga en cola múltiples valores de tensor en la salida de cálculo.
Almohadilla <T>	Almohadillas un tensor.
ParallelBatchDatasetParallelBatchDataset
ParallelConcat <T>	Concatena una lista de tensores `N` a lo largo de la primera dimensión.
ParallelDynamicStitch <T>	Intercala los valores de los tensores `datos` en un solo tensor.
ParseExampleDatasetV2	Transforma `input_dataset` que contiene prototipos de `Ejemplo` como vectores de DT_STRING en un conjunto de datos de objetos `Tensor` o `SparseTensor` que representan las características analizadas.
ParseExampleV2	Transforma un vector de tf.Example protos (como cadenas) en tensores tipados.
ParseSequenceExampleV2	Transforma un vector de protos tf.io.SequenceExample (como cadenas) en tensores con tipo.
Marcador de posición <T>	Un marcador de posición para un valor que se incluirá en el cálculo.
Marcador de posición con valor predeterminado <T>	Una operación de marcador de posición que pasa a través de `entrada` cuando su salida no se alimenta.
prelinealizar	Una operación que linealiza un valor de Tensor a un tensor variante opaco.
PrelinearizeTuple	Una operación que linealiza múltiples valores de Tensor a un tensor variante opaco.
PrimitivoOp	Una clase base para implementaciones `Op` que están respaldadas por una única `Operation` .
Imprimir	Imprime un escalar de cadena.
PrivateThreadPoolDatasetPrivateThreadPoolDataset	Crea un conjunto de datos que utiliza un grupo de subprocesos personalizado para calcular `conjunto_de_datos_de_entrada`.
Prod <T>	Calcula el producto de los elementos a través de las dimensiones de un tensor.
QuantizeAndDequantizeV4 <T extiende Número>	Cuantiza y luego descuantifica un tensor.
QuantizeAndDequantizeV4Grad <T extiende Número>	Devuelve el gradiente de `QuantizeAndDequantizeV4`.
QuantizedConcat <T>	Concatena tensores cuantizados a lo largo de una dimensión.
QuantizedConcatV2 <T>
QuantizedConv2DAndRelu <V>
QuantizedConv2DAndReluAndRequantize <V>
QuantizedConv2DAndRequantize <V>
QuantizedConv2DPerChannel <V>	Calcula QuantizedConv2D por canal.
QuantizedConv2DWithBias <V>
QuantizedConv2DWithBiasAndRelu <V>
QuantizedConv2DWithBiasAndReluAndRequantize <W>
QuantizedConv2DWithBiasAndRequantize <W>
QuantizedConv2DWithBiasSignedSumAndReluAndRequantize <X>
QuantizedConv2DWithBiasSumAndRelu <V>
QuantizedConv2DWithBiasSumAndReluAndRequantize <X>
QuantizedDepthwiseConv2D <V>	Calcula Conv2D cuantificado en profundidad.
QuantizedDepthwiseConv2DWithBias <V>	Calcula Conv2D cuantificado en profundidad con sesgo.
QuantizedDepthwiseConv2DWithBiasAndRelu <V>	Calcula Conv2D cuantificado en profundidad con Bias y Relu.
QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize <W>	Calcula Conv2D cuantificado en profundidad con Bias, Relu y Requantize.
QuantizedMatMulWithBias <W>	Realiza una multiplicación de matriz cuantificada de 'a' por la matriz 'b' con suma de sesgo.
QuantizedMatMulWithBiasAndDequantize <W extiende el número>
QuantizedMatMulWithBiasAndRelu <V>	Realice una multiplicación de matriz cuantificada de `a` por la matriz `b` con adición de sesgo y fusión relu.
QuantizedMatMulWithBiasAndReluAndRequantize <W>	Realice una multiplicación de matriz cuantizada de `a` por la matriz `b` con adición de sesgo y relu y recuantifique la fusión.
QuantizedMatMulWithBiasAndRequantize <W>
QuantizedReshape <T>	Reforma un tensor cuantizado según la operación Reformar.
RaggedBincount <U extiende Número>	Cuenta el número de ocurrencias de cada valor en una matriz de enteros.
RaggedCountSparseOutput <Número de extensión U>	Realiza el conteo de intervalos de salida dispersa para una entrada de tensor irregular.
RaggedCross <T, U extiende Número>	Genera un cruce de características a partir de una lista de tensores y lo devuelve como RaggedTensor.
RaggedFillEmptyRows <T>
RaggedFillEmptyRowsGrad <T>
RaggedGather <T extiende Número, U>	Reúna cortes irregulares del eje `params` `0` de acuerdo con los `índices`.
RaggedRange <U extiende Número, T extiende Número>	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	Crea un conjunto de datos que devuelve números pseudoaleatorios.
RandomIndexShuffle <T extends Number>	Outputs the position of `value` in a permutation of [0, ..., max_index].
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.
RebatchDataset	Creates a dataset that changes the batch size.
RebatchDatasetV2	Creates a dataset that changes the batch size.
Recv <T>	Receives the named tensor from send_device on recv_device.
RecvTPUEmbeddingActivations	An op that receives embedding activations on the TPU.
ReduceAll	Computes the "logical and" of elements across dimensions of a tensor.
ReduceAny	Computes the "logical or" of elements across dimensions of a tensor.
ReduceMax <T>	Computes the maximum of elements across dimensions of a tensor.
ReduceMin <T>	Computes the minimum of elements across dimensions of a tensor.
ReduceProd <T>	Computes the product of elements across dimensions of a tensor.
ReduceSum <T>	Computes the sum of elements across dimensions of a tensor.
RefEnter <T>	Creates or finds a child frame, and makes `data` available to the child frame.
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.
RegisterDatasetV2	Registers a dataset with the tf.data service.
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.
ResourceApplyAdamWithAmsgrad	Update '*var' according to the Adam algorithm.
ResourceApplyKerasMomentum	Update '*var' according to the momentum scheme.
ResourceConditionalAccumulator	A conditional accumulator for aggregating gradients.
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`.
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.
ResourceScatterNdMax
ResourceScatterNdMin
ResourceScatterNdSub	Applies sparse subtraction to individual values or slices in a Variable.
ResourceScatterNdUpdate	Applies sparse `updates` to individual values or slices within a given variable according to `indices`.
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.
ResourceSparseApplyKerasMomentum	Update relevant entries in 'var' and 'accum' according to the momentum scheme.
ResourceStridedSliceAssign	Assign `value` to the sliced l-value reference of `ref`.
RetrieveAllTPUEmbeddingParameters	An op that retrieves optimization parameters from embedding to host memory.
RetrieveTPUEmbeddingADAMParameters	Retrieve ADAM embedding parameters.
RetrieveTPUEmbeddingAdadeltaParameters	Retrieve Adadelta embedding parameters.
RetrieveTPUEmbeddingAdagradMomentumParameters	Retrieve Adagrad Momentum embedding parameters.
RetrieveTPUEmbeddingAdagradParameters	Retrieve Adagrad embedding parameters.
RetrieveTPUEmbeddingCenteredRMSPropParameters	Retrieve centered RMSProp embedding parameters.
RetrieveTPUEmbeddingFTRLParameters	Retrieve FTRL embedding parameters.
RetrieveTPUEmbeddingFrequencyEstimatorParameters	Retrieve frequency estimator embedding parameters.
RetrieveTPUEmbeddingMDLAdagradLightParameters	Retrieve MDL Adagrad Light embedding parameters.
RetrieveTPUEmbeddingMomentumParameters	Retrieve Momentum embedding parameters.
RetrieveTPUEmbeddingProximalAdagradParameters	Retrieve proximal Adagrad embedding parameters.
RetrieveTPUEmbeddingProximalYogiParameters
RetrieveTPUEmbeddingRMSPropParameters	Retrieve RMSProp embedding parameters.
RetrieveTPUEmbeddingStochasticGradientDescentParameters	Retrieve SGD embedding parameters.
Reverse <T>	Reverses specific dimensions of a tensor.
ReverseSequence <T>	Reverses variable length slices.
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>
RiscCos <T extends Number>
RiscDiv <T extends Number>
RiscDot <T extends Number>
RiscExp <T extends Number>
RiscFft <T>
RiscFloor <T extends Number>
RiscGather <T>
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>
RiscPow <T extends Number>
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>
RiscSub <T extends Number>
RiscTranspose <T>
RiscTriangularSolve <T extends Number>
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
ScaleAndTranslateGrad <T extends Number>
ScatterAdd <T>	Adds sparse updates to a variable reference.
ScatterDiv <T>	Divides a variable reference by sparse updates.
ScatterMax <T extends Number>	Reduces sparse updates into a variable reference using the `max` operation.
ScatterMin <T extends Number>	Reduces sparse updates into a variable reference using the `min` operation.
ScatterMul <T>	Multiplies sparse updates into a variable reference.
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.
ScatterNdMax <T>	Computes element-wise maximum.
ScatterNdMin <T>	Computes element-wise minimum.
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.
ScatterNdUpdate <T>	Applies sparse `updates` to individual values or slices within a given variable according to `indices`.
ScatterSub <T>	Subtracts sparse updates to a variable reference.
ScatterUpdate <T>	Applies sparse updates to a variable reference.
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.
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`.
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.
ShuffleAndRepeatDatasetV2
ShuffleDatasetV2
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.
SleepDataset
Slice <T>	Return a slice from 'input'.
SlidingWindowDataset	Creates a dataset that passes a sliding window over `input_dataset`.
Snapshot <T>	Returns a copy of the input tensor.
SnapshotDataset	Creates a dataset that will write to / read from a snapshot.
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.
SparseBincount <U extends Number>	Counts the number of occurrences of each value in an integer array.
SparseCountSparseOutput <U extends Number>	Performs sparse-output bin counting for a sparse tensor input.
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.
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`.
SparseMatrixTranspose	Transposes the inner (matrix) dimensions of a CSRSparseMatrix.
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.
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.
Stack <T>	Packs a list of `N` rank-`R` tensors into one rank-`(R+1)` tensor.
Stage	Stage values similar to a lightweight Enqueue.
StageClear	Op removes all elements in the underlying container.
StagePeek	Op peeks at the values at the specified index.
StageSize	Op returns the number of elements in the underlying container.
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>	Produce números aleatorios pseudoaleatorios deterministas a partir de una distribución gamma.
StatelessRandomGammaV3 <U extends Number>	Produce números aleatorios pseudoaleatorios deterministas a partir de una distribución gamma.
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.
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
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`.
StridedSliceAssign <T>	Assign `value` to the sliced l-value reference of `ref`.
StridedSliceGrad <U>	Returns the gradient of `StridedSlice`.
StringLower	Converts all uppercase characters into their respective lowercase replacements.
StringNGrams <T extends Number>	Creates ngrams from ragged string data.
StringUpper	Converts all lowercase characters into their respective uppercase replacements.
Sum <T>	Computes the sum of elements across dimensions of a tensor.
SwitchCond <T>	Forwards `data` to the output port determined by `pred`.
SyncDevice	Synchronizes the device this op is run on.
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.
TPUOrdinalSelector	A TPU core selector Op.
TPUPartitionedInput <T>	An op that groups a list of partitioned inputs together.
TPUPartitionedInputV2 <T>	An op that groups a list of partitioned inputs together.
TPUPartitionedOutput <T>	An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned outputs outside the XLA computation.
TPUPartitionedOutputV2 <T>	An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned outputs outside the XLA computation.
TPUReplicateMetadata	Metadata indicating how the TPU computation should be replicated.
TPUReplicatedInput <T>	Connects N inputs to an N-way replicated TPU computation.
TPUReplicatedOutput <T>	Connects N outputs from an N-way replicated TPU computation.
TPUReshardVariables	Op that reshards on-device TPU variables to specified state.
TPURoundRobin	Round-robin load balancing on TPU cores.
TemporaryVariable <T>	Returns a tensor that may be mutated, but only persists within a single step.
TensorArray	An array of Tensors of given size.
TensorArrayClose	Delete the TensorArray from its resource container.
TensorArrayConcat <T>	Concat the elements from the TensorArray into value `value`.
TensorArrayGather <T>	Gather specific elements from the TensorArray into output `value`.
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>
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.
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
TensorListSplit	Splits a tensor into a list.
TensorListStack <T>	Stacks all tensors in the list.
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`.
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`.
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.
TpuHandleToProtoKey	Converts XRT's uid handles to TensorFlow-friendly input format.
TridiagonalMatMul <T>	Calculate product with tridiagonal matrix.
TridiagonalSolve <T>	Solves tridiagonal systems of equations.
Unbatch <T>	Reverses the operation of Batch for a single output Tensor.
UnbatchGrad <T>	Gradient of Unbatch.
UncompressElement	Uncompresses a compressed dataset element.
UnicodeDecode <T extends Number>	Decodes each string in `input` into a sequence of Unicode code points.
UnicodeEncode	Encode a tensor of ints into unicode strings.
UniformDequantize <U extends Number>	Perform dequantization on the quantized Tensor `input`.
UniformQuantize <U>	Perform quantization on Tensor `input`.
UniformQuantizedAdd <T>	Perform quantized add of quantized Tensor `lhs` and quantized Tensor `rhs` to make quantized `output`.
UniformQuantizedClipByValue <T>	Perform clip by value on the quantized Tensor `operand`.
UniformQuantizedConvolution <U>	Perform quantized convolution of quantized Tensor `lhs` and quantized Tensor `rhs`.
UniformQuantizedConvolutionHybrid <V extends Number>	Perform hybrid quantized convolution of float Tensor `lhs` and quantized Tensor `rhs`.
UniformQuantizedDot <U>	Perform quantized dot of quantized Tensor `lhs` and quantized Tensor `rhs` to make quantized `output`.
UniformQuantizedDotHybrid <V extends Number>	Perform hybrid quantized dot of float Tensor `lhs` and quantized Tensor `rhs`.
UniformRequantize <U>	Given quantized tensor `input`, requantize it with new quantization parameters.
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`.
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
Unstack <T>	Unpacks a given dimension of a rank-`R` tensor into `num` rank-`(R-1)` tensors.
Unstage	Op is similar to a lightweight Dequeue.
UnwrapDatasetVariant
UpperBound <U extends Number>	Applies upper_bound(sorted_search_values, values) along each row.
VarHandleOp	Creates a handle to a Variable resource.
VarIsInitializedOp	Checks whether a resource handle-based variable has been initialized.
Variable <T>	Holds state in the form of a tensor that persists across steps.
VariableShape <T extends Number>	Returns the shape of the variable pointed to by `resource`.
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.
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.
XlaSendTPUEmbeddingGradients	An op that performs gradient updates of embedding tables.
XlaSendToHost	An op to send a tensor to the host.
XlaSplitND <T>	Splits input tensor across all dimensions.
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.

A marker interface for all operation wrappers.

Operation wrappers provide strongly typed interfaces for building and execution operations without the use of literals and indexes, as required in the core classes.

This interface allows keeping references to any operation wrapper using a common type.

// All values returned by an Ops call can be referred as a Op
 Op split = ops.array().split(...);
 Op shape = ops.array().shape(...);

 // All operations could be added to an Op collection
 Collection&lt;Op&gt; allOps = Arrays.asList(split, shape);

public interface Op

Known Indirect Subclasses

Abort , All , AllToAll <T>, AnonymousHashTable , AnonymousIteratorV2 , AnonymousIteratorV3 , AnonymousMemoryCache , AnonymousMultiDeviceIterator , AnonymousMultiDeviceIteratorV3 , AnonymousMutableDenseHashTable , AnonymousMutableHashTable , AnonymousMutableHashTableOfTensors , AnonymousRandomSeedGenerator , AnonymousSeedGenerator , Any , and 735 others.

Abort	Raise a exception to abort the process when called.
All	Computes the "logical and" of elements across dimensions of a tensor.
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.
AnonymousMutableHashTable	Creates an empty anonymous mutable hash table.
AnonymousMutableHashTableOfTensors	Creates an empty anonymous mutable hash table of vector values.
AnonymousRandomSeedGenerator
AnonymousSeedGenerator
Any	Computes the "logical or" of elements across dimensions of a tensor.
ApplyAdagradV2 <T>	Update '*var' according to the adagrad scheme.
ApproxTopK <T extends Number>	Returns min/max k values and their indices of the input operand in an approximate manner.
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.
Assign <T>	Update 'ref' by assigning 'value' to it.
AssignAdd <T>	Update 'ref' by adding 'value' to it.
AssignAddVariableOp	Adds a value to the current value of a variable.
AssignSub <T>	Update 'ref' by subtracting 'value' from it.
AssignSubVariableOp	Subtracts a value from the current value of a variable.
AssignVariableOp	Assigns a new value to a variable.
AssignVariableXlaConcatND	Concats input tensor across all dimensions.
AutoShardDataset	Creates a dataset that shards the input dataset.
BandedTriangularSolve <T>
Barrier	Defines a barrier that persists across different graph executions.
BarrierClose	Closes the given barrier.
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.
Batch	Batches all input tensors nondeterministically.
BatchMatMulV2 <T>	Multiplies slices of two tensors in batches.
BatchMatMulV3 <V>	Multiplies slices of two tensors in batches.
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 un tensor de un tipo a otro sin copiar datos.
BlockLSTM <T extends Number>	Computes the LSTM cell forward propagation for all the time steps.
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.
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.
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.
BoostedTreesDeserializeEnsemble	Deserializes a serialized tree ensemble config and replaces current tree ensemble.
BoostedTreesEnsembleResourceHandleOp	Creates a handle to a BoostedTreesEnsembleResource
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.
BoostedTreesQuantileStreamResourceGetBucketBoundaries	Generate the bucket boundaries for each feature based on accumulated summaries.
BoostedTreesQuantileStreamResourceHandleOp	Creates a handle to a BoostedTreesQuantileStreamResource.
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.
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.
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'.
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.
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.
CollectiveAllToAllV3 <T extends Number>	Mutually exchanges multiple tensors of identical type and shape.
CollectiveAssignGroupV2	Assign group keys based on group assignment.
CollectiveBcastRecvV2 <U>	Receives a tensor value broadcast from another device.
CollectiveBcastSendV2 <T>	Broadcasts a tensor value to one or more other devices.
CollectiveGather <T extends Number>	Mutually accumulates multiple tensors of identical type and shape.
CollectiveGatherV2 <T extends Number>	Mutually accumulates multiple tensors of identical type and shape.
CollectiveInitializeCommunicator	Initializes a group for collective operations.
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.
CollectiveReduceV2 <T extends Number>	Mutually reduces multiple tensors of identical type and shape.
CollectiveReduceV3 <T extends Number>	Mutually reduces multiple tensors of identical type and shape.
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.
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.
ConfigureDistributedTPU	Sets up the centralized structures for a distributed TPU system.
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.
Conv2DBackpropInputV2 <T extends Number>	Computes the gradients of convolution with respect to the input.
Copy <T>	Copy a tensor from CPU-to-CPU or GPU-to-GPU.
CopyHost <T>	Copy a tensor to host.
CopyToMesh <T>
CopyToMeshGrad <T>
CountUpTo <T extends Number>	Increments 'ref' until it reaches 'limit'.
CrossReplicaSum <T extends Number>	An Op to sum inputs across replicated TPU instances.
CudnnRNNBackpropV3 <T extends Number>	Backprop step of CudnnRNNV3.
CudnnRNNCanonicalToParamsV2 <T extends Number>	Converts CudnnRNN params from canonical form to usable form.
CudnnRNNParamsToCanonicalV2 <T extends Number>	Retrieves CudnnRNN params in canonical form.
CudnnRNNV3 <T extends Number>	A RNN backed by cuDNN.
CumulativeLogsumexp <T extends Number>	Compute the cumulative product of the tensor `x` along `axis`.
DTensorRestoreV2
DTensorSetGlobalTPUArray	An op that informs a host of the global ids of all the of TPUs in the system.
DataServiceDataset	Creates a dataset that reads data from the tf.data service.
DataServiceDatasetV2	Creates a dataset that reads data from the tf.data service.
DatasetCardinality	Returns the cardinality of `input_dataset`.
DatasetFromGraph	Creates a dataset from the given `graph_def`.
DatasetToGraphV2	Returns a serialized GraphDef representing `input_dataset`.
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.
DebugIdentityV2 <T>	Debug Identity V2 Op.
DebugNanCount	Debug NaN Value Counter Op.
DebugNumericSummary	Debug Numeric Summary Op.
DebugNumericSummaryV2 <U extends Number>	Debug Numeric Summary V2 Op.
DecodeImage <T extends Number>	Function for decode_bmp, decode_gif, decode_jpeg, and decode_png.
DecodePaddedRaw <T extends Number>	Reinterpret the bytes of a string as a vector of numbers.
DecodeProto	The op extracts fields from a serialized protocol buffers message into tensors.
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.
DenseCountSparseOutput <U extends Number>	Performs sparse-output bin counting for a tf.tensor input.
DenseToCSRSparseMatrix	Converts a dense tensor to a (possibly batched) CSRSparseMatrix.
DestroyResourceOp	Deletes the resource specified by the handle.
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.
DisableCopyOnRead	Turns off the copy-on-read mode.
DistributedSave
DrawBoundingBoxesV2 <T extends Number>	Draw bounding boxes on a batch of images.
DummyIterationCounter
DummyMemoryCache
DummySeedGenerator
DynamicEnqueueTPUEmbeddingArbitraryTensorBatch	Eases the porting of code that uses tf.nn.embedding_lookup_sparse().
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.
Eig <U>	Computes the eigen decomposition of one or more square matrices.
Einsum <T>	Tensor contraction according to Einstein summation convention.
Empty <T>	Creates a tensor with the given shape.
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.
EnqueueTPUEmbeddingArbitraryTensorBatch	Eases the porting of code that uses tf.nn.embedding_lookup_sparse().
EnqueueTPUEmbeddingBatch	An op that enqueues a list of input batch tensors to TPUEmbedding.
EnqueueTPUEmbeddingIntegerBatch	An op that enqueues a list of input batch tensors to TPUEmbedding.
EnqueueTPUEmbeddingRaggedTensorBatch	Eases the porting of code that uses tf.nn.embedding_lookup().
EnqueueTPUEmbeddingSparseBatch	An op that enqueues TPUEmbedding input indices from a SparseTensor.
EnqueueTPUEmbeddingSparseTensorBatch	Eases the porting of code that uses tf.nn.embedding_lookup_sparse().
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.
Erfinv <T extends Number>
EuclideanNorm <T>	Computes the euclidean norm of elements across dimensions of a tensor.
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.
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.
ExperimentalPrivateThreadPoolDataset	Creates a dataset that uses a custom thread pool to compute `input_dataset`.
ExperimentalRandomDataset	Crea un conjunto de datos que devuelve números pseudoaleatorios.
ExperimentalRebatchDataset	Creates a dataset that changes the batch size.
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.
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.
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`.
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.
FusedBatchNormV3 <T extends Number, U extends Number>	Batch normalization.
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.
Gather <T>	Gather slices from `params` axis `axis` according to `indices`.
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`.
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 `Options.dx()` values are set, they are as the initial symbolic partial derivatives of some loss function `L` wrt
GuaranteeConst <T>	Gives a guarantee to the TF runtime that the input tensor is a constant.
HashTable	Creates a non-initialized hash table.
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.
ImageProjectiveTransformV2 <T extends Number>	Applies the given transform to each of the images.
ImageProjectiveTransformV3 <T extends Number>	Applies the given transform to each of the images.
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.
InfeedEnqueuePrelinearizedBuffer	An op which enqueues prelinearized buffer into TPU infeed.
InfeedEnqueueTuple	Feeds multiple Tensor values into the computation as an XLA tuple.
InitializeTable	Table initializer that takes two tensors for keys and values respectively.
InitializeTableFromDataset
InitializeTableFromTextFile	Initializes a table from a text file.
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.
IsTPUEmbeddingInitialized	Whether TPU Embedding is initialized in a distributed TPU system.
IsVariableInitialized	Checks whether a tensor has been initialized.
IsotonicRegression <U extends Number>	Solves a batch of isotonic regression problems.
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.
LMDBDataset	Creates a dataset that emits the key-value pairs in one or more LMDB files.
LSTMBlockCell <T extends Number>	Computes the LSTM cell forward propagation for 1 time step.
LSTMBlockCellGrad <T extends Number>	Computes the LSTM cell backward propagation for 1 timestep.
LinSpace <T extends Number>	Generates values in an interval.
ListDataset	Creates a dataset that emits each of `tensors` once.
LoadAllTPUEmbeddingParameters	An op that loads optimization parameters into embedding memory.
LoadTPUEmbeddingADAMParameters	Load ADAM embedding parameters.
LoadTPUEmbeddingAdadeltaParameters	Load Adadelta embedding parameters.
LoadTPUEmbeddingAdagradMomentumParameters	Load Adagrad Momentum embedding parameters.
LoadTPUEmbeddingAdagradParameters	Load Adagrad embedding parameters.
LoadTPUEmbeddingCenteredRMSPropParameters	Load centered RMSProp embedding parameters.
LoadTPUEmbeddingFTRLParameters	Load FTRL embedding parameters.
LoadTPUEmbeddingFrequencyEstimatorParameters	Load frequency estimator embedding parameters.
LoadTPUEmbeddingMDLAdagradLightParameters	Load MDL Adagrad Light embedding parameters.
LoadTPUEmbeddingMomentumParameters	Load Momentum embedding parameters.
LoadTPUEmbeddingProximalAdagradParameters	Load proximal Adagrad embedding parameters.
LoadTPUEmbeddingProximalYogiParameters
LoadTPUEmbeddingRMSPropParameters	Load RMSProp embedding parameters.
LoadTPUEmbeddingStochasticGradientDescentParameters	Load SGD embedding parameters.
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.
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.
MapIncompleteSize	Op returns the number of incomplete elements in the underlying container.
MapPeek	Op peeks at the values at the specified key.
MapSize	Op returns the number of elements in the underlying container.
MapStage	Stage (key, values) in the underlying container which behaves like a hashtable.
MapUnstage	Op removes and returns the values associated with the key from the underlying container.
MapUnstageNoKey	Op removes and returns a random (key, value) from the underlying container.
MatrixDiagPartV2 <T>	Returns the batched diagonal part of a batched tensor.
MatrixDiagPartV3 <T>	Returns the batched diagonal part of a batched tensor.
MatrixDiagV2 <T>	Returns a batched diagonal tensor with given batched diagonal values.
MatrixDiagV3 <T>	Returns a batched diagonal tensor with given batched diagonal values.
MatrixSetDiagV2 <T>	Returns a batched matrix tensor with new batched diagonal values.
MatrixSetDiagV3 <T>	Returns a batched matrix tensor with new batched diagonal values.
Max <T>	Computes the maximum of elements across dimensions of a tensor.
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.
Min <T>	Computes the minimum of elements across dimensions of a tensor.
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.
MutableHashTable	Creates an empty hash table.
MutableHashTableOfTensors	Creates an empty hash table.
Mutex	Creates a Mutex resource that can be locked by `MutexLock`.
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.
NoOp	Does nothing.
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.
NonSerializableDataset
OneHot <U>	Returns a one-hot tensor.
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`.
OptionsDataset	Creates a dataset by attaching tf.data.Options to `input_dataset`.
OrderedMapClear	Op removes all elements in the underlying container.
OrderedMapIncompleteSize	Op returns the number of incomplete elements in the underlying container.
OrderedMapPeek	Op peeks at the values at the specified key.
OrderedMapSize	Op returns the number of elements in the underlying container.
OrderedMapStage	Stage (key, values) in the underlying container which behaves like a ordered associative container.
OrderedMapUnstage	Op removes and returns the values associated with the key from the underlying container.
OrderedMapUnstageNoKey	Op removes and returns the (key, value) element with the smallest key from the underlying container.
OutfeedDequeue <T>	Retrieves a single tensor from the computation outfeed.
OutfeedDequeueTuple	Retrieve multiple values from the computation outfeed.
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
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.
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.
Placeholder <T>	A placeholder op for a value that will be fed into the computation.
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.
PrelinearizeTuple	An op which linearizes multiple Tensor values to an opaque variant tensor.
PrimitiveOp	A base class for `Op` implementations that are backed by a single `Operation` .
Print	Prints a string scalar.
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.
QuantizeAndDequantizeV4 <T extends Number>	Quantizes then dequantizes a tensor.
QuantizeAndDequantizeV4Grad <T extends Number>	Returns the gradient of `QuantizeAndDequantizeV4`.
QuantizedConcat <T>	Concatenates quantized tensors along one dimension.
QuantizedConcatV2 <T>
QuantizedConv2DAndRelu <V>
QuantizedConv2DAndReluAndRequantize <V>
QuantizedConv2DAndRequantize <V>
QuantizedConv2DPerChannel <V>	Computes QuantizedConv2D per channel.
QuantizedConv2DWithBias <V>
QuantizedConv2DWithBiasAndRelu <V>
QuantizedConv2DWithBiasAndReluAndRequantize <W>
QuantizedConv2DWithBiasAndRequantize <W>
QuantizedConv2DWithBiasSignedSumAndReluAndRequantize <X>
QuantizedConv2DWithBiasSumAndRelu <V>
QuantizedConv2DWithBiasSumAndReluAndRequantize <X>
QuantizedDepthwiseConv2D <V>	Computes quantized depthwise Conv2D.
QuantizedDepthwiseConv2DWithBias <V>	Computes quantized depthwise Conv2D with Bias.
QuantizedDepthwiseConv2DWithBiasAndRelu <V>	Computes quantized depthwise Conv2D with Bias and Relu.
QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize <W>	Computes quantized depthwise Conv2D with Bias, Relu and Requantize.
QuantizedMatMulWithBias <W>	Performs a quantized matrix multiplication of `a` by the matrix `b` with bias add.
QuantizedMatMulWithBiasAndDequantize <W extends Number>
QuantizedMatMulWithBiasAndRelu <V>	Perform a quantized matrix multiplication of `a` by the matrix `b` with bias add and relu fusion.
QuantizedMatMulWithBiasAndReluAndRequantize <W>	Perform a quantized matrix multiplication of `a` by the matrix `b` with bias add and relu and requantize fusion.
QuantizedMatMulWithBiasAndRequantize <W>
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.
RaggedCountSparseOutput <U extends Number>	Performs sparse-output bin counting for a ragged tensor input.
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	Crea un conjunto de datos que devuelve números pseudoaleatorios.
RandomIndexShuffle <T extends Number>	Outputs the position of `value` in a permutation of [0, ..., max_index].
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.
RebatchDataset	Creates a dataset that changes the batch size.
RebatchDatasetV2	Creates a dataset that changes the batch size.
Recv <T>	Receives the named tensor from send_device on recv_device.
RecvTPUEmbeddingActivations	An op that receives embedding activations on the TPU.
ReduceAll	Computes the "logical and" of elements across dimensions of a tensor.
ReduceAny	Computes the "logical or" of elements across dimensions of a tensor.
ReduceMax <T>	Computes the maximum of elements across dimensions of a tensor.
ReduceMin <T>	Computes the minimum of elements across dimensions of a tensor.
ReduceProd <T>	Computes the product of elements across dimensions of a tensor.
ReduceSum <T>	Computes the sum of elements across dimensions of a tensor.
RefEnter <T>	Creates or finds a child frame, and makes `data` available to the child frame.
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.
RegisterDatasetV2	Registers a dataset with the tf.data service.
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.
ResourceApplyAdamWithAmsgrad	Update '*var' according to the Adam algorithm.
ResourceApplyKerasMomentum	Update '*var' according to the momentum scheme.
ResourceConditionalAccumulator	A conditional accumulator for aggregating gradients.
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`.
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.
ResourceScatterNdMax
ResourceScatterNdMin
ResourceScatterNdSub	Applies sparse subtraction to individual values or slices in a Variable.
ResourceScatterNdUpdate	Applies sparse `updates` to individual values or slices within a given variable according to `indices`.
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.
ResourceSparseApplyKerasMomentum	Update relevant entries in 'var' and 'accum' according to the momentum scheme.
ResourceStridedSliceAssign	Assign `value` to the sliced l-value reference of `ref`.
RetrieveAllTPUEmbeddingParameters	An op that retrieves optimization parameters from embedding to host memory.
RetrieveTPUEmbeddingADAMParameters	Retrieve ADAM embedding parameters.
RetrieveTPUEmbeddingAdadeltaParameters	Retrieve Adadelta embedding parameters.
RetrieveTPUEmbeddingAdagradMomentumParameters	Retrieve Adagrad Momentum embedding parameters.
RetrieveTPUEmbeddingAdagradParameters	Retrieve Adagrad embedding parameters.
RetrieveTPUEmbeddingCenteredRMSPropParameters	Retrieve centered RMSProp embedding parameters.
RetrieveTPUEmbeddingFTRLParameters	Retrieve FTRL embedding parameters.
RetrieveTPUEmbeddingFrequencyEstimatorParameters	Retrieve frequency estimator embedding parameters.
RetrieveTPUEmbeddingMDLAdagradLightParameters	Retrieve MDL Adagrad Light embedding parameters.
RetrieveTPUEmbeddingMomentumParameters	Retrieve Momentum embedding parameters.
RetrieveTPUEmbeddingProximalAdagradParameters	Retrieve proximal Adagrad embedding parameters.
RetrieveTPUEmbeddingProximalYogiParameters
RetrieveTPUEmbeddingRMSPropParameters	Retrieve RMSProp embedding parameters.
RetrieveTPUEmbeddingStochasticGradientDescentParameters	Retrieve SGD embedding parameters.
Reverse <T>	Reverses specific dimensions of a tensor.
ReverseSequence <T>	Reverses variable length slices.
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>
RiscCos <T extends Number>
RiscDiv <T extends Number>
RiscDot <T extends Number>
RiscExp <T extends Number>
RiscFft <T>
RiscFloor <T extends Number>
RiscGather <T>
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>
RiscPow <T extends Number>
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>
RiscSub <T extends Number>
RiscTranspose <T>
RiscTriangularSolve <T extends Number>
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
ScaleAndTranslateGrad <T extends Number>
ScatterAdd <T>	Adds sparse updates to a variable reference.
ScatterDiv <T>	Divides a variable reference by sparse updates.
ScatterMax <T extends Number>	Reduces sparse updates into a variable reference using the `max` operation.
ScatterMin <T extends Number>	Reduces sparse updates into a variable reference using the `min` operation.
ScatterMul <T>	Multiplies sparse updates into a variable reference.
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.
ScatterNdMax <T>	Computes element-wise maximum.
ScatterNdMin <T>	Computes element-wise minimum.
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.
ScatterNdUpdate <T>	Applies sparse `updates` to individual values or slices within a given variable according to `indices`.
ScatterSub <T>	Subtracts sparse updates to a variable reference.
ScatterUpdate <T>	Applies sparse updates to a variable reference.
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.
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`.
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.
ShuffleAndRepeatDatasetV2
ShuffleDatasetV2
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.
SleepDataset
Slice <T>	Return a slice from 'input'.
SlidingWindowDataset	Creates a dataset that passes a sliding window over `input_dataset`.
Snapshot <T>	Returns a copy of the input tensor.
SnapshotDataset	Creates a dataset that will write to / read from a snapshot.
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.
SparseBincount <U extends Number>	Counts the number of occurrences of each value in an integer array.
SparseCountSparseOutput <U extends Number>	Performs sparse-output bin counting for a sparse tensor input.
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.
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`.
SparseMatrixTranspose	Transposes the inner (matrix) dimensions of a CSRSparseMatrix.
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.
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.
Stack <T>	Packs a list of `N` rank-`R` tensors into one rank-`(R+1)` tensor.
Stage	Stage values similar to a lightweight Enqueue.
StageClear	Op removes all elements in the underlying container.
StagePeek	Op peeks at the values at the specified index.
StageSize	Op returns the number of elements in the underlying container.
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>	Produce números aleatorios pseudoaleatorios deterministas a partir de una distribución gamma.
StatelessRandomGammaV3 <U extends Number>	Produce números aleatorios pseudoaleatorios deterministas a partir de una distribución gamma.
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.
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
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`.
StridedSliceAssign <T>	Assign `value` to the sliced l-value reference of `ref`.
StridedSliceGrad <U>	Returns the gradient of `StridedSlice`.
StringLower	Converts all uppercase characters into their respective lowercase replacements.
StringNGrams <T extends Number>	Creates ngrams from ragged string data.
StringUpper	Converts all lowercase characters into their respective uppercase replacements.
Sum <T>	Computes the sum of elements across dimensions of a tensor.
SwitchCond <T>	Forwards `data` to the output port determined by `pred`.
SyncDevice	Synchronizes the device this op is run on.
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.
TPUOrdinalSelector	A TPU core selector Op.
TPUPartitionedInput <T>	An op that groups a list of partitioned inputs together.
TPUPartitionedInputV2 <T>	An op that groups a list of partitioned inputs together.
TPUPartitionedOutput <T>	An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned outputs outside the XLA computation.
TPUPartitionedOutputV2 <T>	An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned outputs outside the XLA computation.
TPUReplicateMetadata	Metadata indicating how the TPU computation should be replicated.
TPUReplicatedInput <T>	Connects N inputs to an N-way replicated TPU computation.
TPUReplicatedOutput <T>	Connects N outputs from an N-way replicated TPU computation.
TPUReshardVariables	Op that reshards on-device TPU variables to specified state.
TPURoundRobin	Round-robin load balancing on TPU cores.
TemporaryVariable <T>	Returns a tensor that may be mutated, but only persists within a single step.
TensorArray	An array of Tensors of given size.
TensorArrayClose	Delete the TensorArray from its resource container.
TensorArrayConcat <T>	Concat the elements from the TensorArray into value `value`.
TensorArrayGather <T>	Gather specific elements from the TensorArray into output `value`.
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>
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.
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
TensorListSplit	Splits a tensor into a list.
TensorListStack <T>	Stacks all tensors in the list.
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`.
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`.
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.
TpuHandleToProtoKey	Converts XRT's uid handles to TensorFlow-friendly input format.
TridiagonalMatMul <T>	Calculate product with tridiagonal matrix.
TridiagonalSolve <T>	Solves tridiagonal systems of equations.
Unbatch <T>	Reverses the operation of Batch for a single output Tensor.
UnbatchGrad <T>	Gradient of Unbatch.
UncompressElement	Uncompresses a compressed dataset element.
UnicodeDecode <T extends Number>	Decodes each string in `input` into a sequence of Unicode code points.
UnicodeEncode	Encode a tensor of ints into unicode strings.
UniformDequantize <U extends Number>	Perform dequantization on the quantized Tensor `input`.
UniformQuantize <U>	Perform quantization on Tensor `input`.
UniformQuantizedAdd <T>	Perform quantized add of quantized Tensor `lhs` and quantized Tensor `rhs` to make quantized `output`.
UniformQuantizedClipByValue <T>	Perform clip by value on the quantized Tensor `operand`.
UniformQuantizedConvolution <U>	Perform quantized convolution of quantized Tensor `lhs` and quantized Tensor `rhs`.
UniformQuantizedConvolutionHybrid <V extends Number>	Perform hybrid quantized convolution of float Tensor `lhs` and quantized Tensor `rhs`.
UniformQuantizedDot <U>	Perform quantized dot of quantized Tensor `lhs` and quantized Tensor `rhs` to make quantized `output`.
UniformQuantizedDotHybrid <V extends Number>	Perform hybrid quantized dot of float Tensor `lhs` and quantized Tensor `rhs`.
UniformRequantize <U>	Given quantized tensor `input`, requantize it with new quantization parameters.
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`.
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
Unstack <T>	Unpacks a given dimension of a rank-`R` tensor into `num` rank-`(R-1)` tensors.
Unstage	Op is similar to a lightweight Dequeue.
UnwrapDatasetVariant
UpperBound <U extends Number>	Applies upper_bound(sorted_search_values, values) along each row.
VarHandleOp	Creates a handle to a Variable resource.
VarIsInitializedOp	Checks whether a resource handle-based variable has been initialized.
Variable <T>	Holds state in the form of a tensor that persists across steps.
VariableShape <T extends Number>	Returns the shape of the variable pointed to by `resource`.
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.
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.
XlaSendTPUEmbeddingGradients	An op that performs gradient updates of embedding tables.
XlaSendToHost	An op to send a tensor to the host.
XlaSplitND <T>	Splits input tensor across all dimensions.
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.

A marker interface for all operation wrappers.

Operation wrappers provide strongly typed interfaces for building and execution operations without the use of literals and indexes, as required in the core classes.

This interface allows keeping references to any operation wrapper using a common type.

// All values returned by an Ops call can be referred as a Op
 Op split = ops.array().split(...);
 Op shape = ops.array().shape(...);

 // All operations could be added to an Op collection
 Collection&lt;Op&gt; allOps = Arrays.asList(split, shape);