A
| Abort | Raise a exception to abort the process when called. |
| Abort.Options | Optional attributes for Abort
|
| Abs<T extends TNumber> | Computes the absolute value of a tensor. |
| AbstractDataBuffer<T> | |
| AbstractDataBufferWindow<B extends DataBuffer<?>> | |
| AbstractDenseNdArray<T, U extends NdArray<T>> | |
| AbstractNdArray<T, U extends NdArray<T>> | |
| AbstractTF_Buffer | |
| AbstractTF_Graph | |
| AbstractTF_ImportGraphDefOptions | |
| AbstractTF_Session | |
| AbstractTF_SessionOptions | |
| AbstractTF_Status | |
| AbstractTF_Tensor | |
| AbstractTFE_Context | |
| AbstractTFE_ContextOptions | |
| AbstractTFE_Op | |
| AbstractTFE_TensorHandle | |
| AccumulateN<T extends TType> | Returns the element-wise sum of a list of tensors. |
| AccumulatorApplyGradient | Applies a gradient to a given accumulator. |
| AccumulatorNumAccumulated | Returns the number of gradients aggregated in the given accumulators. |
| AccumulatorSetGlobalStep | Updates the accumulator with a new value for global_step. |
| AccumulatorTakeGradient<T extends TType> | Extracts the average gradient in the given ConditionalAccumulator. |
| Acos<T extends TType> | Computes acos of x element-wise. |
| Acosh<T extends TType> | Computes inverse hyperbolic cosine of x element-wise. |
| Activation<T extends TNumber> | Abstract base class for Activations
Note: The |
| AdaDelta | Optimizer that implements the Adadelta algorithm. |
| AdaGrad | Optimizer that implements the Adagrad algorithm. |
| AdaGradDA | Optimizer that implements the Adagrad Dual-Averaging algorithm. |
| Adam | Optimizer that implements the Adam algorithm. |
| Adamax | Optimizer that implements the Adamax algorithm. |
| Add<T extends TType> | Returns x + y element-wise. |
| AddManySparseToTensorsMap | Add an `N`-minibatch `SparseTensor` to a `SparseTensorsMap`, return `N` handles. |
| AddManySparseToTensorsMap.Options | Optional attributes for AddManySparseToTensorsMap
|
| AddN<T extends TType> | Add all input tensors element wise. |
| AddSparseToTensorsMap | Add a `SparseTensor` to a `SparseTensorsMap` return its handle. |
| AddSparseToTensorsMap.Options | Optional attributes for AddSparseToTensorsMap
|
| AdjustContrast<T extends TNumber> | Adjust the contrast of one or more images. |
| AdjustHue<T extends TNumber> | Adjust the hue of one or more images. |
| AdjustSaturation<T extends TNumber> | Adjust the saturation of one or more images. |
| All | Computes the "logical and" of elements across dimensions of a tensor. |
| All.Options | Optional attributes for All
|
| AllCandidateSampler | Generates labels for candidate sampling with a learned unigram distribution. |
| AllCandidateSampler.Options | Optional attributes for AllCandidateSampler
|
| AllocationDescription | Protobuf type tensorflow.AllocationDescription
|
| AllocationDescription.Builder | Protobuf type tensorflow.AllocationDescription
|
| AllocationDescriptionOrBuilder | |
| AllocationDescriptionProtos | |
| AllocationRecord | An allocation/de-allocation operation performed by the allocator. |
| AllocationRecord.Builder | An allocation/de-allocation operation performed by the allocator. |
| AllocationRecordOrBuilder | |
| AllocatorMemoryUsed | Protobuf type tensorflow.AllocatorMemoryUsed
|
| AllocatorMemoryUsed.Builder | Protobuf type tensorflow.AllocatorMemoryUsed
|
| AllocatorMemoryUsedOrBuilder | |
| AllReduce<T extends TNumber> | Mutually reduces multiple tensors of identical type and shape. |
| AllReduce.Options | Optional attributes for AllReduce
|
| AllToAll<T extends TType> | An Op to exchange data across TPU replicas. |
| Angle<U extends TNumber> | Returns the argument of a complex number. |
| AnonymousIterator | A container for an iterator resource. |
| AnonymousMemoryCache | |
| AnonymousMultiDeviceIterator | A container for a multi device iterator resource. |
| AnonymousRandomSeedGenerator | |
| AnonymousSeedGenerator | |
| Any | Computes the "logical or" of elements across dimensions of a tensor. |
| Any.Options | Optional attributes for Any
|
| ApiDef | Used to specify and override the default API & behavior in the generated code for client languages, from what you would get from the OpDef alone. |
| ApiDef.Arg | Protobuf type tensorflow.ApiDef.Arg
|
| ApiDef.Arg.Builder | Protobuf type tensorflow.ApiDef.Arg
|
| ApiDef.ArgOrBuilder | |
| ApiDef.Attr | Description of the graph-construction-time configuration of this Op. |
| ApiDef.Attr.Builder | Description of the graph-construction-time configuration of this Op. |
| ApiDef.AttrOrBuilder | |
| ApiDef.Builder | Used to specify and override the default API & behavior in the generated code for client languages, from what you would get from the OpDef alone. |
| ApiDef.Endpoint | If you specify any endpoint, this will replace all of the inherited endpoints. |
| ApiDef.Endpoint.Builder | If you specify any endpoint, this will replace all of the inherited endpoints. |
| ApiDef.EndpointOrBuilder | |
| ApiDef.Visibility | Protobuf enum tensorflow.ApiDef.Visibility
|
| ApiDefOrBuilder | |
| ApiDefProtos | |
| ApiDefs | Protobuf type tensorflow.ApiDefs
|
| ApiDefs.Builder | Protobuf type tensorflow.ApiDefs
|
| ApiDefsOrBuilder | |
| ApplyAdadelta<T extends TType> | Update '*var' according to the adadelta scheme. |
| ApplyAdadelta.Options | Optional attributes for ApplyAdadelta
|
| ApplyAdagrad<T extends TType> | Update '*var' according to the adagrad scheme. |
| ApplyAdagrad.Options | Optional attributes for ApplyAdagrad
|
| ApplyAdagradDa<T extends TType> | Update '*var' according to the proximal adagrad scheme. |
| ApplyAdagradDa.Options | Optional attributes for ApplyAdagradDa
|
| ApplyAdagradV2<T extends TType> | Update '*var' according to the adagrad scheme. |
| ApplyAdagradV2.Options | Optional attributes for ApplyAdagradV2
|
| ApplyAdam<T extends TType> | Update '*var' according to the Adam algorithm. |
| ApplyAdam.Options | Optional attributes for ApplyAdam
|
| ApplyAdaMax<T extends TType> | Update '*var' according to the AdaMax algorithm. |
| ApplyAdaMax.Options | Optional attributes for ApplyAdaMax
|
| ApplyAddSign<T extends TType> | Update '*var' according to the AddSign update. |
| ApplyAddSign.Options | Optional attributes for ApplyAddSign
|
| ApplyCenteredRmsProp<T extends TType> | Update '*var' according to the centered RMSProp algorithm. |
| ApplyCenteredRmsProp.Options | Optional attributes for ApplyCenteredRmsProp
|
| ApplyFtrl<T extends TType> | Update '*var' according to the Ftrl-proximal scheme. |
| ApplyFtrl.Options | Optional attributes for ApplyFtrl
|
| ApplyGradientDescent<T extends TType> | Update '*var' by subtracting 'alpha' * 'delta' from it. |
| ApplyGradientDescent.Options | Optional attributes for ApplyGradientDescent
|
| ApplyMomentum<T extends TType> | Update '*var' according to the momentum scheme. |
| ApplyMomentum.Options | Optional attributes for ApplyMomentum
|
| ApplyPowerSign<T extends TType> | Update '*var' according to the AddSign update. |
| ApplyPowerSign.Options | Optional attributes for ApplyPowerSign
|
| ApplyProximalAdagrad<T extends TType> | Update '*var' and '*accum' according to FOBOS with Adagrad learning rate. |
| ApplyProximalAdagrad.Options | Optional attributes for ApplyProximalAdagrad
|
| ApplyProximalGradientDescent<T extends TType> | Update '*var' as FOBOS algorithm with fixed learning rate. |
| ApplyProximalGradientDescent.Options | Optional attributes for ApplyProximalGradientDescent
|
| ApplyRmsProp<T extends TType> | Update '*var' according to the RMSProp algorithm. |
| ApplyRmsProp.Options | Optional attributes for ApplyRmsProp
|
| ApproximateEqual | Returns the truth value of abs(x-y) < tolerance element-wise. |
| ApproximateEqual.Options | Optional attributes for ApproximateEqual
|
| ArgMax<V extends TNumber> | Returns the index with the largest value across dimensions of a tensor. |
| ArgMin<V extends TNumber> | Returns the index with the smallest value across dimensions of a tensor. |
| Asin<T extends TType> | Computes the trignometric inverse sine of x element-wise. |
| Asinh<T extends TType> | Computes inverse hyperbolic sine of x element-wise. |
| AssertCardinalityDataset | |
| AssertNextDataset | A transformation that asserts which transformations happen next. |
| AssertNextDataset | |
| AssertThat | Asserts that the given condition is true. |
| AssertThat.Options | Optional attributes for AssertThat
|
| AssetFileDef | An asset file def for a single file or a set of sharded files with the same name. |
| AssetFileDef.Builder | An asset file def for a single file or a set of sharded files with the same name. |
| AssetFileDefOrBuilder | |
| Assign<T extends TType> | Update 'ref' by assigning 'value' to it. |
| Assign.Options | Optional attributes for Assign
|
| AssignAdd<T extends TType> | Update 'ref' by adding 'value' to it. |
| AssignAdd.Options | Optional attributes for AssignAdd
|
| AssignAddVariableOp | Adds a value to the current value of a variable. |
| AssignSub<T extends TType> | Update 'ref' by subtracting 'value' from it. |
| AssignSub.Options | Optional attributes for AssignSub
|
| AssignSubVariableOp | Subtracts a value from the current value of a variable. |
| AssignVariableOp | Assigns a new value to a variable. |
| AsString | Converts each entry in the given tensor to strings. |
| AsString.Options | Optional attributes for AsString
|
| Atan<T extends TType> | Computes the trignometric inverse tangent of x element-wise. |
| Atan2<T extends TNumber> | Computes arctangent of `y/x` element-wise, respecting signs of the arguments. |
| Atanh<T extends TType> | Computes inverse hyperbolic tangent of x element-wise. |
| AttrValue | Protocol buffer representing the value for an attr used to configure an Op. |
| AttrValue.Builder | Protocol buffer representing the value for an attr used to configure an Op. |
| AttrValue.ListValue | LINT.IfChangeProtobuf type tensorflow.AttrValue.ListValue
|
| AttrValue.ListValue.Builder | LINT.IfChangeProtobuf type tensorflow.AttrValue.ListValue
|
| AttrValue.ListValueOrBuilder | |
| AttrValue.ValueCase | |
| AttrValueOrBuilder | |
| AttrValueProtos | |
| AudioSpectrogram | Produces a visualization of audio data over time. |
| AudioSpectrogram.Options | Optional attributes for AudioSpectrogram
|
| AudioSummary | Outputs a `Summary` protocol buffer with audio. |
| AudioSummary.Options | Optional attributes for AudioSummary
|
| AutoParallelOptions | Protobuf type tensorflow.AutoParallelOptions
|
| AutoParallelOptions.Builder | Protobuf type tensorflow.AutoParallelOptions
|
| AutoParallelOptionsOrBuilder | |
| AutoShardDataset | Creates a dataset that shards the input dataset. |
| AutoShardDataset | Creates a dataset that shards the input dataset. |
| AutoShardDataset.Options | Optional attributes for AutoShardDataset
|
| AutoShardDataset.Options | Optional attributes for AutoShardDataset
|
| AvailableDeviceInfo | Matches DeviceAttributesProtobuf type tensorflow.AvailableDeviceInfo
|
| AvailableDeviceInfo.Builder | Matches DeviceAttributesProtobuf type tensorflow.AvailableDeviceInfo
|
| AvailableDeviceInfoOrBuilder | |
| AvgPool<T extends TNumber> | Performs average pooling on the input. |
| AvgPool.Options | Optional attributes for AvgPool
|
| AvgPool3d<T extends TNumber> | Performs 3D average pooling on the input. |
| AvgPool3d.Options | Optional attributes for AvgPool3d
|
| AvgPool3dGrad<T extends TNumber> | Computes gradients of average pooling function. |
| AvgPool3dGrad.Options | Optional attributes for AvgPool3dGrad
|
| AvgPoolGrad<T extends TNumber> | Computes gradients of the average pooling function. |
| AvgPoolGrad.Options | Optional attributes for AvgPoolGrad
|
B
| BandedTriangularSolve<T extends TType> | |
| BandedTriangularSolve.Options | Optional attributes for BandedTriangularSolve
|
| BandPart<T extends TType> | Copy a tensor setting everything outside a central band in each innermost matrix to zero. |
| Barrier | Defines a barrier that persists across different graph executions. |
| Barrier.Options | Optional attributes for Barrier
|
| BarrierClose | Closes the given barrier. |
| BarrierClose.Options | Optional attributes for BarrierClose
|
| BarrierIncompleteSize | Computes the number of incomplete elements in the given barrier. |
| BarrierInsertMany | For each key, assigns the respective value to the specified component. |
| BarrierReadySize | Computes the number of complete elements in the given barrier. |
| BarrierTakeMany | Takes the given number of completed elements from a barrier. |
| BarrierTakeMany.Options | Optional attributes for BarrierTakeMany
|
| BaseInitializer<T extends TType> | Abstract base class for all Initializers |
| Batch | Batches all input tensors nondeterministically. |
| Batch.Options | Optional attributes for Batch
|
| BatchCholesky<T extends TNumber> | |
| BatchCholeskyGrad<T extends TNumber> | |
| BatchDataset | |
| BatchDataset | Creates a dataset that batches `batch_size` elements from `input_dataset`. |
| BatchDataset.Options | Optional attributes for BatchDataset
|
| BatchFft | |
| BatchFft2d | |
| BatchFft3d | |
| BatchIfft | |
| BatchIfft2d | |
| BatchIfft3d | |
| BatchMatMul<T extends TType> | Multiplies slices of two tensors in batches. |
| BatchMatMul.Options | Optional attributes for BatchMatMul
|
| BatchMatrixBandPart<T extends TType> | |
| BatchMatrixDeterminant<T extends TType> | |
| BatchMatrixDiag<T extends TType> | |
| BatchMatrixDiagPart<T extends TType> | |
| BatchMatrixInverse<T extends TNumber> | |
| BatchMatrixInverse.Options | Optional attributes for BatchMatrixInverse
|
| BatchMatrixSetDiag<T extends TType> | |
| BatchMatrixSolve<T extends TNumber> | |
| BatchMatrixSolve.Options | Optional attributes for BatchMatrixSolve
|
| BatchMatrixSolveLs<T extends TNumber> | |
| BatchMatrixSolveLs.Options | Optional attributes for BatchMatrixSolveLs
|
| BatchMatrixTriangularSolve<T extends TNumber> | |
| BatchMatrixTriangularSolve.Options | Optional attributes for BatchMatrixTriangularSolve
|
| BatchNormWithGlobalNormalization<T extends TType> | Batch normalization. |
| BatchNormWithGlobalNormalizationGrad<T extends TType> | Gradients for batch normalization. |
| BatchSelfAdjointEig<T extends TNumber> | |
| BatchSelfAdjointEig.Options | Optional attributes for BatchSelfAdjointEig
|
| BatchSvd<T extends TType> | |
| BatchSvd.Options | Optional attributes for BatchSvd
|
| BatchToSpace<T extends TType> | BatchToSpace for 4-D tensors of type T. |
| BatchToSpaceNd<T extends TType> | BatchToSpace for N-D tensors of type T. |
| BenchmarkEntries | Protobuf type tensorflow.BenchmarkEntries
|
| BenchmarkEntries.Builder | Protobuf type tensorflow.BenchmarkEntries
|
| BenchmarkEntriesOrBuilder | |
| BenchmarkEntry | Each unit test or benchmark in a test or benchmark run provides some set of information. |
| BenchmarkEntry.Builder | Each unit test or benchmark in a test or benchmark run provides some set of information. |
| BenchmarkEntryOrBuilder | |
| BesselI0<T extends TNumber> | |
| BesselI0e<T extends TNumber> | |
| BesselI1<T extends TNumber> | |
| BesselI1e<T extends TNumber> | |
| BesselJ0<T extends TNumber> | |
| BesselJ1<T extends TNumber> | |
| BesselK0<T extends TNumber> | |
| BesselK0e<T extends TNumber> | |
| BesselK1<T extends TNumber> | |
| BesselK1e<T extends TNumber> | |
| BesselY0<T extends TNumber> | |
| BesselY1<T extends TNumber> | |
| Betainc<T extends TNumber> | Compute the regularized incomplete beta integral \\(I_x(a, b)\\). |
| BfcMemoryMapProtos | |
| Bfloat16Layout | Data layout that converts 32-bit floats from/to 16-bit, truncating their mantissa to 7 bits but preserving the 8-bit exponent with the same bias. |
| BiasAdd<T extends TType> | Adds `bias` to `value`. |
| BiasAdd.Options | Optional attributes for BiasAdd
|
| BiasAddGrad<T extends TType> | The backward operation for "BiasAdd" on the "bias" tensor. |
| BiasAddGrad.Options | Optional attributes for BiasAddGrad
|
| BinaryCrossentropy | Computes the cross-entropy loss between true labels and predicted labels. |
| BinaryCrossentropy<T extends TNumber> | A Metric that computes the binary cross-entropy loss between true labels and predicted labels. |
| Bincount<T extends TNumber> | Counts the number of occurrences of each value in an integer array. |
| BinSummary | Protobuf type tensorflow.BinSummary
|
| BinSummary.Builder | Protobuf type tensorflow.BinSummary
|
| BinSummaryOrBuilder | |
| Bitcast<U extends TType> | Bitcasts a tensor from one type to another without copying data. |
| BitwiseAnd<T extends TNumber> | Elementwise computes the bitwise AND of `x` and `y`. |
| BitwiseOr<T extends TNumber> | Elementwise computes the bitwise OR of `x` and `y`. |
| BitwiseXor<T extends TNumber> | Elementwise computes the bitwise XOR of `x` and `y`. |
| BlockLSTM<T extends TNumber> | Computes the LSTM cell forward propagation for all the time steps. |
| BlockLSTM.Options | Optional attributes for BlockLSTM
|
| BlockLSTMGrad<T extends TNumber> | Computes the LSTM cell backward propagation for the entire time sequence. |
| BooleanDataBuffer | A DataBuffer of booleans. |
| BooleanDataLayout<S extends DataBuffer<?>> | A DataLayout that converts data stored in a buffer to booleans. |
| BooleanDenseNdArray | |
| BooleanMask | |
| BooleanMask.Options | Optional attributes for BooleanMask
|
| BooleanMaskUpdate | |
| BooleanMaskUpdate.Options | Optional attributes for BooleanMaskUpdate
|
| BooleanNdArray | An NdArray of booleans. |
| BoolLayout | Data layout that converts booleans from/to bytes. |
| BoostedTreesAggregateStats | Aggregates the summary of accumulated stats for the batch. |
| BoostedTreesBucketize | Bucketize each feature based on bucket boundaries. |
| BoostedTreesCalculateBestFeatureSplit | Calculates gains for each feature and returns the best possible split information for the feature. |
| BoostedTreesCalculateBestFeatureSplit.Options | Optional attributes for BoostedTreesCalculateBestFeatureSplit
|
| BoostedTreesCalculateBestFeatureSplitV2 | Calculates gains for each feature and returns the best possible split information for each node. |
| BoostedTreesCalculateBestGainsPerFeature | Calculates gains for each feature and returns the best possible split information for the feature. |
| BoostedTreesCenterBias | Calculates the prior from the training data (the bias) and fills in the first node with the logits' prior. |
| BoostedTreesCreateEnsemble | Creates a tree ensemble model and returns a handle to it. |
| BoostedTreesCreateQuantileStreamResource | Create the Resource for Quantile Streams. |
| BoostedTreesCreateQuantileStreamResource.Options | Optional attributes for BoostedTreesCreateQuantileStreamResource
|
| BoostedTreesDeserializeEnsemble | Deserializes a serialized tree ensemble config and replaces current tree
ensemble. |
| BoostedTreesEnsembleResourceHandleOp | Creates a handle to a BoostedTreesEnsembleResource |
| BoostedTreesEnsembleResourceHandleOp.Options | Optional attributes for BoostedTreesEnsembleResourceHandleOp
|
| BoostedTreesExampleDebugOutputs | Debugging/model interpretability outputs for each example. |
| BoostedTreesFlushQuantileSummaries | Flush the quantile summaries from each quantile stream resource. |
| BoostedTreesGetEnsembleStates | Retrieves the tree ensemble resource stamp token, number of trees and growing statistics. |
| BoostedTreesMakeQuantileSummaries | Makes the summary of quantiles for the batch. |
| BoostedTreesMakeStatsSummary | Makes the summary of accumulated stats for the batch. |
| BoostedTreesPredict | Runs multiple additive regression ensemble predictors on input instances and
computes the logits. |
| BoostedTreesQuantileStreamResourceAddSummaries | Add the quantile summaries to each quantile stream resource. |
| BoostedTreesQuantileStreamResourceDeserialize | Deserialize bucket boundaries and ready flag into current QuantileAccumulator. |
| BoostedTreesQuantileStreamResourceFlush | Flush the summaries for a quantile stream resource. |
| BoostedTreesQuantileStreamResourceFlush.Options | Optional attributes for BoostedTreesQuantileStreamResourceFlush
|
| BoostedTreesQuantileStreamResourceGetBucketBoundaries | Generate the bucket boundaries for each feature based on accumulated summaries. |
| BoostedTreesQuantileStreamResourceHandleOp | Creates a handle to a BoostedTreesQuantileStreamResource. |
| BoostedTreesQuantileStreamResourceHandleOp.Options | Optional attributes for BoostedTreesQuantileStreamResourceHandleOp
|
| BoostedTreesSerializeEnsemble | Serializes the tree ensemble to a proto. |
| BoostedTreesSparseAggregateStats | Aggregates the summary of accumulated stats for the batch. |
| BoostedTreesSparseCalculateBestFeatureSplit | Calculates gains for each feature and returns the best possible split information for the feature. |
| BoostedTreesSparseCalculateBestFeatureSplit.Options | Optional attributes for BoostedTreesSparseCalculateBestFeatureSplit
|
| BoostedTreesTrainingPredict | Runs multiple additive regression ensemble predictors on input instances and
computes the update to cached logits. |
| BoostedTreesUpdateEnsemble | Updates the tree ensemble by either adding a layer to the last tree being grown
or by starting a new tree. |
| BoostedTreesUpdateEnsembleV2 | Updates the tree ensemble by adding a layer to the last tree being grown
or by starting a new tree. |
| BoostedTreesUpdateEnsembleV2.Options | Optional attributes for BoostedTreesUpdateEnsembleV2
|
| BoundedTensorSpecProto | A protobuf to represent tf.BoundedTensorSpec. |
| BoundedTensorSpecProto.Builder | A protobuf to represent tf.BoundedTensorSpec. |
| BoundedTensorSpecProtoOrBuilder | |
| BroadcastDynamicShape<T extends TNumber> | Return the shape of s0 op s1 with broadcast. |
| BroadcastGradientArgs<T extends TNumber> | Return the reduction indices for computing gradients of s0 op s1 with broadcast. |
| BroadcastHelper<T extends TType> | Helper operator for performing XLA-style broadcasts
Broadcasts `lhs` and `rhs` to the same rank, by adding size 1 dimensions to whichever of `lhs` and `rhs` has the lower rank, using XLA's broadcasting rules for binary operators. |
| BroadcastRecv<T extends TType> | Receives a tensor value broadcast from another device. |
| BroadcastRecv.Options | Optional attributes for BroadcastRecv
|
| BroadcastSend<T extends TType> | Broadcasts a tensor value to one or more other devices. |
| BroadcastSend.Options | Optional attributes for BroadcastSend
|
| BroadcastTo<T extends TType> | Broadcast an array for a compatible shape. |
| Bucketize | Bucketizes 'input' based on 'boundaries'. |
| BuildConfiguration | Protobuf type tensorflow.BuildConfiguration
|
| BuildConfiguration.Builder | Protobuf type tensorflow.BuildConfiguration
|
| BuildConfigurationOrBuilder | |
| BundleEntryProto | Describes the metadata related to a checkpointed tensor. |
| BundleEntryProto.Builder | Describes the metadata related to a checkpointed tensor. |
| BundleEntryProtoOrBuilder | |
| BundleHeaderProto | Special header that is associated with a bundle. |
| BundleHeaderProto.Builder | Special header that is associated with a bundle. |
| BundleHeaderProto.Endianness | An enum indicating the endianness of the platform that produced this bundle. |
| BundleHeaderProtoOrBuilder | |
| ByteDataBuffer | A DataBuffer of bytes. |
| ByteDataLayout<S extends DataBuffer<?>> | A DataLayout that converts data stored in a buffer to bytes. |
| ByteDenseNdArray | |
| ByteNdArray | An NdArray of bytes. |
| ByteSequenceProvider<T> | Produces sequence of bytes to be stored in a ByteSequenceTensorBuffer. |
| ByteSequenceTensorBuffer | Buffer for storing string tensor data. |
| BytesList | Containers to hold repeated fundamental values. |
| BytesList.Builder | Containers to hold repeated fundamental values. |
| BytesListOrBuilder | |
| BytesProducedStatsDataset | Records the bytes size of each element of `input_dataset` in a StatsAggregator. |
| BytesProducedStatsDataset | Records the bytes size of each element of `input_dataset` in a StatsAggregator. |
C
| CacheDataset | Creates a dataset that caches elements from `input_dataset`. |
| CacheDatasetV2 | |
| CallableOptions | Defines a subgraph in another `GraphDef` as a set of feed points and nodes to be fetched or executed. |
| CallableOptions.Builder | Defines a subgraph in another `GraphDef` as a set of feed points and nodes to be fetched or executed. |
| CallableOptionsOrBuilder | |
| Cast<U extends TType> | Cast x of type SrcT to y of DstT. |
| Cast.Options | Optional attributes for Cast
|
| CastHelper | A helper class for casting an Operand |
| CategoricalCrossentropy | Computes the crossentropy loss between the labels and predictions. |
| CategoricalCrossentropy<T extends TNumber> | A Metric that computes the categorical cross-entropy loss between true labels and predicted labels. |
| CategoricalHinge | Computes the categorical hinge loss between labels and predictions. |
| CategoricalHinge<T extends TNumber> | A Metric that computes the categorical hinge loss metric between labels and predictions. |
| Ceil<T extends TNumber> | Returns element-wise smallest integer not less than x. |
| CheckNumerics<T extends TNumber> | Checks a tensor for NaN, -Inf and +Inf values. |
| Cholesky<T extends TType> | Computes the Cholesky decomposition of one or more square matrices. |
| CholeskyGrad<T extends TNumber> | Computes the reverse mode backpropagated gradient of the Cholesky algorithm. |
| ChooseFastestDataset | |
| ChooseFastestDataset | |
| ClipByValue<T extends TType> | Clips tensor values to a specified min and max. |
| CloseSummaryWriter | |
| ClusterDef | Defines a TensorFlow cluster as a set of jobs. |
| ClusterDef.Builder | Defines a TensorFlow cluster as a set of jobs. |
| ClusterDefOrBuilder | |
| ClusterDeviceFilters | Defines the device filters for jobs in a cluster. |
| ClusterDeviceFilters.Builder | Defines the device filters for jobs in a cluster. |
| ClusterDeviceFiltersOrBuilder | |
| ClusterOutput<T extends TType> | Operator that connects the output of an XLA computation to other consumer graph nodes. |
| ClusterProtos | |
| Code | The canonical error codes for TensorFlow APIs. |
| CodeLocation | Code location information: A stack trace with host-name information. |
| CodeLocation.Builder | Code location information: A stack trace with host-name information. |
| CodeLocationOrBuilder | |
| CollectionDef | CollectionDef should cover most collections. |
| CollectionDef.AnyList | AnyList is used for collecting Any protos. |
| CollectionDef.AnyList.Builder | AnyList is used for collecting Any protos. |
| CollectionDef.AnyListOrBuilder | |
| CollectionDef.Builder | CollectionDef should cover most collections. |
| CollectionDef.BytesList | BytesList is used for collecting strings and serialized protobufs. |
| CollectionDef.BytesList.Builder | BytesList is used for collecting strings and serialized protobufs. |
| CollectionDef.BytesListOrBuilder | |
| CollectionDef.FloatList | FloatList is used for collecting float values. |
| CollectionDef.FloatList.Builder | FloatList is used for collecting float values. |
| CollectionDef.FloatListOrBuilder | |
| CollectionDef.Int64List | Int64List is used for collecting int, int64 and long values. |
| CollectionDef.Int64List.Builder | Int64List is used for collecting int, int64 and long values. |
| CollectionDef.Int64ListOrBuilder | |
| CollectionDef.KindCase | |
| CollectionDef.NodeList | NodeList is used for collecting nodes in graph. |
| CollectionDef.NodeList.Builder | NodeList is used for collecting nodes in graph. |
| CollectionDef.NodeListOrBuilder | |
| CollectionDefOrBuilder | |
| CollectiveGather<T extends TNumber> | Mutually accumulates multiple tensors of identical type and shape. |
| CollectiveGather.Options | Optional attributes for CollectiveGather
|
| CollectivePermute<T extends TType> | An Op to permute tensors across replicated TPU instances. |
| CombinedNonMaxSuppression | Greedily selects a subset of bounding boxes in descending order of score,
This operation performs non_max_suppression on the inputs per batch, across all classes. |
| CombinedNonMaxSuppression.Options | Optional attributes for CombinedNonMaxSuppression
|
| CommitId | Protobuf type tensorflow.CommitId
|
| CommitId.Builder | Protobuf type tensorflow.CommitId
|
| CommitId.KindCase | |
| CommitIdOrBuilder | |
| CompareAndBitpack | Compare values of `input` to `threshold` and pack resulting bits into a `uint8`. |
| CompilationResult | Returns the result of a TPU compilation. |
| CompileSucceededAssert | Asserts that compilation succeeded. |
| Complex<U extends TType> | Converts two real numbers to a complex number. |
| ComplexAbs<U extends TNumber> | Computes the complex absolute value of a tensor. |
| CompressElement | Compresses a dataset element. |
| Compute_func_Pointer_TF_OpKernelContext | |
| ComputeAccidentalHits | Computes the ids of the positions in sampled_candidates that match true_labels. |
| ComputeAccidentalHits.Options | Optional attributes for ComputeAccidentalHits
|
| ComputeBatchSize | Computes the static batch size of a dataset sans partial batches. |
| Concat<T extends TType> | Concatenates tensors along one dimension. |
| ConcatenateDataset | Creates a dataset that concatenates `input_dataset` with `another_dataset`. |
| ConcreteFunction | A graph that can be invoked as a single function, with an input and output signature. |
| CondContextDef | Protocol buffer representing a CondContext object. |
| CondContextDef.Builder | Protocol buffer representing a CondContext object. |
| CondContextDefOrBuilder | |
| ConditionalAccumulator | A conditional accumulator for aggregating gradients. |
| ConditionalAccumulator.Options | Optional attributes for ConditionalAccumulator
|
| ConfigProto | Session configuration parameters. |
| ConfigProto.Builder | Session configuration parameters. |
| ConfigProto.Experimental | Everything inside Experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat. |
| ConfigProto.Experimental.Builder | Everything inside Experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat. |
| ConfigProto.Experimental.MlirBridgeRollout | An enum that describes the state of the MLIR bridge rollout. |
| ConfigProto.ExperimentalOrBuilder | |
| ConfigProtoOrBuilder | |
| ConfigProtos | |
| ConfigureDistributedTPU | Sets up the centralized structures for a distributed TPU system. |
| ConfigureDistributedTPU.Options | Optional attributes for ConfigureDistributedTPU
|
| ConfigureTPUEmbedding | Sets up TPUEmbedding in a distributed TPU system. |
| Conj<T extends TType> | Returns the complex conjugate of a complex number. |
| ConjugateTranspose<T extends TType> | Shuffle dimensions of x according to a permutation and conjugate the result. |
| Constant<T extends TType> | Initializer that generates tensors with a constant value. |
| Constant<T extends TType> | An operator producing a constant value. |
| Constraint | Base class for Constraints. |
| ConsumeMutexLock | This op consumes a lock created by `MutexLock`. |
| ControlFlowContextDef | Container for any kind of control flow context. |
| ControlFlowContextDef.Builder | Container for any kind of control flow context. |
| ControlFlowContextDef.CtxtCase | |
| ControlFlowContextDefOrBuilder | |
| ControlFlowProtos | |
| ControlTrigger | Does nothing. |
| Conv<T extends TType> | Wraps the XLA ConvGeneralDilated operator, documented at
https://www.tensorflow.org/performance/xla/operation_semantics#conv_convolution . |
| Conv2d<T extends TNumber> | Computes a 2-D convolution given 4-D `input` and `filter` tensors. |
| Conv2d.Options | Optional attributes for Conv2d
|
| Conv2dBackpropFilter<T extends TNumber> | Computes the gradients of convolution with respect to the filter. |
| Conv2dBackpropFilter.Options | Optional attributes for Conv2dBackpropFilter
|
| Conv2dBackpropInput<T extends TNumber> | Computes the gradients of convolution with respect to the input. |
| Conv2dBackpropInput.Options | Optional attributes for Conv2dBackpropInput
|
| Conv3d<T extends TNumber> | Computes a 3-D convolution given 5-D `input` and `filter` tensors. |
| Conv3d.Options | Optional attributes for Conv3d
|
| Conv3dBackpropFilter<T extends TNumber> | Computes the gradients of 3-D convolution with respect to the filter. |
| Conv3dBackpropFilter.Options | Optional attributes for Conv3dBackpropFilter
|
| Conv3dBackpropInput<U extends TNumber> | Computes the gradients of 3-D convolution with respect to the input. |
| Conv3dBackpropInput.Options | Optional attributes for Conv3dBackpropInput
|
| Copy<T extends TType> | Copy a tensor from CPU-to-CPU or GPU-to-GPU. |
| Copy.Options | Optional attributes for Copy
|
| CopyHost<T extends TType> | Copy a tensor to host. |
| CopyHost.Options | Optional attributes for CopyHost
|
| Cos<T extends TType> | Computes cos of x element-wise. |
| Cosh<T extends TType> | Computes hyperbolic cosine of x element-wise. |
| CosineSimilarity | Computes the cosine similarity between labels and predictions. |
| CosineSimilarity<T extends TNumber> | A metric that computes the cosine similarity metric between labels and predictions. |
| CostGraphDef | Protobuf type tensorflow.CostGraphDef
|
| CostGraphDef.AggregatedCost | Total cost of this graph, typically used for balancing decisions. |
| CostGraphDef.AggregatedCost.Builder | Total cost of this graph, typically used for balancing decisions. |
| CostGraphDef.AggregatedCostOrBuilder | |
| CostGraphDef.Builder | Protobuf type tensorflow.CostGraphDef
|
| CostGraphDef.Node | Protobuf type tensorflow.CostGraphDef.Node
|
| CostGraphDef.Node.Builder | Protobuf type tensorflow.CostGraphDef.Node
|
| CostGraphDef.Node.InputInfo | Inputs of this node. |
| CostGraphDef.Node.InputInfo.Builder | Inputs of this node. |
| CostGraphDef.Node.InputInfoOrBuilder | |
| CostGraphDef.Node.OutputInfo | Outputs of this node. |
| CostGraphDef.Node.OutputInfo.Builder | Outputs of this node. |
| CostGraphDef.Node.OutputInfoOrBuilder | |
| CostGraphDef.NodeOrBuilder | |
| CostGraphDefOrBuilder | |
| CostGraphProtos | |
| CountUpTo<T extends TNumber> | Increments 'ref' until it reaches 'limit'. |
| CPUInfo | Protobuf type tensorflow.CPUInfo
|
| CPUInfo.Builder | Protobuf type tensorflow.CPUInfo
|
| CPUInfoOrBuilder | |
| Create_func_TF_OpKernelConstruction | |
| CreateSummaryDbWriter | |
| CreateSummaryFileWriter | |
| CropAndResize | Extracts crops from the input image tensor and resizes them. |
| CropAndResize.Options | Optional attributes for CropAndResize
|
| CropAndResizeGradBoxes | Computes the gradient of the crop_and_resize op wrt the input boxes tensor. |
| CropAndResizeGradBoxes.Options | Optional attributes for CropAndResizeGradBoxes
|
| CropAndResizeGradImage<T extends TNumber> | Computes the gradient of the crop_and_resize op wrt the input image tensor. |
| CropAndResizeGradImage.Options | Optional attributes for CropAndResizeGradImage
|
| Cross<T extends TNumber> | Compute the pairwise cross product. |
| CrossReplicaSum<T extends TNumber> | An Op to sum inputs across replicated TPU instances. |
| CSRSparseMatrixComponents<T extends TType> | Reads out the CSR components at batch `index`. |
| CSRSparseMatrixToDense<T extends TType> | Convert a (possibly batched) CSRSparseMatrix to dense. |
| CSRSparseMatrixToSparseTensor<T extends TType> | Converts a (possibly batched) CSRSparesMatrix to a SparseTensor. |
| CSVDataset | |
| CSVDataset | |
| CSVDatasetV2 | |
| CtcBeamSearchDecoder<T extends TNumber> | Performs beam search decoding on the logits given in input. |
| CtcBeamSearchDecoder.Options | Optional attributes for CtcBeamSearchDecoder
|
| CtcGreedyDecoder<T extends TNumber> | Performs greedy decoding on the logits given in inputs. |
| CtcGreedyDecoder.Options | Optional attributes for CtcGreedyDecoder
|
| CtcLoss<T extends TNumber> | Calculates the CTC Loss (log probability) for each batch entry. |
| CtcLoss.Options | Optional attributes for CtcLoss
|
| CTCLossV2 | Calculates the CTC Loss (log probability) for each batch entry. |
| CTCLossV2.Options | Optional attributes for CTCLossV2
|
| CudnnRNN<T extends TNumber> | A RNN backed by cuDNN. |
| CudnnRNN.Options | Optional attributes for CudnnRNN
|
| CudnnRNNBackprop<T extends TNumber> | Backprop step of CudnnRNNV3. |
| CudnnRNNBackprop.Options | Optional attributes for CudnnRNNBackprop
|
| CudnnRNNCanonicalToParams<T extends TNumber> | Converts CudnnRNN params from canonical form to usable form. |
| CudnnRNNCanonicalToParams.Options | Optional attributes for CudnnRNNCanonicalToParams
|
| CudnnRnnParamsSize<U extends TNumber> | Computes size of weights that can be used by a Cudnn RNN model. |
| CudnnRnnParamsSize.Options | Optional attributes for CudnnRnnParamsSize
|
| CudnnRNNParamsToCanonical<T extends TNumber> | Retrieves CudnnRNN params in canonical form. |
| CudnnRNNParamsToCanonical.Options | Optional attributes for CudnnRNNParamsToCanonical
|
| Cumprod<T extends TType> | Compute the cumulative product of the tensor `x` along `axis`. |
| Cumprod.Options | Optional attributes for Cumprod
|
| Cumsum<T extends TType> | Compute the cumulative sum of the tensor `x` along `axis`. |
| Cumsum.Options | Optional attributes for Cumsum
|
| CumulativeLogsumexp<T extends TNumber> | Compute the cumulative product of the tensor `x` along `axis`. |
| CumulativeLogsumexp.Options | Optional attributes for CumulativeLogsumexp
|
D
| DataBuffer<T> | A container of data of a specific type. |
| DataBufferAdapterFactory | Factory of data buffer adapters. |
| DataBuffers | Helper class for creating DataBuffer instances. |
| DataBufferWindow<B extends DataBuffer<?>> | A mutable container for viewing part of a DataBuffer. |
| DataClass | Protobuf enum tensorflow.DataClass
|
| DataFormatDimMap<T extends TNumber> | Returns the dimension index in the destination data format given the one in
the source data format. |
| DataFormatDimMap.Options | Optional attributes for DataFormatDimMap
|
| DataFormatVecPermute<T extends TNumber> | Permute input tensor from `src_format` to `dst_format`. |
| DataFormatVecPermute.Options | Optional attributes for DataFormatVecPermute
|
| DataLayout<S extends DataBuffer<?>, T> | Converts data stored in a buffer to a given type. |
| DataLayouts | Exposes DataLayout instances of data formats frequently used in linear algebra computation. |
| DataServiceDataset | |
| DataServiceDataset.Options | Optional attributes for DataServiceDataset
|
| Dataset | Represents a potentially large list of independent elements (samples), and allows iteration and transformations to be performed across these elements. |
| DatasetCardinality | Returns the cardinality of `input_dataset`. |
| DatasetCardinality | Returns the cardinality of `input_dataset`. |
| DatasetFromGraph | Creates a dataset from the given `graph_def`. |
| DatasetIterator | Represents the state of an iteration through a tf.data Datset. |
| DatasetOptional | An optional represents the result of a dataset getNext operation that may fail, when the end of the dataset has been reached. |
| DatasetToGraph | Returns a serialized GraphDef representing `input_dataset`. |
| DatasetToGraph.Options | Optional attributes for DatasetToGraph
|
| DatasetToSingleElement | Outputs the single element from the given dataset. |
| DatasetToTfRecord | Writes the given dataset to the given file using the TFRecord format. |
| DatasetToTFRecord | Writes the given dataset to the given file using the TFRecord format. |
| DataStorageVisitor<R> | Visit the backing storage of DataBuffer instances. |
| DataType | (== suppress_warning documentation-presence ==) LINT.IfChangeProtobuf enum tensorflow.DataType
|
| Dawsn<T extends TNumber> | |
| Deallocator_Pointer_long_Pointer | |
| DebugEvent | An Event related to the debugging of a TensorFlow program. |
| DebugEvent.Builder | An Event related to the debugging of a TensorFlow program. |
| DebugEvent.WhatCase | |
| DebugEventOrBuilder | |
| DebugEventProtos | |
| DebuggedDevice | A device on which ops and/or tensors are instrumented by the debugger. |
| DebuggedDevice.Builder | A device on which ops and/or tensors are instrumented by the debugger. |
| DebuggedDeviceOrBuilder | |
| DebuggedGraph | A debugger-instrumented graph. |
| DebuggedGraph.Builder | A debugger-instrumented graph. |
| DebuggedGraphOrBuilder | |
| DebuggedSourceFile | Protobuf type tensorflow.DebuggedSourceFile
|
| DebuggedSourceFile.Builder | Protobuf type tensorflow.DebuggedSourceFile
|
| DebuggedSourceFileOrBuilder | |
| DebuggedSourceFiles | Protobuf type tensorflow.DebuggedSourceFiles
|
| DebuggedSourceFiles.Builder | Protobuf type tensorflow.DebuggedSourceFiles
|
| DebuggedSourceFilesOrBuilder | |
| DebugGradientIdentity<T extends TType> | Identity op for gradient debugging. |
| DebugGradientRefIdentity<T extends TType> | Identity op for gradient debugging. |
| DebugIdentity<T extends TType> | Debug Identity V2 Op. |
| DebugIdentity.Options | Optional attributes for DebugIdentity
|
| DebugMetadata | Metadata about the debugger and the debugged TensorFlow program. |
| DebugMetadata.Builder | Metadata about the debugger and the debugged TensorFlow program. |
| DebugMetadataOrBuilder | |
| DebugNanCount | Debug NaN Value Counter Op. |
| DebugNanCount.Options | Optional attributes for DebugNanCount
|
| DebugNumericsSummary<U extends TNumber> | Debug Numeric Summary V2 Op. |
| DebugNumericsSummary.Options | Optional attributes for DebugNumericsSummary
|
| DebugOptions | Options for initializing DebuggerState in TensorFlow Debugger (tfdbg). |
| DebugOptions.Builder | Options for initializing DebuggerState in TensorFlow Debugger (tfdbg). |
| DebugOptionsOrBuilder | |
| DebugProtos | |
| DebugTensorWatch | Option for watching a node in TensorFlow Debugger (tfdbg). |
| DebugTensorWatch.Builder | Option for watching a node in TensorFlow Debugger (tfdbg). |
| DebugTensorWatchOrBuilder | |
| DecodeAndCropJpeg | Decode and Crop a JPEG-encoded image to a uint8 tensor. |
| DecodeAndCropJpeg.Options | Optional attributes for DecodeAndCropJpeg
|
| DecodeBase64 | Decode web-safe base64-encoded strings. |
| DecodeBmp | Decode the first frame of a BMP-encoded image to a uint8 tensor. |
| DecodeBmp.Options | Optional attributes for DecodeBmp
|
| DecodeCompressed | Decompress strings. |
| DecodeCompressed.Options | Optional attributes for DecodeCompressed
|
| DecodeCsv | Convert CSV records to tensors. |
| DecodeCsv.Options | Optional attributes for DecodeCsv
|
| DecodeGif | Decode the frame(s) of a GIF-encoded image to a uint8 tensor. |
| DecodeImage<T extends TNumber> | Function for decode_bmp, decode_gif, decode_jpeg, and decode_png. |
| DecodeImage.Options | Optional attributes for DecodeImage
|
| DecodeJpeg | Decode a JPEG-encoded image to a uint8 tensor. |
| DecodeJpeg.Options | Optional attributes for DecodeJpeg
|
| DecodeJsonExample | Convert JSON-encoded Example records to binary protocol buffer strings. |
| DecodePaddedRaw<T extends TNumber> | Reinterpret the bytes of a string as a vector of numbers. |
| DecodePaddedRaw.Options | Optional attributes for DecodePaddedRaw
|
| DecodePng<T extends TNumber> | Decode a PNG-encoded image to a uint8 or uint16 tensor. |
| DecodePng.Options | Optional attributes for DecodePng
|
| DecodeProto | The op extracts fields from a serialized protocol buffers message into tensors. |
| DecodeProto.Options | Optional attributes for DecodeProto
|
| DecodeRaw<T extends TType> | Reinterpret the bytes of a string as a vector of numbers. |
| DecodeRaw.Options | Optional attributes for DecodeRaw
|
| DecodeWav | Decode a 16-bit PCM WAV file to a float tensor. |
| DecodeWav.Options | Optional attributes for DecodeWav
|
| DeepCopy<T extends TType> | Makes a copy of `x`. |
| Delete_func_Pointer | |
| 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 TNumber> | Counts the number of occurrences of each value in an integer array. |
| DenseBincount.Options | Optional attributes for DenseBincount
|
| DenseCountSparseOutput<U extends TNumber> | Performs sparse-output bin counting for a tf.tensor input. |
| DenseCountSparseOutput.Options | Optional attributes for DenseCountSparseOutput
|
| DenseNdArray<T> | |
| DenseToCSRSparseMatrix | Converts a dense tensor to a (possibly batched) CSRSparseMatrix. |
| DenseToDenseSetOperation<T extends TType> | Applies set operation along last dimension of 2 `Tensor` inputs. |
| DenseToDenseSetOperation.Options | Optional attributes for DenseToDenseSetOperation
|
| DenseToSparseBatchDataset | Creates a dataset that batches input elements into a SparseTensor. |
| DenseToSparseBatchDataset | Creates a dataset that batches input elements into a SparseTensor. |
| DenseToSparseSetOperation<T extends TType> | Applies set operation along last dimension of `Tensor` and `SparseTensor`. |
| DenseToSparseSetOperation.Options | Optional attributes for DenseToSparseSetOperation
|
| DepthToSpace<T extends TType> | DepthToSpace for tensors of type T. |
| DepthToSpace.Options | Optional attributes for DepthToSpace
|
| DepthwiseConv2dNative<T extends TNumber> | Computes a 2-D depthwise convolution given 4-D `input` and `filter` tensors. |
| DepthwiseConv2dNative.Options | Optional attributes for DepthwiseConv2dNative
|
| DepthwiseConv2dNativeBackpropFilter<T extends TNumber> | Computes the gradients of depthwise convolution with respect to the filter. |
| DepthwiseConv2dNativeBackpropFilter.Options | Optional attributes for DepthwiseConv2dNativeBackpropFilter
|
| DepthwiseConv2dNativeBackpropInput<T extends TNumber> | Computes the gradients of depthwise convolution with respect to the input. |
| DepthwiseConv2dNativeBackpropInput.Options | Optional attributes for DepthwiseConv2dNativeBackpropInput
|
| Dequantize<U extends TNumber> | Dequantize the 'input' tensor into a float or bfloat16 Tensor. |
| Dequantize | Takes the packed uint32 input and unpacks the input to uint8 to do
Dequantization on device. |
| Dequantize.Options | Optional attributes for Dequantize
|
| DeserializeIterator | Converts the given variant tensor to an iterator and stores it in the given resource. |
| DeserializeManySparse<T extends TType> | Deserialize and concatenate `SparseTensors` from a serialized minibatch. |
| DeserializeSparse<U extends TType> | Deserialize `SparseTensor` objects. |
| DestroyResourceOp | Deletes the resource specified by the handle. |
| DestroyResourceOp.Options | Optional attributes for DestroyResourceOp
|
| DestroyTemporaryVariable<T extends TType> | Destroys the temporary variable and returns its final value. |
| Det<T extends TType> | Computes the determinant of one or more square matrices. |
| DeviceAttributes | Protobuf type tensorflow.DeviceAttributes
|
| DeviceAttributes.Builder | Protobuf type tensorflow.DeviceAttributes
|
| DeviceAttributesOrBuilder | |
| DeviceAttributesProtos | |
| DeviceFiltersProtos | |
| DeviceIndex | Return the index of device the op runs. |
| DeviceLocality | Protobuf type tensorflow.DeviceLocality
|
| DeviceLocality.Builder | Protobuf type tensorflow.DeviceLocality
|
| DeviceLocalityOrBuilder | |
| DeviceProperties | Protobuf type tensorflow.DeviceProperties
|
| DeviceProperties.Builder | Protobuf type tensorflow.DeviceProperties
|
| DevicePropertiesOrBuilder | |
| DevicePropertiesProtos | |
| DeviceSpec | Represents a (possibly partial) specification for a TensorFlow device. |
| DeviceSpec.Builder | A Builder class for building DeviceSpec class. |
| DeviceSpec.DeviceType | |
| DeviceStepStats | Protobuf type tensorflow.DeviceStepStats
|
| DeviceStepStats.Builder | Protobuf type tensorflow.DeviceStepStats
|
| DeviceStepStatsOrBuilder | |
| DictValue | Represents a Python dict keyed by `str`. |
| DictValue.Builder | Represents a Python dict keyed by `str`. |
| DictValueOrBuilder | |
| Digamma<T extends TNumber> | Computes Psi, the derivative of Lgamma (the log of the absolute value of
`Gamma(x)`), element-wise. |
| Dilation2d<T extends TNumber> | Computes the grayscale dilation of 4-D `input` and 3-D `filter` tensors. |
| Dilation2dBackpropFilter<T extends TNumber> | Computes the gradient of morphological 2-D dilation with respect to the filter. |
| Dilation2dBackpropInput<T extends TNumber> | Computes the gradient of morphological 2-D dilation with respect to the input. |
| Dimension | |
| DimensionalSpace | |
| DirectedInterleaveDataset | A substitute for `InterleaveDataset` on a fixed list of `N` datasets. |
| DirectedInterleaveDataset | A substitute for `InterleaveDataset` on a fixed list of `N` datasets. |
| Div<T extends TType> | Returns x / y element-wise. |
| DivNoNan<T extends TType> | Returns 0 if the denominator is zero. |
| Dot<T extends TType> | Wraps the XLA DotGeneral operator, documented at
https://www.tensorflow.org/performance/xla/operation_semantics#dotgeneral . |
| DoubleDataBuffer | A DataBuffer of doubles. |
| DoubleDataLayout<S extends DataBuffer<?>> | A DataLayout that converts data stored in a buffer to doubles. |
| DoubleDenseNdArray | |
| DoubleNdArray | An NdArray of doubles. |
| DrawBoundingBoxes<T extends TNumber> | Draw bounding boxes on a batch of images. |
| DummyIterationCounter | |
| DummyMemoryCache | |
| DummySeedGenerator | |
| DynamicPartition<T extends TType> | Partitions `data` into `num_partitions` tensors using indices from `partitions`. |
| DynamicSlice<T extends TType> | Wraps the XLA DynamicSlice operator, documented at
https://www.tensorflow.org/performance/xla/operation_semantics#dynamicslice . |
| DynamicStitch<T extends TType> | Interleave the values from the `data` tensors into a single tensor. |
| DynamicUpdateSlice<T extends TType> | Wraps the XLA DynamicUpdateSlice operator, documented at
https://www.tensorflow.org/performance/xla/operation_semantics#dynamicupdateslice . |
E
| EagerSession | An environment for executing TensorFlow operations eagerly. |
| EagerSession.DevicePlacementPolicy | Controls how to act when we try to run an operation on a given device but some input tensors are not on that device. |
| EagerSession.Options | |
| EditDistance | Computes the (possibly normalized) Levenshtein Edit Distance. |
| EditDistance.Options | Optional attributes for EditDistance
|
| Eig<U extends TType> | Computes the eigen decomposition of one or more square matrices. |
| Eig.Options | Optional attributes for Eig
|
| Einsum<T extends TType> | Tensor contraction according to Einstein summation convention. |
| Einsum<T extends TType> | An op which supports basic einsum op with 2 inputs and 1 output. |
| Elu<T extends TNumber> | Computes exponential linear: `exp(features) - 1` if < 0, `features` otherwise. |
| ELU<T extends TFloating> | Exponential linear unit. |
| EluGrad<T extends TNumber> | Computes gradients for the exponential linear (Elu) operation. |
| EmbeddingActivations | An op enabling differentiation of TPU Embeddings. |
| Empty<T extends TType> | Creates a tensor with the given shape. |
| Empty.Options | Optional attributes for Empty
|
| EmptyTensorList | Creates and returns an empty tensor list. |
| EmptyTensorMap | Creates and returns an empty tensor map. |
| EncodeBase64 | Encode strings into web-safe base64 format. |
| EncodeBase64.Options | Optional attributes for EncodeBase64
|
| EncodeJpeg | JPEG-encode an image. |
| EncodeJpeg.Options | Optional attributes for EncodeJpeg
|
| EncodeJpegVariableQuality | JPEG encode input image with provided compression quality. |
| EncodePng | PNG-encode an image. |
| EncodePng.Options | Optional attributes for EncodePng
|
| EncodeProto | The op serializes protobuf messages provided in the input tensors. |
| EncodeProto.Options | Optional attributes for EncodeProto
|
| EncodeWav | Encode audio data using the WAV file format. |
| Endpoint | Annotation used to mark a method of a class annotated with @Operator that should
generate an endpoint into ERROR(Ops/org.tensorflow.op.Ops Ops) or one of its groups. |
| EnqueueTPUEmbeddingIntegerBatch | An op that enqueues a list of input batch tensors to TPUEmbedding. |
| EnqueueTPUEmbeddingIntegerBatch.Options | Optional attributes for EnqueueTPUEmbeddingIntegerBatch
|
| EnqueueTPUEmbeddingRaggedTensorBatch | Eases the porting of code that uses tf.nn.embedding_lookup(). |
| EnqueueTPUEmbeddingRaggedTensorBatch.Options | Optional attributes for EnqueueTPUEmbeddingRaggedTensorBatch
|
| EnqueueTPUEmbeddingSparseBatch | An op that enqueues TPUEmbedding input indices from a SparseTensor. |
| EnqueueTPUEmbeddingSparseBatch.Options | Optional attributes for EnqueueTPUEmbeddingSparseBatch
|
| EnqueueTPUEmbeddingSparseTensorBatch | Eases the porting of code that uses tf.nn.embedding_lookup_sparse(). |
| EnqueueTPUEmbeddingSparseTensorBatch.Options | Optional attributes for EnqueueTPUEmbeddingSparseTensorBatch
|
| EnsureShape<T extends TType> | Ensures that the tensor's shape matches the expected shape. |
| Enter<T extends TType> | Creates or finds a child frame, and makes `data` available to the child frame. |
| Enter.Options | Optional attributes for Enter
|
| EntryValue | Protobuf type tensorflow.EntryValue
|
| EntryValue.Builder | Protobuf type tensorflow.EntryValue
|
| EntryValue.KindCase | |
| EntryValueOrBuilder | |
| Equal | Returns the truth value of (x == y) element-wise. |
| Equal.Options | Optional attributes for Equal
|
| Erf<T extends TNumber> | Computes the Gauss error function of `x` element-wise. |
| Erfc<T extends TNumber> | Computes the complementary error function of `x` element-wise. |
| erfinv<T extends TNumber> | |
| ErrorCodes | |
| ErrorCodesProtos | |
| EuclideanNorm<T extends TType> | Computes the euclidean norm of elements across dimensions of a tensor. |
| EuclideanNorm.Options | Optional attributes for EuclideanNorm
|
| Event | Protocol buffer representing an event that happened during the execution of a Brain model. |
| Event.Builder | Protocol buffer representing an event that happened during the execution of a Brain model. |
| Event.WhatCase | |
| EventOrBuilder | |
| EventProtos | |
| Example | Protobuf type tensorflow.Example
|
| Example.Builder | Protobuf type tensorflow.Example
|
| ExampleOrBuilder | |
| ExampleParserConfiguration | Protobuf type tensorflow.ExampleParserConfiguration
|
| ExampleParserConfiguration.Builder | Protobuf type tensorflow.ExampleParserConfiguration
|
| ExampleParserConfigurationOrBuilder | |
| ExampleParserConfigurationProtos | |
| ExampleProtos | |
| Execute | Op that loads and executes a TPU program on a TPU device. |
| ExecuteAndUpdateVariables | Op that executes a program with optional in-place variable updates. |
| Execution | Data relating to the eager execution of an op or a Graph. |
| Execution.Builder | Data relating to the eager execution of an op or a Graph. |
| ExecutionEnvironment | Defines an environment for creating and executing TensorFlow Operations. |
| ExecutionEnvironment.Types | |
| ExecutionOrBuilder | |
| Exit<T extends TType> | Exits the current frame to its parent frame. |
| Exp<T extends TType> | Computes exponential of x element-wise. |
| ExpandDims<T extends TType> | Inserts a dimension of 1 into a tensor's shape. |
| Expint<T extends TNumber> | |
| Expm1<T extends TType> | Computes `exp(x) - 1` element-wise. |
| Exponential<T extends TFloating> | Exponential activation function. |
| ExtractGlimpse | Extracts a glimpse from the input tensor. |
| ExtractGlimpse.Options | Optional attributes for ExtractGlimpse
|
| ExtractImagePatches<T extends TType> | Extract `patches` from `images` and put them in the "depth" output dimension. |
| ExtractJpegShape<T extends TNumber> | Extract the shape information of a JPEG-encoded image. |
| ExtractVolumePatches<T extends TNumber> | Extract `patches` from `input` and put them in the `"depth"` output dimension. |
F
| Fact | Output a fact about factorials. |
| FakeQuantWithMinMaxArgs | Fake-quantize the 'inputs' tensor, type float to 'outputs' tensor of same type. |
| FakeQuantWithMinMaxArgs.Options | Optional attributes for FakeQuantWithMinMaxArgs
|
| FakeQuantWithMinMaxArgsGradient | Compute gradients for a FakeQuantWithMinMaxArgs operation. |
| FakeQuantWithMinMaxArgsGradient.Options | Optional attributes for FakeQuantWithMinMaxArgsGradient
|
| FakeQuantWithMinMaxVars | Fake-quantize the 'inputs' tensor of type float via global float scalars
Fake-quantize the `inputs` tensor of type float via global float scalars `min` and `max` to `outputs` tensor of same shape as `inputs`. |
| FakeQuantWithMinMaxVars.Options | Optional attributes for FakeQuantWithMinMaxVars
|
| FakeQuantWithMinMaxVarsGradient | Compute gradients for a FakeQuantWithMinMaxVars operation. |
| FakeQuantWithMinMaxVarsGradient.Options | Optional attributes for FakeQuantWithMinMaxVarsGradient
|
| FakeQuantWithMinMaxVarsPerChannel | Fake-quantize the 'inputs' tensor of type float via per-channel floats
Fake-quantize the `inputs` tensor of type float per-channel and one of the shapes: `[d]`, `[b, d]` `[b, h, w, d]` via per-channel floats `min` and `max` of shape `[d]` to `outputs` tensor of same shape as `inputs`. |
| FakeQuantWithMinMaxVarsPerChannel.Options | Optional attributes for FakeQuantWithMinMaxVarsPerChannel
|
| FakeQuantWithMinMaxVarsPerChannelGradient | Compute gradients for a FakeQuantWithMinMaxVarsPerChannel operation. |
| FakeQuantWithMinMaxVarsPerChannelGradient.Options | Optional attributes for FakeQuantWithMinMaxVarsPerChannelGradient
|
| FastElementSequence<T, U extends NdArray<T>> | A sequence recycling the same NdArray instance when iterating its elements |
| Feature | Containers for non-sequential data. |
| Feature.Builder | Containers for non-sequential data. |
| Feature.KindCase | |
| FeatureConfiguration | Protobuf type tensorflow.FeatureConfiguration
|
| FeatureConfiguration.Builder | Protobuf type tensorflow.FeatureConfiguration
|
| FeatureConfiguration.ConfigCase | |
| FeatureConfigurationOrBuilder | |
| FeatureList | Containers for sequential data. |
| FeatureList.Builder | Containers for sequential data. |
| FeatureListOrBuilder | |
| FeatureLists | Protobuf type tensorflow.FeatureLists
|
| FeatureLists.Builder | Protobuf type tensorflow.FeatureLists
|
| FeatureListsOrBuilder | |
| FeatureOrBuilder | |
| FeatureProtos | |
| Features | Protobuf type tensorflow.Features
|
| Features.Builder | Protobuf type tensorflow.Features
|
| FeaturesOrBuilder | |
| Fft<T extends TType> | Fast Fourier transform. |
| Fft2d<T extends TType> | 2D fast Fourier transform. |
| Fft3d<T extends TType> | 3D fast Fourier transform. |
| FifoQueue | A queue that produces elements in first-in first-out order. |
| FifoQueue.Options | Optional attributes for FifoQueue
|
| Fill<U extends TType> | Creates a tensor filled with a scalar value. |
| FilterByLastComponentDataset | Creates a dataset containing elements of first component of `input_dataset` having true in the last component. |
| Fingerprint | Generates fingerprint values. |
| FixedLenFeatureProto | Protobuf type tensorflow.FixedLenFeatureProto
|
| FixedLenFeatureProto.Builder | Protobuf type tensorflow.FixedLenFeatureProto
|
| FixedLenFeatureProtoOrBuilder | |
| FixedLengthRecordDataset | |
| FixedLengthRecordReader | A Reader that outputs fixed-length records from a file. |
| FixedLengthRecordReader.Options | Optional attributes for FixedLengthRecordReader
|
| FixedUnigramCandidateSampler | Generates labels for candidate sampling with a learned unigram distribution. |
| FixedUnigramCandidateSampler.Options | Optional attributes for FixedUnigramCandidateSampler
|
| Float16Layout | Data layout that converts 32-bit floats from/to 16-bit, accordingly to the IEEE-754 half-precision floating point specification. |
| FloatDataBuffer | A DataBuffer of floats. |
| FloatDataLayout<S extends DataBuffer<?>> | A DataLayout that converts data stored in a buffer to floats. |
| FloatDenseNdArray | |
| FloatList | Protobuf type tensorflow.FloatList
|
| FloatList.Builder | Protobuf type tensorflow.FloatList
|
| FloatListOrBuilder | |
| FloatNdArray | An NdArray of floats. |
| Floor<T extends TNumber> | Returns element-wise largest integer not greater than x. |
| FloorDiv<T extends TType> | Returns x // y element-wise. |
| FloorMod<T extends TNumber> | Returns element-wise remainder of division. |
| FlushSummaryWriter | |
| FractionalAvgPool<T extends TNumber> | Performs fractional average pooling on the input. |
| FractionalAvgPool.Options | Optional attributes for FractionalAvgPool
|
| FractionalAvgPoolGrad<T extends TNumber> | Computes gradient of the FractionalAvgPool function. |
| FractionalAvgPoolGrad.Options | Optional attributes for FractionalAvgPoolGrad
|
| FractionalMaxPool<T extends TNumber> | Performs fractional max pooling on the input. |
| FractionalMaxPool.Options | Optional attributes for FractionalMaxPool
|
| FractionalMaxPoolGrad<T extends TNumber> | Computes gradient of the FractionalMaxPool function. |
| FractionalMaxPoolGrad.Options | Optional attributes for FractionalMaxPoolGrad
|
| FresnelCos<T extends TNumber> | |
| FresnelSin<T extends TNumber> | |
| Ftrl | Optimizer that implements the FTRL algorithm. |
| FunctionDef | A function can be instantiated when the runtime can bind every attr with a value. |
| FunctionDef.ArgAttrs | Attributes for function arguments. |
| FunctionDef.ArgAttrs.Builder | Attributes for function arguments. |
| FunctionDef.ArgAttrsOrBuilder | |
| FunctionDef.Builder | A function can be instantiated when the runtime can bind every attr with a value. |
| FunctionDefLibrary | A library is a set of named functions. |
| FunctionDefLibrary.Builder | A library is a set of named functions. |
| FunctionDefLibraryOrBuilder | |
| FunctionDefOrBuilder | |
| FunctionProtos | |
| FunctionSpec | Represents `FunctionSpec` used in `Function`. |
| FunctionSpec.Builder | Represents `FunctionSpec` used in `Function`. |
| FunctionSpec.ExperimentalCompile | Whether the function should be compiled by XLA. |
| FunctionSpecOrBuilder | |
| FusedBatchNorm<T extends TNumber, U extends TNumber> | Batch normalization. |
| FusedBatchNorm.Options | Optional attributes for FusedBatchNorm
|
| FusedBatchNormGrad<T extends TNumber, U extends TNumber> | Gradient for batch normalization. |
| FusedBatchNormGrad.Options | Optional attributes for FusedBatchNormGrad
|
| FusedPadConv2d<T extends TNumber> | Performs a padding as a preprocess during a convolution. |
| FusedResizeAndPadConv2d<T extends TNumber> | Performs a resize and padding as a preprocess during a convolution. |
| FusedResizeAndPadConv2d.Options | Optional attributes for FusedResizeAndPadConv2d
|
G
| Gather<T extends TNumber> | Mutually accumulates multiple tensors of identical type and shape. |
| Gather<T extends TType> | Gather slices from `params` axis `axis` according to `indices`. |
| Gather<T extends TType> | Wraps the XLA Gather operator documented at
https://www.tensorflow.org/xla/operation_semantics#gather |
| Gather.Options | Optional attributes for Gather
|
| Gather.Options | Optional attributes for Gather
|
| GatherNd<T extends TType> | Gather slices from `params` into a Tensor with shape specified by `indices`. |
| GatherV2<T extends TNumber> | Mutually accumulates multiple tensors of identical type and shape. |
| GatherV2.Options | Optional attributes for GatherV2
|
| GenerateBoundingBoxProposals | This op produces Region of Interests from given bounding boxes(bbox_deltas) encoded wrt anchors according to eq.2 in arXiv:1506.01497
The op selects top `pre_nms_topn` scoring boxes, decodes them with respect to anchors, applies non-maximal suppression on overlapping boxes with higher than `nms_threshold` intersection-over-union (iou) value, discarding boxes where shorter side is less than `min_size`. |
| GenerateBoundingBoxProposals.Options | Optional attributes for GenerateBoundingBoxProposals
|
| GenerateVocabRemapping | Given a path to new and old vocabulary files, returns a remapping Tensor of
length `num_new_vocab`, where `remapping[i]` contains the row number in the old vocabulary that corresponds to row `i` in the new vocabulary (starting at line `new_vocab_offset` and up to `num_new_vocab` entities), or `-1` if entry `i` in the new vocabulary is not in the old vocabulary. |
| GenerateVocabRemapping.Options | Optional attributes for GenerateVocabRemapping
|
| GetSessionHandle | Store the input tensor in the state of the current session. |
| GetSessionTensor<T extends TType> | Get the value of the tensor specified by its handle. |
| Glorot<T extends TFloating> | The Glorot initializer, also called Xavier initializer. |
| GPUInfo | Protobuf type tensorflow.GPUInfo
|
| GPUInfo.Builder | Protobuf type tensorflow.GPUInfo
|
| GPUInfoOrBuilder | |
| GPUOptions | Protobuf type tensorflow.GPUOptions
|
| GPUOptions.Builder | Protobuf type tensorflow.GPUOptions
|
| GPUOptions.Experimental | Protobuf type tensorflow.GPUOptions.Experimental
|
| GPUOptions.Experimental.Builder | Protobuf type tensorflow.GPUOptions.Experimental
|
| GPUOptions.Experimental.VirtualDevices | Configuration for breaking down a visible GPU into multiple "virtual" devices. |
| GPUOptions.Experimental.VirtualDevices.Builder | Configuration for breaking down a visible GPU into multiple "virtual" devices. |
| GPUOptions.Experimental.VirtualDevicesOrBuilder | |
| GPUOptions.ExperimentalOrBuilder | |
| GPUOptionsOrBuilder | |
| GradientDef | GradientDef defines the gradient function of a function defined in a function library. |
| GradientDef.Builder | GradientDef defines the gradient function of a function defined in a function library. |
| GradientDefOrBuilder | |
| GradientDescent | Basic Stochastic gradient descent optimizer. |
| Gradients | Adds operations to compute the partial derivatives of sum of ys w.r.t xs,
i.e., d(y_1 + y_2 + ...)/dx_1, d(y_1 + y_2 + ...)/dx_2...
If |
| Gradients.Options | Optional attributes for Gradients
|
| Graph | A data flow graph representing a TensorFlow computation. |
| Graph.WhileSubgraphBuilder | Used to instantiate an abstract class which overrides the buildSubgraph method to build a conditional or body subgraph for a while loop. |
| GraphDebugInfo | Protobuf type tensorflow.GraphDebugInfo
|
| GraphDebugInfo.Builder | Protobuf type tensorflow.GraphDebugInfo
|
| GraphDebugInfo.FileLineCol | This represents a file/line location in the source code. |
| GraphDebugInfo.FileLineCol.Builder | This represents a file/line location in the source code. |
| GraphDebugInfo.FileLineColOrBuilder | |
| GraphDebugInfo.StackTrace | This represents a stack trace which is a ordered list of `FileLineCol`. |
| GraphDebugInfo.StackTrace.Builder | This represents a stack trace which is a ordered list of `FileLineCol`. |
| GraphDebugInfo.StackTraceOrBuilder | |
| GraphDebugInfoOrBuilder | |
| GraphDebugInfoProtos | |
| GraphDef | Represents the graph of operationsProtobuf type tensorflow.GraphDef
|
| GraphDef.Builder | Represents the graph of operationsProtobuf type tensorflow.GraphDef
|
| GraphDefOrBuilder | |
| GraphExecutionTrace | Data relating to an execution of a Graph (e.g., an eager execution of a FuncGraph). |
| GraphExecutionTrace.Builder | Data relating to an execution of a Graph (e.g., an eager execution of a FuncGraph). |
| GraphExecutionTraceOrBuilder | |
| GraphOpCreation | The creation of an op in a TensorFlow Graph (e.g., FuncGraph in TF2). |
| GraphOpCreation.Builder | The creation of an op in a TensorFlow Graph (e.g., FuncGraph in TF2). |
| GraphOpCreationOrBuilder | |
| GraphOperation | Implementation for an Operation added as a node to a Graph. |
| GraphOperationBuilder | An OperationBuilder for adding GraphOperations to a Graph. |
| GraphOptions | Protobuf type tensorflow.GraphOptions
|
| GraphOptions.Builder | Protobuf type tensorflow.GraphOptions
|
| GraphOptionsOrBuilder | |
| GraphProtos | |
| GraphTransferConstNodeInfo | Protobuf type tensorflow.GraphTransferConstNodeInfo
|
| GraphTransferConstNodeInfo.Builder | Protobuf type tensorflow.GraphTransferConstNodeInfo
|
| GraphTransferConstNodeInfoOrBuilder | |
| GraphTransferGraphInputNodeInfo | Protobuf type tensorflow.GraphTransferGraphInputNodeInfo
|
| GraphTransferGraphInputNodeInfo.Builder | Protobuf type tensorflow.GraphTransferGraphInputNodeInfo
|
| GraphTransferGraphInputNodeInfoOrBuilder | |
| GraphTransferGraphOutputNodeInfo | Protobuf type tensorflow.GraphTransferGraphOutputNodeInfo
|
| GraphTransferGraphOutputNodeInfo.Builder | Protobuf type tensorflow.GraphTransferGraphOutputNodeInfo
|
| GraphTransferGraphOutputNodeInfoOrBuilder | |
| GraphTransferInfo | Protocol buffer representing a handle to a tensorflow resource. |
| GraphTransferInfo.Builder | Protocol buffer representing a handle to a tensorflow resource. |
| GraphTransferInfo.Destination | Protobuf enum tensorflow.GraphTransferInfo.Destination
|
| GraphTransferInfoOrBuilder | |
| GraphTransferInfoProto | |
| GraphTransferNodeInfo | Protobuf type tensorflow.GraphTransferNodeInfo
|
| GraphTransferNodeInfo.Builder | Protobuf type tensorflow.GraphTransferNodeInfo
|
| GraphTransferNodeInfoOrBuilder | |
| GraphTransferNodeInput | Protobuf type tensorflow.GraphTransferNodeInput
|
| GraphTransferNodeInput.Builder | Protobuf type tensorflow.GraphTransferNodeInput
|
| GraphTransferNodeInputInfo | Protobuf type tensorflow.GraphTransferNodeInputInfo
|
| GraphTransferNodeInputInfo.Builder | Protobuf type tensorflow.GraphTransferNodeInputInfo
|
| GraphTransferNodeInputInfoOrBuilder | |
| GraphTransferNodeInputOrBuilder | |
| GraphTransferNodeOutputInfo | Protobuf type tensorflow.GraphTransferNodeOutputInfo
|
| GraphTransferNodeOutputInfo.Builder | Protobuf type tensorflow.GraphTransferNodeOutputInfo
|
| GraphTransferNodeOutputInfoOrBuilder | |
| Greater | Returns the truth value of (x > y) element-wise. |
| GreaterEqual | Returns the truth value of (x >= y) element-wise. |
| GRUBlockCell<T extends TNumber> | Computes the GRU cell forward propagation for 1 time step. |
| GRUBlockCellGrad<T extends TNumber> | Computes the GRU cell back-propagation for 1 time step. |
| GuaranteeConst<T extends TType> | Gives a guarantee to the TF runtime that the input tensor is a constant. |
H
| HardSigmoid<T extends TFloating> | Hard sigmoid activation. |
| HashTable | Creates a non-initialized hash table. |
| HashTable.Options | Optional attributes for HashTable
|
| He<T extends TFloating> | He initializer. |
| Helpers | Container class for core methods which add or perform several operations and return one of them. |
| Hinge | Computes the hinge loss between labels and predictions. |
| Hinge<T extends TNumber> | A metric that computes the hinge loss metric between labels and predictions. |
| HistogramFixedWidth<U extends TNumber> | Return histogram of values. |
| HistogramProto | Serialization format for histogram module in core/lib/histogram/histogram.hProtobuf type tensorflow.HistogramProto
|
| HistogramProto.Builder | Serialization format for histogram module in core/lib/histogram/histogram.hProtobuf type tensorflow.HistogramProto
|
| HistogramProtoOrBuilder | |
| HistogramSummary | Outputs a `Summary` protocol buffer with a histogram. |
| HsvToRgb<T extends TNumber> | Convert one or more images from HSV to RGB. |
| Huber | Computes the Huber loss between labels and predictions. |
I
| Identity<T extends TFloating> | Initializer that generates the identity matrix. |
| Identity<T extends TType> | 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. |
| IdentityReader | A Reader that outputs the queued work as both the key and value. |
| IdentityReader.Options | Optional attributes for IdentityReader
|
| Ifft<T extends TType> | Inverse fast Fourier transform. |
| Ifft2d<T extends TType> | Inverse 2D fast Fourier transform. |
| Ifft3d<T extends TType> | Inverse 3D fast Fourier transform. |
| Igamma<T extends TNumber> | Compute the lower regularized incomplete Gamma function `P(a, x)`. |
| Igammac<T extends TNumber> | Compute the upper regularized incomplete Gamma function `Q(a, x)`. |
| IgammaGradA<T extends TNumber> | Computes the gradient of `igamma(a, x)` wrt `a`. |
| IgnoreErrorsDataset | Creates a dataset that contains the elements of `input_dataset` ignoring errors. |
| IgnoreErrorsDataset | Creates a dataset that contains the elements of `input_dataset` ignoring errors. |
| IgnoreErrorsDataset.Options | Optional attributes for IgnoreErrorsDataset
|
| IgnoreErrorsDataset.Options | Optional attributes for IgnoreErrorsDataset
|
| IllegalRankException | Exception thrown when an operation cannot be completed because of the rank of the targeted array. |
| Imag<U extends TNumber> | Returns the imaginary part of a complex number. |
| ImageProjectiveTransformV2<T extends TNumber> | Applies the given transform to each of the images. |
| ImageProjectiveTransformV2.Options | Optional attributes for ImageProjectiveTransformV2
|
| ImageProjectiveTransformV3<T extends TNumber> | Applies the given transform to each of the images. |
| ImageProjectiveTransformV3.Options | Optional attributes for ImageProjectiveTransformV3
|
| ImageSummary | Outputs a `Summary` protocol buffer with images. |
| ImageSummary.Options | Optional attributes for ImageSummary
|
| ImmutableConst<T extends TType> | Returns immutable tensor from memory region. |
| ImportEvent | |
| Index | An index used for slicing a view out of an N-dimensional array. |
| IndexedPositionIterator | |
| IndexedPositionIterator.CoordsLongConsumer | |
| Indices | Helper class for instantiating Index objects. |
| InfeedDequeue<T extends TType> | A placeholder op for a value that will be fed into the computation. |
| InfeedDequeueTuple | Fetches multiple values from infeed as an XLA tuple. |
| InfeedEnqueue | An op which feeds a single Tensor value into the computation. |
| InfeedEnqueue.Options | Optional attributes for InfeedEnqueue
|
| InfeedEnqueuePrelinearizedBuffer | An op which enqueues prelinearized buffer into TPU infeed. |
| InfeedEnqueuePrelinearizedBuffer.Options | Optional attributes for InfeedEnqueuePrelinearizedBuffer
|
| InfeedEnqueueTuple | Feeds multiple Tensor values into the computation as an XLA tuple. |
| InfeedEnqueueTuple.Options | Optional attributes for InfeedEnqueueTuple
|
| Init | |
| Initializer<T extends TType> | An interface for Initializers |
| InitializeTable | Table initializer that takes two tensors for keys and values respectively. |
| InitializeTableFromDataset | |
| InitializeTableFromTextFile | Initializes a table from a text file. |
| InitializeTableFromTextFile.Options | Optional attributes for InitializeTableFromTextFile
|
| InplaceAdd<T extends TType> | Adds v into specified rows of x. |
| InplaceSub<T extends TType> | Subtracts `v` into specified rows of `x`. |
| InplaceUpdate<T extends TType> | Updates specified rows 'i' with values 'v'. |
| Int64List | Protobuf type tensorflow.Int64List
|
| Int64List.Builder | Protobuf type tensorflow.Int64List
|
| Int64ListOrBuilder | |
| IntDataBuffer | A DataBuffer of ints. |
| IntDataLayout<S extends DataBuffer<?>> | A DataLayout that converts data stored in a buffer to ints. |
| IntDenseNdArray | |
| InterconnectLink | Protobuf type tensorflow.InterconnectLink
|
| InterconnectLink.Builder | Protobuf type tensorflow.InterconnectLink
|
| InterconnectLinkOrBuilder | |
| IntNdArray | An NdArray of integers. |
| InTopK | Says whether the targets are in the top `K` predictions. |
| Inv<T extends TType> | Computes the inverse of one or more square invertible matrices or their adjoints (conjugate transposes). |
| Inv.Options | Optional attributes for Inv
|
| Invert<T extends TNumber> | Invert (flip) each bit of supported types; for example, type `uint8` value 01010101 becomes 10101010. |
| InvertPermutation<T extends TNumber> | Computes the inverse permutation of a tensor. |
| InvGrad<T extends TType> | Computes the gradient for the inverse of `x` wrt its input. |
| Irfft<U extends TNumber> | Inverse real-valued fast Fourier transform. |
| Irfft2d<U extends TNumber> | Inverse 2D real-valued fast Fourier transform. |
| Irfft3d<U extends TNumber> | Inverse 3D real-valued fast Fourier transform. |
| IsBoostedTreesEnsembleInitialized | Checks whether a tree ensemble has been initialized. |
| IsBoostedTreesQuantileStreamResourceInitialized | Checks whether a quantile stream has been initialized. |
| IsFinite | Returns which elements of x are finite. |
| IsInf | Returns which elements of x are Inf. |
| IsNan | Returns which elements of x are NaN. |
| IsotonicRegression<U extends TNumber> | Solves a batch of isotonic regression problems. |
| IsVariableInitialized | Checks whether a tensor has been initialized. |
| Iterator | |
| IteratorFromStringHandle | |
| IteratorFromStringHandle.Options | Optional attributes for IteratorFromStringHandle
|
| IteratorGetDevice | Returns the name of the device on which `resource` has been placed. |
| IteratorGetDevice | Returns the name of the device on which `resource` has been placed. |
| IteratorGetNext | Gets the next output from the given iterator . |
| IteratorGetNextAsOptional | Gets the next output from the given iterator as an Optional variant. |
| IteratorGetNextSync | Gets the next output from the given iterator. |
| IteratorToStringHandle | Converts the given `resource_handle` representing an iterator to a string. |
J
| JobDef | Defines a single job in a TensorFlow cluster. |
| JobDef.Builder | Defines a single job in a TensorFlow cluster. |
| JobDefOrBuilder | |
| JobDeviceFilters | Defines the device filters for tasks in a job. |
| JobDeviceFilters.Builder | Defines the device filters for tasks in a job. |
| JobDeviceFiltersOrBuilder | |
| Join | Joins the strings in the given list of string tensors into one tensor;
with the given separator (default is an empty separator). |
| Join.Options | Optional attributes for Join
|
K
| KernelDef | Protobuf type tensorflow.KernelDef
|
| KernelDef.AttrConstraint | Protobuf type tensorflow.KernelDef.AttrConstraint
|
| KernelDef.AttrConstraint.Builder | Protobuf type tensorflow.KernelDef.AttrConstraint
|
| KernelDef.AttrConstraintOrBuilder | |
| KernelDef.Builder | Protobuf type tensorflow.KernelDef
|
| KernelDefOrBuilder | |
| KernelDefProtos | |
| KernelList | A collection of KernelDefsProtobuf type tensorflow.KernelList
|
| KernelList.Builder | A collection of KernelDefsProtobuf type tensorflow.KernelList
|
| KernelListOrBuilder | |
| KeyValueSort<T extends TNumber, U extends TType> | Wraps the XLA Sort operator, documented at
https://www.tensorflow.org/performance/xla/operation_semantics#sort . |
| KLDivergence | Computes Kullback-Leibler divergence loss between labels and predictions. |
| KLDivergence<T extends TNumber> | A metric that computes the Kullback-Leibler divergence loss metric between labels and predictions. |
| KMC2ChainInitialization | Returns the index of a data point that should be added to the seed set. |
| KmeansPlusPlusInitialization | Selects num_to_sample rows of input using the KMeans++ criterion. |
| KthOrderStatistic | Computes the Kth order statistic of a data set. |
L
| L2Loss<T extends TNumber> | L2 Loss. |
| LatencyStatsDataset | Records the latency of producing `input_dataset` elements in a StatsAggregator. |
| LatencyStatsDataset | Records the latency of producing `input_dataset` elements in a StatsAggregator. |
| LeakyRelu<T extends TNumber> | Computes rectified linear: `max(features, features * alpha)`. |
| LeakyRelu.Options | Optional attributes for LeakyRelu
|
| LeakyReluGrad<T extends TNumber> | Computes rectified linear gradients for a LeakyRelu operation. |
| LeakyReluGrad.Options | Optional attributes for LeakyReluGrad
|
| LearnedUnigramCandidateSampler | Generates labels for candidate sampling with a learned unigram distribution. |
| LearnedUnigramCandidateSampler.Options | Optional attributes for LearnedUnigramCandidateSampler
|
| LeCun<T extends TFloating> | LeCun normal initializer. |
| LeftShift<T extends TNumber> | Elementwise computes the bitwise left-shift of `x` and `y`. |
| Less | Returns the truth value of (x < y) element-wise. |
| LessEqual | Returns the truth value of (x <= y) element-wise. |
| Lgamma<T extends TNumber> | Computes the log of the absolute value of `Gamma(x)` element-wise. |
| Linear<U extends TNumber> | Linear activation function (pass-through). |
| LinSpace<T extends TNumber> | Generates values in an interval. |
| Listener_BytePointer | |
| Listener_String | |
| ListValue | Represents a Python list. |
| ListValue.Builder | Represents a Python list. |
| ListValueOrBuilder | |
| LMDBDataset | Creates a dataset that emits the key-value pairs in one or more LMDB files. |
| LmdbDataset | |
| LmdbReader | A Reader that outputs the records from a LMDB file. |
| LmdbReader.Options | Optional attributes for LmdbReader
|
| LoadAndRemapMatrix | Loads a 2-D (matrix) `Tensor` with name `old_tensor_name` from the checkpoint
at `ckpt_path` and potentially reorders its rows and columns using the specified remappings. |
| LoadAndRemapMatrix.Options | Optional attributes for LoadAndRemapMatrix
|
| LoadTPUEmbeddingAdadeltaParameters | Load Adadelta embedding parameters. |
| LoadTPUEmbeddingAdadeltaParameters.Options | Optional attributes for LoadTPUEmbeddingAdadeltaParameters
|
| LoadTPUEmbeddingAdadeltaParametersGradAccumDebug | Load Adadelta parameters with debug support. |
| LoadTPUEmbeddingAdadeltaParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingAdadeltaParametersGradAccumDebug
|
| LoadTPUEmbeddingAdagradParameters | Load Adagrad embedding parameters. |
| LoadTPUEmbeddingAdagradParameters.Options | Optional attributes for LoadTPUEmbeddingAdagradParameters
|
| LoadTPUEmbeddingAdagradParametersGradAccumDebug | Load Adagrad embedding parameters with debug support. |
| LoadTPUEmbeddingAdagradParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingAdagradParametersGradAccumDebug
|
| LoadTPUEmbeddingADAMParameters | Load ADAM embedding parameters. |
| LoadTPUEmbeddingADAMParameters.Options | Optional attributes for LoadTPUEmbeddingADAMParameters
|
| LoadTPUEmbeddingADAMParametersGradAccumDebug | Load ADAM embedding parameters with debug support. |
| LoadTPUEmbeddingADAMParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingADAMParametersGradAccumDebug
|
| LoadTPUEmbeddingCenteredRMSPropParameters | Load centered RMSProp embedding parameters. |
| LoadTPUEmbeddingCenteredRMSPropParameters.Options | Optional attributes for LoadTPUEmbeddingCenteredRMSPropParameters
|
| LoadTPUEmbeddingFTRLParameters | Load FTRL embedding parameters. |
| LoadTPUEmbeddingFTRLParameters.Options | Optional attributes for LoadTPUEmbeddingFTRLParameters
|
| LoadTPUEmbeddingFTRLParametersGradAccumDebug | Load FTRL embedding parameters with debug support. |
| LoadTPUEmbeddingFTRLParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingFTRLParametersGradAccumDebug
|
| LoadTPUEmbeddingMDLAdagradLightParameters | Load MDL Adagrad Light embedding parameters. |
| LoadTPUEmbeddingMDLAdagradLightParameters.Options | Optional attributes for LoadTPUEmbeddingMDLAdagradLightParameters
|
| LoadTPUEmbeddingMomentumParameters | Load Momentum embedding parameters. |
| LoadTPUEmbeddingMomentumParameters.Options | Optional attributes for LoadTPUEmbeddingMomentumParameters
|
| LoadTPUEmbeddingMomentumParametersGradAccumDebug | Load Momentum embedding parameters with debug support. |
| LoadTPUEmbeddingMomentumParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingMomentumParametersGradAccumDebug
|
| LoadTPUEmbeddingProximalAdagradParameters | Load proximal Adagrad embedding parameters. |
| LoadTPUEmbeddingProximalAdagradParameters.Options | Optional attributes for LoadTPUEmbeddingProximalAdagradParameters
|
| LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug | Load proximal Adagrad embedding parameters with debug support. |
| LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug
|
| LoadTPUEmbeddingProximalYogiParameters | |
| LoadTPUEmbeddingProximalYogiParameters.Options | Optional attributes for LoadTPUEmbeddingProximalYogiParameters
|
| LoadTPUEmbeddingProximalYogiParametersGradAccumDebug | |
| LoadTPUEmbeddingProximalYogiParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingProximalYogiParametersGradAccumDebug
|
| LoadTPUEmbeddingRMSPropParameters | Load RMSProp embedding parameters. |
| LoadTPUEmbeddingRMSPropParameters.Options | Optional attributes for LoadTPUEmbeddingRMSPropParameters
|
| LoadTPUEmbeddingRMSPropParametersGradAccumDebug | Load RMSProp embedding parameters with debug support. |
| LoadTPUEmbeddingRMSPropParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingRMSPropParametersGradAccumDebug
|
| LoadTPUEmbeddingStochasticGradientDescentParameters | Load SGD embedding parameters. |
| LoadTPUEmbeddingStochasticGradientDescentParameters.Options | Optional attributes for LoadTPUEmbeddingStochasticGradientDescentParameters
|
| LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug | Load SGD embedding parameters. |
| LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug
|
| LocalLinks | Protobuf type tensorflow.LocalLinks
|
| LocalLinks.Builder | Protobuf type tensorflow.LocalLinks
|
| LocalLinksOrBuilder | |
| LocalResponseNormalization<T extends TNumber> | Local Response Normalization. |
| LocalResponseNormalization.Options | Optional attributes for LocalResponseNormalization
|
| LocalResponseNormalizationGrad<T extends TNumber> | Gradients for Local Response Normalization. |
| LocalResponseNormalizationGrad.Options | Optional attributes for LocalResponseNormalizationGrad
|
| Log<T extends TType> | Computes natural logarithm of x element-wise. |
| Log1p<T extends TType> | Computes natural logarithm of (1 + x) element-wise. |
| LogCosh | Computes Computes the logarithm of the hyperbolic cosine of the prediction error. |
| LogCoshError<T extends TNumber> | A metric that computes the logarithm of the hyperbolic cosine of the prediction error metric between labels and predictions. |
| LogicalAnd | Returns the truth value of x AND y element-wise. |
| LogicalNot | Returns the truth value of `NOT x` element-wise. |
| LogicalOr | Returns the truth value of x OR y element-wise. |
| LogMatrixDeterminant<T extends TType> | Computes the sign and the log of the absolute value of the determinant of
one or more square matrices. |
| LogMemoryProtos | |
| LogMessage | Protocol buffer used for logging messages to the events file. |
| LogMessage.Builder | Protocol buffer used for logging messages to the events file. |
| LogMessage.Level | Protobuf enum tensorflow.LogMessage.Level
|
| LogMessageOrBuilder | |
| LogSoftmax<T extends TNumber> | Computes log softmax activations. |
| LogUniformCandidateSampler | Generates labels for candidate sampling with a log-uniform distribution. |
| LogUniformCandidateSampler.Options | Optional attributes for LogUniformCandidateSampler
|
| LongDataBuffer | A DataBuffer of longs. |
| LongDataLayout<S extends DataBuffer<?>> | A DataLayout that converts data stored in a buffer to longs. |
| LongDenseNdArray | |
| LongNdArray | An NdArray of longs. |
| LookupTableExport<T extends TType, U extends TType> | Outputs all keys and values in the table. |
| LookupTableFind<U extends TType> | Looks up keys in a table, outputs the corresponding values. |
| LookupTableImport | Replaces the contents of the table with the specified keys and values. |
| LookupTableInsert | Updates the table to associates keys with values. |
| LookupTableRemove | Removes keys and its associated values from a table. |
| LookupTableSize | Computes the number of elements in the given table. |
| LoopCond | Forwards the input to the output. |
| Loss | |
| Losses | Built-in loss functions. |
| LossesHelper | These are helper methods for Losses and Metrics and will be module private when Java modularity is applied to TensorFlow Java. |
| LossMetric<T extends TNumber> | Interface for Metrics that wrap Loss functions. |
| LossTuple<T extends TNumber> | A helper class for loss methods to return labels, target, and sampleWeights |
| Lower | Converts all uppercase characters into their respective lowercase replacements. |
| Lower.Options | Optional attributes for Lower
|
| LowerBound<U extends TNumber> | Applies lower_bound(sorted_search_values, values) along each row. |
| LSTMBlockCell<T extends TNumber> | Computes the LSTM cell forward propagation for 1 time step. |
| LSTMBlockCell.Options | Optional attributes for LSTMBlockCell
|
| LSTMBlockCellGrad<T extends TNumber> | Computes the LSTM cell backward propagation for 1 timestep. |
| Lu<T extends TType, U extends TNumber> | Computes the LU decomposition of one or more square matrices. |
M
| MachineConfiguration | Protobuf type tensorflow.MachineConfiguration
|
| MachineConfiguration.Builder | Protobuf type tensorflow.MachineConfiguration
|
| MachineConfigurationOrBuilder | |
| MakeIterator | Makes a new iterator from the given `dataset` and stores it in `iterator`. |
| MakeUnique | Make all elements in the non-Batch dimension unique, but \"close\" to
their initial value. |
| MapClear | Op removes all elements in the underlying container. |
| MapClear.Options | Optional attributes for MapClear
|
| MapDataset | |
| MapIncompleteSize | Op returns the number of incomplete elements in the underlying container. |
| MapIncompleteSize.Options | Optional attributes for MapIncompleteSize
|
| MapIterator | |
| MapOptional | |
| MapPeek | Op peeks at the values at the specified key. |
| MapPeek.Options | Optional attributes for MapPeek
|
| MapSize | Op returns the number of elements in the underlying container. |
| MapSize.Options | Optional attributes for MapSize
|
| MapStage | Stage (key, values) in the underlying container which behaves like a hashtable. |
| MapStage.Options | Optional attributes for MapStage
|
| MapUnstage | Op removes and returns the values associated with the key
from the underlying container. |
| MapUnstage.Options | Optional attributes for MapUnstage
|
| MapUnstageNoKey | Op removes and returns a random (key, value)
from the underlying container. |
| MapUnstageNoKey.Options | Optional attributes for MapUnstageNoKey
|
| MatchingFiles | Returns the set of files matching one or more glob patterns. |
| MatchingFilesDataset | |
| MatchingFilesDataset | |
| MatMul<T extends TType> | Multiply the matrix "a" by the matrix "b". |
| MatMul.Options | Optional attributes for MatMul
|
| MatrixDiag<T extends TType> | Returns a batched diagonal tensor with given batched diagonal values. |
| MatrixDiagPart<T extends TType> | Returns the batched diagonal part of a batched tensor. |
| MatrixDiagPartV3<T extends TType> | Returns the batched diagonal part of a batched tensor. |
| MatrixDiagPartV3.Options | Optional attributes for MatrixDiagPartV3
|
| MatrixDiagV3<T extends TType> | Returns a batched diagonal tensor with given batched diagonal values. |
| MatrixDiagV3.Options | Optional attributes for MatrixDiagV3
|
| MatrixLogarithm<T extends TType> | Computes the matrix logarithm of one or more square matrices:
\\(log(exp(A)) = A\\) This op is only defined for complex matrices. |
| MatrixSetDiag<T extends TType> | Returns a batched matrix tensor with new batched diagonal values. |
| MatrixSetDiag.Options | Optional attributes for MatrixSetDiag
|
| MatrixSolveLs<T extends TType> | Solves one or more linear least-squares problems. |
| MatrixSolveLs.Options | Optional attributes for MatrixSolveLs
|
| Max<T extends TType> | Computes the maximum of elements across dimensions of a tensor. |
| Max.Options | Optional attributes for Max
|
| Maximum<T extends TNumber> | Returns the max of x and y (i.e. |
| MaxIntraOpParallelismDataset | Creates a dataset that overrides the maximum intra-op parallelism. |
| MaxIntraOpParallelismDataset | Creates a dataset that overrides the maximum intra-op parallelism. |
| MaxNorm | Constrains the weights incident to each hidden unit to have a norm less than or equal to a desired value. |
| MaxPool<T extends TType> | Performs max pooling on the input. |
| MaxPool.Options | Optional attributes for MaxPool
|
| MaxPool3d<T extends TNumber> | Performs 3D max pooling on the input. |
| MaxPool3d.Options | Optional attributes for MaxPool3d
|
| MaxPool3dGrad<U extends TNumber> | Computes gradients of 3D max pooling function. |
| MaxPool3dGrad.Options | Optional attributes for MaxPool3dGrad
|
| MaxPool3dGradGrad<T extends TNumber> | Computes second-order gradients of the maxpooling function. |
| MaxPool3dGradGrad.Options | Optional attributes for MaxPool3dGradGrad
|
| MaxPoolGrad<T extends TNumber> | Computes gradients of the maxpooling function. |
| MaxPoolGrad.Options | Optional attributes for MaxPoolGrad
|
| MaxPoolGradGrad<T extends TNumber> | Computes second-order gradients of the maxpooling function. |
| MaxPoolGradGrad.Options | Optional attributes for MaxPoolGradGrad
|
| MaxPoolGradGradWithArgmax<T extends TNumber> | Computes second-order gradients of the maxpooling function. |
| MaxPoolGradGradWithArgmax.Options | Optional attributes for MaxPoolGradGradWithArgmax
|
| MaxPoolGradWithArgmax<T extends TNumber> | Computes gradients of the maxpooling function. |
| MaxPoolGradWithArgmax.Options | Optional attributes for MaxPoolGradWithArgmax
|
| MaxPoolWithArgmax<T extends TNumber, U extends TNumber> | Performs max pooling on the input and outputs both max values and indices. |
| MaxPoolWithArgmax.Options | Optional attributes for MaxPoolWithArgmax
|
| Mean<T extends TNumber> | A metric that that implements a weighted mean WEIGHTED_MEAN |
| Mean<T extends TType> | Computes the mean of elements across dimensions of a tensor. |
| Mean.Options | Optional attributes for Mean
|
| MeanAbsoluteError | Computes the mean of absolute difference between labels and predictions. |
| MeanAbsoluteError<T extends TNumber> | A metric that computes the mean of absolute difference between labels and predictions. |
| MeanAbsolutePercentageError | Computes the mean absolute percentage error between labels and predictions. |
| MeanAbsolutePercentageError<T extends TNumber> | A metric that computes the mean of absolute difference between labels and predictions. |
| MeanMetricWrapper<T extends TNumber> | A class that bridges a stateless loss function with the Mean metric using a reduction of
WEIGHTED_MEAN. |
| MeanSquaredError | Computes the mean of squares of errors between labels and predictions. |
| MeanSquaredError<T extends TNumber> | A metric that computes the mean of absolute difference between labels and predictions. |
| MeanSquaredLogarithmicError | Computes the mean squared logarithmic errors between labels and predictions. |
| MeanSquaredLogarithmicError<T extends TNumber> | A metric that computes the mean of absolute difference between labels and predictions. |
| MemAllocatorStats | Some of the data from AllocatorStatsProtobuf type tensorflow.MemAllocatorStats
|
| MemAllocatorStats.Builder | Some of the data from AllocatorStatsProtobuf type tensorflow.MemAllocatorStats
|
| MemAllocatorStatsOrBuilder | |
| MemChunk | Protobuf type tensorflow.MemChunk
|
| MemChunk.Builder | Protobuf type tensorflow.MemChunk
|
| MemChunkOrBuilder | |
| MemmappedFileSystemDirectory | A directory of regions in a memmapped file. |
| MemmappedFileSystemDirectory.Builder | A directory of regions in a memmapped file. |
| MemmappedFileSystemDirectoryElement | A message that describes one region of memmapped file. |
| MemmappedFileSystemDirectoryElement.Builder | A message that describes one region of memmapped file. |
| MemmappedFileSystemDirectoryElementOrBuilder | |
| MemmappedFileSystemDirectoryOrBuilder | |
| MemmappedFileSystemProtos | |
| MemoryDump | Protobuf type tensorflow.MemoryDump
|
| MemoryDump.Builder | Protobuf type tensorflow.MemoryDump
|
| MemoryDumpOrBuilder | |
| MemoryInfo | Protobuf type tensorflow.MemoryInfo
|
| MemoryInfo.Builder | Protobuf type tensorflow.MemoryInfo
|
| MemoryInfoOrBuilder | |
| MemoryLogRawAllocation | Protobuf type tensorflow.MemoryLogRawAllocation
|
| MemoryLogRawAllocation.Builder | Protobuf type tensorflow.MemoryLogRawAllocation
|
| MemoryLogRawAllocationOrBuilder | |
| MemoryLogRawDeallocation | Protobuf type tensorflow.MemoryLogRawDeallocation
|
| MemoryLogRawDeallocation.Builder | Protobuf type tensorflow.MemoryLogRawDeallocation
|
| MemoryLogRawDeallocationOrBuilder | |
| MemoryLogStep | Protobuf type tensorflow.MemoryLogStep
|
| MemoryLogStep.Builder | Protobuf type tensorflow.MemoryLogStep
|
| MemoryLogStepOrBuilder | |
| MemoryLogTensorAllocation | Protobuf type tensorflow.MemoryLogTensorAllocation
|
| MemoryLogTensorAllocation.Builder | Protobuf type tensorflow.MemoryLogTensorAllocation
|
| MemoryLogTensorAllocationOrBuilder | |
| MemoryLogTensorDeallocation | Protobuf type tensorflow.MemoryLogTensorDeallocation
|
| MemoryLogTensorDeallocation.Builder | Protobuf type tensorflow.MemoryLogTensorDeallocation
|
| MemoryLogTensorDeallocationOrBuilder | |
| MemoryLogTensorOutput | Protobuf type tensorflow.MemoryLogTensorOutput
|
| MemoryLogTensorOutput.Builder | Protobuf type tensorflow.MemoryLogTensorOutput
|
| MemoryLogTensorOutputOrBuilder | |
| MemoryStats | For memory tracking. |
| MemoryStats.Builder | For memory tracking. |
| MemoryStatsOrBuilder | |
| Merge<T extends TType> | Forwards the value of an available tensor from `inputs` to `output`. |
| MergeSummary | Merges summaries. |
| MergeV2Checkpoints | V2 format specific: merges the metadata files of sharded checkpoints. |
| MergeV2Checkpoints.Options | Optional attributes for MergeV2Checkpoints
|
| MetaGraphDef | NOTE: This protocol buffer is evolving, and will go through revisions in the coming months. |
| MetaGraphDef.Builder | NOTE: This protocol buffer is evolving, and will go through revisions in the coming months. |
| MetaGraphDef.MetaInfoDef | Meta information regarding the graph to be exported. |
| MetaGraphDef.MetaInfoDef.Builder | Meta information regarding the graph to be exported. |
| MetaGraphDef.MetaInfoDefOrBuilder | |
| MetaGraphDefOrBuilder | |
| MetaGraphProtos | |
| Metric<T extends TNumber> | Base class for Metrics |
| MetricEntry | Protobuf type tensorflow.MetricEntry
|
| MetricEntry.Builder | Protobuf type tensorflow.MetricEntry
|
| MetricEntryOrBuilder | |
| MetricReduction | Defines the different types of metric reductions |
| Metrics | Helper class with built-in metrics functions. |
| MetricsHelper | These are helper methods for Metrics and will be module private when Java modularity is applied to TensorFlow Java. |
| Mfcc | Transforms a spectrogram into a form that's useful for speech recognition. |
| Mfcc.Options | Optional attributes for Mfcc
|
| Min<T extends TType> | Computes the minimum of elements across dimensions of a tensor. |
| Min.Options | Optional attributes for Min
|
| Minimum<T extends TNumber> | Returns the min of x and y (i.e. |
| MinMaxNorm | Constrains the weights to have the norm between a lower bound and an upper bound. |
| MirrorPad<T extends TType> | Pads a tensor with mirrored values. |
| MirrorPadGrad<T extends TType> | Gradient op for `MirrorPad` op. |
| MiscDataBufferFactory | Factory of miscellaneous data buffers |
| MlirPassthroughOp | Wraps an arbitrary MLIR computation expressed as a module with a main() function. |
| Mod<T extends TNumber> | Returns element-wise remainder of division. |
| ModelDataset | Identity transformation that models performance. |
| ModelDataset.Options | Optional attributes for ModelDataset
|
| Momentum | Stochastic gradient descent plus momentum, either nesterov or traditional. |
| Mul<T extends TType> | Returns x * y element-wise. |
| MulNoNan<T extends TType> | Returns x * y element-wise. |
| MultiDeviceIterator | Creates a MultiDeviceIterator resource. |
| MultiDeviceIteratorFromStringHandle | Generates a MultiDeviceIterator resource from its provided string handle. |
| MultiDeviceIteratorFromStringHandle.Options | Optional attributes for MultiDeviceIteratorFromStringHandle
|
| MultiDeviceIteratorGetNextFromShard | Gets next element for the provided shard number. |
| MultiDeviceIteratorInit | Initializes the multi device iterator with the given dataset. |
| MultiDeviceIteratorToStringHandle | Produces a string handle for the given MultiDeviceIterator. |
| Multinomial<U extends TNumber> | Draws samples from a multinomial distribution. |
| Multinomial.Options | Optional attributes for Multinomial
|
| MutableDenseHashTable | Creates an empty hash table that uses tensors as the backing store. |
| MutableDenseHashTable.Options | Optional attributes for MutableDenseHashTable
|
| MutableHashTable | Creates an empty hash table. |
| MutableHashTable.Options | Optional attributes for MutableHashTable
|
| MutableHashTableOfTensors | Creates an empty hash table. |
| MutableHashTableOfTensors.Options | Optional attributes for MutableHashTableOfTensors
|
| Mutex | Creates a Mutex resource that can be locked by `MutexLock`. |
| Mutex.Options | Optional attributes for Mutex
|
| MutexLock | Locks a mutex resource. |
N
| Nadam | Nadam Optimizer that implements the NAdam algorithm. |
| NameAttrList | A list of attr names and their values. |
| NameAttrList.Builder | A list of attr names and their values. |
| NameAttrListOrBuilder | |
| NamedDevice | Protobuf type tensorflow.NamedDevice
|
| NamedDevice.Builder | Protobuf type tensorflow.NamedDevice
|
| NamedDeviceOrBuilder | |
| NamedTensorProto | A pair of tensor name and tensor values. |
| NamedTensorProto.Builder | A pair of tensor name and tensor values. |
| NamedTensorProtoOrBuilder | |
| NamedTensorProtos | |
| NamedTupleValue | Represents Python's namedtuple. |
| NamedTupleValue.Builder | Represents Python's namedtuple. |
| NamedTupleValueOrBuilder | |
| NcclAllReduce<T extends TNumber> | Outputs a tensor containing the reduction across all input tensors. |
| NcclAllReduce<T extends TNumber> | Outputs a tensor containing the reduction across all input tensors. |
| NcclBroadcast<T extends TNumber> | Sends `input` to all devices that are connected to the output. |
| NcclBroadcast<T extends TNumber> | Sends `input` to all devices that are connected to the output. |
| NcclReduce<T extends TNumber> | Reduces `input` from `num_devices` using `reduction` to a single device. |
| NcclReduce<T extends TNumber> | Reduces `input` from `num_devices` using `reduction` to a single device. |
| NdArray<T> | A data structure of N-dimensions. |
| NdArrays | Utility class for instantiating NdArray objects. |
| NdArraySequence<T extends NdArray<?>> | A sequence of elements of an N-dimensional array. |
| Ndtri<T extends TNumber> | |
| NearestNeighbors | Selects the k nearest centers for each point. |
| Neg<T extends TType> | Computes numerical negative value element-wise. |
| NegTrain | Training via negative sampling. |
| NextAfter<T extends TNumber> | Returns the next representable value of `x1` in the direction of `x2`, element-wise. |
| NextIteration<T extends TType> | Makes its input available to the next iteration. |
| NioDataBufferFactory | Factory of JDK NIO-based data buffers |
| NodeDef | Protobuf type tensorflow.NodeDef
|
| NodeDef.Builder | Protobuf type tensorflow.NodeDef
|
| NodeDef.ExperimentalDebugInfo | Protobuf type tensorflow.NodeDef.ExperimentalDebugInfo
|
| NodeDef.ExperimentalDebugInfo.Builder | Protobuf type tensorflow.NodeDef.ExperimentalDebugInfo
|
| NodeDef.ExperimentalDebugInfoOrBuilder | |
| NodeDefOrBuilder | |
| NodeExecStats | Time/size stats recorded for a single execution of a graph node. |
| NodeExecStats.Builder | Time/size stats recorded for a single execution of a graph node. |
| NodeExecStatsOrBuilder | |
| NodeOutput | Output sizes recorded for a single execution of a graph node. |
| NodeOutput.Builder | Output sizes recorded for a single execution of a graph node. |
| NodeOutputOrBuilder | |
| NodeProto | |
| NonDeterministicInts<U extends TType> | Non-deterministically generates some integers. |
| NoneValue | Represents None. |
| NoneValue.Builder | Represents None. |
| NoneValueOrBuilder | |
| NonMaxSuppression<T extends TNumber> | Greedily selects a subset of bounding boxes in descending order of score,
pruning away boxes that have high intersection-over-union (IOU) overlap with previously selected boxes. |
| NonMaxSuppression.Options | Optional attributes for NonMaxSuppression
|
| NonMaxSuppressionWithOverlaps | Greedily selects a subset of bounding boxes in descending order of score,
pruning away boxes that have high overlaps with previously selected boxes. |
| NonNeg | Constrains the weights to be non-negative. |
| NonSerializableDataset | |
| NonSerializableDataset | |
| NoOp | Does nothing. |
| NotBroadcastableException | Exception that indicates that static shapes are not able to broadcast among each other during arithmetic operations. |
| NotEqual | Returns the truth value of (x != y) element-wise. |
| NotEqual.Options | Optional attributes for NotEqual
|
| NthElement<T extends TNumber> | Finds values of the `n`-th order statistic for the last dimension. |
| NthElement.Options | Optional attributes for NthElement
|
O
| OneHot<U extends TType> | Returns a one-hot tensor. |
| OneHot.Options | Optional attributes for OneHot
|
| Ones<T extends TType> | Initializer that generates tensors initialized to 1. |
| Ones<T extends TType> | An operator creating a constant initialized with ones of the shape given by `dims`. |
| OnesLike<T extends TType> | Returns a tensor of ones with the same shape and type as x. |
| Op | A logical unit of computation. |
| OpDef | Defines an operation. |
| OpDef.ArgDef | For describing inputs and outputs. |
| OpDef.ArgDef.Builder | For describing inputs and outputs. |
| OpDef.ArgDefOrBuilder | |
| OpDef.AttrDef | Description of the graph-construction-time configuration of this Op. |
| OpDef.AttrDef.Builder | Description of the graph-construction-time configuration of this Op. |
| OpDef.AttrDefOrBuilder | |
| OpDef.Builder | Defines an operation. |
| OpDefOrBuilder | |
| OpDefProtos | |
| OpDeprecation | Information about version-dependent deprecation of an opProtobuf type tensorflow.OpDeprecation
|
| OpDeprecation.Builder | Information about version-dependent deprecation of an opProtobuf type tensorflow.OpDeprecation
|
| OpDeprecationOrBuilder | |
| Operand<T extends TType> | Interface implemented by operands of a TensorFlow operation. |
| Operands | Utilities for manipulating operand related types and lists. |
| Operation | Performs computation on Tensors. |
| OperationBuilder | A builder for Operations. |
| Operator | Annotation used by classes to make TensorFlow operations conveniently accessible via org.tensorflow.op.Ops or one of its groups. |
| OpList | A collection of OpDefsProtobuf type tensorflow.OpList
|
| OpList.Builder | A collection of OpDefsProtobuf type tensorflow.OpList
|
| OpListOrBuilder | |
| OptimizeDataset | Creates a dataset by applying optimizations to `input_dataset`. |
| OptimizeDataset.Options | Optional attributes for OptimizeDataset
|
| OptimizeDatasetV2 | Creates a dataset by applying related optimizations to `input_dataset`. |
| OptimizeDatasetV2.Options | Optional attributes for OptimizeDatasetV2
|
| Optimizer | Base class for gradient optimizers. |
| Optimizer.GradAndVar<T extends TType> | A class that holds a paired gradient and variable. |
| Optimizer.Options | Optional attributes for Optimizer |
| OptimizerOptions | Options passed to the graph optimizerProtobuf type tensorflow.OptimizerOptions
|
| OptimizerOptions.Builder | Options passed to the graph optimizerProtobuf type tensorflow.OptimizerOptions
|
| OptimizerOptions.GlobalJitLevel | Control the use of the compiler/jit. |
| OptimizerOptions.Level | Optimization levelProtobuf enum tensorflow.OptimizerOptions.Level
|
| OptimizerOptionsOrBuilder | |
| Optimizers | Enumerator used to create a new Optimizer with default parameters. |
| OptionalFromValue | Constructs an Optional variant from a tuple of tensors. |
| OptionalGetValue | Returns the value stored in an Optional variant or raises an error if none exists. |
| OptionalHasValue | Returns true if and only if the given Optional variant has a value. |
| OptionalNone | Creates an Optional variant with no value. |
| OrderedMapClear | Op removes all elements in the underlying container. |
| OrderedMapClear.Options | Optional attributes for OrderedMapClear
|
| OrderedMapIncompleteSize | Op returns the number of incomplete elements in the underlying container. |
| OrderedMapIncompleteSize.Options | Optional attributes for OrderedMapIncompleteSize
|
| OrderedMapPeek | Op peeks at the values at the specified key. |
| OrderedMapPeek.Options | Optional attributes for OrderedMapPeek
|
| OrderedMapSize | Op returns the number of elements in the underlying container. |
| OrderedMapSize.Options | Optional attributes for OrderedMapSize
|
| OrderedMapStage | Stage (key, values) in the underlying container which behaves like a ordered
associative container. |
| OrderedMapStage.Options | Optional attributes for OrderedMapStage
|
| OrderedMapUnstage | Op removes and returns the values associated with the key
from the underlying container. |
| OrderedMapUnstage.Options | Optional attributes for OrderedMapUnstage
|
| OrderedMapUnstageNoKey | Op removes and returns the (key, value) element with the smallest
key from the underlying container. |
| OrderedMapUnstageNoKey.Options | Optional attributes for OrderedMapUnstageNoKey
|
| OrdinalSelector | A TPU core selector Op. |
| Orthogonal<T extends TFloating> | Initializer that generates an orthogonal matrix. |
| OutfeedDequeue<T extends TType> | Retrieves a single tensor from the computation outfeed. |
| OutfeedDequeue.Options | Optional attributes for OutfeedDequeue
|
| OutfeedDequeueTuple | Retrieve multiple values from the computation outfeed. |
| OutfeedDequeueTuple.Options | Optional attributes for OutfeedDequeueTuple
|
| OutfeedDequeueTupleV2 | Retrieve multiple values from the computation outfeed. |
| OutfeedDequeueV2<T extends TType> | Retrieves a single tensor from the computation outfeed. |
| OutfeedEnqueue | Enqueue a Tensor on the computation outfeed. |
| OutfeedEnqueueTuple | Enqueue multiple Tensor values on the computation outfeed. |
| Output<T extends TType> | A symbolic handle to a tensor produced by an Operation. |
P
| Pad<T extends TType> | Pads a tensor. |
| Pad<T extends TType> | Wraps the XLA Pad operator, documented at
https://www.tensorflow.org/performance/xla/operation_semantics#pad . |
| PaddedBatchDataset | Creates a dataset that batches and pads `batch_size` elements from the input. |
| PaddedBatchDataset.Options | Optional attributes for PaddedBatchDataset
|
| PaddingFifoQueue | A queue that produces elements in first-in first-out order. |
| PaddingFifoQueue.Options | Optional attributes for PaddingFifoQueue
|
| PairValue | Represents a (key, value) pair. |
| PairValue.Builder | Represents a (key, value) pair. |
| PairValueOrBuilder | |
| ParallelConcat<T extends TType> | Concatenates a list of `N` tensors along the first dimension. |
| ParallelDynamicStitch<T extends TType> | Interleave the values from the `data` tensors into a single tensor. |
| ParameterizedTruncatedNormal<U extends TNumber> | Outputs random values from a normal distribution. |
| ParameterizedTruncatedNormal.Options | Optional attributes for ParameterizedTruncatedNormal
|
| ParseExample | Transforms a vector of tf.Example protos (as strings) into typed tensors. |
| ParseExampleDataset | Transforms `input_dataset` containing `Example` protos as vectors of DT_STRING into a dataset of `Tensor` or `SparseTensor` objects representing the parsed features. |
| ParseExampleDataset.Options | Optional attributes for ParseExampleDataset
|
| ParseSequenceExample | Transforms a vector of tf.io.SequenceExample protos (as strings) into typed tensors. |
| ParseSequenceExample.Options | Optional attributes for ParseSequenceExample
|
| ParseSingleExample | Transforms a tf.Example proto (as a string) into typed tensors. |
| ParseSingleSequenceExample | Transforms a scalar brain.SequenceExample proto (as strings) into typed tensors. |
| ParseSingleSequenceExample.Options | Optional attributes for ParseSingleSequenceExample
|
| ParseTensor<T extends TType> | Transforms a serialized tensorflow.TensorProto proto into a Tensor. |
| PartitionedInput<T extends TType> | An op that groups a list of partitioned inputs together. |
| PartitionedInput.Options | Optional attributes for PartitionedInput
|
| PartitionedOutput<T extends TType> | An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned
outputs outside the XLA computation. |
| PartitionedOutput.Options | Optional attributes for PartitionedOutput
|
| Placeholder<T extends TType> | A placeholder op for a value that will be fed into the computation. |
| Placeholder.Options | Optional attributes for Placeholder
|
| PlaceholderWithDefault<T extends TType> | A placeholder op that passes through `input` when its output is not fed. |
| PlatformInfo | Protobuf type tensorflow.PlatformInfo
|
| PlatformInfo.Builder | Protobuf type tensorflow.PlatformInfo
|
| PlatformInfoOrBuilder | |
| Poisson | Computes the Poisson loss between labels and predictions. |
| Poisson<T extends TNumber> | A metric that computes the poisson loss metric between labels and predictions. |
| Polygamma<T extends TNumber> | Compute the polygamma function \\(\psi^{(n)}(x)\\). |
| PopulationCount | Computes element-wise population count (a.k.a. |
| PositionIterator | |
| Pow<T extends TType> | Computes the power of one value to another. |
| PrefetchDataset | Creates a dataset that asynchronously prefetches elements from `input_dataset`. |
| PrefetchDataset.Options | Optional attributes for PrefetchDataset
|
| Prelinearize | An op which linearizes one Tensor value to an opaque variant tensor. |
| Prelinearize.Options | Optional attributes for Prelinearize
|
| PrelinearizeTuple | An op which linearizes multiple Tensor values to an opaque variant tensor. |
| PrelinearizeTuple.Options | Optional attributes for PrelinearizeTuple
|
| PreventGradient<T extends TType> | An identity op that triggers an error if a gradient is requested. |
| PreventGradient.Options | Optional attributes for PreventGradient
|
| Prints a string scalar. | |
| Print.Options | Optional attributes for Print
|
| PriorityQueue | A queue that produces elements sorted by the first component value. |
| PriorityQueue.Options | Optional attributes for PriorityQueue
|
| PrivateThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| PrivateThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| Prod<T extends TType> | Computes the product of elements across dimensions of a tensor. |
| Prod.Options | Optional attributes for Prod
|
| ProfileOptions | Next ID: 11Protobuf type tensorflow.ProfileOptions
|
| ProfileOptions.Builder | Next ID: 11Protobuf type tensorflow.ProfileOptions
|
| ProfileOptions.DeviceType | Protobuf enum tensorflow.ProfileOptions.DeviceType
|
| ProfileOptionsOrBuilder | |
| ProfilerOptionsProtos |
Q
| Qr<T extends TType> | Computes the QR decompositions of one or more matrices. |
| Qr.Options | Optional attributes for Qr
|
| Quantize<T extends TType> | Quantize the 'input' tensor of type float to 'output' tensor of type 'T'. |
| Quantize.Options | Optional attributes for Quantize
|
| QuantizeAndDequantize<T extends TNumber> | Quantizes then dequantizes a tensor. |
| QuantizeAndDequantize.Options | Optional attributes for QuantizeAndDequantize
|
| QuantizeAndDequantizeV3<T extends TNumber> | Quantizes then dequantizes a tensor. |
| QuantizeAndDequantizeV3.Options | Optional attributes for QuantizeAndDequantizeV3
|
| QuantizeAndDequantizeV4<T extends TNumber> | Returns the gradient of `quantization.QuantizeAndDequantizeV4`. |
| QuantizeAndDequantizeV4.Options | Optional attributes for QuantizeAndDequantizeV4
|
| QuantizeAndDequantizeV4Grad<T extends TNumber> | Returns the gradient of `QuantizeAndDequantizeV4`. |
| QuantizeAndDequantizeV4Grad.Options | Optional attributes for QuantizeAndDequantizeV4Grad
|
| QuantizedAdd<V extends TType> | Returns x + y element-wise, working on quantized buffers. |
| QuantizedAvgPool<T extends TType> | Produces the average pool of the input tensor for quantized types. |
| QuantizedBatchNormWithGlobalNormalization<U extends TType> | Quantized Batch normalization. |
| QuantizedBiasAdd<V extends TType> | Adds Tensor 'bias' to Tensor 'input' for Quantized types. |
| QuantizedConcat<T extends TType> | Concatenates quantized tensors along one dimension. |
| QuantizedConv2d<V extends TType> | Computes a 2D convolution given quantized 4D input and filter tensors. |
| QuantizedConv2d.Options | Optional attributes for QuantizedConv2d
|
| QuantizedConv2DAndRelu<V extends TType> | |
| QuantizedConv2DAndRelu.Options | Optional attributes for QuantizedConv2DAndRelu
|
| QuantizedConv2DAndReluAndRequantize<V extends TType> | |
| QuantizedConv2DAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DAndReluAndRequantize
|
| QuantizedConv2DAndRequantize<V extends TType> | |
| QuantizedConv2DAndRequantize.Options | Optional attributes for QuantizedConv2DAndRequantize
|
| QuantizedConv2DPerChannel<V extends TType> | Computes QuantizedConv2D per channel. |
| QuantizedConv2DPerChannel.Options | Optional attributes for QuantizedConv2DPerChannel
|
| QuantizedConv2DWithBias<V extends TType> | |
| QuantizedConv2DWithBias.Options | Optional attributes for QuantizedConv2DWithBias
|
| QuantizedConv2DWithBiasAndRelu<V extends TType> | |
| QuantizedConv2DWithBiasAndRelu.Options | Optional attributes for QuantizedConv2DWithBiasAndRelu
|
| QuantizedConv2DWithBiasAndReluAndRequantize<W extends TType> | |
| QuantizedConv2DWithBiasAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasAndReluAndRequantize
|
| QuantizedConv2DWithBiasAndRequantize<W extends TType> | |
| QuantizedConv2DWithBiasAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasAndRequantize
|
| QuantizedConv2DWithBiasSignedSumAndReluAndRequantize<X extends TType> | |
| QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasSignedSumAndReluAndRequantize
|
| QuantizedConv2DWithBiasSumAndRelu<V extends TType> | |
| QuantizedConv2DWithBiasSumAndRelu.Options | Optional attributes for QuantizedConv2DWithBiasSumAndRelu
|
| QuantizedConv2DWithBiasSumAndReluAndRequantize<X extends TType> | |
| QuantizedConv2DWithBiasSumAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasSumAndReluAndRequantize
|
| QuantizedDepthwiseConv2D<V extends TType> | Computes quantized depthwise Conv2D. |
| QuantizedDepthwiseConv2D.Options | Optional attributes for QuantizedDepthwiseConv2D
|
| QuantizedDepthwiseConv2DWithBias<V extends TType> | Computes quantized depthwise Conv2D with Bias. |
| QuantizedDepthwiseConv2DWithBias.Options | Optional attributes for QuantizedDepthwiseConv2DWithBias
|
| QuantizedDepthwiseConv2DWithBiasAndRelu<V extends TType> | Computes quantized depthwise Conv2D with Bias and Relu. |
| QuantizedDepthwiseConv2DWithBiasAndRelu.Options | Optional attributes for QuantizedDepthwiseConv2DWithBiasAndRelu
|
| QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize<W extends TType> | Computes quantized depthwise Conv2D with Bias, Relu and Requantize. |
| QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.Options | Optional attributes for QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize
|
| QuantizedInstanceNorm<T extends TType> | Quantized Instance normalization. |
| QuantizedInstanceNorm.Options | Optional attributes for QuantizedInstanceNorm
|
| QuantizedMatMul<V extends TType> | Perform a quantized matrix multiplication of `a` by the matrix `b`. |
| QuantizedMatMul.Options | Optional attributes for QuantizedMatMul
|
| QuantizedMatMulWithBias<W extends TType> | Performs a quantized matrix multiplication of `a` by the matrix `b` with bias add. |
| QuantizedMatMulWithBias.Options | Optional attributes for QuantizedMatMulWithBias
|
| QuantizedMatMulWithBiasAndDequantize<W extends TNumber> | |
| QuantizedMatMulWithBiasAndDequantize.Options | Optional attributes for QuantizedMatMulWithBiasAndDequantize
|
| QuantizedMatMulWithBiasAndRelu<V extends TType> | Perform a quantized matrix multiplication of `a` by the matrix `b` with bias add and relu fusion. |
| QuantizedMatMulWithBiasAndRelu.Options | Optional attributes for QuantizedMatMulWithBiasAndRelu
|
| QuantizedMatMulWithBiasAndReluAndRequantize<W extends TType> | Perform a quantized matrix multiplication of `a` by the matrix `b` with bias add and relu and requantize fusion. |
| QuantizedMatMulWithBiasAndReluAndRequantize.Options | Optional attributes for QuantizedMatMulWithBiasAndReluAndRequantize
|
| QuantizedMatMulWithBiasAndRequantize<W extends TType> | |
| QuantizedMatMulWithBiasAndRequantize.Options | Optional attributes for QuantizedMatMulWithBiasAndRequantize
|
| QuantizedMaxPool<T extends TType> | Produces the max pool of the input tensor for quantized types. |
| QuantizedMul<V extends TType> | Returns x * y element-wise, working on quantized buffers. |
| QuantizeDownAndShrinkRange<U extends TType> | Convert the quantized 'input' tensor into a lower-precision 'output', using the
actual distribution of the values to maximize the usage of the lower bit depth and adjusting the output min and max ranges accordingly. |
| QuantizedRelu<U extends TType> | Computes Quantized Rectified Linear: `max(features, 0)` |
| QuantizedRelu6<U extends TType> | Computes Quantized Rectified Linear 6: `min(max(features, 0), 6)` |
| QuantizedReluX<U extends TType> | Computes Quantized Rectified Linear X: `min(max(features, 0), max_value)` |
| QuantizedReshape<T extends TType> | Reshapes a quantized tensor as per the Reshape op. |
| QuantizedResizeBilinear<T extends TType> | Resize quantized `images` to `size` using quantized bilinear interpolation. |
| QuantizedResizeBilinear.Options | Optional attributes for QuantizedResizeBilinear
|
| QueueClose | Closes the given queue. |
| QueueClose.Options | Optional attributes for QueueClose
|
| QueueDequeue | Dequeues a tuple of one or more tensors from the given queue. |
| QueueDequeue.Options | Optional attributes for QueueDequeue
|
| QueueDequeueMany | Dequeues `n` tuples of one or more tensors from the given queue. |
| QueueDequeueMany.Options | Optional attributes for QueueDequeueMany
|
| QueueDequeueUpTo | Dequeues `n` tuples of one or more tensors from the given queue. |
| QueueDequeueUpTo.Options | Optional attributes for QueueDequeueUpTo
|
| QueueEnqueue | Enqueues a tuple of one or more tensors in the given queue. |
| QueueEnqueue.Options | Optional attributes for QueueEnqueue
|
| QueueEnqueueMany | Enqueues zero or more tuples of one or more tensors in the given queue. |
| QueueEnqueueMany.Options | Optional attributes for QueueEnqueueMany
|
| QueueIsClosed | Returns true if queue is closed. |
| QueueRunnerDef | Protocol buffer representing a QueueRunner. |
| QueueRunnerDef.Builder | Protocol buffer representing a QueueRunner. |
| QueueRunnerDefOrBuilder | |
| QueueRunnerProtos | |
| QueueSize | Computes the number of elements in the given queue. |
R
| RaggedBincount<U extends TNumber> | Counts the number of occurrences of each value in an integer array. |
| RaggedBincount.Options | Optional attributes for RaggedBincount
|
| RaggedCountSparseOutput<U extends TNumber> | Performs sparse-output bin counting for a ragged tensor input. |
| RaggedCountSparseOutput.Options | Optional attributes for RaggedCountSparseOutput
|
| RaggedCross<T extends TType, U extends TNumber> | Generates a feature cross from a list of tensors, and returns it as a RaggedTensor. |
| RaggedGather<T extends TNumber, U extends TType> | Gather ragged slices from `params` axis `0` according to `indices`. |
| RaggedRange<U extends TNumber, T extends TNumber> | Returns a `RaggedTensor` containing the specified sequences of numbers. |
| RaggedTensorFromVariant<U extends TNumber, T extends TType> | Decodes a `variant` Tensor into a `RaggedTensor`. |
| RaggedTensorToSparse<U extends TType> | Converts a `RaggedTensor` into a `SparseTensor` with the same values. |
| RaggedTensorToTensor<U extends TType> | Create a dense tensor from a ragged tensor, possibly altering its shape. |
| RaggedTensorToVariant | Encodes a `RaggedTensor` into a `variant` Tensor. |
| RaggedTensorToVariantGradient<U extends TType> | Helper used to compute the gradient for `RaggedTensorToVariant`. |
| RandomCrop<T extends TNumber> | Randomly crop `image`. |
| RandomCrop.Options | Optional attributes for RandomCrop
|
| RandomDataset | Creates a Dataset that returns pseudorandom numbers. |
| RandomDataset | Creates a Dataset that returns pseudorandom numbers. |
| RandomGamma<U extends TNumber> | Outputs random values from the Gamma distribution(s) described by alpha. |
| RandomGamma.Options | Optional attributes for RandomGamma
|
| RandomGammaGrad<T extends TNumber> | Computes the derivative of a Gamma random sample w.r.t. |
| RandomNormal<T extends TFloating> | Initializer that generates tensors with a normal distribution. |
| RandomPoisson<V extends TNumber> | Outputs random values from the Poisson distribution(s) described by rate. |
| RandomPoisson.Options | Optional attributes for RandomPoisson
|
| RandomShuffle<T extends TType> | Randomly shuffles a tensor along its first dimension. |
| RandomShuffle.Options | Optional attributes for RandomShuffle
|
| RandomShuffleQueue | A queue that randomizes the order of elements. |
| RandomShuffleQueue.Options | Optional attributes for RandomShuffleQueue
|
| RandomStandardNormal<U extends TNumber> | Outputs random values from a normal distribution. |
| RandomStandardNormal.Options | Optional attributes for RandomStandardNormal
|
| RandomUniform<T extends TNumber> | Initializer that generates tensors with a uniform distribution. |
| RandomUniform<U extends TNumber> | Outputs random values from a uniform distribution. |
| RandomUniform.Options | Optional attributes for RandomUniform
|
| RandomUniformInt<U extends TNumber> | Outputs random integers from a uniform distribution. |
| RandomUniformInt.Options | Optional attributes for RandomUniformInt
|
| Range<T extends TNumber> | Creates a sequence of numbers. |
| RangeDataset | Creates a dataset with a range of values. |
| Rank | Returns the rank of a tensor. |
| RawDataBufferFactory | Factory of raw data buffers |
| RawOp | A base class for Op implementations that are backed by a single Operation. |
| RawTensor | A tensor which memory has not been mapped to a data space directly accessible from the JVM. |
| ReaderBaseProtos | |
| ReaderBaseState | For serializing and restoring the state of ReaderBase, see reader_base.h for details. |
| ReaderBaseState.Builder | For serializing and restoring the state of ReaderBase, see reader_base.h for details. |
| ReaderBaseStateOrBuilder | |
| ReaderNumRecordsProduced | Returns the number of records this Reader has produced. |
| ReaderNumWorkUnitsCompleted | Returns the number of work units this Reader has finished processing. |
| ReaderRead | Returns the next record (key, value pair) produced by a Reader. |
| ReaderReadUpTo | Returns up to `num_records` (key, value) pairs produced by a Reader. |
| ReaderReset | Restore a Reader to its initial clean state. |
| ReaderRestoreState | Restore a reader to a previously saved state. |
| ReaderSerializeState | Produce a string tensor that encodes the state of a Reader. |
| ReadFile | Reads and outputs the entire contents of the input filename. |
| ReadVariableOp<T extends TType> | Reads the value of a variable. |
| Real<U extends TNumber> | Returns the real part of a complex number. |
| RealDiv<T extends TType> | Returns x / y element-wise for real types. |
| RebatchDataset | Creates a dataset that changes the batch size. |
| RebatchDataset | Creates a dataset that changes the batch size. |
| RebatchDataset.Options | Optional attributes for RebatchDataset
|
| RebatchDataset.Options | Optional attributes for RebatchDataset
|
| RebatchDatasetV2 | Creates a dataset that changes the batch size. |
| Reciprocal<T extends TType> | Computes the reciprocal of x element-wise. |
| ReciprocalGrad<T extends TType> | Computes the gradient for the inverse of `x` wrt its input. |
| RecordInput | Emits randomized records. |
| RecordInput.Options | Optional attributes for RecordInput
|
| Recv<T extends TType> | Receives the named tensor from send_device on recv_device. |
| Recv<T extends TType> | Receives the named tensor from another XLA computation. |
| Recv.Options | Optional attributes for Recv
|
| RecvTPUEmbeddingActivations | An op that receives embedding activations on the TPU. |
| Reduce<T extends TNumber> | Encapsulates metrics that perform a reduce operation on the metric values. |
| Reduce<T extends TNumber> | Mutually reduces multiple tensors of identical type and shape. |
| Reduce.Options | Optional attributes for Reduce
|
| ReduceAll | Computes the "logical and" of elements across dimensions of a tensor. |
| ReduceAll.Options | Optional attributes for ReduceAll
|
| ReduceAny | Computes the "logical or" of elements across dimensions of a tensor. |
| ReduceAny.Options | Optional attributes for ReduceAny
|
| ReduceJoin | Joins a string Tensor across the given dimensions. |
| ReduceJoin.Options | Optional attributes for ReduceJoin
|
| ReduceMax<T extends TType> | Computes the maximum of elements across dimensions of a tensor. |
| ReduceMax.Options | Optional attributes for ReduceMax
|
| ReduceMin<T extends TType> | Computes the minimum of elements across dimensions of a tensor. |
| ReduceMin.Options | Optional attributes for ReduceMin
|
| ReduceProd<T extends TType> | Computes the product of elements across dimensions of a tensor. |
| ReduceProd.Options | Optional attributes for ReduceProd
|
| ReduceSum<T extends TType> | Computes the sum of elements across dimensions of a tensor. |
| ReduceSum.Options | Optional attributes for ReduceSum
|
| ReduceV2<T extends TNumber> | Mutually reduces multiple tensors of identical type and shape. |
| ReduceV2.Options | Optional attributes for ReduceV2
|
| Reduction | Type of Loss Reduction
|
| RefEnter<T extends TType> | Creates or finds a child frame, and makes `data` available to the child frame. |
| RefEnter.Options | Optional attributes for RefEnter
|
| RefExit<T extends TType> | Exits the current frame to its parent frame. |
| RefIdentity<T extends TType> | Return the same ref tensor as the input ref tensor. |
| RefMerge<T extends TType> | Forwards the value of an available tensor from `inputs` to `output`. |
| RefNextIteration<T extends TType> | Makes its input available to the next iteration. |
| RefSelect<T extends TType> | Forwards the `index`th element of `inputs` to `output`. |
| RefSwitch<T extends TType> | Forwards the ref tensor `data` to the output port determined by `pred`. |
| RegexFullMatch | Check if the input matches the regex pattern. |
| RegexReplace | Replaces matches of the `pattern` regular expression in `input` with the replacement string provided in `rewrite`. |
| RegexReplace.Options | Optional attributes for RegexReplace
|
| RegisterDataset | Registers a dataset with the tf.data service. |
| RelativeDimensionalSpace | |
| Relu<T extends TType> | Computes rectified linear: `max(features, 0)`. |
| ReLU<T extends TNumber> | Rectified Linear Unit(ReLU) activation. |
| Relu6<T extends TNumber> | Computes rectified linear 6: `min(max(features, 0), 6)`. |
| Relu6Grad<T extends TNumber> | Computes rectified linear 6 gradients for a Relu6 operation. |
| ReluGrad<T extends TNumber> | Computes rectified linear gradients for a Relu operation. |
| RemoteFusedGraphExecute | Execute a sub graph on a remote processor. |
| RemoteFusedGraphExecuteInfo | Protocol buffer representing a handle to a tensorflow resource. |
| RemoteFusedGraphExecuteInfo.Builder | Protocol buffer representing a handle to a tensorflow resource. |
| RemoteFusedGraphExecuteInfo.TensorShapeTypeProto | Protobuf type tensorflow.RemoteFusedGraphExecuteInfo.TensorShapeTypeProto
|
| RemoteFusedGraphExecuteInfo.TensorShapeTypeProto.Builder | Protobuf type tensorflow.RemoteFusedGraphExecuteInfo.TensorShapeTypeProto
|
| RemoteFusedGraphExecuteInfo.TensorShapeTypeProtoOrBuilder | |
| RemoteFusedGraphExecuteInfoOrBuilder | |
| RemoteFusedGraphExecuteInfoProto | |
| RemoteProfilerSessionManagerOptions | Options for remote profiler session manager. |
| RemoteProfilerSessionManagerOptions.Builder | Options for remote profiler session manager. |
| RemoteProfilerSessionManagerOptionsOrBuilder | |
| RemoteTensorHandle | Protobuf type tensorflow.eager.RemoteTensorHandle
|
| RemoteTensorHandle.Builder | Protobuf type tensorflow.eager.RemoteTensorHandle
|
| RemoteTensorHandleOrBuilder | |
| RemoteTensorHandleProtos | |
| RepeatDataset | Creates a dataset that emits the outputs of `input_dataset` `count` times. |
| ReplicaId | Replica ID. |
| ReplicatedInput<T extends TType> | Connects N inputs to an N-way replicated TPU computation. |
| ReplicatedInput.Options | Optional attributes for ReplicatedInput
|
| ReplicatedOutput<T extends TType> | Connects N outputs from an N-way replicated TPU computation. |
| ReplicateMetadata | Metadata indicating how the TPU computation should be replicated. |
| ReplicateMetadata.Options | Optional attributes for ReplicateMetadata
|
| RequantizationRange | Computes a range that covers the actual values present in a quantized tensor. |
| RequantizationRangePerChannel | Computes requantization range per channel. |
| Requantize<U extends TType> | Converts the quantized `input` tensor into a lower-precision `output`. |
| RequantizePerChannel<U extends TType> | Requantizes input with min and max values known per channel. |
| RequestedExitCode | Protobuf type tensorflow.RequestedExitCode
|
| RequestedExitCode.Builder | Protobuf type tensorflow.RequestedExitCode
|
| RequestedExitCodeOrBuilder | |
| Reshape<T extends TType> | Reshapes a tensor. |
| ResizeArea | Resize `images` to `size` using area interpolation. |
| ResizeArea.Options | Optional attributes for ResizeArea
|
| ResizeBicubic | Resize `images` to `size` using bicubic interpolation. |
| ResizeBicubic.Options | Optional attributes for ResizeBicubic
|
| ResizeBicubicGrad<T extends TNumber> | Computes the gradient of bicubic interpolation. |
| ResizeBicubicGrad.Options | Optional attributes for ResizeBicubicGrad
|
| ResizeBilinear | Resize `images` to `size` using bilinear interpolation. |
| ResizeBilinear.Options | Optional attributes for ResizeBilinear
|
| ResizeBilinearGrad<T extends TNumber> | Computes the gradient of bilinear interpolation. |
| ResizeBilinearGrad.Options | Optional attributes for ResizeBilinearGrad
|
| ResizeNearestNeighbor<T extends TNumber> | Resize `images` to `size` using nearest neighbor interpolation. |
| ResizeNearestNeighbor.Options | Optional attributes for ResizeNearestNeighbor
|
| ResizeNearestNeighborGrad<T extends TNumber> | Computes the gradient of nearest neighbor interpolation. |
| ResizeNearestNeighborGrad.Options | Optional attributes for ResizeNearestNeighborGrad
|
| ResourceAccumulatorApplyGradient | Applies a gradient to a given accumulator. |
| ResourceAccumulatorNumAccumulated | Returns the number of gradients aggregated in the given accumulators. |
| ResourceAccumulatorSetGlobalStep | Updates the accumulator with a new value for global_step. |
| ResourceAccumulatorTakeGradient<T extends TType> | Extracts the average gradient in the given ConditionalAccumulator. |
| ResourceApplyAdadelta | Update '*var' according to the adadelta scheme. |
| ResourceApplyAdadelta.Options | Optional attributes for ResourceApplyAdadelta
|
| ResourceApplyAdagrad | Update '*var' according to the adagrad scheme. |
| ResourceApplyAdagrad.Options | Optional attributes for ResourceApplyAdagrad
|
| ResourceApplyAdagradDa | Update '*var' according to the proximal adagrad scheme. |
| ResourceApplyAdagradDa.Options | Optional attributes for ResourceApplyAdagradDa
|
| ResourceApplyAdam | Update '*var' according to the Adam algorithm. |
| ResourceApplyAdam.Options | Optional attributes for ResourceApplyAdam
|
| ResourceApplyAdaMax | Update '*var' according to the AdaMax algorithm. |
| ResourceApplyAdaMax.Options | Optional attributes for ResourceApplyAdaMax
|
| ResourceApplyAdamWithAmsgrad | Update '*var' according to the Adam algorithm. |
| ResourceApplyAdamWithAmsgrad.Options | Optional attributes for ResourceApplyAdamWithAmsgrad
|
| ResourceApplyAddSign | Update '*var' according to the AddSign update. |
| ResourceApplyAddSign.Options | Optional attributes for ResourceApplyAddSign
|
| ResourceApplyCenteredRmsProp | Update '*var' according to the centered RMSProp algorithm. |
| ResourceApplyCenteredRmsProp.Options | Optional attributes for ResourceApplyCenteredRmsProp
|
| ResourceApplyFtrl | Update '*var' according to the Ftrl-proximal scheme. |
| ResourceApplyFtrl.Options | Optional attributes for ResourceApplyFtrl
|
| ResourceApplyGradientDescent | Update '*var' by subtracting 'alpha' * 'delta' from it. |
| ResourceApplyGradientDescent.Options | Optional attributes for ResourceApplyGradientDescent
|
| ResourceApplyKerasMomentum | Update '*var' according to the momentum scheme. |
| ResourceApplyKerasMomentum.Options | Optional attributes for ResourceApplyKerasMomentum
|
| ResourceApplyMomentum | Update '*var' according to the momentum scheme. |
| ResourceApplyMomentum.Options | Optional attributes for ResourceApplyMomentum
|
| ResourceApplyPowerSign | Update '*var' according to the AddSign update. |
| ResourceApplyPowerSign.Options | Optional attributes for ResourceApplyPowerSign
|
| ResourceApplyProximalAdagrad | Update '*var' and '*accum' according to FOBOS with Adagrad learning rate. |
| ResourceApplyProximalAdagrad.Options | Optional attributes for ResourceApplyProximalAdagrad
|
| ResourceApplyProximalGradientDescent | Update '*var' as FOBOS algorithm with fixed learning rate. |
| ResourceApplyProximalGradientDescent.Options | Optional attributes for ResourceApplyProximalGradientDescent
|
| ResourceApplyRmsProp | Update '*var' according to the RMSProp algorithm. |
| ResourceApplyRmsProp.Options | Optional attributes for ResourceApplyRmsProp
|
| ResourceConditionalAccumulator | A conditional accumulator for aggregating gradients. |
| ResourceConditionalAccumulator.Options | Optional attributes for ResourceConditionalAccumulator
|
| ResourceCountUpTo<T extends TNumber> | Increments variable pointed to by 'resource' until it reaches 'limit'. |
| ResourceDtypeAndShape | Protobuf type tensorflow.eager.ResourceDtypeAndShape
|
| ResourceDtypeAndShape.Builder | Protobuf type tensorflow.eager.ResourceDtypeAndShape
|
| ResourceDtypeAndShapeOrBuilder | |
| ResourceGather<U extends TType> | Gather slices from the variable pointed to by `resource` according to `indices`. |
| ResourceGather.Options | Optional attributes for ResourceGather
|
| ResourceGatherNd<U extends TType> | |
| ResourceHandle | |
| ResourceHandleProto | Protocol buffer representing a handle to a tensorflow resource. |
| ResourceHandleProto.Builder | Protocol buffer representing a handle to a tensorflow resource. |
| ResourceHandleProto.DtypeAndShape | Protocol buffer representing a pair of (data type, tensor shape). |
| ResourceHandleProto.DtypeAndShape.Builder | Protocol buffer representing a pair of (data type, tensor shape). |
| ResourceHandleProto.DtypeAndShapeOrBuilder | |
| ResourceHandleProtoOrBuilder | |
| ResourceScatterAdd | Adds sparse updates to the variable referenced by `resource`. |
| ResourceScatterDiv | Divides sparse updates into the variable referenced by `resource`. |
| ResourceScatterMax | Reduces sparse updates into the variable referenced by `resource` using the `max` operation. |
| ResourceScatterMin | Reduces sparse updates into the variable referenced by `resource` using the `min` operation. |
| ResourceScatterMul | Multiplies sparse updates into the variable referenced by `resource`. |
| ResourceScatterNdAdd | Applies sparse addition to individual values or slices in a Variable. |
| ResourceScatterNdAdd.Options | Optional attributes for ResourceScatterNdAdd
|
| ResourceScatterNdMax | |
| ResourceScatterNdMax.Options | Optional attributes for ResourceScatterNdMax
|
| ResourceScatterNdMin | |
| ResourceScatterNdMin.Options | Optional attributes for ResourceScatterNdMin
|
| ResourceScatterNdSub | Applies sparse subtraction to individual values or slices in a Variable. |
| ResourceScatterNdSub.Options | Optional attributes for ResourceScatterNdSub
|
| ResourceScatterNdUpdate | Applies sparse `updates` to individual values or slices within a given
variable according to `indices`. |
| ResourceScatterNdUpdate.Options | Optional attributes for ResourceScatterNdUpdate
|
| ResourceScatterSub | Subtracts sparse updates from the variable referenced by `resource`. |
| ResourceScatterUpdate | Assigns sparse updates to the variable referenced by `resource`. |
| ResourceSparseApplyAdadelta | var: Should be from a Variable(). |
| ResourceSparseApplyAdadelta.Options | Optional attributes for ResourceSparseApplyAdadelta
|
| ResourceSparseApplyAdagrad | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
| ResourceSparseApplyAdagrad.Options | Optional attributes for ResourceSparseApplyAdagrad
|
| ResourceSparseApplyAdagradDa | Update entries in '*var' and '*accum' according to the proximal adagrad scheme. |
| ResourceSparseApplyAdagradDa.Options | Optional attributes for ResourceSparseApplyAdagradDa
|
| ResourceSparseApplyAdagradV2 | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
| ResourceSparseApplyAdagradV2.Options | Optional attributes for ResourceSparseApplyAdagradV2
|
| ResourceSparseApplyCenteredRmsProp | Update '*var' according to the centered RMSProp algorithm. |
| ResourceSparseApplyCenteredRmsProp.Options | Optional attributes for ResourceSparseApplyCenteredRmsProp
|
| ResourceSparseApplyFtrl | Update relevant entries in '*var' according to the Ftrl-proximal scheme. |
| ResourceSparseApplyFtrl.Options | Optional attributes for ResourceSparseApplyFtrl
|
| ResourceSparseApplyKerasMomentum | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
| ResourceSparseApplyKerasMomentum.Options | Optional attributes for ResourceSparseApplyKerasMomentum
|
| ResourceSparseApplyMomentum | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
| ResourceSparseApplyMomentum.Options | Optional attributes for ResourceSparseApplyMomentum
|
| ResourceSparseApplyProximalAdagrad | Sparse update entries in '*var' and '*accum' according to FOBOS algorithm. |
| ResourceSparseApplyProximalAdagrad.Options | Optional attributes for ResourceSparseApplyProximalAdagrad
|
| ResourceSparseApplyProximalGradientDescent | Sparse update '*var' as FOBOS algorithm with fixed learning rate. |
| ResourceSparseApplyProximalGradientDescent.Options | Optional attributes for ResourceSparseApplyProximalGradientDescent
|
| ResourceSparseApplyRmsProp | Update '*var' according to the RMSProp algorithm. |
| ResourceSparseApplyRmsProp.Options | Optional attributes for ResourceSparseApplyRmsProp
|
| ResourceStridedSliceAssign | Assign `value` to the sliced l-value reference of `ref`. |
| ResourceStridedSliceAssign.Options | Optional attributes for ResourceStridedSliceAssign
|
| Restore | Restores tensors from a V2 checkpoint. |
| RestoreSlice<T extends TType> | Restores a tensor from checkpoint files. |
| RestoreSlice.Options | Optional attributes for RestoreSlice
|
| RetrieveTPUEmbeddingAdadeltaParameters | Retrieve Adadelta embedding parameters. |
| RetrieveTPUEmbeddingAdadeltaParameters.Options | Optional attributes for RetrieveTPUEmbeddingAdadeltaParameters
|
| RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug | Retrieve Adadelta embedding parameters with debug support. |
| RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug
|
| RetrieveTPUEmbeddingAdagradParameters | Retrieve Adagrad embedding parameters. |
| RetrieveTPUEmbeddingAdagradParameters.Options | Optional attributes for RetrieveTPUEmbeddingAdagradParameters
|
| RetrieveTPUEmbeddingAdagradParametersGradAccumDebug | Retrieve Adagrad embedding parameters with debug support. |
| RetrieveTPUEmbeddingAdagradParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingAdagradParametersGradAccumDebug
|
| RetrieveTPUEmbeddingADAMParameters | Retrieve ADAM embedding parameters. |
| RetrieveTPUEmbeddingADAMParameters.Options | Optional attributes for RetrieveTPUEmbeddingADAMParameters
|
| RetrieveTPUEmbeddingADAMParametersGradAccumDebug | Retrieve ADAM embedding parameters with debug support. |
| RetrieveTPUEmbeddingADAMParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingADAMParametersGradAccumDebug
|
| RetrieveTPUEmbeddingCenteredRMSPropParameters | Retrieve centered RMSProp embedding parameters. |
| RetrieveTPUEmbeddingCenteredRMSPropParameters.Options | Optional attributes for RetrieveTPUEmbeddingCenteredRMSPropParameters
|
| RetrieveTPUEmbeddingFTRLParameters | Retrieve FTRL embedding parameters. |
| RetrieveTPUEmbeddingFTRLParameters.Options | Optional attributes for RetrieveTPUEmbeddingFTRLParameters
|
| RetrieveTPUEmbeddingFTRLParametersGradAccumDebug | Retrieve FTRL embedding parameters with debug support. |
| RetrieveTPUEmbeddingFTRLParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingFTRLParametersGradAccumDebug
|
| RetrieveTPUEmbeddingMDLAdagradLightParameters | Retrieve MDL Adagrad Light embedding parameters. |
| RetrieveTPUEmbeddingMDLAdagradLightParameters.Options | Optional attributes for RetrieveTPUEmbeddingMDLAdagradLightParameters
|
| RetrieveTPUEmbeddingMomentumParameters | Retrieve Momentum embedding parameters. |
| RetrieveTPUEmbeddingMomentumParameters.Options | Optional attributes for RetrieveTPUEmbeddingMomentumParameters
|
| RetrieveTPUEmbeddingMomentumParametersGradAccumDebug | Retrieve Momentum embedding parameters with debug support. |
| RetrieveTPUEmbeddingMomentumParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingMomentumParametersGradAccumDebug
|
| RetrieveTPUEmbeddingProximalAdagradParameters | Retrieve proximal Adagrad embedding parameters. |
| RetrieveTPUEmbeddingProximalAdagradParameters.Options | Optional attributes for RetrieveTPUEmbeddingProximalAdagradParameters
|
| RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug | Retrieve proximal Adagrad embedding parameters with debug support. |
| RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug
|
| RetrieveTPUEmbeddingProximalYogiParameters | |
| RetrieveTPUEmbeddingProximalYogiParameters.Options | Optional attributes for RetrieveTPUEmbeddingProximalYogiParameters
|
| RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug | |
| RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug
|
| RetrieveTPUEmbeddingRMSPropParameters | Retrieve RMSProp embedding parameters. |
| RetrieveTPUEmbeddingRMSPropParameters.Options | Optional attributes for RetrieveTPUEmbeddingRMSPropParameters
|
| RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug | Retrieve RMSProp embedding parameters with debug support. |
| RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug
|
| RetrieveTPUEmbeddingStochasticGradientDescentParameters | Retrieve SGD embedding parameters. |
| RetrieveTPUEmbeddingStochasticGradientDescentParameters.Options | Optional attributes for RetrieveTPUEmbeddingStochasticGradientDescentParameters
|
| RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug | Retrieve SGD embedding parameters with debug support. |
| RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug
|
| Reverse<T extends TType> | Reverses specific dimensions of a tensor. |
| ReverseSequence<T extends TType> | Reverses variable length slices. |
| ReverseSequence.Options | Optional attributes for ReverseSequence
|
| RewriterConfig | Graph rewriting is experimental and subject to change, not covered by any API stability guarantees. |
| RewriterConfig.Builder | Graph rewriting is experimental and subject to change, not covered by any API stability guarantees. |
| RewriterConfig.CpuLayout | Enum for layout conversion between NCHW and NHWC on CPU. |
| RewriterConfig.CustomGraphOptimizer | Message to describe custom graph optimizer and its parametersProtobuf type tensorflow.RewriterConfig.CustomGraphOptimizer
|
| RewriterConfig.CustomGraphOptimizer.Builder | Message to describe custom graph optimizer and its parametersProtobuf type tensorflow.RewriterConfig.CustomGraphOptimizer
|
| RewriterConfig.CustomGraphOptimizerOrBuilder | |
| RewriterConfig.MemOptType | Protobuf enum tensorflow.RewriterConfig.MemOptType
|
| RewriterConfig.NumIterationsType | Enum controlling the number of times to run optimizers. |
| RewriterConfig.Toggle | Protobuf enum tensorflow.RewriterConfig.Toggle
|
| RewriterConfigOrBuilder | |
| RewriterConfigProtos | |
| Rfft<U extends TType> | Real-valued fast Fourier transform. |
| Rfft2d<U extends TType> | 2D real-valued fast Fourier transform. |
| Rfft3d<U extends TType> | 3D real-valued fast Fourier transform. |
| RgbToHsv<T extends TNumber> | Converts one or more images from RGB to HSV. |
| RightShift<T extends TNumber> | Elementwise computes the bitwise right-shift of `x` and `y`. |
| Rint<T extends TNumber> | Returns element-wise integer closest to x. |
| RMSProp | Optimizer that implements the RMSProp algorithm. |
| RngReadAndSkip | Advance the counter of a counter-based RNG. |
| RngSkip | Advance the counter of a counter-based RNG. |
| Roll<T extends TType> | Rolls the elements of a tensor along an axis. |
| Round<T extends TType> | Rounds the values of a tensor to the nearest integer, element-wise. |
| Rpc | Perform batches of RPC requests. |
| Rpc.Options | Optional attributes for Rpc
|
| RPCOptions | Protobuf type tensorflow.RPCOptions
|
| RPCOptions.Builder | Protobuf type tensorflow.RPCOptions
|
| RPCOptionsOrBuilder | |
| Rsqrt<T extends TType> | Computes reciprocal of square root of x element-wise. |
| RsqrtGrad<T extends TType> | Computes the gradient for the rsqrt of `x` wrt its input. |
| RunConfiguration | Run-specific items such as arguments to the test / benchmark. |
| RunConfiguration.Builder | Run-specific items such as arguments to the test / benchmark. |
| RunConfigurationOrBuilder | |
| RunMetadata | Metadata output (i.e., non-Tensor) for a single Run() call. |
| RunMetadata.Builder | Metadata output (i.e., non-Tensor) for a single Run() call. |
| RunMetadata.FunctionGraphs | Protobuf type tensorflow.RunMetadata.FunctionGraphs
|
| RunMetadata.FunctionGraphs.Builder | Protobuf type tensorflow.RunMetadata.FunctionGraphs
|
| RunMetadata.FunctionGraphsOrBuilder | |
| RunMetadataOrBuilder | |
| RunOptions | Options for a single Run() call. |
| RunOptions.Builder | Options for a single Run() call. |
| RunOptions.Experimental | Everything inside Experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat. |
| RunOptions.Experimental.Builder | Everything inside Experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat. |
| RunOptions.Experimental.RunHandlerPoolOptions | Options for run handler thread pool. |
| RunOptions.Experimental.RunHandlerPoolOptions.Builder | Options for run handler thread pool. |
| RunOptions.Experimental.RunHandlerPoolOptionsOrBuilder | |
| RunOptions.ExperimentalOrBuilder | |
| RunOptions.TraceLevel | TODO(pbar) Turn this into a TraceOptions proto which allows tracing to be controlled in a more orthogonal manner?Protobuf enum tensorflow.RunOptions.TraceLevel
|
| RunOptionsOrBuilder |
S
| SampleDistortedBoundingBox<T extends TNumber> | Generate a single randomly distorted bounding box for an image. |
| SampleDistortedBoundingBox.Options | Optional attributes for SampleDistortedBoundingBox
|
| SamplingDataset | Creates a dataset that takes a Bernoulli sample of the contents of another dataset. |
| Save | Saves tensors in V2 checkpoint format. |
| SaveableObject | Protobuf type tensorflow.SaveableObject
|
| SaveableObject.Builder | Protobuf type tensorflow.SaveableObject
|
| SaveableObjectOrBuilder | |
| SavedAsset | A SavedAsset points to an asset in the MetaGraph. |
| SavedAsset.Builder | A SavedAsset points to an asset in the MetaGraph. |
| SavedAssetOrBuilder | |
| SavedBareConcreteFunction | Protobuf type tensorflow.SavedBareConcreteFunction
|
| SavedBareConcreteFunction.Builder | Protobuf type tensorflow.SavedBareConcreteFunction
|
| SavedBareConcreteFunctionOrBuilder | |
| SavedConcreteFunction | Stores low-level information about a concrete function. |
| SavedConcreteFunction.Builder | Stores low-level information about a concrete function. |
| SavedConcreteFunctionOrBuilder | |
| SavedConstant | Protobuf type tensorflow.SavedConstant
|
| SavedConstant.Builder | Protobuf type tensorflow.SavedConstant
|
| SavedConstantOrBuilder | |
| SavedFunction | A function with multiple signatures, possibly with non-Tensor arguments. |
| SavedFunction.Builder | A function with multiple signatures, possibly with non-Tensor arguments. |
| SavedFunctionOrBuilder | |
| SavedModel | SavedModel is the high level serialization format for TensorFlow Models. |
| SavedModel.Builder | SavedModel is the high level serialization format for TensorFlow Models. |
| SavedModelBundle | SavedModelBundle represents a model loaded from storage. |
| SavedModelBundle.Exporter | Options for exporting a SavedModel. |
| SavedModelBundle.Loader | Options for loading a SavedModel. |
| SavedModelOrBuilder | |
| SavedModelProtos | |
| SavedObject | Protobuf type tensorflow.SavedObject
|
| SavedObject.Builder | Protobuf type tensorflow.SavedObject
|
| SavedObject.KindCase | |
| SavedObjectGraph | Protobuf type tensorflow.SavedObjectGraph
|
| SavedObjectGraph.Builder | Protobuf type tensorflow.SavedObjectGraph
|
| SavedObjectGraphOrBuilder | |
| SavedObjectGraphProtos | |
| SavedObjectOrBuilder | |
| SavedResource | A SavedResource represents a TF object that holds state during its lifetime. |
| SavedResource.Builder | A SavedResource represents a TF object that holds state during its lifetime. |
| SavedResourceOrBuilder | |
| SavedSlice | Saved tensor slice: it stores the name of the tensors, the slice, and the raw data. |
| SavedSlice.Builder | Saved tensor slice: it stores the name of the tensors, the slice, and the raw data. |
| SavedSliceMeta | Metadata describing the set of slices of the same tensor saved in a checkpoint file. |
| SavedSliceMeta.Builder | Metadata describing the set of slices of the same tensor saved in a checkpoint file. |
| SavedSliceMetaOrBuilder | |
| SavedSliceOrBuilder | |
| SavedTensorSliceMeta | Metadata describing the set of tensor slices saved in a checkpoint file. |
| SavedTensorSliceMeta.Builder | Metadata describing the set of tensor slices saved in a checkpoint file. |
| SavedTensorSliceMetaOrBuilder | |
| SavedTensorSliceProtos | |
| SavedTensorSlices | Each record in a v3 checkpoint file is a serialized SavedTensorSlices message. |
| SavedTensorSlices.Builder | Each record in a v3 checkpoint file is a serialized SavedTensorSlices message. |
| SavedTensorSlicesOrBuilder | |
| SavedUserObject | A SavedUserObject is an object (in the object-oriented language of the TensorFlow program) of some user- or framework-defined class other than those handled specifically by the other kinds of SavedObjects. |
| SavedUserObject.Builder | A SavedUserObject is an object (in the object-oriented language of the TensorFlow program) of some user- or framework-defined class other than those handled specifically by the other kinds of SavedObjects. |
| SavedUserObjectOrBuilder | |
| SavedVariable | Represents a Variable that is initialized by loading the contents from the checkpoint. |
| SavedVariable.Builder | Represents a Variable that is initialized by loading the contents from the checkpoint. |
| SavedVariableOrBuilder | |
| SaverDef | Protocol buffer representing the configuration of a Saver. |
| SaverDef.Builder | Protocol buffer representing the configuration of a Saver. |
| SaverDef.CheckpointFormatVersion | A version number that identifies a different on-disk checkpoint format. |
| SaverDefOrBuilder | |
| SaverProtos | |
| SaveSliceInfoDef | Protobuf type tensorflow.SaveSliceInfoDef
|
| SaveSliceInfoDef.Builder | Protobuf type tensorflow.SaveSliceInfoDef
|
| SaveSliceInfoDefOrBuilder | |
| SaveSlices | Saves input tensors slices to disk. |
| ScalarSummary | Outputs a `Summary` protocol buffer with scalar values. |
| ScaleAndTranslate | |
| ScaleAndTranslate.Options | Optional attributes for ScaleAndTranslate
|
| ScaleAndTranslateGrad<T extends TNumber> | |
| ScaleAndTranslateGrad.Options | Optional attributes for ScaleAndTranslateGrad
|
| ScatterAdd<T extends TType> | Adds sparse updates to a variable reference. |
| ScatterAdd.Options | Optional attributes for ScatterAdd
|
| ScatterDiv<T extends TType> | Divides a variable reference by sparse updates. |
| ScatterDiv.Options | Optional attributes for ScatterDiv
|
| ScatterMax<T extends TNumber> | Reduces sparse updates into a variable reference using the `max` operation. |
| ScatterMax.Options | Optional attributes for ScatterMax
|
| ScatterMin<T extends TNumber> | Reduces sparse updates into a variable reference using the `min` operation. |
| ScatterMin.Options | Optional attributes for ScatterMin
|
| ScatterMul<T extends TType> | Multiplies sparse updates into a variable reference. |
| ScatterMul.Options | Optional attributes for ScatterMul
|
| ScatterNd<U extends TType> | Scatter `updates` into a new tensor according to `indices`. |
| ScatterNdAdd<T extends TType> | Applies sparse addition to individual values or slices in a Variable. |
| ScatterNdAdd.Options | Optional attributes for ScatterNdAdd
|
| ScatterNdMax<T extends TType> | Computes element-wise maximum. |
| ScatterNdMax.Options | Optional attributes for ScatterNdMax
|
| ScatterNdMin<T extends TType> | Computes element-wise minimum. |
| ScatterNdMin.Options | Optional attributes for ScatterNdMin
|
| ScatterNdNonAliasingAdd<T extends TType> | Applies sparse addition to `input` using individual values or slices
from `updates` according to indices `indices`. |
| ScatterNdSub<T extends TType> | Applies sparse subtraction to individual values or slices in a Variable. |
| ScatterNdSub.Options | Optional attributes for ScatterNdSub
|
| ScatterNdUpdate<T extends TType> | Applies sparse `updates` to individual values or slices within a given
variable according to `indices`. |
| ScatterNdUpdate.Options | Optional attributes for ScatterNdUpdate
|
| ScatterSub<T extends TType> | Subtracts sparse updates to a variable reference. |
| ScatterSub.Options | Optional attributes for ScatterSub
|
| ScatterUpdate<T extends TType> | Applies sparse updates to a variable reference. |
| ScatterUpdate.Options | Optional attributes for ScatterUpdate
|
| Scope | Manages groups of related properties when creating Tensorflow Operations, such as a common name prefix. |
| ScopedAllocatorOptions | Protobuf type tensorflow.ScopedAllocatorOptions
|
| ScopedAllocatorOptions.Builder | Protobuf type tensorflow.ScopedAllocatorOptions
|
| ScopedAllocatorOptionsOrBuilder | |
| SdcaFprint | Computes fingerprints of the input strings. |
| SdcaOptimizer | Distributed version of Stochastic Dual Coordinate Ascent (SDCA) optimizer for
linear models with L1 + L2 regularization. |
| SdcaOptimizer.Options | Optional attributes for SdcaOptimizer
|
| SdcaShrinkL1 | Applies L1 regularization shrink step on the parameters. |
| SegmentMax<T extends TNumber> | Computes the maximum along segments of a tensor. |
| SegmentMean<T extends TType> | Computes the mean along segments of a tensor. |
| SegmentMin<T extends TNumber> | Computes the minimum along segments of a tensor. |
| SegmentProd<T extends TType> | Computes the product along segments of a tensor. |
| SegmentSum<T extends TType> | Computes the sum along segments of a tensor. |
| Select<T extends TType> | |
| SelfAdjointEig<T extends TType> | Computes the eigen decomposition of one or more square self-adjoint matrices. |
| SelfAdjointEig<T extends TType> | Computes the eigen decomposition of a batch of self-adjoint matrices
(Note: Only real inputs are supported). |
| SelfAdjointEig.Options | Optional attributes for SelfAdjointEig
|
| Selu<T extends TNumber> | Computes scaled exponential linear: `scale * alpha * (exp(features) - 1)`
if < 0, `scale * features` otherwise. |
| SELU<T extends TFloating> | Scaled Exponential Linear Unit (SELU). |
| SeluGrad<T extends TNumber> | Computes gradients for the scaled exponential linear (Selu) operation. |
| Send | Sends the named tensor from send_device to recv_device. |
| Send | Sends the named tensor to another XLA computation. |
| Send.Options | Optional attributes for Send
|
| SendTPUEmbeddingGradients | Performs gradient updates of embedding tables. |
| SequenceExample | Protobuf type tensorflow.SequenceExample
|
| SequenceExample.Builder | Protobuf type tensorflow.SequenceExample
|
| SequenceExampleOrBuilder | |
| SerializeIterator | Converts the given `resource_handle` representing an iterator to a variant tensor. |
| SerializeIterator.Options | Optional attributes for SerializeIterator
|
| SerializeManySparse<U extends TType> | Serialize an `N`-minibatch `SparseTensor` into an `[N, 3]` `Tensor` object. |
| SerializeSparse<U extends TType> | Serialize a `SparseTensor` into a `[3]` `Tensor` object. |
| SerializeTensor | Transforms a Tensor into a serialized TensorProto proto. |
| Server | An in-process TensorFlow server, for use in distributed training. |
| ServerDef | Defines the configuration of a single TensorFlow server. |
| ServerDef.Builder | Defines the configuration of a single TensorFlow server. |
| ServerDefOrBuilder | |
| ServerProtos | |
| ServiceConfig | |
| ServiceConfig.DispatcherConfig | Configuration for a tf.data service DispatchServer. |
| ServiceConfig.DispatcherConfig.Builder | Configuration for a tf.data service DispatchServer. |
| ServiceConfig.DispatcherConfigOrBuilder | |
| ServiceConfig.WorkerConfig | Configuration for a tf.data service WorkerServer. |
| ServiceConfig.WorkerConfig.Builder | Configuration for a tf.data service WorkerServer. |
| ServiceConfig.WorkerConfigOrBuilder | |
| Session | Driver for Graph execution. |
| Session.Run | Output tensors and metadata obtained when executing a session. |
| Session.Runner | Run Operations and evaluate Tensors. |
| SessionLog | Protocol buffer used for logging session state. |
| SessionLog.Builder | Protocol buffer used for logging session state. |
| SessionLog.SessionStatus | Protobuf enum tensorflow.SessionLog.SessionStatus
|
| SessionLogOrBuilder | |
| SessionMetadata | Metadata about the session. |
| SessionMetadata.Builder | Metadata about the session. |
| SessionMetadataOrBuilder | |
| SetDiff1d<T extends TType, U extends TNumber> | Computes the difference between two lists of numbers or strings. |
| SetSize | Number of unique elements along last dimension of input `set`. |
| SetSize.Options | Optional attributes for SetSize
|
| SetsOps | Implementation of set operations |
| SetsOps.Operation | Enumeration containing the string operation values to be passed to the TensorFlow Sparse Ops
function ERROR(/SparseOps#denseToDenseSetOperation)
|
| SetStatsAggregatorDataset | |
| SetStatsAggregatorDataset | |
| Shape | The shape of a Tensor or NdArray. |
| Shape<U extends TNumber> | Returns the shape of a tensor. |
| Shape_inference_func_TF_ShapeInferenceContext_TF_Status | |
| Shaped | Any data container with a given Shape. |
| ShapeN<U extends TNumber> | Returns shape of tensors. |
| Shapes | An operator providing methods on org.tensorflow.op.core.Shape tensors and 1d operands that represent the dimensions of a shape. |
| ShapeUtils | Various methods for processing with Shapes and Operands |
| ShardDataset | Creates a `Dataset` that includes only 1/`num_shards` of this dataset. |
| ShardDataset.Options | Optional attributes for ShardDataset
|
| ShardedFilename | Generate a sharded filename. |
| ShardedFilespec | Generate a glob pattern matching all sharded file names. |
| Sharding<T extends TType> | An op which shards the input based on the given sharding attribute. |
| ShortDataBuffer | A DataBuffer of shorts. |
| ShortDataLayout<S extends DataBuffer<?>> | A DataLayout that converts data stored in a buffer to shorts. |
| ShortDenseNdArray | |
| ShortNdArray | An NdArray of shorts. |
| ShuffleAndRepeatDataset | |
| ShuffleAndRepeatDataset.Options | Optional attributes for ShuffleAndRepeatDataset
|
| ShuffleDataset | |
| ShuffleDataset.Options | Optional attributes for ShuffleDataset
|
| ShutdownDistributedTPU | Shuts down a running distributed TPU system. |
| Sigmoid<T extends TFloating> | Sigmoid activation. |
| Sigmoid<T extends TType> | Computes sigmoid of `x` element-wise. |
| SigmoidCrossEntropyWithLogits | |
| SigmoidGrad<T extends TType> | Computes the gradient of the sigmoid of `x` wrt its input. |
| Sign<T extends TType> | Returns an element-wise indication of the sign of a number. |
| Signature | Describe the inputs and outputs of an executable entity, such as a ConcreteFunction, among
other useful metadata. |
| Signature.Builder | Builds a new function signature. |
| Signature.TensorDescription | |
| SignatureDef | SignatureDef defines the signature of a computation supported by a TensorFlow graph. |
| SignatureDef.Builder | SignatureDef defines the signature of a computation supported by a TensorFlow graph. |
| SignatureDefOrBuilder | |
| Sin<T extends TType> | Computes sine of x element-wise. |
| SingleElementSequence<T, U extends NdArray<T>> | A sequence of one single element |
| Sinh<T extends TType> | Computes hyperbolic sine of x element-wise. |
| Size<U extends TNumber> | Returns the size of a tensor. |
| SkipDataset | |
| SkipDataset | Creates a dataset that skips `count` elements from the `input_dataset`. |
| Skipgram | Parses a text file and creates a batch of examples. |
| Skipgram.Options | Optional attributes for Skipgram
|
| SleepDataset | |
| SleepDataset | |
| Slice<T extends TType> | Return a slice from 'input'. |
| SlicingElementSequence<T, U extends NdArray<T>> | A sequence creating a new NdArray instance (slice) for each element of an iteration |
| SlidingWindowDataset | Creates a dataset that passes a sliding window over `input_dataset`. |
| SlidingWindowDataset | Creates a dataset that passes a sliding window over `input_dataset`. |
| Snapshot<T extends TType> | Returns a copy of the input tensor. |
| SnapShot | Protobuf type tensorflow.SnapShot
|
| SnapShot.Builder | Protobuf type tensorflow.SnapShot
|
| SnapshotMetadataRecord | This stores the metadata information present in each snapshot record. |
| SnapshotMetadataRecord.Builder | This stores the metadata information present in each snapshot record. |
| SnapshotMetadataRecordOrBuilder | |
| SnapShotOrBuilder | |
| SnapshotProtos | |
| SnapshotRecord | Each SnapshotRecord represents one batch of pre-processed input data. |
| SnapshotRecord.Builder | Each SnapshotRecord represents one batch of pre-processed input data. |
| SnapshotRecordOrBuilder | |
| SnapshotTensorMetadata | Metadata for all the tensors in a Snapshot Record. |
| SnapshotTensorMetadata.Builder | Metadata for all the tensors in a Snapshot Record. |
| SnapshotTensorMetadataOrBuilder | |
| SobolSample<T extends TNumber> | Generates points from the Sobol sequence. |
| Softmax<T extends TFloating> | Softmax converts a real vector to a vector of categorical probabilities. |
| Softmax<T extends TNumber> | Computes softmax activations. |
| SoftmaxCrossEntropyWithLogits | |
| SoftmaxCrossEntropyWithLogits<T extends TNumber> | Computes softmax cross entropy cost and gradients to backpropagate. |
| Softplus<T extends TFloating> | Softplus activation function, softplus(x) = log(exp(x) + 1). |
| Softplus<T extends TNumber> | Computes softplus: `log(exp(features) + 1)`. |
| SoftplusGrad<T extends TNumber> | Computes softplus gradients for a softplus operation. |
| Softsign<T extends TFloating> | Softsign activation function, softsign(x) = x / (abs(x) + 1). |
| Softsign<T extends TNumber> | Computes softsign: `features / (abs(features) + 1)`. |
| SoftsignGrad<T extends TNumber> | Computes softsign gradients for a softsign operation. |
| Solve<T extends TType> | Solves systems of linear equations. |
| Solve.Options | Optional attributes for Solve
|
| Sort<T extends TType> | Wraps the XLA Sort operator, documented at
https://www.tensorflow.org/performance/xla/operation_semantics#sort . |
| SourceFile | Content of a source file involved in the execution of the debugged TensorFlow program. |
| SourceFile.Builder | Content of a source file involved in the execution of the debugged TensorFlow program. |
| SourceFileOrBuilder | |
| SpaceToBatch<T extends TType> | SpaceToBatch for 4-D tensors of type T. |
| SpaceToBatchNd<T extends TType> | SpaceToBatch for N-D tensors of type T. |
| SpaceToDepth<T extends TType> | SpaceToDepth for tensors of type T. |
| SpaceToDepth.Options | Optional attributes for SpaceToDepth
|
| SparseAccumulatorApplyGradient | Applies a sparse gradient to a given accumulator. |
| SparseAccumulatorTakeGradient<T extends TType> | Extracts the average sparse gradient in a SparseConditionalAccumulator. |
| SparseAdd<T extends TType> | Adds two `SparseTensor` objects to produce another `SparseTensor`. |
| SparseAddGrad<T extends TType> | The gradient operator for the SparseAdd op. |
| SparseApplyAdadelta<T extends TType> | var: Should be from a Variable(). |
| SparseApplyAdadelta.Options | Optional attributes for SparseApplyAdadelta
|
| SparseApplyAdagrad<T extends TType> | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
| SparseApplyAdagrad.Options | Optional attributes for SparseApplyAdagrad
|
| SparseApplyAdagradDa<T extends TType> | Update entries in '*var' and '*accum' according to the proximal adagrad scheme. |
| SparseApplyAdagradDa.Options | Optional attributes for SparseApplyAdagradDa
|
| SparseApplyCenteredRmsProp<T extends TType> | Update '*var' according to the centered RMSProp algorithm. |
| SparseApplyCenteredRmsProp.Options | Optional attributes for SparseApplyCenteredRmsProp
|
| SparseApplyFtrl<T extends TType> | Update relevant entries in '*var' according to the Ftrl-proximal scheme. |
| SparseApplyFtrl.Options | Optional attributes for SparseApplyFtrl
|
| SparseApplyMomentum<T extends TType> | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
| SparseApplyMomentum.Options | Optional attributes for SparseApplyMomentum
|
| SparseApplyProximalAdagrad<T extends TType> | Sparse update entries in '*var' and '*accum' according to FOBOS algorithm. |
| SparseApplyProximalAdagrad.Options | Optional attributes for SparseApplyProximalAdagrad
|
| SparseApplyProximalGradientDescent<T extends TType> | Sparse update '*var' as FOBOS algorithm with fixed learning rate. |
| SparseApplyProximalGradientDescent.Options | Optional attributes for SparseApplyProximalGradientDescent
|
| SparseApplyRmsProp<T extends TType> | Update '*var' according to the RMSProp algorithm. |
| SparseApplyRmsProp.Options | Optional attributes for SparseApplyRmsProp
|
| SparseBincount<U extends TNumber> | Counts the number of occurrences of each value in an integer array. |
| SparseBincount.Options | Optional attributes for SparseBincount
|
| SparseCategoricalCrossentropy | Computes the crossentropy loss between labels and predictions. |
| SparseCategoricalCrossentropy<T extends TNumber> | A metric that computes the sparse categorical cross-entropy loss between true labels and predicted labels. |
| SparseConcat<T extends TType> | Concatenates a list of `SparseTensor` along the specified dimension. |
| SparseConditionalAccumulator | A conditional accumulator for aggregating sparse gradients. |
| SparseConditionalAccumulator.Options | Optional attributes for SparseConditionalAccumulator
|
| SparseCountSparseOutput<U extends TNumber> | Performs sparse-output bin counting for a sparse tensor input. |
| SparseCountSparseOutput.Options | Optional attributes for SparseCountSparseOutput
|
| SparseCross | Generates sparse cross from a list of sparse and dense tensors. |
| SparseCrossHashed | Generates sparse cross from a list of sparse and dense tensors. |
| SparseDenseCwiseAdd<T extends TType> | Adds up a SparseTensor and a dense Tensor, using these special rules:
(1) Broadcasts the dense side to have the same shape as the sparse side, if eligible; (2) Then, only the dense values pointed to by the indices of the SparseTensor participate in the cwise addition. |
| SparseDenseCwiseDiv<T extends TType> | Component-wise divides a SparseTensor by a dense Tensor. |
| SparseDenseCwiseMul<T extends TType> | Component-wise multiplies a SparseTensor by a dense Tensor. |
| SparseFillEmptyRows<T extends TType> | Fills empty rows in the input 2-D `SparseTensor` with a default value. |
| SparseFillEmptyRowsGrad<T extends TType> | The gradient of SparseFillEmptyRows. |
| SparseMatMul | Multiply matrix "a" by matrix "b". |
| SparseMatMul.Options | Optional attributes for SparseMatMul
|
| SparseMatrixAdd | Sparse addition of two CSR matrices, C = alpha * A + beta * B. |
| SparseMatrixMatMul<T extends TType> | Matrix-multiplies a sparse matrix with a dense matrix. |
| SparseMatrixMatMul.Options | Optional attributes for SparseMatrixMatMul
|
| SparseMatrixMul | Element-wise multiplication of a sparse matrix with a dense tensor. |
| SparseMatrixNNZ | Returns the number of nonzeroes of `sparse_matrix`. |
| SparseMatrixOrderingAMD | Computes the Approximate Minimum Degree (AMD) ordering of `input`. |
| SparseMatrixSoftmax | Calculates the softmax of a CSRSparseMatrix. |
| SparseMatrixSoftmaxGrad | Calculates the gradient of the SparseMatrixSoftmax op. |
| SparseMatrixSparseCholesky | Computes the sparse Cholesky decomposition of `input`. |
| SparseMatrixSparseMatMul | Sparse-matrix-multiplies two CSR matrices `a` and `b`. |
| SparseMatrixSparseMatMul.Options | Optional attributes for SparseMatrixSparseMatMul
|
| SparseMatrixTranspose | Transposes the inner (matrix) dimensions of a CSRSparseMatrix. |
| SparseMatrixTranspose.Options | Optional attributes for SparseMatrixTranspose
|
| SparseMatrixZeros | Creates an all-zeros CSRSparseMatrix with shape `dense_shape`. |
| SparseReduceMax<T extends TNumber> | Computes the max of elements across dimensions of a SparseTensor. |
| SparseReduceMax.Options | Optional attributes for SparseReduceMax
|
| SparseReduceMaxSparse<T extends TNumber> | Computes the max of elements across dimensions of a SparseTensor. |
| SparseReduceMaxSparse.Options | Optional attributes for SparseReduceMaxSparse
|
| SparseReduceSum<T extends TType> | Computes the sum of elements across dimensions of a SparseTensor. |
| SparseReduceSum.Options | Optional attributes for SparseReduceSum
|
| SparseReduceSumSparse<T extends TType> | Computes the sum of elements across dimensions of a SparseTensor. |
| SparseReduceSumSparse.Options | Optional attributes for SparseReduceSumSparse
|
| SparseReorder<T extends TType> | Reorders a SparseTensor into the canonical, row-major ordering. |
| SparseReshape | Reshapes a SparseTensor to represent values in a new dense shape. |
| SparseSegmentMean<T extends TNumber> | Computes the mean along sparse segments of a tensor. |
| SparseSegmentMeanGrad<T extends TNumber> | Computes gradients for SparseSegmentMean. |
| SparseSegmentMeanWithNumSegments<T extends TNumber> | Computes the mean along sparse segments of a tensor. |
| SparseSegmentSqrtN<T extends TNumber> | Computes the sum along sparse segments of a tensor divided by the sqrt of N. |
| SparseSegmentSqrtNGrad<T extends TNumber> | Computes gradients for SparseSegmentSqrtN. |
| SparseSegmentSqrtNWithNumSegments<T extends TNumber> | Computes the sum along sparse segments of a tensor divided by the sqrt of N. |
| SparseSegmentSum<T extends TNumber> | Computes the sum along sparse segments of a tensor. |
| SparseSegmentSumWithNumSegments<T extends TNumber> | Computes the sum along sparse segments of a tensor. |
| SparseSlice<T extends TType> | Slice a `SparseTensor` based on the `start` and `size`. |
| SparseSliceGrad<T extends TType> | The gradient operator for the SparseSlice op. |
| SparseSoftmax<T extends TNumber> | Applies softmax to a batched N-D `SparseTensor`. |
| SparseSoftmaxCrossEntropyWithLogits | |
| SparseSoftmaxCrossEntropyWithLogits<T extends TNumber> | Computes softmax cross entropy cost and gradients to backpropagate. |
| SparseSparseMaximum<T extends TNumber> | Returns the element-wise max of two SparseTensors. |
| SparseSparseMinimum<T extends TType> | Returns the element-wise min of two SparseTensors. |
| SparseSplit<T extends TType> | Split a `SparseTensor` into `num_split` tensors along one dimension. |
| SparseTensorDenseAdd<U extends TType> | Adds up a `SparseTensor` and a dense `Tensor`, producing a dense `Tensor`. |
| SparseTensorDenseMatMul<U extends TType> | Multiply SparseTensor (of rank 2) "A" by dense matrix "B". |
| SparseTensorDenseMatMul.Options | Optional attributes for SparseTensorDenseMatMul
|
| SparseTensorSliceDataset | Creates a dataset that splits a SparseTensor into elements row-wise. |
| SparseTensorToCSRSparseMatrix | Converts a SparseTensor to a (possibly batched) CSRSparseMatrix. |
| SparseToDense<U extends TType> | Converts a sparse representation into a dense tensor. |
| SparseToDense.Options | Optional attributes for SparseToDense
|
| SparseToSparseSetOperation<T extends TType> | Applies set operation along last dimension of 2 `SparseTensor` inputs. |
| SparseToSparseSetOperation.Options | Optional attributes for SparseToSparseSetOperation
|
| SpecializedType | For identifying the underlying type of a variant. |
| Spence<T extends TNumber> | |
| Split<T extends TType> | Splits a tensor into `num_split` tensors along one dimension. |
| SplitV<T extends TType> | Splits a tensor into `num_split` tensors along one dimension. |
| SqlDataset | Creates a dataset that executes a SQL query and emits rows of the result set. |
| SqlDataset | Creates a dataset that executes a SQL query and emits rows of the result set. |
| Sqrt<T extends TType> | Computes square root of x element-wise. |
| SqrtGrad<T extends TType> | Computes the gradient for the sqrt of `x` wrt its input. |
| Sqrtm<T extends TType> | Computes the matrix square root of one or more square matrices:
matmul(sqrtm(A), sqrtm(A)) = A The input matrix should be invertible. |
| Square<T extends TType> | Computes square of x element-wise. |
| SquaredDifference<T extends TType> | Returns conj(x - y)(x - y) element-wise. |
| SquaredHinge | Computes the squared hinge loss between labels and predictions. |
| SquaredHinge<T extends TNumber> | A metric that computes the squared hinge loss metric between labels and predictions. |
| Squeeze<T extends TType> | Removes dimensions of size 1 from the shape of a tensor. |
| Squeeze.Options | Optional attributes for Squeeze
|
| Stack<T extends TType> | Packs a list of `N` rank-`R` tensors into one rank-`(R+1)` tensor. |
| Stack.Options | Optional attributes for Stack
|
| StackFrameWithId | A stack frame with ID. |
| StackFrameWithId.Builder | A stack frame with ID. |
| StackFrameWithIdOrBuilder | |
| Stage | Stage values similar to a lightweight Enqueue. |
| Stage.Options | Optional attributes for Stage
|
| StageClear | Op removes all elements in the underlying container. |
| StageClear.Options | Optional attributes for StageClear
|
| StagePeek | Op peeks at the values at the specified index. |
| StagePeek.Options | Optional attributes for StagePeek
|
| StageSize | Op returns the number of elements in the underlying container. |
| StageSize.Options | Optional attributes for StageSize
|
| StatefulRandomBinomial<V extends TNumber> | |
| StatefulStandardNormal<U extends TType> | Outputs random values from a normal distribution. |
| StatefulTruncatedNormal<U extends TType> | Outputs random values from a truncated normal distribution. |
| StatefulUniform<U extends TType> | Outputs random values from a uniform distribution. |
| StatefulUniformFullInt<U extends TType> | Outputs random integers from a uniform distribution. |
| StatefulUniformInt<U extends TType> | Outputs random integers from a uniform distribution. |
| StatelessMultinomial<V extends TNumber> | Draws samples from a multinomial distribution. |
| StatelessParameterizedTruncatedNormal<V extends TNumber> | |
| StatelessRandomBinomial<W extends TNumber> | Outputs deterministic pseudorandom random numbers from a binomial distribution. |
| StatelessRandomGamma<V extends TNumber> | Outputs deterministic pseudorandom random numbers from a gamma distribution. |
| StatelessRandomGetKeyCounterAlg | Picks the best algorithm based on device, and scrambles seed into key and counter. |
| StatelessRandomNormal<V extends TNumber> | Outputs deterministic pseudorandom values from a normal distribution. |
| StatelessRandomNormalV2<U extends TNumber> | Outputs deterministic pseudorandom values from a normal distribution. |
| StatelessRandomPoisson<W extends TNumber> | Outputs deterministic pseudorandom random numbers from a Poisson distribution. |
| StatelessRandomUniform<V extends TNumber> | Outputs deterministic pseudorandom random values from a uniform distribution. |
| StatelessRandomUniformFullInt<V extends TNumber> | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformFullIntV2<U extends TNumber> | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformInt<V extends TNumber> | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformIntV2<U extends TNumber> | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformV2<U extends TNumber> | Outputs deterministic pseudorandom random values from a uniform distribution. |
| StatelessSampleDistortedBoundingBox<T extends TNumber> | Generate a randomly distorted bounding box for an image deterministically. |
| StatelessSampleDistortedBoundingBox.Options | Optional attributes for StatelessSampleDistortedBoundingBox
|
| StatelessTruncatedNormal<V extends TNumber> | Outputs deterministic pseudorandom values from a truncated normal distribution. |
| StatelessTruncatedNormalV2<U extends TNumber> | Outputs deterministic pseudorandom values from a truncated normal distribution. |
| StaticRegexFullMatch | Check if the input matches the regex pattern. |
| StaticRegexReplace | Replaces the match of pattern in input with rewrite. |
| StaticRegexReplace.Options | Optional attributes for StaticRegexReplace
|
| StatsAggregatorHandle | Creates a statistics manager resource. |
| StatsAggregatorHandle | |
| StatsAggregatorHandle.Options | Optional attributes for StatsAggregatorHandle
|
| StatsAggregatorHandle.Options | Optional attributes for StatsAggregatorHandle
|
| StatsAggregatorSetSummaryWriter | Set a summary_writer_interface to record statistics using given stats_aggregator. |
| StatsAggregatorSummary | Produces a summary of any statistics recorded by the given statistics manager. |
| StatsAggregatorSummary | Produces a summary of any statistics recorded by the given statistics manager. |
| StdArrays | Utility class for working with NdArray instances mixed with standard Java arrays. |
| StepStats | Protobuf type tensorflow.StepStats
|
| StepStats.Builder | Protobuf type tensorflow.StepStats
|
| StepStatsOrBuilder | |
| StepStatsProtos | |
| StopGradient<T extends TType> | Stops gradient computation. |
| StridedSlice<T extends TType> | Return a strided slice from `input`. |
| StridedSlice.Options | Optional attributes for StridedSlice
|
| StridedSliceAssign<T extends TType> | Assign `value` to the sliced l-value reference of `ref`. |
| StridedSliceAssign.Options | Optional attributes for StridedSliceAssign
|
| StridedSliceGrad<U extends TType> | Returns the gradient of `StridedSlice`. |
| StridedSliceGrad.Options | Optional attributes for StridedSliceGrad
|
| StridedSliceHelper | Helper endpoint methods for Python like indexing. |
| StringFormat | Formats a string template using a list of tensors. |
| StringFormat.Options | Optional attributes for StringFormat
|
| StringLayout | Data layout that converts a String to/from a sequence of bytes applying a given charset. |
| StringLength | String lengths of `input`. |
| StringLength.Options | Optional attributes for StringLength
|
| StringNGrams<T extends TNumber> | Creates ngrams from ragged string data. |
| StringSplit | Split elements of `source` based on `sep` into a `SparseTensor`. |
| StringSplit.Options | Optional attributes for StringSplit
|
| Strip | Strip leading and trailing whitespaces from the Tensor. |
| StructProtos | |
| StructuredValue | `StructuredValue` represents a dynamically typed value representing various data structures that are inspired by Python data structures typically used in TensorFlow functions as inputs and outputs. |
| StructuredValue.Builder | `StructuredValue` represents a dynamically typed value representing various data structures that are inspired by Python data structures typically used in TensorFlow functions as inputs and outputs. |
| StructuredValue.KindCase | |
| StructuredValueOrBuilder | |
| Sub<T extends TType> | Returns x - y element-wise. |
| Substr | Return substrings from `Tensor` of strings. |
| Substr.Options | Optional attributes for Substr
|
| Sum<T extends TType> | Computes the sum of elements across dimensions of a tensor. |
| Sum.Options | Optional attributes for Sum
|
| Summary | A Summary is a set of named values to be displayed by the visualizer. |
| Summary.Audio | Protobuf type tensorflow.Summary.Audio
|
| Summary.Audio.Builder | Protobuf type tensorflow.Summary.Audio
|
| Summary.AudioOrBuilder | |
| Summary.Builder | A Summary is a set of named values to be displayed by the visualizer. |
| Summary.Image | Protobuf type tensorflow.Summary.Image
|
| Summary.Image.Builder | Protobuf type tensorflow.Summary.Image
|
| Summary.ImageOrBuilder | |
| Summary.Value | Protobuf type tensorflow.Summary.Value
|
| Summary.Value.Builder | Protobuf type tensorflow.Summary.Value
|
| Summary.Value.ValueCase | |
| Summary.ValueOrBuilder | |
| SummaryDescription | Metadata associated with a series of Summary dataProtobuf type tensorflow.SummaryDescription
|
| SummaryDescription.Builder | Metadata associated with a series of Summary dataProtobuf type tensorflow.SummaryDescription
|
| SummaryDescriptionOrBuilder | |
| SummaryMetadata | A SummaryMetadata encapsulates information on which plugins are able to make use of a certain summary value. |
| SummaryMetadata.Builder | A SummaryMetadata encapsulates information on which plugins are able to make use of a certain summary value. |
| SummaryMetadata.PluginData | Protobuf type tensorflow.SummaryMetadata.PluginData
|
| SummaryMetadata.PluginData.Builder | Protobuf type tensorflow.SummaryMetadata.PluginData
|
| SummaryMetadata.PluginDataOrBuilder | |
| SummaryMetadataOrBuilder | |
| SummaryOrBuilder | |
| SummaryProtos | |
| SummaryWriter | |
| SummaryWriter.Options | Optional attributes for SummaryWriter
|
| Svd<T extends TType> | Computes the singular value decompositions of one or more matrices. |
| Svd<T extends TType> | Computes the eigen decomposition of a batch of self-adjoint matrices
(Note: Only real inputs are supported). |
| Svd.Options | Optional attributes for Svd
|
| Swish<T extends TFloating> | Swish activation function. |
| SwitchCond<T extends TType> | Forwards `data` to the output port determined by `pred`. |
T
| TaggedRunMetadata | For logging the metadata output for a single session.run() call. |
| TaggedRunMetadata.Builder | For logging the metadata output for a single session.run() call. |
| TaggedRunMetadataOrBuilder | |
| TakeDataset | |
| TakeDataset | Creates a dataset that contains `count` elements from the `input_dataset`. |
| TakeManySparseFromTensorsMap<T extends TType> | Read `SparseTensors` from a `SparseTensorsMap` and concatenate them. |
| TakeManySparseFromTensorsMap.Options | Optional attributes for TakeManySparseFromTensorsMap
|
| Tan<T extends TType> | Computes tan of x element-wise. |
| Tanh<T extends TFloating> | Hyperbolic tangent activation function. |
| Tanh<T extends TType> | Computes hyperbolic tangent of `x` element-wise. |
| TanhGrad<T extends TType> | Computes the gradient for the tanh of `x` wrt its input. |
| TaskDeviceFilters | Defines the device filters for a remote task. |
| TaskDeviceFilters.Builder | Defines the device filters for a remote task. |
| TaskDeviceFiltersOrBuilder | |
| TBfloat16 | Brain 16-bit float tensor type. |
| TBfloat16Mapper | Maps memory of DT_BFLOAT16 tensors
to a n-dimensional data space. |
| TBool | Boolean tensor type. |
| TBoolMapper | Maps memory of DT_BOOL tensors
to a n-dimensional data space. |
| TemporaryVariable<T extends TType> | Returns a tensor that may be mutated, but only persists within a single step. |
| TemporaryVariable.Options | Optional attributes for TemporaryVariable
|
| Tensor | A statically typed multi-dimensional array. |
| Tensor | |
| TensorArray | An array of Tensors of given size. |
| TensorArray.Options | Optional attributes for TensorArray
|
| TensorArrayClose | Delete the TensorArray from its resource container. |
| TensorArrayConcat<T extends TType> | Concat the elements from the TensorArray into value `value`. |
| TensorArrayConcat.Options | Optional attributes for TensorArrayConcat
|
| TensorArrayGather<T extends TType> | Gather specific elements from the TensorArray into output `value`. |
| TensorArrayGather.Options | Optional attributes for TensorArrayGather
|
| TensorArrayGrad | Creates a TensorArray for storing the gradients of values in the given handle. |
| TensorArrayGradWithShape | Creates a TensorArray for storing multiple gradients of values in the given handle. |
| TensorArrayPack<T extends TType> | |
| TensorArrayPack.Options | Optional attributes for TensorArrayPack
|
| TensorArrayRead<T extends TType> | Read an element from the TensorArray into output `value`. |
| TensorArrayScatter | Scatter the data from the input value into specific TensorArray elements. |
| TensorArraySize | Get the current size of the TensorArray. |
| TensorArraySplit | Split the data from the input value into TensorArray elements. |
| TensorArrayUnpack | |
| TensorArrayWrite | Push an element onto the tensor_array. |
| TensorBuffers | Maps native tensor memory into DataBuffers, allowing I/O operations from the JVM. |
| TensorBundleProtos | |
| TensorConnection | Defines a connection between two tensors in a `GraphDef`. |
| TensorConnection.Builder | Defines a connection between two tensors in a `GraphDef`. |
| TensorConnectionOrBuilder | |
| TensorDataset | Creates a dataset that emits `components` as a tuple of tensors once. |
| TensorDebugMode | Available modes for extracting debugging information from a Tensor. |
| TensorDescription | Protobuf type tensorflow.TensorDescription
|
| TensorDescription.Builder | Protobuf type tensorflow.TensorDescription
|
| TensorDescriptionOrBuilder | |
| TensorDescriptionProtos | |
| TensorDiag<T extends TType> | Returns a diagonal tensor with a given diagonal values. |
| TensorDiagPart<T extends TType> | Returns the diagonal part of the tensor. |
| TensorFlow | Static utility methods describing the TensorFlow runtime. |
| tensorflow | |
| tensorflow | |
| TensorFlowException | Unchecked exception thrown by TensorFlow core classes |
| TensorForestCreateTreeVariable | Creates a tree resource and returns a handle to it. |
| TensorForestTreeDeserialize | Deserializes a proto into the tree handle |
| TensorForestTreeIsInitializedOp | Checks whether a tree has been initialized. |
| TensorForestTreePredict | Output the logits for the given input data |
| TensorForestTreeResourceHandleOp | Creates a handle to a TensorForestTreeResource |
| TensorForestTreeResourceHandleOp.Options | Optional attributes for TensorForestTreeResourceHandleOp
|
| TensorForestTreeSerialize | Serializes the tree handle to a proto |
| TensorForestTreeSize | Get the number of nodes in a tree |
| TensorInfo | Information about a Tensor necessary for feeding or retrieval. |
| TensorInfo.Builder | Information about a Tensor necessary for feeding or retrieval. |
| TensorInfo.CompositeTensor | Generic encoding for composite tensors. |
| TensorInfo.CompositeTensor.Builder | Generic encoding for composite tensors. |
| TensorInfo.CompositeTensorOrBuilder | |
| TensorInfo.CooSparse | For sparse tensors, The COO encoding stores a triple of values, indices, and shape. |
| TensorInfo.CooSparse.Builder | For sparse tensors, The COO encoding stores a triple of values, indices, and shape. |
| TensorInfo.CooSparseOrBuilder | |
| TensorInfo.EncodingCase | |
| TensorInfoOrBuilder | |
| TensorListConcat<U extends TType> | Concats all tensors in the list along the 0th dimension. |
| TensorListConcatLists | |
| TensorListElementShape<T extends TNumber> | The shape of the elements of the given list, as a tensor. |
| TensorListFromTensor | Creates a TensorList which, when stacked, has the value of `tensor`. |
| TensorListGather<T extends TType> | Creates a Tensor by indexing into the TensorList. |
| TensorListGetItem<T extends TType> | |
| TensorListLength | Returns the number of tensors in the input tensor list. |
| TensorListPopBack<T extends TType> | Returns the last element of the input list as well as a list with all but that element. |
| TensorListPushBack | Returns a list which has the passed-in `Tensor` as last element and the other elements of the given list in `input_handle`. |
| TensorListPushBackBatch | |
| TensorListReserve | List of the given size with empty elements. |
| TensorListResize | Resizes the list. |
| TensorListScatter | Creates a TensorList by indexing into a Tensor. |
| TensorListScatterIntoExistingList | Scatters tensor at indices in an input list. |
| TensorListSetItem | |
| TensorListSplit | Splits a tensor into a list. |
| TensorListStack<T extends TType> | Stacks all tensors in the list. |
| TensorListStack.Options | Optional attributes for TensorListStack
|
| TensorMapErase | Returns a tensor map with item from given key erased. |
| TensorMapHasKey | Returns whether the given key exists in the map. |
| TensorMapInsert | Returns a map that is the 'input_handle' with the given key-value pair inserted. |
| TensorMapLookup<U extends TType> | Returns the value from a given key in a tensor map. |
| TensorMapper<T extends TType> | Maps the native memory of a RawTensor to a n-dimensional typed data space
accessible from the JVM. |
| TensorMapSize | Returns the number of tensors in the input tensor map. |
| TensorMapStackKeys<T extends TType> | Returns a Tensor stack of all keys in a tensor map. |
| TensorMetadata | Metadata for a single tensor in the Snapshot Record. |
| TensorMetadata.Builder | Metadata for a single tensor in the Snapshot Record. |
| TensorMetadataOrBuilder | |
| TensorProto | Protocol buffer representing a tensor. |
| TensorProto.Builder | Protocol buffer representing a tensor. |
| TensorProtoOrBuilder | |
| TensorProtos | |
| TensorScatterNdAdd<T extends TType> | Adds sparse `updates` to an existing tensor according to `indices`. |
| TensorScatterNdMax<T extends TType> | |
| TensorScatterNdMin<T extends TType> | |
| TensorScatterNdSub<T extends TType> | Subtracts sparse `updates` from an existing tensor according to `indices`. |
| TensorScatterNdUpdate<T extends TType> | Scatter `updates` into an existing tensor according to `indices`. |
| TensorShapeProto | Dimensions of a tensor. |
| TensorShapeProto.Builder | Dimensions of a tensor. |
| TensorShapeProto.Dim | One dimension of the tensor. |
| TensorShapeProto.Dim.Builder | One dimension of the tensor. |
| TensorShapeProto.DimOrBuilder | |
| TensorShapeProtoOrBuilder | |
| TensorShapeProtos | |
| TensorSliceDataset | |
| TensorSliceDataset | Creates a dataset that emits each dim-0 slice of `components` once. |
| TensorSliceProto | Can only be interpreted if you know the corresponding TensorShape. |
| TensorSliceProto.Builder | Can only be interpreted if you know the corresponding TensorShape. |
| TensorSliceProto.Extent | Extent of the slice in one dimension. |
| TensorSliceProto.Extent.Builder | Extent of the slice in one dimension. |
| TensorSliceProto.Extent.HasLengthCase | |
| TensorSliceProto.ExtentOrBuilder | |
| TensorSliceProtoOrBuilder | |
| TensorSliceProtos | |
| TensorSpecProto | A protobuf to represent tf.TensorSpec. |
| TensorSpecProto.Builder | A protobuf to represent tf.TensorSpec. |
| TensorSpecProtoOrBuilder | |
| TensorStridedSliceUpdate<T extends TType> | Assign `value` to the sliced l-value reference of `input`. |
| TensorStridedSliceUpdate.Options | Optional attributes for TensorStridedSliceUpdate
|
| TensorSummary | Outputs a `Summary` protocol buffer with a tensor and per-plugin data. |
| TensorType | Annotation for all tensor types. |
| TensorTypeInfo<T extends TType> | Registered information about a tensor type. |
| TensorTypeRegistry | Repository of all registered tensor types. |
| TestLogProtos | |
| TestResults | The output of one benchmark / test run. |
| TestResults.BenchmarkType | The type of benchmark. |
| TestResults.Builder | The output of one benchmark / test run. |
| TestResultsOrBuilder | |
| TextLineDataset | |
| TextLineDataset | Creates a dataset that emits the lines of one or more text files. |
| TextLineReader | A Reader that outputs the lines of a file delimited by '\n'. |
| TextLineReader.Options | Optional attributes for TextLineReader
|
| TF_AllocatorAttributes | |
| TF_ApiDefMap | |
| TF_AttrMetadata | |
| TF_Buffer | |
| TF_Buffer.Data_deallocator_Pointer_long | |
| TF_DeprecatedSession | |
| TF_DeviceList | |
| TF_DimensionHandle | |
| TF_Function | |
| TF_FunctionOptions | |
| TF_Graph | |
| TF_ImportGraphDefOptions | |
| TF_ImportGraphDefResults | |
| TF_Input | |
| TF_KernelBuilder | |
| TF_Library | |
| TF_OpDefinitionBuilder | |
| TF_Operation | |
| TF_OperationDescription | |
| TF_OpKernelConstruction | |
| TF_OpKernelContext | |
| TF_Output | |
| TF_Server | |
| TF_Session | |
| TF_SessionOptions | |
| TF_ShapeHandle | |
| TF_ShapeInferenceContext | |
| TF_Status | |
| TF_StringView | |
| TF_Tensor | |
| TF_TString | |
| TF_TString_Large | |
| TF_TString_Offset | |
| TF_TString_Raw | |
| TF_TString_Small | |
| TF_TString_Union | |
| TF_TString_View | |
| TF_WhileParams | |
| TFE_Context | |
| TFE_ContextOptions | |
| TFE_Op | |
| TFE_TensorDebugInfo | |
| TFE_TensorHandle | |
| TFFailedPreconditionException | |
| TFInvalidArgumentException | |
| TFloat16 | IEEE-754 half-precision 16-bit float tensor type. |
| TFloat16Mapper | Maps memory of DT_HALF tensors
to a n-dimensional data space. |
| TFloat32 | IEEE-754 single-precision 32-bit float tensor type. |
| TFloat32Mapper | Maps memory of DT_FLOAT tensors
to a n-dimensional data space. |
| TFloat64 | IEEE-754 double-precision 64-bit float tensor type. |
| TFloat64Mapper | Maps memory of DT_DOUBLE tensors
to a n-dimensional data space. |
| TFloating | Common interface for all floating point tensors. |
| TFOutOfRangeException | |
| TFPermissionDeniedException | |
| TfRecordDataset | Creates a dataset that emits the records from one or more TFRecord files. |
| TFRecordDataset | |
| TfRecordReader | A Reader that outputs the records from a TensorFlow Records file. |
| TfRecordReader.Options | Optional attributes for TfRecordReader
|
| TFResourceExhaustedException | |
| TFUnauthenticatedException | |
| TFUnimplementedException | |
| ThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| ThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| ThreadPoolHandle | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| ThreadPoolHandle | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| ThreadPoolHandle.Options | Optional attributes for ThreadPoolHandle
|
| ThreadPoolHandle.Options | Optional attributes for ThreadPoolHandle
|
| ThreadPoolOptionProto | Protobuf type tensorflow.ThreadPoolOptionProto
|
| ThreadPoolOptionProto.Builder | Protobuf type tensorflow.ThreadPoolOptionProto
|
| ThreadPoolOptionProtoOrBuilder | |
| Tile<T extends TType> | Constructs a tensor by tiling a given tensor. |
| TileGrad<T extends TType> | Returns the gradient of `Tile`. |
| Timestamp | Provides the time since epoch in seconds. |
| TInt32 | 32-bit signed integer tensor type. |
| TInt32Mapper | Maps memory of DT_INT32 tensors
to a n-dimensional data space. |
| TInt64 | 64-bit signed integer tensor type. |
| TInt64Mapper | Maps memory of DT_INT64 tensors
to a n-dimensional data space. |
| TIntegral | Common interface for all integral numeric tensors. |
| TNumber | Common interface for all numeric tensors. |
| ToBool | Converts a tensor to a scalar predicate. |
| ToHashBucket | Converts each string in the input Tensor to its hash mod by a number of buckets. |
| ToHashBucketFast | Converts each string in the input Tensor to its hash mod by a number of buckets. |
| ToHashBucketStrong | Converts each string in the input Tensor to its hash mod by a number of buckets. |
| ToNumber<T extends TNumber> | Converts each string in the input Tensor to the specified numeric type. |
| TopK<T extends TNumber> | Finds values and indices of the `k` largest elements for the last dimension. |
| TopK.Options | Optional attributes for TopK
|
| TopKUnique | Returns the TopK unique values in the array in sorted order. |
| TopKWithUnique | Returns the TopK values in the array in sorted order. |
| TPUCompilationResult | Returns the result of a TPU compilation. |
| TPUEmbeddingActivations | An op enabling differentiation of TPU Embeddings. |
| TPUReplicatedInput<T extends TType> | Connects N inputs to an N-way replicated TPU computation. |
| TPUReplicatedInput.Options | Optional attributes for TPUReplicatedInput
|
| TPUReplicatedOutput<T extends TType> | Connects N outputs from an N-way replicated TPU computation. |
| TPUReplicateMetadata | Metadata indicating how the TPU computation should be replicated. |
| TPUReplicateMetadata.Options | Optional attributes for TPUReplicateMetadata
|
| TrackableObjectGraph | Protobuf type tensorflow.TrackableObjectGraph
|
| TrackableObjectGraph.Builder | Protobuf type tensorflow.TrackableObjectGraph
|
| TrackableObjectGraph.TrackableObject | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject
|
| TrackableObjectGraph.TrackableObject.Builder | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject
|
| TrackableObjectGraph.TrackableObject.ObjectReference | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference
|
| TrackableObjectGraph.TrackableObject.ObjectReference.Builder | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference
|
| TrackableObjectGraph.TrackableObject.ObjectReferenceOrBuilder | |
| TrackableObjectGraph.TrackableObject.SerializedTensor | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.SerializedTensor
|
| TrackableObjectGraph.TrackableObject.SerializedTensor.Builder | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.SerializedTensor
|
| TrackableObjectGraph.TrackableObject.SerializedTensorOrBuilder | |
| TrackableObjectGraph.TrackableObject.SlotVariableReference | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference
|
| TrackableObjectGraph.TrackableObject.SlotVariableReference.Builder | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference
|
| TrackableObjectGraph.TrackableObject.SlotVariableReferenceOrBuilder | |
| TrackableObjectGraph.TrackableObjectOrBuilder | |
| TrackableObjectGraphOrBuilder | |
| TrackableObjectGraphProtos | |
| TransportOptions | |
| TransportOptions.RecvBufRespExtra | Extra data needed on a non-RDMA RecvBufResponse. |
| TransportOptions.RecvBufRespExtra.Builder | Extra data needed on a non-RDMA RecvBufResponse. |
| TransportOptions.RecvBufRespExtraOrBuilder | |
| Transpose<T extends TType> | Shuffle dimensions of x according to a permutation. |
| TriangularSolve<T extends TType> | Solves systems of linear equations with upper or lower triangular matrices by backsubstitution. |
| TriangularSolve.Options | Optional attributes for TriangularSolve
|
| TridiagonalMatMul<T extends TType> | Calculate product with tridiagonal matrix. |
| TridiagonalSolve<T extends TType> | Solves tridiagonal systems of equations. |
| TridiagonalSolve.Options | Optional attributes for TridiagonalSolve
|
| TruncateDiv<T extends TType> | Returns x / y element-wise for integer types. |
| TruncatedNormal<T extends TFloating> | Initializer that generates a truncated normal distribution. |
| TruncatedNormal<U extends TNumber> | Outputs random values from a truncated normal distribution. |
| TruncatedNormal.Options | Optional attributes for TruncatedNormal
|
| TruncateMod<T extends TNumber> | Returns element-wise remainder of division. |
| TryRpc | Perform batches of RPC requests. |
| TryRpc.Options | Optional attributes for TryRpc
|
| TString | String type. |
| TStringInitializer<T> | Helper class for initializing a TString tensor. |
| TStringMapper | Maps memory of DT_STRING tensors
to a n-dimensional data space. |
| TType | Common interface for all typed tensors. |
| TUint8 | 8-bit unsigned integer tensor type. |
| TUint8Mapper | Maps memory of DT_UINT8 tensors
to a n-dimensional data space. |
| TupleValue | Represents a Python tuple. |
| TupleValue.Builder | Represents a Python tuple. |
| TupleValueOrBuilder | |
| TypeSpecProto | Represents a tf.TypeSpecProtobuf type tensorflow.TypeSpecProto
|
| TypeSpecProto.Builder | Represents a tf.TypeSpecProtobuf type tensorflow.TypeSpecProto
|
| TypeSpecProto.TypeSpecClass | Protobuf enum tensorflow.TypeSpecProto.TypeSpecClass
|
| TypeSpecProtoOrBuilder | |
| TypesProtos |
U
| Unbatch<T extends TType> | Reverses the operation of Batch for a single output Tensor. |
| Unbatch.Options | Optional attributes for Unbatch
|
| UnbatchDataset | A dataset that splits the elements of its input into multiple elements. |
| UnbatchDataset | A dataset that splits the elements of its input into multiple elements. |
| UnbatchGrad<T extends TType> | Gradient of Unbatch. |
| UnbatchGrad.Options | Optional attributes for UnbatchGrad
|
| UncompressElement | Uncompresses a compressed dataset element. |
| UnicodeDecode<T extends TNumber> | Decodes each string in `input` into a sequence of Unicode code points. |
| UnicodeDecode.Options | Optional attributes for UnicodeDecode
|
| UnicodeDecodeWithOffsets<T extends TNumber> | Decodes each string in `input` into a sequence of Unicode code points. |
| UnicodeDecodeWithOffsets.Options | Optional attributes for UnicodeDecodeWithOffsets
|
| UnicodeEncode | Encode a tensor of ints into unicode strings. |
| UnicodeEncode.Options | Optional attributes for UnicodeEncode
|
| UnicodeScript | Determine the script codes of a given tensor of Unicode integer code points. |
| UnicodeTranscode | Transcode the input text from a source encoding to a destination encoding. |
| UnicodeTranscode.Options | Optional attributes for UnicodeTranscode
|
| UniformCandidateSampler | Generates labels for candidate sampling with a uniform distribution. |
| UniformCandidateSampler.Options | Optional attributes for UniformCandidateSampler
|
| Unique<T extends TType, V extends TNumber> | Finds unique elements along an axis of a tensor. |
| UniqueDataset | Creates a dataset that contains the unique elements of `input_dataset`. |
| UniqueDataset | Creates a dataset that contains the unique elements of `input_dataset`. |
| UniqueWithCounts<T extends TType, V extends TNumber> | Finds unique elements along an axis of a tensor. |
| UnitNorm | Constrains the weights to have unit norm. |
| UnravelIndex<T extends TNumber> | Converts an array of flat indices into a tuple of coordinate arrays. |
| UnsortedSegmentJoin | Joins the elements of `inputs` based on `segment_ids`. |
| UnsortedSegmentJoin.Options | Optional attributes for UnsortedSegmentJoin
|
| UnsortedSegmentMax<T extends TNumber> | Computes the maximum along segments of a tensor. |
| UnsortedSegmentMin<T extends TNumber> | Computes the minimum along segments of a tensor. |
| UnsortedSegmentProd<T extends TType> | Computes the product along segments of a tensor. |
| UnsortedSegmentSum<T extends TType> | Computes the sum along segments of a tensor. |
| Unstack<T extends TType> | Unpacks a given dimension of a rank-`R` tensor into `num` rank-`(R-1)` tensors. |
| Unstack.Options | Optional attributes for Unstack
|
| Unstage | Op is similar to a lightweight Dequeue. |
| Unstage.Options | Optional attributes for Unstage
|
| UnwrapDatasetVariant | |
| Upper | Converts all lowercase characters into their respective uppercase replacements. |
| Upper.Options | Optional attributes for Upper
|
| UpperBound<U extends TNumber> | Applies upper_bound(sorted_search_values, values) along each row. |
V
| Validator | |
| Validator | |
| ValuesDef | Protocol buffer representing the values in ControlFlowContext. |
| ValuesDef.Builder | Protocol buffer representing the values in ControlFlowContext. |
| ValuesDefOrBuilder | |
| VarHandleOp | Creates a handle to a Variable resource. |
| VarHandleOp.Options | Optional attributes for VarHandleOp
|
| Variable<T extends TType> | Holds state in the form of a tensor that persists across steps. |
| Variable.Options | Optional attributes for Variable
|
| VariableAggregation | Indicates how a distributed variable will be aggregated. |
| VariableDef | Protocol buffer representing a Variable. |
| VariableDef.Builder | Protocol buffer representing a Variable. |
| VariableDefOrBuilder | |
| VariableProtos | |
| VariableShape<T extends TNumber> | Returns the shape of the variable pointed to by `resource`. |
| VariableSynchronization | Indicates when a distributed variable will be synced. |
| VarianceScaling<T extends TFloating> | Initializer capable of adapting its scale to the shape of weights tensors. |
| VarianceScaling.Distribution | The random distribution to use when initializing the values. |
| VarianceScaling.Mode | The mode to use for calculating the fan values. |
| VariantTensorDataProto | Protocol buffer representing the serialization format of DT_VARIANT tensors. |
| VariantTensorDataProto.Builder | Protocol buffer representing the serialization format of DT_VARIANT tensors. |
| VariantTensorDataProtoOrBuilder | |
| VarIsInitializedOp | Checks whether a resource handle-based variable has been initialized. |
| VarLenFeatureProto | Protobuf type tensorflow.VarLenFeatureProto
|
| VarLenFeatureProto.Builder | Protobuf type tensorflow.VarLenFeatureProto
|
| VarLenFeatureProtoOrBuilder | |
| VerifierConfig | The config for graph verifiers. |
| VerifierConfig.Builder | The config for graph verifiers. |
| VerifierConfig.Toggle | Protobuf enum tensorflow.VerifierConfig.Toggle
|
| VerifierConfigOrBuilder | |
| VerifierConfigProtos | |
| VersionDef | Version information for a piece of serialized data There are different types of versions for each type of data (GraphDef, etc.), but they all have the same common shape described here. |
| VersionDef.Builder | Version information for a piece of serialized data There are different types of versions for each type of data (GraphDef, etc.), but they all have the same common shape described here. |
| VersionDefOrBuilder | |
| VersionsProtos |
W
| WatchdogConfig | Protobuf type tensorflow.WatchdogConfig
|
| WatchdogConfig.Builder | Protobuf type tensorflow.WatchdogConfig
|
| WatchdogConfigOrBuilder | |
| WeakPointerScope | A minimalist pointer scope only keeping weak references to its elements. |
| Where | Returns locations of nonzero / true values in a tensor. |
| WhileContextDef | Protocol buffer representing a WhileContext object. |
| WhileContextDef.Builder | Protocol buffer representing a WhileContext object. |
| WhileContextDefOrBuilder | |
| WholeFileReader | A Reader that outputs the entire contents of a file as a value. |
| WholeFileReader.Options | Optional attributes for WholeFileReader
|
| WindowDataset | Combines (nests of) input elements into a dataset of (nests of) windows. |
| WorkerHealth | Current health status of a worker. |
| WorkerHeartbeat | Worker heartbeat op. |
| WorkerHeartbeatRequest | Protobuf type tensorflow.WorkerHeartbeatRequest
|
| WorkerHeartbeatRequest.Builder | Protobuf type tensorflow.WorkerHeartbeatRequest
|
| WorkerHeartbeatRequestOrBuilder | |
| WorkerHeartbeatResponse | Protobuf type tensorflow.WorkerHeartbeatResponse
|
| WorkerHeartbeatResponse.Builder | Protobuf type tensorflow.WorkerHeartbeatResponse
|
| WorkerHeartbeatResponseOrBuilder | |
| WorkerShutdownMode | Indicates the behavior of the worker when an internal error or shutdown signal is received. |
| WrapDatasetVariant | |
| WriteAudioSummary | Writes an audio summary. |
| WriteAudioSummary.Options | Optional attributes for WriteAudioSummary
|
| WriteFile | Writes contents to the file at input filename. |
| WriteGraphSummary | Writes a graph summary. |
| WriteHistogramSummary | Writes a histogram summary. |
| WriteImageSummary | Writes an image summary. |
| WriteImageSummary.Options | Optional attributes for WriteImageSummary
|
| WriteRawProtoSummary | Writes a serialized proto summary. |
| WriteScalarSummary | Writes a scalar summary. |
| WriteSummary | Writes a tensor summary. |
X
| Xdivy<T extends TType> | Returns 0 if x == 0, and x / y otherwise, elementwise. |
| XEvent | An XEvent is a trace event, optionally annotated with XStats. |
| XEvent.Builder | An XEvent is a trace event, optionally annotated with XStats. |
| XEvent.DataCase | |
| XEventMetadata | Metadata for an XEvent, corresponds to an event type and is shared by all XEvents with the same metadata_id. |
| XEventMetadata.Builder | Metadata for an XEvent, corresponds to an event type and is shared by all XEvents with the same metadata_id. |
| XEventMetadataOrBuilder | |
| XEventOrBuilder | |
| XlaRecvFromHost<T extends TType> | An op to receive a tensor from the host. |
| XlaSendToHost | An op to send a tensor to the host. |
| XlaSetBound | Set a bound for the given input value as a hint to Xla compiler,
returns the same value. |
| XlaSpmdFullToShardShape<T extends TType> | An op used by XLA SPMD partitioner to switch from automatic partitioning to
manual partitioning. |
| XlaSpmdShardToFullShape<T extends TType> | An op used by XLA SPMD partitioner to switch from manual partitioning to
automatic partitioning. |
| XLine | An XLine is a timeline of trace events (XEvents). |
| XLine.Builder | An XLine is a timeline of trace events (XEvents). |
| XLineOrBuilder | |
| Xlog1py<T extends TType> | Returns 0 if x == 0, and x * log1p(y) otherwise, elementwise. |
| Xlogy<T extends TType> | Returns 0 if x == 0, and x * log(y) otherwise, elementwise. |
| XPlane | An XPlane is a container of parallel timelines (XLines), generated by a profiling source or by post-processing one or more XPlanes. |
| XPlane.Builder | An XPlane is a container of parallel timelines (XLines), generated by a profiling source or by post-processing one or more XPlanes. |
| XPlaneOrBuilder | |
| XPlaneProtos | |
| XSpace | A container of parallel XPlanes, generated by one or more profiling sources. |
| XSpace.Builder | A container of parallel XPlanes, generated by one or more profiling sources. |
| XSpaceOrBuilder | |
| XStat | An XStat is a named value associated with an XEvent, e.g., a performance counter value, a metric computed by a formula applied over nested XEvents and XStats. |
| XStat.Builder | An XStat is a named value associated with an XEvent, e.g., a performance counter value, a metric computed by a formula applied over nested XEvents and XStats. |
| XStat.ValueCase | |
| XStatMetadata | Metadata for an XStat, corresponds to a stat type and is shared by all XStats with the same metadata_id. |
| XStatMetadata.Builder | Metadata for an XStat, corresponds to a stat type and is shared by all XStats with the same metadata_id. |
| XStatMetadataOrBuilder | |
| XStatOrBuilder |
Z
| Zeros<T extends TType> | Creates an Initializer that sets all values to zero. |
| Zeros<T extends TType> | An operator creating a constant initialized with zeros of the shape given by `dims`. |
| ZerosLike<T extends TType> | Returns a tensor of zeros with the same shape and type as x. |
| Zeta<T extends TNumber> | Compute the Hurwitz zeta function \\(\zeta(x, q)\\). |
| ZipDataset | Creates a dataset that zips together `input_datasets`. |