All Classes Interface Summary Class Summary Enum Summary Exception Summary Annotation Types Summary
| Class |
Description |
| Abort |
Raise a exception to abort the process when called.
|
| Abort.Inputs |
|
| Abort.Options |
Optional attributes for Abort |
| Abs<T extends TNumber> |
Computes the absolute value of a tensor.
|
| Abs.Inputs<T extends TNumber> |
|
| AccumulateN<T extends TType> |
Returns the element-wise sum of a list of tensors.
|
| AccumulateN.Inputs<T extends TType> |
|
| AccumulatorApplyGradient |
Applies a gradient to a given accumulator.
|
| AccumulatorApplyGradient.Inputs |
|
| AccumulatorNumAccumulated |
Returns the number of gradients aggregated in the given accumulators.
|
| AccumulatorNumAccumulated.Inputs |
|
| AccumulatorSetGlobalStep |
Updates the accumulator with a new value for global_step.
|
| AccumulatorSetGlobalStep.Inputs |
|
| AccumulatorTakeGradient<T extends TType> |
Extracts the average gradient in the given ConditionalAccumulator.
|
| AccumulatorTakeGradient.Inputs |
|
| Acos<T extends TType> |
Computes acos of x element-wise.
|
| Acos.Inputs<T extends TType> |
|
| Acosh<T extends TType> |
Computes inverse hyperbolic cosine of x element-wise.
|
| Acosh.Inputs<T extends TType> |
|
| Add<T extends TType> |
Returns x + y element-wise.
|
| Add.Inputs<T extends TType> |
|
| AddManySparseToTensorsMap |
Add an N-minibatch SparseTensor to a SparseTensorsMap, return N handles.
|
| AddManySparseToTensorsMap.Inputs |
|
| AddManySparseToTensorsMap.Options |
|
| AddN<T extends TType> |
Add all input tensors element wise.
|
| AddN.Inputs<T extends TType> |
|
| AddSparseToTensorsMap |
Add a SparseTensor to a SparseTensorsMap return its handle.
|
| AddSparseToTensorsMap.Inputs |
|
| AddSparseToTensorsMap.Options |
|
| AdjustContrast<T extends TNumber> |
Adjust the contrast of one or more images.
|
| AdjustContrast.Inputs<T extends TNumber> |
|
| AdjustHue<T extends TNumber> |
Adjust the hue of one or more images.
|
| AdjustHue.Inputs<T extends TNumber> |
|
| AdjustSaturation<T extends TNumber> |
Adjust the saturation of one or more images.
|
| AdjustSaturation.Inputs<T extends TNumber> |
|
| All |
Computes the "logical and" of elements across dimensions of a tensor.
|
| All.Inputs |
|
| All.Options |
Optional attributes for All |
| AllCandidateSampler |
Generates labels for candidate sampling with a learned unigram distribution.
|
| AllCandidateSampler.Inputs |
|
| AllCandidateSampler.Options |
|
| 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> |
Wraps the XLA AllReduce operator
documented at https://www.tensorflow.org/xla/operation_semantics#allreduce.
|
| AllReduce.Inputs<T extends TNumber> |
|
| AllToAll<T extends TType> |
An Op to exchange data across TPU replicas.
|
| AllToAll.Inputs<T extends TType> |
|
| Angle<U extends TNumber> |
Returns the argument of a complex number.
|
| Angle.Inputs |
|
| AnonymousHashTable |
Creates a uninitialized anonymous hash table.
|
| AnonymousHashTable.Inputs |
|
| AnonymousIterator |
A container for an iterator resource.
|
| AnonymousIterator.Inputs |
|
| AnonymousMemoryCache |
The AnonymousMemoryCache operation
|
| AnonymousMemoryCache.Inputs |
|
| AnonymousMultiDeviceIterator |
A container for a multi device iterator resource.
|
| AnonymousMultiDeviceIterator.Inputs |
|
| AnonymousMutableDenseHashTable |
Creates an empty anonymous mutable hash table that uses tensors as the backing store.
|
| AnonymousMutableDenseHashTable.Inputs<T extends TType> |
|
| AnonymousMutableDenseHashTable.Options |
|
| AnonymousMutableHashTable |
Creates an empty anonymous mutable hash table.
|
| AnonymousMutableHashTable.Inputs |
|
| AnonymousMutableHashTableOfTensors |
Creates an empty anonymous mutable hash table of vector values.
|
| AnonymousMutableHashTableOfTensors.Inputs |
|
| AnonymousMutableHashTableOfTensors.Options |
|
| AnonymousRandomSeedGenerator |
The AnonymousRandomSeedGenerator operation
|
| AnonymousRandomSeedGenerator.Inputs |
|
| AnonymousSeedGenerator |
The AnonymousSeedGenerator operation
|
| AnonymousSeedGenerator.Inputs |
|
| Any |
Computes the "logical or" of elements across dimensions of a tensor.
|
| Any.Inputs |
|
| 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.Inputs<T extends TType> |
|
| ApplyAdadelta.Options |
|
| ApplyAdagrad<T extends TType> |
Update '*var' according to the adagrad scheme.
|
| ApplyAdagrad.Inputs<T extends TType> |
|
| ApplyAdagrad.Options |
|
| ApplyAdagradDa<T extends TType> |
Update '*var' according to the proximal adagrad scheme.
|
| ApplyAdagradDa.Inputs<T extends TType> |
|
| ApplyAdagradDa.Options |
|
| ApplyAdagradV2<T extends TType> |
Update '*var' according to the adagrad scheme.
|
| ApplyAdagradV2.Inputs<T extends TType> |
|
| ApplyAdagradV2.Options |
|
| ApplyAdam<T extends TType> |
Update '*var' according to the Adam algorithm.
|
| ApplyAdam.Inputs<T extends TType> |
|
| ApplyAdam.Options |
|
| ApplyAdaMax<T extends TType> |
Update '*var' according to the AdaMax algorithm.
|
| ApplyAdaMax.Inputs<T extends TType> |
|
| ApplyAdaMax.Options |
|
| ApplyAddSign<T extends TType> |
Update '*var' according to the AddSign update.
|
| ApplyAddSign.Inputs<T extends TType> |
|
| ApplyAddSign.Options |
|
| ApplyCenteredRmsProp<T extends TType> |
Update '*var' according to the centered RMSProp algorithm.
|
| ApplyCenteredRmsProp.Inputs<T extends TType> |
|
| ApplyCenteredRmsProp.Options |
|
| ApplyFtrl<T extends TType> |
Update '*var' according to the Ftrl-proximal scheme.
|
| ApplyFtrl.Inputs<T extends TType> |
|
| ApplyFtrl.Options |
|
| ApplyGradientDescent<T extends TType> |
Update '*var' by subtracting 'alpha' * 'delta' from it.
|
| ApplyGradientDescent.Inputs<T extends TType> |
|
| ApplyGradientDescent.Options |
|
| ApplyMomentum<T extends TType> |
Update '*var' according to the momentum scheme.
|
| ApplyMomentum.Inputs<T extends TType> |
|
| ApplyMomentum.Options |
|
| ApplyPowerSign<T extends TType> |
Update '*var' according to the AddSign update.
|
| ApplyPowerSign.Inputs<T extends TType> |
|
| ApplyPowerSign.Options |
|
| ApplyProximalAdagrad<T extends TType> |
Update '*var' and '*accum' according to FOBOS with Adagrad learning rate.
|
| ApplyProximalAdagrad.Inputs<T extends TType> |
|
| ApplyProximalAdagrad.Options |
|
| ApplyProximalGradientDescent<T extends TType> |
Update '*var' as FOBOS algorithm with fixed learning rate.
|
| ApplyProximalGradientDescent.Inputs<T extends TType> |
|
| ApplyProximalGradientDescent.Options |
|
| ApplyRmsProp<T extends TType> |
Update '*var' according to the RMSProp algorithm.
|
| ApplyRmsProp.Inputs<T extends TType> |
|
| ApplyRmsProp.Options |
|
| ApproximateEqual |
Returns the truth value of abs(x-y) < tolerance element-wise.
|
| ApproximateEqual.Inputs<T extends TType> |
|
| ApproximateEqual.Options |
|
| ApproxTopK<T extends TNumber> |
Returns min/max k values and their indices of the input operand in an approximate manner.
|
| ApproxTopK.Inputs<T extends TNumber> |
|
| ApproxTopK.Options |
|
| ArgMax<V extends TNumber> |
Returns the index with the largest value across dimensions of a tensor.
|
| ArgMax.Inputs |
|
| ArgMin<V extends TNumber> |
Returns the index with the smallest value across dimensions of a tensor.
|
| ArgMin.Inputs |
|
| Asin<T extends TType> |
Computes the trignometric inverse sine of x element-wise.
|
| Asin.Inputs<T extends TType> |
|
| Asinh<T extends TType> |
Computes inverse hyperbolic sine of x element-wise.
|
| Asinh.Inputs<T extends TType> |
|
| AssertCardinalityDataset |
The AssertCardinalityDataset operation
|
| AssertCardinalityDataset.Inputs |
|
| AssertNextDataset |
A transformation that asserts which transformations happen next.
|
| AssertNextDataset |
The ExperimentalAssertNextDataset operation
|
| AssertNextDataset.Inputs |
|
| AssertNextDataset.Inputs |
|
| AssertPrevDataset |
A transformation that asserts which transformations happened previously.
|
| AssertPrevDataset.Inputs |
|
| AssertThat |
Asserts that the given condition is true.
|
| AssertThat.Inputs |
|
| AssertThat.Options |
|
| 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.Inputs<T extends TType> |
|
| Assign.Options |
Optional attributes for Assign |
| AssignAdd<T extends TType> |
Update 'ref' by adding 'value' to it.
|
| AssignAdd.Inputs<T extends TType> |
|
| AssignAdd.Options |
|
| AssignAddVariableOp |
Adds a value to the current value of a variable.
|
| AssignAddVariableOp.Inputs |
|
| AssignSub<T extends TType> |
Update 'ref' by subtracting 'value' from it.
|
| AssignSub.Inputs<T extends TType> |
|
| AssignSub.Options |
|
| AssignSubVariableOp |
Subtracts a value from the current value of a variable.
|
| AssignSubVariableOp.Inputs |
|
| AssignVariableConcatND |
Concats input tensor across all dimensions.
|
| AssignVariableConcatND.Inputs |
|
| AssignVariableConcatND.Options |
|
| AssignVariableOp |
Assigns a new value to a variable.
|
| AssignVariableOp.Inputs |
|
| AssignVariableOp.Options |
|
| AsString |
Converts each entry in the given tensor to strings.
|
| AsString.Inputs |
|
| AsString.Options |
|
| Atan<T extends TType> |
Computes the trignometric inverse tangent of x element-wise.
|
| Atan.Inputs<T extends TType> |
|
| Atan2<T extends TNumber> |
Computes arctangent of y/x element-wise, respecting signs of the arguments.
|
| Atan2.Inputs<T extends TNumber> |
|
| Atanh<T extends TType> |
Computes inverse hyperbolic tangent of x element-wise.
|
| Atanh.Inputs<T extends TType> |
|
| AttributeMetadata |
Metadata of an op's attribute.
|
| 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.IfChange
|
| AttrValue.ListValue.Builder |
LINT.IfChange
|
| AttrValue.ListValueOrBuilder |
|
| AttrValue.ValueCase |
|
| AttrValueOrBuilder |
|
| AttrValueProtos |
|
| AudioOps |
An API for building audio operations as Ops |
| AudioSpectrogram |
Produces a visualization of audio data over time.
|
| AudioSpectrogram.Inputs |
|
| AudioSpectrogram.Options |
|
| AudioSummary |
Outputs a Summary protocol buffer with audio.
|
| AudioSummary.Inputs |
|
| AudioSummary.Options |
|
| 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.Inputs |
|
| AutoShardDataset.Inputs |
|
| AutoShardDataset.Options |
|
| AutoShardDataset.Options |
|
| AutoShardPolicy |
Represents the type of auto-sharding we enable.
|
| AutotuneAlgorithm |
Algorithm used for model autotuning optimization.
|
| AutotuneOptions |
next: 5
|
| AutotuneOptions.Builder |
next: 5
|
| AutotuneOptions.OptionalAutotuneAlgorithmCase |
|
| AutotuneOptions.OptionalCpuBudgetCase |
|
| AutotuneOptions.OptionalEnabledCase |
|
| AutotuneOptions.OptionalRamBudgetCase |
|
| AutotuneOptionsOrBuilder |
|
| AvailableDeviceInfo |
Matches DeviceAttributes
|
| AvailableDeviceInfo.Builder |
Matches DeviceAttributes
|
| AvailableDeviceInfoOrBuilder |
|
| AvgPool<T extends TNumber> |
Performs average pooling on the input.
|
| AvgPool.Inputs<T extends TNumber> |
|
| AvgPool.Options |
|
| AvgPool3d<T extends TNumber> |
Performs 3D average pooling on the input.
|
| AvgPool3d.Inputs<T extends TNumber> |
|
| AvgPool3d.Options |
|
| AvgPool3dGrad<T extends TNumber> |
Computes gradients of average pooling function.
|
| AvgPool3dGrad.Inputs<T extends TNumber> |
|
| AvgPool3dGrad.Options |
|
| AvgPoolGrad<T extends TNumber> |
Computes gradients of the average pooling function.
|
| AvgPoolGrad.Inputs<T extends TNumber> |
|
| AvgPoolGrad.Options |
|
| BandedTriangularSolve<T extends TType> |
The BandedTriangularSolve operation
|
| BandedTriangularSolve.Inputs<T extends TType> |
|
| BandedTriangularSolve.Options |
|
| BandPart<T extends TType> |
Copy a tensor setting everything outside a central band in each innermost matrix to zero.
|
| BandPart.Inputs<T extends TType,U extends TNumber> |
|
| Barrier |
Defines a barrier that persists across different graph executions.
|
| Barrier.Inputs |
|
| Barrier.Options |
|
| BarrierClose |
Closes the given barrier.
|
| BarrierClose.Inputs |
|
| BarrierClose.Options |
|
| BarrierIncompleteSize |
Computes the number of incomplete elements in the given barrier.
|
| BarrierIncompleteSize.Inputs |
|
| BarrierInsertMany |
For each key, assigns the respective value to the specified component.
|
| BarrierInsertMany.Inputs |
|
| BarrierReadySize |
Computes the number of complete elements in the given barrier.
|
| BarrierReadySize.Inputs |
|
| BarrierTakeMany |
Takes the given number of completed elements from a barrier.
|
| BarrierTakeMany.Inputs |
|
| BarrierTakeMany.Options |
|
| BaseGradientAdapter |
Helper base class for custom gradient adapters INTERNAL USE ONLY
|
| Batch |
Batches all input tensors nondeterministically.
|
| Batch.Inputs |
|
| Batch.Options |
Optional attributes for Batch |
| BatchCholesky<T extends TNumber> |
The BatchCholesky operation
|
| BatchCholesky.Inputs<T extends TNumber> |
|
| BatchCholeskyGrad<T extends TNumber> |
The BatchCholeskyGrad operation
|
| BatchCholeskyGrad.Inputs<T extends TNumber> |
|
| BatchDataset |
Creates a dataset that batches batch_size elements from input_dataset.
|
| BatchDataset.Inputs |
|
| BatchDataset.Options |
|
| BatchFft |
The BatchFFT operation
|
| BatchFft.Inputs |
|
| BatchFft2d |
The BatchFFT2D operation
|
| BatchFft2d.Inputs |
|
| BatchFft3d |
The BatchFFT3D operation
|
| BatchFft3d.Inputs |
|
| BatchFunction |
Batches all the inputs tensors to the computation done by the function.
|
| BatchFunction.Inputs |
|
| BatchFunction.Options |
|
| BatchIfft |
The BatchIFFT operation
|
| BatchIfft.Inputs |
|
| BatchIfft2d |
The BatchIFFT2D operation
|
| BatchIfft2d.Inputs |
|
| BatchIfft3d |
The BatchIFFT3D operation
|
| BatchIfft3d.Inputs |
|
| BatchMatMul<V extends TType> |
Multiplies slices of two tensors in batches.
|
| BatchMatMul.Inputs |
|
| BatchMatMul.Options |
|
| BatchMatrixBandPart<T extends TType> |
The BatchMatrixBandPart operation
|
| BatchMatrixBandPart.Inputs<T extends TType> |
|
| BatchMatrixDeterminant<T extends TType> |
The BatchMatrixDeterminant operation
|
| BatchMatrixDeterminant.Inputs<T extends TType> |
|
| BatchMatrixDiag<T extends TType> |
The BatchMatrixDiag operation
|
| BatchMatrixDiag.Inputs<T extends TType> |
|
| BatchMatrixDiagPart<T extends TType> |
The BatchMatrixDiagPart operation
|
| BatchMatrixDiagPart.Inputs<T extends TType> |
|
| BatchMatrixInverse<T extends TNumber> |
The BatchMatrixInverse operation
|
| BatchMatrixInverse.Inputs<T extends TNumber> |
|
| BatchMatrixInverse.Options |
|
| BatchMatrixSetDiag<T extends TType> |
The BatchMatrixSetDiag operation
|
| BatchMatrixSetDiag.Inputs<T extends TType> |
|
| BatchMatrixSolve<T extends TNumber> |
The BatchMatrixSolve operation
|
| BatchMatrixSolve.Inputs<T extends TNumber> |
|
| BatchMatrixSolve.Options |
|
| BatchMatrixSolveLs<T extends TNumber> |
The BatchMatrixSolveLs operation
|
| BatchMatrixSolveLs.Inputs<T extends TNumber> |
|
| BatchMatrixSolveLs.Options |
|
| BatchMatrixTriangularSolve<T extends TNumber> |
The BatchMatrixTriangularSolve operation
|
| BatchMatrixTriangularSolve.Inputs<T extends TNumber> |
|
| BatchMatrixTriangularSolve.Options |
|
| BatchNormWithGlobalNormalization<T extends TType> |
Batch normalization.
|
| BatchNormWithGlobalNormalization.Inputs<T extends TType> |
|
| BatchNormWithGlobalNormalizationGrad<T extends TType> |
Gradients for batch normalization.
|
| BatchNormWithGlobalNormalizationGrad.Inputs<T extends TType> |
|
| BatchSelfAdjointEig<T extends TNumber> |
The BatchSelfAdjointEigV2 operation
|
| BatchSelfAdjointEig.Inputs<T extends TNumber> |
|
| BatchSelfAdjointEig.Options |
|
| BatchSvd<T extends TType> |
The BatchSvd operation
|
| BatchSvd.Inputs<T extends TType> |
|
| BatchSvd.Options |
|
| BatchToSpace<T extends TType> |
BatchToSpace for 4-D tensors of type T.
|
| BatchToSpace.Inputs<T extends TType> |
|
| BatchToSpaceNd<T extends TType> |
BatchToSpace for N-D tensors of type T.
|
| BatchToSpaceNd.Inputs<T extends TType> |
|
| 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> |
The BesselI0 operation
|
| BesselI0.Inputs<T extends TNumber> |
|
| BesselI0e<T extends TNumber> |
The BesselI0e operation
|
| BesselI0e.Inputs<T extends TNumber> |
|
| BesselI1<T extends TNumber> |
The BesselI1 operation
|
| BesselI1.Inputs<T extends TNumber> |
|
| BesselI1e<T extends TNumber> |
The BesselI1e operation
|
| BesselI1e.Inputs<T extends TNumber> |
|
| BesselJ0<T extends TNumber> |
The BesselJ0 operation
|
| BesselJ0.Inputs<T extends TNumber> |
|
| BesselJ1<T extends TNumber> |
The BesselJ1 operation
|
| BesselJ1.Inputs<T extends TNumber> |
|
| BesselK0<T extends TNumber> |
The BesselK0 operation
|
| BesselK0.Inputs<T extends TNumber> |
|
| BesselK0e<T extends TNumber> |
The BesselK0e operation
|
| BesselK0e.Inputs<T extends TNumber> |
|
| BesselK1<T extends TNumber> |
The BesselK1 operation
|
| BesselK1.Inputs<T extends TNumber> |
|
| BesselK1e<T extends TNumber> |
The BesselK1e operation
|
| BesselK1e.Inputs<T extends TNumber> |
|
| BesselY0<T extends TNumber> |
The BesselY0 operation
|
| BesselY0.Inputs<T extends TNumber> |
|
| BesselY1<T extends TNumber> |
The BesselY1 operation
|
| BesselY1.Inputs<T extends TNumber> |
|
| Betainc<T extends TNumber> |
Compute the regularized incomplete beta integral \(I_x(a, b)\).
|
| Betainc.Inputs<T extends TNumber> |
|
| BfcMemoryMapProtos |
|
| BiasAdd<T extends TType> |
Adds bias to value.
|
| BiasAdd.Inputs<T extends TType> |
|
| BiasAdd.Options |
|
| BiasAddGrad<T extends TType> |
The backward operation for "BiasAdd" on the "bias" tensor.
|
| BiasAddGrad.Inputs<T extends TType> |
|
| BiasAddGrad.Options |
|
| Bincount<T extends TNumber> |
Counts the number of occurrences of each value in an integer array.
|
| Bincount.Inputs<T extends TNumber> |
|
| 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.
|
| Bitcast.Inputs |
|
| BitwiseAnd<T extends TNumber> |
Elementwise computes the bitwise AND of x and y.
|
| BitwiseAnd.Inputs<T extends TNumber> |
|
| BitwiseOps |
An API for building bitwise operations as Ops |
| BitwiseOr<T extends TNumber> |
Elementwise computes the bitwise OR of x and y.
|
| BitwiseOr.Inputs<T extends TNumber> |
|
| BitwiseXor<T extends TNumber> |
Elementwise computes the bitwise XOR of x and y.
|
| BitwiseXor.Inputs<T extends TNumber> |
|
| BlockLSTM<T extends TNumber> |
Computes the LSTM cell forward propagation for all the time steps.
|
| BlockLSTM.Inputs<T extends TNumber> |
|
| BlockLSTM.Options |
|
| BlockLSTMGrad<T extends TNumber> |
Computes the LSTM cell backward propagation for the entire time sequence.
|
| BlockLSTMGrad.Inputs<T extends TNumber> |
|
| BooleanMask |
|
| BooleanMask.Options |
|
| BooleanMaskUpdate |
|
| BooleanMaskUpdate.Options |
|
| BoostedTreesAggregateStats |
Aggregates the summary of accumulated stats for the batch.
|
| BoostedTreesAggregateStats.Inputs |
|
| BoostedTreesBucketize |
Bucketize each feature based on bucket boundaries.
|
| BoostedTreesBucketize.Inputs |
|
| BoostedTreesCalculateBestFeatureSplit |
Calculates gains for each feature and returns the best possible split information for the feature.
|
| BoostedTreesCalculateBestFeatureSplit.Inputs |
|
| BoostedTreesCalculateBestFeatureSplit.Options |
|
| BoostedTreesCalculateBestFeatureSplitV2 |
Calculates gains for each feature and returns the best possible split information for each node.
|
| BoostedTreesCalculateBestFeatureSplitV2.Inputs |
|
| BoostedTreesCalculateBestGainsPerFeature |
Calculates gains for each feature and returns the best possible split information for the feature.
|
| BoostedTreesCalculateBestGainsPerFeature.Inputs |
|
| BoostedTreesCenterBias |
Calculates the prior from the training data (the bias) and fills in the first node with the logits' prior.
|
| BoostedTreesCenterBias.Inputs |
|
| BoostedTreesCreateEnsemble |
Creates a tree ensemble model and returns a handle to it.
|
| BoostedTreesCreateEnsemble.Inputs |
|
| BoostedTreesCreateQuantileStreamResource |
Create the Resource for Quantile Streams.
|
| BoostedTreesCreateQuantileStreamResource.Inputs |
|
| BoostedTreesCreateQuantileStreamResource.Options |
|
| BoostedTreesDeserializeEnsemble |
Deserializes a serialized tree ensemble config and replaces current tree
ensemble.
|
| BoostedTreesDeserializeEnsemble.Inputs |
|
| BoostedTreesEnsembleResourceHandleOp |
Creates a handle to a BoostedTreesEnsembleResource
|
| BoostedTreesEnsembleResourceHandleOp.Inputs |
|
| BoostedTreesEnsembleResourceHandleOp.Options |
|
| BoostedTreesExampleDebugOutputs |
Debugging/model interpretability outputs for each example.
|
| BoostedTreesExampleDebugOutputs.Inputs |
|
| BoostedTreesFlushQuantileSummaries |
Flush the quantile summaries from each quantile stream resource.
|
| BoostedTreesFlushQuantileSummaries.Inputs |
|
| BoostedTreesGetEnsembleStates |
Retrieves the tree ensemble resource stamp token, number of trees and growing statistics.
|
| BoostedTreesGetEnsembleStates.Inputs |
|
| BoostedTreesMakeQuantileSummaries |
Makes the summary of quantiles for the batch.
|
| BoostedTreesMakeQuantileSummaries.Inputs |
|
| BoostedTreesMakeStatsSummary |
Makes the summary of accumulated stats for the batch.
|
| BoostedTreesMakeStatsSummary.Inputs |
|
| BoostedTreesPredict |
Runs multiple additive regression ensemble predictors on input instances and
computes the logits.
|
| BoostedTreesPredict.Inputs |
|
| BoostedTreesQuantileStreamResourceAddSummaries |
Add the quantile summaries to each quantile stream resource.
|
| BoostedTreesQuantileStreamResourceAddSummaries.Inputs |
|
| BoostedTreesQuantileStreamResourceDeserialize |
Deserialize bucket boundaries and ready flag into current QuantileAccumulator.
|
| BoostedTreesQuantileStreamResourceDeserialize.Inputs |
|
| BoostedTreesQuantileStreamResourceFlush |
Flush the summaries for a quantile stream resource.
|
| BoostedTreesQuantileStreamResourceFlush.Inputs |
|
| BoostedTreesQuantileStreamResourceFlush.Options |
|
| BoostedTreesQuantileStreamResourceGetBucketBoundaries |
Generate the bucket boundaries for each feature based on accumulated summaries.
|
| BoostedTreesQuantileStreamResourceGetBucketBoundaries.Inputs |
|
| BoostedTreesQuantileStreamResourceHandleOp |
Creates a handle to a BoostedTreesQuantileStreamResource.
|
| BoostedTreesQuantileStreamResourceHandleOp.Inputs |
|
| BoostedTreesQuantileStreamResourceHandleOp.Options |
|
| BoostedTreesSerializeEnsemble |
Serializes the tree ensemble to a proto.
|
| BoostedTreesSerializeEnsemble.Inputs |
|
| BoostedTreesSparseAggregateStats |
Aggregates the summary of accumulated stats for the batch.
|
| BoostedTreesSparseAggregateStats.Inputs |
|
| BoostedTreesSparseCalculateBestFeatureSplit |
Calculates gains for each feature and returns the best possible split information for the feature.
|
| BoostedTreesSparseCalculateBestFeatureSplit.Inputs |
|
| BoostedTreesSparseCalculateBestFeatureSplit.Options |
|
| BoostedTreesTrainingPredict |
Runs multiple additive regression ensemble predictors on input instances and
computes the update to cached logits.
|
| BoostedTreesTrainingPredict.Inputs |
|
| BoostedTreesUpdateEnsemble |
Updates the tree ensemble by either adding a layer to the last tree being grown
or by starting a new tree.
|
| BoostedTreesUpdateEnsemble.Inputs |
|
| BoostedTreesUpdateEnsembleV2 |
Updates the tree ensemble by adding a layer to the last tree being grown
or by starting a new tree.
|
| BoostedTreesUpdateEnsembleV2.Inputs |
|
| BoostedTreesUpdateEnsembleV2.Options |
|
| 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.
|
| BroadcastDynamicShape.Inputs<T extends TNumber> |
|
| BroadcastGradientArgs<T extends TNumber> |
Return the reduction indices for computing gradients of s0 op s1 with broadcast.
|
| BroadcastGradientArgs.Inputs<T extends TNumber> |
|
| 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.
|
| BroadcastHelper.Inputs<T extends TType> |
|
| BroadcastTo<T extends TType> |
Broadcast an array for a compatible shape.
|
| BroadcastTo.Inputs<T extends TType> |
|
| Bucketize |
Bucketizes 'input' based on 'boundaries'.
|
| Bucketize.Inputs |
|
| 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 |
|
| BytesList |
LINT.IfChange
Containers to hold repeated fundamental values.
|
| BytesList.Builder |
LINT.IfChange
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.
|
| BytesProducedStatsDataset.Inputs |
|
| BytesProducedStatsDataset.Inputs |
|
| CacheDataset |
The CacheDatasetV2 operation
|
| CacheDataset.Inputs |
|
| CacheDataset.Options |
|
| 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 |
|
| CapturedTensor |
Protobuf type tensorflow.CapturedTensor
|
| CapturedTensor.Builder |
Protobuf type tensorflow.CapturedTensor
|
| CapturedTensorOrBuilder |
|
| CardinalityOptions |
next: 2
|
| CardinalityOptions.Builder |
next: 2
|
| CardinalityOptions.ComputeLevel |
Protobuf enum tensorflow.data.CardinalityOptions.ComputeLevel
|
| CardinalityOptionsOrBuilder |
|
| Case |
An n-way switch statement which calls a single branch function.
|
| Case.Options |
Optional attributes for Case |
| Cast<U extends TType> |
Cast x of type SrcT to y of DstT.
|
| Cast.Inputs |
|
| Cast.Options |
Optional attributes for Cast |
| Ceil<T extends TNumber> |
Returns element-wise smallest integer not less than x.
|
| Ceil.Inputs<T extends TNumber> |
|
| CheckNumerics<T extends TNumber> |
Checks a tensor for NaN, -Inf and +Inf values.
|
| CheckNumerics.Inputs<T extends TNumber> |
|
| Cholesky<T extends TType> |
Computes the Cholesky decomposition of one or more square matrices.
|
| Cholesky.Inputs<T extends TType> |
|
| CholeskyGrad<T extends TNumber> |
Computes the reverse mode backpropagated gradient of the Cholesky algorithm.
|
| CholeskyGrad.Inputs<T extends TNumber> |
|
| ChooseFastestBranchDataset |
The ChooseFastestBranchDataset operation
|
| ChooseFastestBranchDataset.Inputs |
|
| ChooseFastestDataset |
The ChooseFastestDataset operation
|
| ChooseFastestDataset |
The ExperimentalChooseFastestDataset operation
|
| ChooseFastestDataset.Inputs |
|
| ChooseFastestDataset.Inputs |
|
| ClipByValue<T extends TType> |
Clips tensor values to a specified min and max.
|
| ClipByValue.Inputs<T extends TType> |
|
| CloseSummaryWriter |
The CloseSummaryWriter operation
|
| CloseSummaryWriter.Inputs |
|
| 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.
|
| ClusterOutput.Inputs<T extends TType> |
|
| 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 |
|
| CollateTPUEmbeddingMemory |
An op that merges the string-encoded memory config protos from all hosts.
|
| CollateTPUEmbeddingMemory.Inputs |
|
| 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 |
|
| CollectiveAllToAll<T extends TNumber> |
Mutually exchanges multiple tensors of identical type and shape.
|
| CollectiveAllToAll.Inputs<T extends TNumber> |
|
| CollectiveAllToAll.Options |
|
| CollectiveAssignGroup |
Assign group keys based on group assignment.
|
| CollectiveAssignGroup.Inputs |
|
| CollectiveBcastRecv<U extends TType> |
Receives a tensor value broadcast from another device.
|
| CollectiveBcastRecv.Inputs |
|
| CollectiveBcastRecv.Options |
|
| CollectiveBcastSend<T extends TType> |
Broadcasts a tensor value to one or more other devices.
|
| CollectiveBcastSend.Inputs<T extends TType> |
|
| CollectiveBcastSend.Options |
|
| CollectiveGather<T extends TNumber> |
Mutually accumulates multiple tensors of identical type and shape.
|
| CollectiveGather.Inputs<T extends TNumber> |
|
| CollectiveGather.Options |
|
| CollectiveInitializeCommunicator |
Initializes a group for collective operations.
|
| CollectiveInitializeCommunicator.Inputs |
|
| CollectiveInitializeCommunicator.Options |
|
| CollectivePermute<T extends TType> |
An Op to permute tensors across replicated TPU instances.
|
| CollectivePermute.Inputs<T extends TType> |
|
| CollectiveReduce<T extends TNumber> |
Mutually reduces multiple tensors of identical type and shape.
|
| CollectiveReduce.Inputs<T extends TNumber> |
|
| CollectiveReduce.Options |
|
| 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.Inputs |
|
| CombinedNonMaxSuppression.Options |
|
| CommitId |
Protobuf type tensorflow.CommitId
|
| CommitId.Builder |
Protobuf type tensorflow.CommitId
|
| CommitId.KindCase |
|
| CommitIdOrBuilder |
|
| CompilationResult |
Returns the result of a TPU compilation.
|
| CompilationResult.Inputs |
|
| Compile |
Compiles a computations for execution on one or more TPU devices.
|
| Compile.Inputs |
|
| CompileSucceededAssert |
Asserts that compilation succeeded.
|
| CompileSucceededAssert.Inputs |
|
| Complex<U extends TType> |
Converts two real numbers to a complex number.
|
| Complex.Inputs<T extends TNumber> |
|
| ComplexAbs<U extends TNumber> |
Computes the complex absolute value of a tensor.
|
| ComplexAbs.Inputs |
|
| CompositeTensorVariant |
|
| CompositeTensorVariant.CompositeTensorVariantMetadata |
Metadata for CompositeTensorVariant, used when serializing as Variant.
|
| CompositeTensorVariant.CompositeTensorVariantMetadata.Builder |
Metadata for CompositeTensorVariant, used when serializing as Variant.
|
| CompositeTensorVariant.CompositeTensorVariantMetadataOrBuilder |
|
| CompositeTensorVariantFromComponents |
Encodes an ExtensionType value into a variant scalar Tensor.
|
| CompositeTensorVariantFromComponents.Inputs |
|
| CompositeTensorVariantToComponents |
Decodes a variant scalar Tensor into an ExtensionType value.
|
| CompositeTensorVariantToComponents.Inputs |
|
| CompressElement |
Compresses a dataset element.
|
| CompressElement.Inputs |
|
| Compute_func_Pointer_TF_OpKernelContext |
|
| ComputeAccidentalHits |
Computes the ids of the positions in sampled_candidates that match true_labels.
|
| ComputeAccidentalHits.Inputs |
|
| ComputeAccidentalHits.Options |
|
| ComputeBatchSize |
Computes the static batch size of a dataset sans partial batches.
|
| ComputeBatchSize.Inputs |
|
| Concat<T extends TType> |
Concatenates tensors along one dimension.
|
| Concat.Inputs<T extends TType> |
|
| ConcatenateDataset |
Creates a dataset that concatenates input_dataset with another_dataset.
|
| ConcatenateDataset.Inputs |
|
| ConcatenateDataset.Options |
|
| ConcatND<T extends TType> |
Concats input tensor across all dimensions.
|
| ConcatND.Inputs<T extends TType> |
|
| ConcatND.Options |
|
| 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.Inputs |
|
| ConditionalAccumulator.Options |
|
| 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 |
|
| ConfigureAndInitializeGlobalTPU |
An op that sets up the centralized structures for a distributed TPU system.
|
| ConfigureAndInitializeGlobalTPU.Inputs |
|
| ConfigureDistributedTPU |
Sets up the centralized structures for a distributed TPU system.
|
| ConfigureDistributedTPU.Inputs |
|
| ConfigureDistributedTPU.Options |
|
| ConfigureTPUEmbedding |
Sets up TPUEmbedding in a distributed TPU system.
|
| ConfigureTPUEmbedding.Inputs |
|
| ConfigureTPUEmbeddingHost |
An op that configures the TPUEmbedding software on a host.
|
| ConfigureTPUEmbeddingHost.Inputs |
|
| ConfigureTPUEmbeddingMemory |
An op that configures the TPUEmbedding software on a host.
|
| ConfigureTPUEmbeddingMemory.Inputs |
|
| Conj<T extends TType> |
Returns the complex conjugate of a complex number.
|
| Conj.Inputs<T extends TType> |
|
| ConjugateTranspose<T extends TType> |
Shuffle dimensions of x according to a permutation and conjugate the result.
|
| ConjugateTranspose.Inputs<T extends TType> |
|
| ConnectTPUEmbeddingHosts |
An op that sets up communication between TPUEmbedding host software instances
after ConfigureTPUEmbeddingHost has been called on each host.
|
| ConnectTPUEmbeddingHosts.Inputs |
|
| Constant<T extends TType> |
An operator producing a constant value.
|
| ConsumeMutexLock |
This op consumes a lock created by MutexLock.
|
| ConsumeMutexLock.Inputs |
|
| 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.
|
| ControlTrigger.Inputs |
|
| Conv<W extends TType> |
Wraps the XLA ConvGeneralDilated operator, documented at
https://www.tensorflow.org/performance/xla/operation_semantics#conv_convolution
.
|
| Conv.Inputs<V extends TNumber> |
|
| Conv.Options |
Optional attributes for Conv |
| Conv2d<T extends TNumber> |
Computes a 2-D convolution given 4-D input and filter tensors.
|
| Conv2d.Inputs<T extends TNumber> |
|
| Conv2d.Options |
Optional attributes for Conv2d |
| Conv2dBackpropFilter<T extends TNumber> |
Computes the gradients of convolution with respect to the filter.
|
| Conv2dBackpropFilter.Inputs<T extends TNumber> |
|
| Conv2dBackpropFilter.Options |
|
| Conv2dBackpropInput<T extends TNumber> |
Computes the gradients of convolution with respect to the input.
|
| Conv2dBackpropInput.Inputs<T extends TNumber> |
|
| Conv2dBackpropInput.Options |
|
| Conv3d<T extends TNumber> |
Computes a 3-D convolution given 5-D input and filter tensors.
|
| Conv3d.Inputs<T extends TNumber> |
|
| Conv3d.Options |
Optional attributes for Conv3d |
| Conv3dBackpropFilter<T extends TNumber> |
Computes the gradients of 3-D convolution with respect to the filter.
|
| Conv3dBackpropFilter.Inputs<T extends TNumber> |
|
| Conv3dBackpropFilter.Options |
|
| Conv3dBackpropInput<U extends TNumber> |
Computes the gradients of 3-D convolution with respect to the input.
|
| Conv3dBackpropInput.Inputs<U extends TNumber> |
|
| Conv3dBackpropInput.Options |
|
| CoordinationConfig |
|
| CoordinationConfig.CoordinationServiceConfig |
Coordination service configuration parameters.
|
| CoordinationConfig.CoordinationServiceConfig.Builder |
Coordination service configuration parameters.
|
| CoordinationConfig.CoordinationServiceConfigOrBuilder |
|
| Copy<T extends TType> |
Copy a tensor from CPU-to-CPU or GPU-to-GPU.
|
| Copy.Inputs<T extends TType> |
|
| Copy.Options |
Optional attributes for Copy |
| CopyHost<T extends TType> |
Copy a tensor to host.
|
| CopyHost.Inputs<T extends TType> |
|
| CopyHost.Options |
|
| CopyToMesh<T extends TType> |
The CopyToMesh operation
|
| CopyToMesh.Inputs<T extends TType> |
|
| CopyToMesh.Options |
|
| CorePlatformPayloads |
|
| CorePlatformPayloads.ErrorSourceProto |
If included as a payload, this message contains the error source information
where the error was raised.
|
| CorePlatformPayloads.ErrorSourceProto.Builder |
If included as a payload, this message contains the error source information
where the error was raised.
|
| CorePlatformPayloads.ErrorSourceProto.ErrorSource |
Protobuf enum tensorflow.core.platform.ErrorSourceProto.ErrorSource
|
| CorePlatformPayloads.ErrorSourceProtoOrBuilder |
|
| Cos<T extends TType> |
Computes cos of x element-wise.
|
| Cos.Inputs<T extends TType> |
|
| Cosh<T extends TType> |
Computes hyperbolic cosine of x element-wise.
|
| Cosh.Inputs<T extends TType> |
|
| 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'.
|
| CountUpTo.Inputs<T extends TNumber> |
|
| CPUInfo |
Protobuf type tensorflow.CPUInfo
|
| CPUInfo.Builder |
Protobuf type tensorflow.CPUInfo
|
| CPUInfoOrBuilder |
|
| Create_func_TF_OpKernelConstruction |
|
| CreateSummaryDbWriter |
The CreateSummaryDbWriter operation
|
| CreateSummaryDbWriter.Inputs |
|
| CreateSummaryFileWriter |
The CreateSummaryFileWriter operation
|
| CreateSummaryFileWriter.Inputs |
|
| CropAndResize |
Extracts crops from the input image tensor and resizes them.
|
| CropAndResize.Inputs |
|
| CropAndResize.Options |
|
| CropAndResizeGradBoxes |
Computes the gradient of the crop_and_resize op wrt the input boxes tensor.
|
| CropAndResizeGradBoxes.Inputs |
|
| CropAndResizeGradBoxes.Options |
|
| CropAndResizeGradImage<T extends TNumber> |
Computes the gradient of the crop_and_resize op wrt the input image tensor.
|
| CropAndResizeGradImage.Inputs |
|
| CropAndResizeGradImage.Options |
|
| Cross<T extends TNumber> |
Compute the pairwise cross product.
|
| Cross.Inputs<T extends TNumber> |
|
| CrossReplicaSum<T extends TNumber> |
An Op to sum inputs across replicated TPU instances.
|
| CrossReplicaSum.Inputs<T extends TNumber> |
|
| CSRSparseMatrixComponents<T extends TType> |
Reads out the CSR components at batch index.
|
| CSRSparseMatrixComponents.Inputs |
|
| CSRSparseMatrixToDense<T extends TType> |
Convert a (possibly batched) CSRSparseMatrix to dense.
|
| CSRSparseMatrixToDense.Inputs |
|
| CSRSparseMatrixToSparseTensor<T extends TType> |
Converts a (possibly batched) CSRSparesMatrix to a SparseTensor.
|
| CSRSparseMatrixToSparseTensor.Inputs |
|
| CSVDataset |
The CSVDatasetV2 operation
|
| CSVDataset |
The ExperimentalCSVDataset operation
|
| CSVDataset.Inputs |
|
| CSVDataset.Inputs |
|
| CtcBeamSearchDecoder<T extends TNumber> |
Performs beam search decoding on the logits given in input.
|
| CtcBeamSearchDecoder.Inputs<T extends TNumber> |
|
| CtcBeamSearchDecoder.Options |
|
| CtcGreedyDecoder<T extends TNumber> |
Performs greedy decoding on the logits given in inputs.
|
| CtcGreedyDecoder.Inputs<T extends TNumber> |
|
| CtcGreedyDecoder.Options |
|
| CtcLoss<T extends TNumber> |
Calculates the CTC Loss (log probability) for each batch entry.
|
| CtcLoss.Inputs<T extends TNumber> |
|
| CtcLoss.Options |
|
| CTCLossV2 |
Calculates the CTC Loss (log probability) for each batch entry.
|
| CTCLossV2.Inputs |
|
| CTCLossV2.Options |
|
| CudnnRNN<T extends TNumber> |
A RNN backed by cuDNN.
|
| CudnnRNN.Inputs<T extends TNumber> |
|
| CudnnRNN.Options |
|
| CudnnRNNBackprop<T extends TNumber> |
Backprop step of CudnnRNNV3.
|
| CudnnRNNBackprop.Inputs<T extends TNumber> |
|
| CudnnRNNBackprop.Options |
|
| CudnnRNNCanonicalToParams<T extends TNumber> |
Converts CudnnRNN params from canonical form to usable form.
|
| CudnnRNNCanonicalToParams.Inputs<T extends TNumber> |
|
| CudnnRNNCanonicalToParams.Options |
|
| CudnnRnnParamsSize<T extends TNumber> |
Computes size of weights that can be used by a Cudnn RNN model.
|
| CudnnRnnParamsSize.Inputs |
|
| CudnnRnnParamsSize.Options |
|
| CudnnRNNParamsToCanonical<T extends TNumber> |
Retrieves CudnnRNN params in canonical form.
|
| CudnnRNNParamsToCanonical.Inputs<T extends TNumber> |
|
| CudnnRNNParamsToCanonical.Options |
|
| Cumprod<T extends TType> |
Compute the cumulative product of the tensor x along axis.
|
| Cumprod.Inputs<T extends TType> |
|
| Cumprod.Options |
|
| Cumsum<T extends TType> |
Compute the cumulative sum of the tensor x along axis.
|
| Cumsum.Inputs<T extends TType> |
|
| Cumsum.Options |
Optional attributes for Cumsum |
| CumulativeLogsumexp<T extends TNumber> |
Compute the cumulative product of the tensor x along axis.
|
| CumulativeLogsumexp.Inputs<T extends TNumber> |
|
| CumulativeLogsumexp.Options |
|
| CustomCall<T extends TType> |
Wraps the XLA CustomCall operator
documented at https://www.tensorflow.org/xla/operation_semantics#customcall.
|
| CustomCall.Inputs |
|
| CustomGradient<T extends RawOpInputs> |
|
| 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.Inputs<T extends TNumber> |
|
| DataFormatDimMap.Options |
|
| DataFormatVecPermute<T extends TNumber> |
Permute input tensor from src_format to dst_format.
|
| DataFormatVecPermute.Inputs<T extends TNumber> |
|
| DataFormatVecPermute.Options |
|
| DataOps |
An API for building data operations as Ops |
| DataService |
|
| DataService.CrossTrainerCacheOptions |
Protobuf type tensorflow.data.CrossTrainerCacheOptions
|
| DataService.CrossTrainerCacheOptions.Builder |
Protobuf type tensorflow.data.CrossTrainerCacheOptions
|
| DataService.CrossTrainerCacheOptionsOrBuilder |
|
| DataService.DataServiceConfig |
Data service config available to the client through GetDataServiceConfig RPC.
|
| DataService.DataServiceConfig.Builder |
Data service config available to the client through GetDataServiceConfig RPC.
|
| DataService.DataServiceConfigOrBuilder |
|
| DataService.DataServiceMetadata |
Metadata related to tf.data service datasets.
|
| DataService.DataServiceMetadata.Builder |
Metadata related to tf.data service datasets.
|
| DataService.DataServiceMetadata.Compression |
Protobuf enum tensorflow.data.DataServiceMetadata.Compression
|
| DataService.DataServiceMetadata.OptionalElementSpecCase |
|
| DataService.DataServiceMetadataOrBuilder |
|
| DataService.DeploymentMode |
tf.data service deployment mode.
|
| DataService.ProcessingModeDef |
Next tag: 2
|
| DataService.ProcessingModeDef.Builder |
Next tag: 2
|
| DataService.ProcessingModeDef.ShardingPolicy |
Specifies how data is sharded among tf.data service workers.
|
| DataService.ProcessingModeDefOrBuilder |
|
| DataServiceDataset |
Creates a dataset that reads data from the tf.data service.
|
| DataServiceDataset.Inputs |
|
| DataServiceDataset.Options |
|
| DatasetCardinality |
Returns the cardinality of input_dataset.
|
| DatasetCardinality |
Returns the cardinality of input_dataset.
|
| DatasetCardinality.Inputs |
|
| DatasetCardinality.Inputs |
|
| DatasetFromGraph |
Creates a dataset from the given graph_def.
|
| DatasetFromGraph.Inputs |
|
| DatasetMetadata |
|
| DatasetMetadata.Metadata |
next: 2
|
| DatasetMetadata.Metadata.Builder |
next: 2
|
| DatasetMetadata.MetadataOrBuilder |
|
| DatasetOptionsProtos |
|
| DatasetToGraph |
Returns a serialized GraphDef representing input_dataset.
|
| DatasetToGraph.Inputs |
|
| DatasetToGraph.Options |
|
| DatasetToSingleElement |
Outputs the single element from the given dataset.
|
| DatasetToSingleElement.Inputs |
|
| DatasetToSingleElement.Options |
|
| 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.
|
| DatasetToTfRecord.Inputs |
|
| DatasetToTFRecord.Inputs |
|
| DataType |
(== suppress_warning documentation-presence ==)
LINT.IfChange
|
| Dawsn<T extends TNumber> |
The Dawsn operation
|
| Dawsn.Inputs<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.
|
| DebugGradientIdentity.Inputs<T extends TType> |
|
| DebugGradientRefIdentity<T extends TType> |
Identity op for gradient debugging.
|
| DebugGradientRefIdentity.Inputs<T extends TType> |
|
| DebugIdentity<T extends TType> |
Debug Identity V2 Op.
|
| DebugIdentity.Inputs<T extends TType> |
|
| DebugIdentity.Options |
|
| 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.Inputs |
|
| DebugNanCount.Options |
|
| DebugNumericsSummary<U extends TNumber> |
Debug Numeric Summary V2 Op.
|
| DebugNumericsSummary.Inputs |
|
| DebugNumericsSummary.Options |
|
| 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.Inputs |
|
| DecodeAndCropJpeg.Options |
|
| DecodeBase64 |
Decode web-safe base64-encoded strings.
|
| DecodeBase64.Inputs |
|
| DecodeBmp |
Decode the first frame of a BMP-encoded image to a uint8 tensor.
|
| DecodeBmp.Inputs |
|
| DecodeBmp.Options |
|
| DecodeCompressed |
Decompress strings.
|
| DecodeCompressed.Inputs |
|
| DecodeCompressed.Options |
|
| DecodeCsv |
Convert CSV records to tensors.
|
| DecodeCsv.Inputs |
|
| DecodeCsv.Options |
|
| DecodeGif |
Decode the frame(s) of a GIF-encoded image to a uint8 tensor.
|
| DecodeGif.Inputs |
|
| DecodeImage<T extends TNumber> |
Function for decode_bmp, decode_gif, decode_jpeg, and decode_png.
|
| DecodeImage.Inputs |
|
| DecodeImage.Options |
|
| DecodeJpeg |
Decode a JPEG-encoded image to a uint8 tensor.
|
| DecodeJpeg.Inputs |
|
| DecodeJpeg.Options |
|
| DecodeJsonExample |
Convert JSON-encoded Example records to binary protocol buffer strings.
|
| DecodeJsonExample.Inputs |
|
| DecodePaddedRaw<T extends TNumber> |
Reinterpret the bytes of a string as a vector of numbers.
|
| DecodePaddedRaw.Inputs |
|
| DecodePaddedRaw.Options |
|
| DecodePng<T extends TNumber> |
Decode a PNG-encoded image to a uint8 or uint16 tensor.
|
| DecodePng.Inputs |
|
| DecodePng.Options |
|
| DecodeProto |
The op extracts fields from a serialized protocol buffers message into tensors.
|
| DecodeProto.Inputs |
|
| DecodeProto.Options |
|
| DecodeRaw<T extends TType> |
Reinterpret the bytes of a string as a vector of numbers.
|
| DecodeRaw.Inputs |
|
| DecodeRaw.Options |
|
| DecodeWav |
Decode a 16-bit PCM WAV file to a float tensor.
|
| DecodeWav.Inputs |
|
| DecodeWav.Options |
|
| DeepCopy<T extends TType> |
Makes a copy of x.
|
| DeepCopy.Inputs<T extends TType> |
|
| Delete_func_Pointer |
|
| DeleteIterator |
A container for an iterator resource.
|
| DeleteIterator.Inputs |
|
| DeleteMemoryCache |
The DeleteMemoryCache operation
|
| DeleteMemoryCache.Inputs |
|
| DeleteMultiDeviceIterator |
A container for an iterator resource.
|
| DeleteMultiDeviceIterator.Inputs |
|
| DeleteRandomSeedGenerator |
The DeleteRandomSeedGenerator operation
|
| DeleteRandomSeedGenerator.Inputs |
|
| DeleteSeedGenerator |
The DeleteSeedGenerator operation
|
| DeleteSeedGenerator.Inputs |
|
| DeleteSessionTensor |
Delete the tensor specified by its handle in the session.
|
| DeleteSessionTensor.Inputs |
|
| DenseBincount<U extends TNumber> |
Counts the number of occurrences of each value in an integer array.
|
| DenseBincount.Inputs<T extends TNumber,U extends TNumber> |
|
| DenseBincount.Options |
|
| DenseCountSparseOutput<U extends TNumber> |
Performs sparse-output bin counting for a tf.tensor input.
|
| DenseCountSparseOutput.Inputs<U extends TNumber> |
|
| DenseCountSparseOutput.Options |
|
| DenseToCSRSparseMatrix |
Converts a dense tensor to a (possibly batched) CSRSparseMatrix.
|
| DenseToCSRSparseMatrix.Inputs |
|
| DenseToDenseSetOperation<T extends TType> |
Applies set operation along last dimension of 2 Tensor inputs.
|
| DenseToDenseSetOperation.Inputs<T extends TType> |
|
| DenseToDenseSetOperation.Options |
|
| DenseToSparseBatchDataset |
Creates a dataset that batches input elements into a SparseTensor.
|
| DenseToSparseBatchDataset |
Creates a dataset that batches input elements into a SparseTensor.
|
| DenseToSparseBatchDataset.Inputs |
|
| DenseToSparseBatchDataset.Inputs |
|
| DenseToSparseSetOperation<T extends TType> |
Applies set operation along last dimension of Tensor and SparseTensor.
|
| DenseToSparseSetOperation.Inputs<T extends TType> |
|
| DenseToSparseSetOperation.Options |
|
| DepthToSpace<T extends TType> |
DepthToSpace for tensors of type T.
|
| DepthToSpace.Inputs<T extends TType> |
|
| DepthToSpace.Options |
|
| DepthwiseConv2dNative<T extends TNumber> |
Computes a 2-D depthwise convolution given 4-D input and filter tensors.
|
| DepthwiseConv2dNative.Inputs<T extends TNumber> |
|
| DepthwiseConv2dNative.Options |
|
| DepthwiseConv2dNativeBackpropFilter<T extends TNumber> |
Computes the gradients of depthwise convolution with respect to the filter.
|
| DepthwiseConv2dNativeBackpropFilter.Inputs<T extends TNumber> |
|
| DepthwiseConv2dNativeBackpropFilter.Options |
|
| DepthwiseConv2dNativeBackpropInput<T extends TNumber> |
Computes the gradients of depthwise convolution with respect to the input.
|
| DepthwiseConv2dNativeBackpropInput.Inputs<T extends TNumber> |
|
| DepthwiseConv2dNativeBackpropInput.Options |
|
| 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.Inputs |
|
| Dequantize.Inputs |
|
| Dequantize.Options |
|
| DeserializeIterator |
Converts the given variant tensor to an iterator and stores it in the given resource.
|
| DeserializeIterator.Inputs |
|
| DeserializeManySparse<T extends TType> |
Deserialize and concatenate SparseTensors from a serialized minibatch.
|
| DeserializeManySparse.Inputs |
|
| DeserializeSparse<U extends TType> |
Deserialize SparseTensor objects.
|
| DeserializeSparse.Inputs |
|
| DestroyResourceOp |
Deletes the resource specified by the handle.
|
| DestroyResourceOp.Inputs |
|
| DestroyResourceOp.Options |
|
| DestroyTemporaryVariable<T extends TType> |
Destroys the temporary variable and returns its final value.
|
| DestroyTemporaryVariable.Inputs<T extends TType> |
|
| Det<T extends TType> |
Computes the determinant of one or more square matrices.
|
| Det.Inputs<T extends TType> |
|
| DeviceAttributes |
Protobuf type tensorflow.DeviceAttributes
|
| DeviceAttributes.Builder |
Protobuf type tensorflow.DeviceAttributes
|
| DeviceAttributesOrBuilder |
|
| DeviceAttributesProtos |
|
| DeviceFiltersProtos |
|
| DeviceIndex |
Return the index of device the op runs.
|
| DeviceIndex.Inputs |
|
| 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 |
|
| 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.
|
| Digamma.Inputs<T extends TNumber> |
|
| Dilation2d<T extends TNumber> |
Computes the grayscale dilation of 4-D input and 3-D filter tensors.
|
| Dilation2d.Inputs<T extends TNumber> |
|
| Dilation2dBackpropFilter<T extends TNumber> |
Computes the gradient of morphological 2-D dilation with respect to the filter.
|
| Dilation2dBackpropFilter.Inputs<T extends TNumber> |
|
| Dilation2dBackpropInput<T extends TNumber> |
Computes the gradient of morphological 2-D dilation with respect to the input.
|
| Dilation2dBackpropInput.Inputs<T extends TNumber> |
|
| DirectedInterleaveDataset |
A substitute for InterleaveDataset on a fixed list of N datasets.
|
| DirectedInterleaveDataset |
A substitute for InterleaveDataset on a fixed list of N datasets.
|
| DirectedInterleaveDataset.Inputs |
|
| DirectedInterleaveDataset.Inputs |
|
| DirectedInterleaveDataset.Options |
|
| DisableCopyOnRead |
Turns off the copy-on-read mode.
|
| DisableCopyOnRead.Inputs |
|
| DistributedRuntimePayloads |
|
| DistributedRuntimePayloads.GrpcPayloadContainer |
Used to serialize and transmit tensorflow::Status payloads through
grpc::Status `error_details` since grpc::Status lacks payload API.
|
| DistributedRuntimePayloads.GrpcPayloadContainer.Builder |
Used to serialize and transmit tensorflow::Status payloads through
grpc::Status `error_details` since grpc::Status lacks payload API.
|
| DistributedRuntimePayloads.GrpcPayloadContainerOrBuilder |
|
| DistributedRuntimePayloads.GrpcPayloadsLost |
If included as a payload, this message flags the Status to have lost payloads
during the GRPC transmission.
|
| DistributedRuntimePayloads.GrpcPayloadsLost.Builder |
If included as a payload, this message flags the Status to have lost payloads
during the GRPC transmission.
|
| DistributedRuntimePayloads.GrpcPayloadsLostOrBuilder |
|
| DistributedRuntimePayloads.WorkerPossiblyRestarted |
If included as a payload, this message flags the Status to be a possible
outcome of a worker restart.
|
| DistributedRuntimePayloads.WorkerPossiblyRestarted.Builder |
If included as a payload, this message flags the Status to be a possible
outcome of a worker restart.
|
| DistributedRuntimePayloads.WorkerPossiblyRestartedOrBuilder |
|
| DistributeOptions |
next: 3
|
| DistributeOptions.Builder |
next: 3
|
| DistributeOptions.OptionalNumDevicesCase |
|
| DistributeOptionsOrBuilder |
|
| Div<T extends TType> |
Returns x / y element-wise.
|
| Div.Inputs<T extends TType> |
|
| DivNoNan<T extends TType> |
Returns 0 if the denominator is zero.
|
| DivNoNan.Inputs<T extends TType> |
|
| Dot<V extends TType> |
Wraps the XLA DotGeneral operator, documented at
https://www.tensorflow.org/performance/xla/operation_semantics#dotgeneral
.
|
| Dot.Inputs |
|
| DrawBoundingBoxes<T extends TNumber> |
Draw bounding boxes on a batch of images.
|
| DrawBoundingBoxes.Inputs<T extends TNumber> |
|
| DTensorRestore |
The DTensorRestoreV2 operation
|
| DTensorRestore.Inputs |
|
| DTensorShardedPrefix |
The DTensorShardedPrefix operation
|
| DTensorShardedPrefix.Inputs |
|
| DtypesOps |
An API for building dtypes operations as Ops |
| DummyIterationCounter |
The DummyIterationCounter operation
|
| DummyIterationCounter.Inputs |
|
| DummyMemoryCache |
The DummyMemoryCache operation
|
| DummyMemoryCache.Inputs |
|
| DummySeedGenerator |
The DummySeedGenerator operation
|
| DummySeedGenerator.Inputs |
|
| DynamicEnqueueTPUEmbeddingArbitraryTensorBatch |
Eases the porting of code that uses tf.nn.embedding_lookup_sparse().
|
| DynamicEnqueueTPUEmbeddingArbitraryTensorBatch.Inputs |
|
| DynamicEnqueueTPUEmbeddingArbitraryTensorBatch.Options |
|
| DynamicPartition<T extends TType> |
Partitions data into num_partitions tensors using indices from partitions.
|
| DynamicPartition.Inputs<T extends TType> |
|
| DynamicSlice<T extends TType> |
Wraps the XLA DynamicSlice operator, documented at
https://www.tensorflow.org/performance/xla/operation_semantics#dynamicslice
.
|
| DynamicSlice.Inputs<T extends TType,U extends TNumber> |
|
| DynamicStitch<T extends TType> |
Interleave the values from the data tensors into a single tensor.
|
| DynamicStitch.Inputs<T extends TType> |
|
| DynamicUpdateSlice<T extends TType> |
Wraps the XLA DynamicUpdateSlice operator, documented at
https://www.tensorflow.org/performance/xla/operation_semantics#dynamicupdateslice
.
|
| DynamicUpdateSlice.Inputs<T extends TType> |
|
| 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.Inputs<T extends TType> |
|
| EditDistance.Options |
|
| Eig<U extends TType> |
Computes the eigen decomposition of one or more square matrices.
|
| Eig.Inputs |
|
| 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.
|
| Einsum.Inputs<T extends TType> |
|
| Einsum.Inputs<T extends TType> |
|
| Elu<T extends TNumber> |
Computes the exponential linear function.
|
| Elu.Inputs<T extends TNumber> |
|
| EluGrad<T extends TNumber> |
Computes gradients for the exponential linear (Elu) operation.
|
| EluGrad.Inputs<T extends TNumber> |
|
| EmbeddingActivations |
An op enabling differentiation of TPU Embeddings.
|
| EmbeddingActivations.Inputs |
|
| Empty<T extends TType> |
Creates a tensor with the given shape.
|
| Empty.Inputs |
|
| Empty.Options |
Optional attributes for Empty |
| EmptyTensorList |
Creates and returns an empty tensor list.
|
| EmptyTensorList.Inputs |
|
| EmptyTensorMap |
Creates and returns an empty tensor map.
|
| EmptyTensorMap.Inputs |
|
| EncodeBase64 |
Encode strings into web-safe base64 format.
|
| EncodeBase64.Inputs |
|
| EncodeBase64.Options |
|
| EncodeJpeg |
JPEG-encode an image.
|
| EncodeJpeg.Inputs |
|
| EncodeJpeg.Options |
|
| EncodeJpegVariableQuality |
JPEG encode input image with provided compression quality.
|
| EncodeJpegVariableQuality.Inputs |
|
| EncodePng |
PNG-encode an image.
|
| EncodePng.Inputs |
|
| EncodePng.Options |
|
| EncodeProto |
The op serializes protobuf messages provided in the input tensors.
|
| EncodeProto.Inputs |
|
| EncodeProto.Options |
|
| EncodeWav |
Encode audio data using the WAV file format.
|
| EncodeWav.Inputs |
|
| Endpoint |
Annotation used to mark a method of a class annotated with @Operator that should
generate an endpoint into Ops or one of its groups. |
| EnqueueTPUEmbeddingArbitraryTensorBatch |
Eases the porting of code that uses tf.nn.embedding_lookup_sparse().
|
| EnqueueTPUEmbeddingArbitraryTensorBatch.Inputs |
|
| EnqueueTPUEmbeddingArbitraryTensorBatch.Options |
|
| EnqueueTPUEmbeddingBatch |
An op that enqueues a list of input batch tensors to TPUEmbedding.
|
| EnqueueTPUEmbeddingBatch.Inputs |
|
| EnqueueTPUEmbeddingBatch.Options |
|
| EnqueueTPUEmbeddingIntegerBatch |
An op that enqueues a list of input batch tensors to TPUEmbedding.
|
| EnqueueTPUEmbeddingIntegerBatch.Inputs |
|
| EnqueueTPUEmbeddingIntegerBatch.Options |
|
| EnqueueTPUEmbeddingRaggedTensorBatch |
Eases the porting of code that uses tf.nn.embedding_lookup().
|
| EnqueueTPUEmbeddingRaggedTensorBatch.Inputs |
|
| EnqueueTPUEmbeddingRaggedTensorBatch.Options |
|
| EnqueueTPUEmbeddingSparseBatch |
An op that enqueues TPUEmbedding input indices from a SparseTensor.
|
| EnqueueTPUEmbeddingSparseBatch.Inputs |
|
| EnqueueTPUEmbeddingSparseBatch.Options |
|
| EnqueueTPUEmbeddingSparseTensorBatch |
Eases the porting of code that uses tf.nn.embedding_lookup_sparse().
|
| EnqueueTPUEmbeddingSparseTensorBatch.Inputs |
|
| EnqueueTPUEmbeddingSparseTensorBatch.Options |
|
| EnsureShape<T extends TType> |
Ensures that the tensor's shape matches the expected shape.
|
| EnsureShape.Inputs<T extends TType> |
|
| Enter<T extends TType> |
Creates or finds a child frame, and makes data available to the child frame.
|
| Enter.Inputs<T extends TType> |
|
| 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.Inputs<T extends TType> |
|
| Equal.Options |
Optional attributes for Equal |
| Erf<T extends TNumber> |
|
| Erf.Inputs<T extends TNumber> |
|
| Erfc<T extends TNumber> |
Computes the complementary error function of x element-wise.
|
| Erfc.Inputs<T extends TNumber> |
|
| erfinv<T extends TNumber> |
The Erfinv operation
|
| erfinv.Inputs<T extends TNumber> |
|
| ErrorCodes |
|
| ErrorCodesProtos |
|
| EuclideanNorm<T extends TType> |
Computes the euclidean norm of elements across dimensions of a tensor.
|
| EuclideanNorm.Inputs<T extends TType> |
|
| EuclideanNorm.Options |
|
| 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.
|
| Execute.Inputs |
|
| ExecuteAndUpdateVariables |
Op that executes a program with optional in-place variable updates.
|
| ExecuteAndUpdateVariables.Inputs |
|
| ExecuteTPUEmbeddingPartitioner |
An op that executes the TPUEmbedding partitioner on the central configuration
device and computes the HBM size (in bytes) required for TPUEmbedding operation.
|
| ExecuteTPUEmbeddingPartitioner.Inputs |
|
| 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.
|
| Exit.Inputs<T extends TType> |
|
| Exp<T extends TType> |
Computes exponential of x element-wise.
|
| Exp.Inputs<T extends TType> |
|
| ExpandDims<T extends TType> |
Inserts a dimension of 1 into a tensor's shape.
|
| ExpandDims.Inputs<T extends TType> |
|
| Expint<T extends TNumber> |
The Expint operation
|
| Expint.Inputs<T extends TNumber> |
|
| Expm1<T extends TType> |
Computes exp(x) - 1 element-wise.
|
| Expm1.Inputs<T extends TType> |
|
| ExternalStatePolicy |
Represents how to handle external state during serialization.
|
| ExtractGlimpse |
Extracts a glimpse from the input tensor.
|
| ExtractGlimpse.Inputs |
|
| ExtractGlimpse.Options |
|
| ExtractImagePatches<T extends TType> |
Extract patches from images and put them in the "depth" output dimension.
|
| ExtractImagePatches.Inputs<T extends TType> |
|
| ExtractJpegShape<T extends TNumber> |
Extract the shape information of a JPEG-encoded image.
|
| ExtractJpegShape.Inputs |
|
| ExtractVolumePatches<T extends TNumber> |
Extract patches from input and put them in the "depth" output dimension.
|
| ExtractVolumePatches.Inputs<T extends TNumber> |
|
| Fact |
Output a fact about factorials.
|
| Fact.Inputs |
|
| FakeQuantWithMinMaxArgs |
Fake-quantize the 'inputs' tensor, type float to 'outputs' tensor of same type.
|
| FakeQuantWithMinMaxArgs.Inputs |
|
| FakeQuantWithMinMaxArgs.Options |
|
| FakeQuantWithMinMaxArgsGradient |
Compute gradients for a FakeQuantWithMinMaxArgs operation.
|
| FakeQuantWithMinMaxArgsGradient.Inputs |
|
| FakeQuantWithMinMaxArgsGradient.Options |
|
| 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.Inputs |
|
| FakeQuantWithMinMaxVars.Options |
|
| FakeQuantWithMinMaxVarsGradient |
Compute gradients for a FakeQuantWithMinMaxVars operation.
|
| FakeQuantWithMinMaxVarsGradient.Inputs |
|
| FakeQuantWithMinMaxVarsGradient.Options |
|
| 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.Inputs |
|
| FakeQuantWithMinMaxVarsPerChannel.Options |
|
| FakeQuantWithMinMaxVarsPerChannelGradient |
Compute gradients for a FakeQuantWithMinMaxVarsPerChannel operation.
|
| FakeQuantWithMinMaxVarsPerChannelGradient.Inputs |
|
| FakeQuantWithMinMaxVarsPerChannelGradient.Options |
|
| 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.
|
| Fft.Inputs<T extends TType> |
|
| Fft2d<T extends TType> |
2D fast Fourier transform.
|
| Fft2d.Inputs<T extends TType> |
|
| Fft3d<T extends TType> |
3D fast Fourier transform.
|
| Fft3d.Inputs<T extends TType> |
|
| FifoQueue |
A queue that produces elements in first-in first-out order.
|
| FifoQueue.Inputs |
|
| FifoQueue.Options |
|
| FileSystemSetConfiguration |
Set configuration of the file system.
|
| FileSystemSetConfiguration.Inputs |
|
| Fill<U extends TType> |
Creates a tensor filled with a scalar value.
|
| Fill.Inputs<U extends TType> |
|
| FilterByLastComponentDataset |
Creates a dataset containing elements of first component of input_dataset having true in the last component.
|
| FilterByLastComponentDataset.Inputs |
|
| FilterDataset |
Creates a dataset containing elements of input_dataset matching predicate.
|
| FilterDataset.Inputs |
|
| FilterDataset.Options |
|
| FinalizeDataset |
Creates a dataset by applying tf.data.Options to input_dataset.
|
| FinalizeDataset.Inputs |
|
| FinalizeDataset.Options |
|
| FinalizeTPUEmbedding |
An op that finalizes the TPUEmbedding configuration.
|
| FinalizeTPUEmbedding.Inputs |
|
| Fingerprint |
Generates fingerprint values.
|
| Fingerprint.Inputs |
|
| FingerprintDef |
Protocol buffer representing a SavedModel Fingerprint.
|
| FingerprintDef.Builder |
Protocol buffer representing a SavedModel Fingerprint.
|
| FingerprintDefOrBuilder |
|
| FingerprintProtos |
|
| FixedLenFeatureProto |
Protobuf type tensorflow.FixedLenFeatureProto
|
| FixedLenFeatureProto.Builder |
Protobuf type tensorflow.FixedLenFeatureProto
|
| FixedLenFeatureProtoOrBuilder |
|
| FixedLengthRecordDataset |
The FixedLengthRecordDatasetV2 operation
|
| FixedLengthRecordDataset.Inputs |
|
| FixedLengthRecordDataset.Options |
|
| FixedLengthRecordReader |
A Reader that outputs fixed-length records from a file.
|
| FixedLengthRecordReader.Inputs |
|
| FixedLengthRecordReader.Options |
|
| FixedUnigramCandidateSampler |
Generates labels for candidate sampling with a learned unigram distribution.
|
| FixedUnigramCandidateSampler.Inputs |
|
| FixedUnigramCandidateSampler.Options |
|
| FlatMapDataset |
Creates a dataset that applies f to the outputs of input_dataset.
|
| FlatMapDataset.Inputs |
|
| FlatMapDataset.Options |
|
| FloatList |
Protobuf type tensorflow.FloatList
|
| FloatList.Builder |
Protobuf type tensorflow.FloatList
|
| FloatListOrBuilder |
|
| Floor<T extends TNumber> |
Returns element-wise largest integer not greater than x.
|
| Floor.Inputs<T extends TNumber> |
|
| FloorDiv<T extends TType> |
Returns x // y element-wise.
|
| FloorDiv.Inputs<T extends TType> |
|
| FloorMod<T extends TNumber> |
Returns element-wise remainder of division.
|
| FloorMod.Inputs<T extends TNumber> |
|
| FlushSummaryWriter |
The FlushSummaryWriter operation
|
| FlushSummaryWriter.Inputs |
|
| For |
Applies a for loop.
|
| For.Inputs |
|
| FractionalAvgPool<T extends TNumber> |
Performs fractional average pooling on the input.
|
| FractionalAvgPool.Inputs<T extends TNumber> |
|
| FractionalAvgPool.Options |
|
| FractionalAvgPoolGrad<T extends TNumber> |
Computes gradient of the FractionalAvgPool function.
|
| FractionalAvgPoolGrad.Inputs<T extends TNumber> |
|
| FractionalAvgPoolGrad.Options |
|
| FractionalMaxPool<T extends TNumber> |
Performs fractional max pooling on the input.
|
| FractionalMaxPool.Inputs<T extends TNumber> |
|
| FractionalMaxPool.Options |
|
| FractionalMaxPoolGrad<T extends TNumber> |
Computes gradient of the FractionalMaxPool function.
|
| FractionalMaxPoolGrad.Inputs<T extends TNumber> |
|
| FractionalMaxPoolGrad.Options |
|
| FresnelCos<T extends TNumber> |
The FresnelCos operation
|
| FresnelCos.Inputs<T extends TNumber> |
|
| FresnelSin<T extends TNumber> |
The FresnelSin operation
|
| FresnelSin.Inputs<T extends TNumber> |
|
| FullTypeDef |
Highly experimental and very likely to change.
|
| FullTypeDef.AttrCase |
|
| FullTypeDef.Builder |
Highly experimental and very likely to change.
|
| FullTypeDefOrBuilder |
|
| FullTypeId |
LINT.IfChange
Experimental.
|
| FullTypeProtos |
|
| Function |
|
| 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.JitCompile |
Whether the function should be compiled by XLA.
|
| FunctionSpecOrBuilder |
|
| FusedBatchNorm<T extends TNumber,U extends TNumber> |
Batch normalization.
|
| FusedBatchNorm.Inputs<T extends TNumber,U extends TNumber> |
|
| FusedBatchNorm.Options |
|
| FusedBatchNormGrad<T extends TNumber,U extends TNumber> |
Gradient for batch normalization.
|
| FusedBatchNormGrad.Inputs<T extends TNumber,U extends TNumber> |
|
| FusedBatchNormGrad.Options |
|
| FusedPadConv2d<T extends TNumber> |
Performs a padding as a preprocess during a convolution.
|
| FusedPadConv2d.Inputs<T extends TNumber> |
|
| FusedResizeAndPadConv2d<T extends TNumber> |
Performs a resize and padding as a preprocess during a convolution.
|
| FusedResizeAndPadConv2d.Inputs<T extends TNumber> |
|
| FusedResizeAndPadConv2d.Options |
|
| 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.Inputs<T extends TType> |
|
| Gather.Inputs<T extends TType,U extends TNumber> |
|
| Gather.Options |
Optional attributes for Gather |
| GatherNd<T extends TType> |
Gather slices from params into a Tensor with shape specified by indices.
|
| GatherNd.Inputs<T extends TType> |
|
| GenerateBoundingBoxProposals |
This op produces Region of Interests from given bounding boxes(bbox_deltas) encoded wrt anchors according to eq.2 in arXiv:1506.01497
|
| GenerateBoundingBoxProposals.Inputs |
|
| GenerateBoundingBoxProposals.Options |
|
| 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.Inputs |
|
| GenerateVocabRemapping.Options |
|
| GeneratorDataset |
Creates a dataset that invokes a function to generate elements.
|
| GeneratorDataset.Inputs |
|
| GeneratorDataset.Options |
|
| GetElementAtIndex |
Gets the element at the specified index in a dataset.
|
| GetElementAtIndex.Inputs |
|
| GetOptions |
Returns the tf.data.Options attached to input_dataset.
|
| GetOptions.Inputs |
|
| GetSessionHandle |
Store the input tensor in the state of the current session.
|
| GetSessionHandle.Inputs |
|
| GetSessionTensor<T extends TType> |
Get the value of the tensor specified by its handle.
|
| GetSessionTensor.Inputs |
|
| 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 |
|
| GradFunc |
GradFunc is the signature for all gradient functions in GradOpRegistry.
|
| 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 |
|
| 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...
|
| Gradients.Options |
|
| GradientScope |
A Scope implementation backed by a native scope. |
| GradOpRegistry |
GradOpRegistry maintains a static registry of gradient functions.
|
| 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 operations
|
| GraphDef.Builder |
Represents the graph of operations
|
| 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 |
|
| GraphOperationBuilder |
|
| 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.
|
| Greater.Inputs<T extends TNumber> |
|
| GreaterEqual |
Returns the truth value of (x >= y) element-wise.
|
| GreaterEqual.Inputs<T extends TNumber> |
|
| GroupByReducerDataset |
Creates a dataset that computes a group-by on input_dataset.
|
| GroupByReducerDataset |
Creates a dataset that computes a group-by on input_dataset.
|
| GroupByReducerDataset.Inputs |
|
| GroupByReducerDataset.Inputs |
|
| GroupByWindowDataset |
Creates a dataset that computes a windowed group-by on input_dataset.
|
| GroupByWindowDataset |
Creates a dataset that computes a windowed group-by on input_dataset.
|
| GroupByWindowDataset.Inputs |
|
| GroupByWindowDataset.Inputs |
|
| GroupByWindowDataset.Options |
|
| GRUBlockCell<T extends TNumber> |
Computes the GRU cell forward propagation for 1 time step.
|
| GRUBlockCell.Inputs<T extends TNumber> |
|
| GRUBlockCellGrad<T extends TNumber> |
Computes the GRU cell back-propagation for 1 time step.
|
| GRUBlockCellGrad.Inputs<T extends TNumber> |
|
| GuaranteeConst<T extends TType> |
Gives a guarantee to the TF runtime that the input tensor is a constant.
|
| GuaranteeConst.Inputs<T extends TType> |
|
| HashTable |
Creates a non-initialized hash table.
|
| HashTable.Inputs |
|
| HashTable.Options |
|
| Helpers |
Container class for core methods which add or perform several operations and return one of them.
|
| HistogramFixedWidth<U extends TNumber> |
Return histogram of values.
|
| HistogramFixedWidth.Inputs<T extends TNumber> |
|
| HistogramProto |
Serialization format for histogram module in
core/lib/histogram/histogram.h
|
| HistogramProto.Builder |
Serialization format for histogram module in
core/lib/histogram/histogram.h
|
| HistogramProtoOrBuilder |
|
| HistogramSummary |
Outputs a Summary protocol buffer with a histogram.
|
| HistogramSummary.Inputs |
|
| HsvToRgb<T extends TNumber> |
Convert one or more images from HSV to RGB.
|
| HsvToRgb.Inputs<T extends TNumber> |
|
| Identity<T extends TType> |
Return a tensor with the same shape and contents as the input tensor or value.
|
| Identity.Inputs<T extends TType> |
|
| IdentityN |
Returns a list of tensors with the same shapes and contents as the input
tensors.
|
| IdentityN.Inputs |
|
| IdentityReader |
A Reader that outputs the queued work as both the key and value.
|
| IdentityReader.Inputs |
|
| IdentityReader.Options |
|
| If |
output = cond ? then_branch(input) : else_branch(input)
|
| If |
output = cond ? then_branch(inputs) : else_branch(inputs).
|
| If.Inputs |
|
| If.Options |
Optional attributes for If |
| Ifft<T extends TType> |
Inverse fast Fourier transform.
|
| Ifft.Inputs<T extends TType> |
|
| Ifft2d<T extends TType> |
Inverse 2D fast Fourier transform.
|
| Ifft2d.Inputs<T extends TType> |
|
| Ifft3d<T extends TType> |
Inverse 3D fast Fourier transform.
|
| Ifft3d.Inputs<T extends TType> |
|
| Igamma<T extends TNumber> |
Compute the lower regularized incomplete Gamma function P(a, x).
|
| Igamma.Inputs<T extends TNumber> |
|
| Igammac<T extends TNumber> |
Compute the upper regularized incomplete Gamma function Q(a, x).
|
| Igammac.Inputs<T extends TNumber> |
|
| IgammaGradA<T extends TNumber> |
Computes the gradient of igamma(a, x) wrt a.
|
| IgammaGradA.Inputs<T extends TNumber> |
|
| 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.Inputs |
|
| IgnoreErrorsDataset.Inputs |
|
| IgnoreErrorsDataset.Options |
|
| IgnoreErrorsDataset.Options |
|
| Imag<U extends TNumber> |
Returns the imaginary part of a complex number.
|
| Imag.Inputs |
|
| ImageOps |
An API for building image operations as Ops |
| ImageProjectiveTransformV2<T extends TNumber> |
Applies the given transform to each of the images.
|
| ImageProjectiveTransformV2.Inputs<T extends TNumber> |
|
| ImageProjectiveTransformV2.Options |
|
| ImageProjectiveTransformV3<T extends TNumber> |
Applies the given transform to each of the images.
|
| ImageProjectiveTransformV3.Inputs<T extends TNumber> |
|
| ImageProjectiveTransformV3.Options |
|
| ImageSummary |
Outputs a Summary protocol buffer with images.
|
| ImageSummary.Inputs |
|
| ImageSummary.Options |
|
| ImmutableConst<T extends TType> |
Returns immutable tensor from memory region.
|
| ImmutableConst.Inputs |
|
| ImportEvent |
The ImportEvent operation
|
| ImportEvent.Inputs |
|
| InfeedDequeue<T extends TType> |
A placeholder op for a value that will be fed into the computation.
|
| InfeedDequeue.Inputs |
|
| InfeedDequeueTuple |
Fetches multiple values from infeed as an XLA tuple.
|
| InfeedDequeueTuple.Inputs |
|
| InfeedEnqueue |
An op which feeds a single Tensor value into the computation.
|
| InfeedEnqueue.Inputs |
|
| InfeedEnqueue.Options |
|
| InfeedEnqueuePrelinearizedBuffer |
An op which enqueues prelinearized buffer into TPU infeed.
|
| InfeedEnqueuePrelinearizedBuffer.Inputs |
|
| InfeedEnqueuePrelinearizedBuffer.Options |
|
| InfeedEnqueueTuple |
Feeds multiple Tensor values into the computation as an XLA tuple.
|
| InfeedEnqueueTuple.Inputs |
|
| InfeedEnqueueTuple.Options |
|
| InitializeTable |
Table initializer that takes two tensors for keys and values respectively.
|
| InitializeTable.Inputs |
|
| InitializeTableFromDataset |
The InitializeTableFromDataset operation
|
| InitializeTableFromDataset.Inputs |
|
| InitializeTableFromTextFile |
Initializes a table from a text file.
|
| InitializeTableFromTextFile.Inputs |
|
| InitializeTableFromTextFile.Options |
|
| InplaceAdd<T extends TType> |
Adds v into specified rows of x.
|
| InplaceAdd.Inputs<T extends TType> |
|
| InplaceSub<T extends TType> |
Subtracts `v` into specified rows of `x`.
|
| InplaceSub.Inputs<T extends TType> |
|
| InplaceUpdate<T extends TType> |
Updates specified rows 'i' with values 'v'.
|
| InplaceUpdate.Inputs<T extends TType> |
|
| Int64List |
Protobuf type tensorflow.Int64List
|
| Int64List.Builder |
Protobuf type tensorflow.Int64List
|
| Int64ListOrBuilder |
|
| InterconnectLink |
Protobuf type tensorflow.InterconnectLink
|
| InterconnectLink.Builder |
Protobuf type tensorflow.InterconnectLink
|
| InterconnectLinkOrBuilder |
|
| InterleaveDataset |
Creates a dataset that applies f to the outputs of input_dataset.
|
| InterleaveDataset.Inputs |
|
| InterleaveDataset.Options |
|
| InTopK |
Says whether the targets are in the top K predictions.
|
| InTopK.Inputs<T extends TNumber> |
|
| Inv<T extends TType> |
Computes the inverse of one or more square invertible matrices or their adjoints (conjugate transposes).
|
| Inv.Inputs<T extends TType> |
|
| 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.
|
| Invert.Inputs<T extends TNumber> |
|
| InvertPermutation<T extends TNumber> |
Computes the inverse permutation of a tensor.
|
| InvertPermutation.Inputs<T extends TNumber> |
|
| InvGrad<T extends TType> |
Computes the gradient for the inverse of x wrt its input.
|
| InvGrad.Inputs<T extends TType> |
|
| IoOps |
An API for building io operations as Ops |
| Irfft<U extends TNumber> |
Inverse real-valued fast Fourier transform.
|
| Irfft.Inputs |
|
| Irfft2d<U extends TNumber> |
Inverse 2D real-valued fast Fourier transform.
|
| Irfft2d.Inputs |
|
| Irfft3d<U extends TNumber> |
Inverse 3D real-valued fast Fourier transform.
|
| Irfft3d.Inputs |
|
| IsBoostedTreesEnsembleInitialized |
Checks whether a tree ensemble has been initialized.
|
| IsBoostedTreesEnsembleInitialized.Inputs |
|
| IsBoostedTreesQuantileStreamResourceInitialized |
Checks whether a quantile stream has been initialized.
|
| IsBoostedTreesQuantileStreamResourceInitialized.Inputs |
|
| IsFinite |
Returns which elements of x are finite.
|
| IsFinite.Inputs |
|
| IsInf |
Returns which elements of x are Inf.
|
| IsInf.Inputs |
|
| IsNan |
Returns which elements of x are NaN.
|
| IsNan.Inputs |
|
| IsotonicRegression<U extends TNumber> |
Solves a batch of isotonic regression problems.
|
| IsotonicRegression.Inputs |
|
| IsTPUEmbeddingInitialized |
Whether TPU Embedding is initialized in a distributed TPU system.
|
| IsTPUEmbeddingInitialized.Inputs |
|
| IsTPUEmbeddingInitialized.Options |
|
| IsVariableInitialized |
Checks whether a tensor has been initialized.
|
| IsVariableInitialized.Inputs |
|
| Iterator |
The IteratorV2 operation
|
| Iterator.Inputs |
|
| IteratorFromStringHandle |
The IteratorFromStringHandleV2 operation
|
| IteratorFromStringHandle.Inputs |
|
| IteratorFromStringHandle.Options |
|
| 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.
|
| IteratorGetDevice.Inputs |
|
| IteratorGetDevice.Inputs |
|
| IteratorGetNext |
Gets the next output from the given iterator .
|
| IteratorGetNext.Inputs |
|
| IteratorGetNextAsOptional |
Gets the next output from the given iterator as an Optional variant.
|
| IteratorGetNextAsOptional.Inputs |
|
| IteratorGetNextSync |
Gets the next output from the given iterator.
|
| IteratorGetNextSync.Inputs |
|
| IteratorToStringHandle |
Converts the given resource_handle representing an iterator to a string.
|
| IteratorToStringHandle.Inputs |
|
| 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.Inputs |
|
| Join.Options |
Optional attributes for Join |
| 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 KernelDefs
|
| KernelList.Builder |
A collection of KernelDefs
|
| KernelListOrBuilder |
|
| KeyValueSort<T extends TNumber,U extends TType> |
Wraps the XLA Sort operator, documented at
https://www.tensorflow.org/performance/xla/operation_semantics#sort
.
|
| KeyValueSort.Inputs<T extends TNumber,U extends TType> |
|
| KMC2ChainInitialization |
Returns the index of a data point that should be added to the seed set.
|
| KMC2ChainInitialization.Inputs |
|
| KmeansPlusPlusInitialization |
Selects num_to_sample rows of input using the KMeans++ criterion.
|
| KmeansPlusPlusInitialization.Inputs |
|
| KthOrderStatistic |
Computes the Kth order statistic of a data set.
|
| KthOrderStatistic.Inputs |
|
| L2Loss<T extends TNumber> |
L2 Loss.
|
| L2Loss.Inputs<T extends TNumber> |
|
| LatencyStatsDataset |
Records the latency of producing input_dataset elements in a StatsAggregator.
|
| LatencyStatsDataset |
Records the latency of producing input_dataset elements in a StatsAggregator.
|
| LatencyStatsDataset.Inputs |
|
| LatencyStatsDataset.Inputs |
|
| LeakyRelu<T extends TNumber> |
Computes rectified linear: max(features, features * alpha).
|
| LeakyRelu.Inputs<T extends TNumber> |
|
| LeakyRelu.Options |
|
| LeakyReluGrad<T extends TNumber> |
Computes rectified linear gradients for a LeakyRelu operation.
|
| LeakyReluGrad.Inputs<T extends TNumber> |
|
| LeakyReluGrad.Options |
|
| LearnedUnigramCandidateSampler |
Generates labels for candidate sampling with a learned unigram distribution.
|
| LearnedUnigramCandidateSampler.Inputs |
|
| LearnedUnigramCandidateSampler.Options |
|
| LeftShift<T extends TNumber> |
Elementwise computes the bitwise left-shift of x and y.
|
| LeftShift.Inputs<T extends TNumber> |
|
| LegacyParallelInterleaveDataset |
Creates a dataset that applies f to the outputs of input_dataset.
|
| LegacyParallelInterleaveDataset.Inputs |
|
| LegacyParallelInterleaveDataset.Options |
|
| Less |
Returns the truth value of (x < y) element-wise.
|
| Less.Inputs<T extends TNumber> |
|
| LessEqual |
Returns the truth value of (x <= y) element-wise.
|
| LessEqual.Inputs<T extends TNumber> |
|
| Lgamma<T extends TNumber> |
Computes the log of the absolute value of Gamma(x) element-wise.
|
| Lgamma.Inputs<T extends TNumber> |
|
| LinalgOps |
An API for building linalg operations as Ops |
| LinSpace<T extends TNumber> |
Generates values in an interval.
|
| LinSpace.Inputs<T extends TNumber> |
|
| ListDataset |
Creates a dataset that emits each of tensors once.
|
| ListDataset.Inputs |
|
| ListDataset.Options |
|
| Listener_BytePointer |
|
| Listener_String |
|
| ListValue |
Represents a Python list.
|
| ListValue.Builder |
Represents a Python list.
|
| ListValueOrBuilder |
|
| LmdbDataset |
The ExperimentalLMDBDataset operation
|
| LMDBDataset |
Creates a dataset that emits the key-value pairs in one or more LMDB files.
|
| LmdbDataset.Inputs |
|
| LMDBDataset.Inputs |
|
| LmdbReader |
A Reader that outputs the records from a LMDB file.
|
| LmdbReader.Inputs |
|
| LmdbReader.Options |
|
| LoadAllTPUEmbeddingParameters |
An op that loads optimization parameters into embedding memory.
|
| LoadAllTPUEmbeddingParameters.Inputs |
|
| 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.Inputs |
|
| LoadAndRemapMatrix.Options |
|
| LoadDataset |
The LoadDataset operation
|
| LoadDataset.Inputs |
|
| LoadDataset.Options |
|
| LoadTPUEmbeddingAdadeltaParameters |
Load Adadelta embedding parameters.
|
| LoadTPUEmbeddingAdadeltaParameters.Inputs |
|
| LoadTPUEmbeddingAdadeltaParameters.Options |
|
| LoadTPUEmbeddingAdagradMomentumParameters |
Load Adagrad Momentum embedding parameters.
|
| LoadTPUEmbeddingAdagradMomentumParameters.Inputs |
|
| LoadTPUEmbeddingAdagradMomentumParameters.Options |
|
| LoadTPUEmbeddingAdagradParameters |
Load Adagrad embedding parameters.
|
| LoadTPUEmbeddingAdagradParameters.Inputs |
|
| LoadTPUEmbeddingAdagradParameters.Options |
|
| LoadTPUEmbeddingADAMParameters |
Load ADAM embedding parameters.
|
| LoadTPUEmbeddingADAMParameters.Inputs |
|
| LoadTPUEmbeddingADAMParameters.Options |
|
| LoadTPUEmbeddingCenteredRMSPropParameters |
Load centered RMSProp embedding parameters.
|
| LoadTPUEmbeddingCenteredRMSPropParameters.Inputs |
|
| LoadTPUEmbeddingCenteredRMSPropParameters.Options |
|
| LoadTPUEmbeddingFrequencyEstimatorParameters |
Load frequency estimator embedding parameters.
|
| LoadTPUEmbeddingFrequencyEstimatorParameters.Inputs |
|
| LoadTPUEmbeddingFrequencyEstimatorParameters.Options |
|
| LoadTPUEmbeddingFTRLParameters |
Load FTRL embedding parameters.
|
| LoadTPUEmbeddingFTRLParameters.Inputs |
|
| LoadTPUEmbeddingFTRLParameters.Options |
|
| LoadTPUEmbeddingMDLAdagradLightParameters |
Load MDL Adagrad Light embedding parameters.
|
| LoadTPUEmbeddingMDLAdagradLightParameters.Inputs |
|
| LoadTPUEmbeddingMDLAdagradLightParameters.Options |
|
| LoadTPUEmbeddingMomentumParameters |
Load Momentum embedding parameters.
|
| LoadTPUEmbeddingMomentumParameters.Inputs |
|
| LoadTPUEmbeddingMomentumParameters.Options |
|
| LoadTPUEmbeddingProximalAdagradParameters |
Load proximal Adagrad embedding parameters.
|
| LoadTPUEmbeddingProximalAdagradParameters.Inputs |
|
| LoadTPUEmbeddingProximalAdagradParameters.Options |
|
| LoadTPUEmbeddingProximalYogiParameters |
The LoadTPUEmbeddingProximalYogiParameters operation
|
| LoadTPUEmbeddingProximalYogiParameters.Inputs |
|
| LoadTPUEmbeddingProximalYogiParameters.Options |
|
| LoadTPUEmbeddingRMSPropParameters |
Load RMSProp embedding parameters.
|
| LoadTPUEmbeddingRMSPropParameters.Inputs |
|
| LoadTPUEmbeddingRMSPropParameters.Options |
|
| LoadTPUEmbeddingStochasticGradientDescentParameters |
Load SGD embedding parameters.
|
| LoadTPUEmbeddingStochasticGradientDescentParameters.Inputs |
|
| LoadTPUEmbeddingStochasticGradientDescentParameters.Options |
|
| LocalLinks |
Protobuf type tensorflow.LocalLinks
|
| LocalLinks.Builder |
Protobuf type tensorflow.LocalLinks
|
| LocalLinksOrBuilder |
|
| LocalResponseNormalization<T extends TNumber> |
Local Response Normalization.
|
| LocalResponseNormalization.Inputs<T extends TNumber> |
|
| LocalResponseNormalization.Options |
|
| LocalResponseNormalizationGrad<T extends TNumber> |
Gradients for Local Response Normalization.
|
| LocalResponseNormalizationGrad.Inputs<T extends TNumber> |
|
| LocalResponseNormalizationGrad.Options |
|
| Log<T extends TType> |
Computes natural logarithm of x element-wise.
|
| Log.Inputs<T extends TType> |
|
| Log1p<T extends TType> |
Computes natural logarithm of (1 + x) element-wise.
|
| Log1p.Inputs<T extends TType> |
|
| LogicalAnd |
Returns the truth value of x AND y element-wise.
|
| LogicalAnd.Inputs |
|
| LogicalNot |
Returns the truth value of NOT x element-wise.
|
| LogicalNot.Inputs |
|
| LogicalOr |
Returns the truth value of x OR y element-wise.
|
| LogicalOr.Inputs |
|
| LogMatrixDeterminant<T extends TType> |
Computes the sign and the log of the absolute value of the determinant of
one or more square matrices.
|
| LogMatrixDeterminant.Inputs<T extends TType> |
|
| LogMemoryProtos |
|
| LogMessage |
Deprecated. |
| LogMessage.Builder |
Protocol buffer used for logging messages to the events file.
|
| LogMessage.Level |
Protobuf enum tensorflow.LogMessage.Level
|
| LogMessageOrBuilder |
Deprecated. |
| LogNormalDistribution |
Protobuf type tensorflow.LogNormalDistribution
|
| LogNormalDistribution.Builder |
Protobuf type tensorflow.LogNormalDistribution
|
| LogNormalDistributionOrBuilder |
|
| LogSoftmax<T extends TNumber> |
Computes log softmax activations.
|
| LogSoftmax.Inputs<T extends TNumber> |
|
| LogUniformCandidateSampler |
Generates labels for candidate sampling with a log-uniform distribution.
|
| LogUniformCandidateSampler.Inputs |
|
| LogUniformCandidateSampler.Options |
|
| LookupTableExport<T extends TType,U extends TType> |
Outputs all keys and values in the table.
|
| LookupTableExport.Inputs |
|
| LookupTableFind<U extends TType> |
Looks up keys in a table, outputs the corresponding values.
|
| LookupTableFind.Inputs<U extends TType> |
|
| LookupTableImport |
Replaces the contents of the table with the specified keys and values.
|
| LookupTableImport.Inputs |
|
| LookupTableInsert |
Updates the table to associates keys with values.
|
| LookupTableInsert.Inputs |
|
| LookupTableRemove |
Removes keys and its associated values from a table.
|
| LookupTableRemove.Inputs |
|
| LookupTableSize |
Computes the number of elements in the given table.
|
| LookupTableSize.Inputs |
|
| LoopCond |
Forwards the input to the output.
|
| LoopCond.Inputs |
|
| Lower |
Converts all uppercase characters into their respective lowercase replacements.
|
| Lower.Inputs |
|
| Lower.Options |
Optional attributes for Lower |
| LowerBound<U extends TNumber> |
Applies lower_bound(sorted_search_values, values) along each row.
|
| LowerBound.Inputs<T extends TType> |
|
| LSTMBlockCell<T extends TNumber> |
Computes the LSTM cell forward propagation for 1 time step.
|
| LSTMBlockCell.Inputs<T extends TNumber> |
|
| LSTMBlockCell.Options |
|
| LSTMBlockCellGrad<T extends TNumber> |
Computes the LSTM cell backward propagation for 1 timestep.
|
| LSTMBlockCellGrad.Inputs<T extends TNumber> |
|
| Lu<T extends TType,U extends TNumber> |
Computes the LU decomposition of one or more square matrices.
|
| Lu.Inputs<T extends TType> |
|
| 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.
|
| MakeIterator.Inputs |
|
| MakeUnique |
Make all elements in the non-Batch dimension unique, but "close" to
their initial value.
|
| MakeUnique.Inputs |
|
| MapAndBatchDataset |
Creates a dataset that fuses mapping with batching.
|
| MapAndBatchDataset |
Creates a dataset that fuses mapping with batching.
|
| MapAndBatchDataset.Inputs |
|
| MapAndBatchDataset.Inputs |
|
| MapAndBatchDataset.Options |
|
| MapAndBatchDataset.Options |
|
| MapClear |
Op removes all elements in the underlying container.
|
| MapClear.Inputs |
|
| MapClear.Options |
|
| MapDataset |
Creates a dataset that applies f to the outputs of input_dataset.
|
| MapDataset |
Creates a dataset that applies f to the outputs of input_dataset.
|
| MapDataset.Inputs |
|
| MapDataset.Inputs |
|
| MapDataset.Options |
|
| MapDataset.Options |
|
| MapDefun |
Maps a function on the list of tensors unpacked from arguments on dimension 0.
|
| MapDefun.Inputs |
|
| MapDefun.Options |
|
| MapIncompleteSize |
Op returns the number of incomplete elements in the underlying container.
|
| MapIncompleteSize.Inputs |
|
| MapIncompleteSize.Options |
|
| MapPeek |
Op peeks at the values at the specified key.
|
| MapPeek.Inputs |
|
| MapPeek.Options |
|
| MapSize |
Op returns the number of elements in the underlying container.
|
| MapSize.Inputs |
|
| MapSize.Options |
|
| MapStage |
Stage (key, values) in the underlying container which behaves like a hashtable.
|
| MapStage.Inputs |
|
| MapStage.Options |
|
| MapUnstage |
Op removes and returns the values associated with the key
from the underlying container.
|
| MapUnstage.Inputs |
|
| MapUnstage.Options |
|
| MapUnstageNoKey |
Op removes and returns a random (key, value)
from the underlying container.
|
| MapUnstageNoKey.Inputs |
|
| MapUnstageNoKey.Options |
|
| MatchingFiles |
Returns the set of files matching one or more glob patterns.
|
| MatchingFiles.Inputs |
|
| MatchingFilesDataset |
The ExperimentalMatchingFilesDataset operation
|
| MatchingFilesDataset |
The MatchingFilesDataset operation
|
| MatchingFilesDataset.Inputs |
|
| MatchingFilesDataset.Inputs |
|
| MathOps |
An API for building math operations as Ops |
| MatMul<T extends TType> |
Multiply the matrix "a" by the matrix "b".
|
| MatMul.Inputs<T extends TType> |
|
| MatMul.Options |
Optional attributes for MatMul |
| MatrixDiag<T extends TType> |
Returns a batched diagonal tensor with given batched diagonal values.
|
| MatrixDiag.Inputs<T extends TType> |
|
| MatrixDiagPart<T extends TType> |
Returns the batched diagonal part of a batched tensor.
|
| MatrixDiagPart.Inputs<T extends TType> |
|
| MatrixDiagPartV3<T extends TType> |
Returns the batched diagonal part of a batched tensor.
|
| MatrixDiagPartV3.Inputs<T extends TType> |
|
| MatrixDiagPartV3.Options |
|
| MatrixDiagV3<T extends TType> |
Returns a batched diagonal tensor with given batched diagonal values.
|
| MatrixDiagV3.Inputs<T extends TType> |
|
| MatrixDiagV3.Options |
|
| MatrixLogarithm<T extends TType> |
Computes the matrix logarithm of one or more square matrices:
\(log(exp(A)) = A\)
|
| MatrixLogarithm.Inputs<T extends TType> |
|
| MatrixSetDiag<T extends TType> |
Returns a batched matrix tensor with new batched diagonal values.
|
| MatrixSetDiag.Inputs<T extends TType> |
|
| MatrixSetDiag.Options |
|
| MatrixSolveLs<T extends TType> |
Solves one or more linear least-squares problems.
|
| MatrixSolveLs.Inputs<T extends TType> |
|
| MatrixSolveLs.Options |
|
| Max<T extends TNumber> |
Computes the maximum of elements across dimensions of a tensor.
|
| Max.Inputs<T extends TNumber> |
|
| Max.Options |
Optional attributes for Max |
| Maximum<T extends TNumber> |
Returns the max of x and y (i.e.
|
| Maximum.Inputs<T extends TNumber> |
|
| MaxIntraOpParallelismDataset |
Creates a dataset that overrides the maximum intra-op parallelism.
|
| MaxIntraOpParallelismDataset |
Creates a dataset that overrides the maximum intra-op parallelism.
|
| MaxIntraOpParallelismDataset.Inputs |
|
| MaxIntraOpParallelismDataset.Inputs |
|
| MaxPool<T extends TNumber> |
Performs max pooling on the input.
|
| MaxPool.Inputs<T extends TNumber> |
|
| MaxPool.Options |
|
| MaxPool3d<T extends TNumber> |
Performs 3D max pooling on the input.
|
| MaxPool3d.Inputs<T extends TNumber> |
|
| MaxPool3d.Options |
|
| MaxPool3dGrad<U extends TNumber> |
Computes gradients of 3D max pooling function.
|
| MaxPool3dGrad.Inputs<T extends TNumber,U extends TNumber> |
|
| MaxPool3dGrad.Options |
|
| MaxPool3dGradGrad<T extends TNumber> |
Computes second-order gradients of the maxpooling function.
|
| MaxPool3dGradGrad.Inputs<T extends TNumber> |
|
| MaxPool3dGradGrad.Options |
|
| MaxPoolGrad<T extends TNumber> |
Computes gradients of the maxpooling function.
|
| MaxPoolGrad.Inputs<T extends TNumber> |
|
| MaxPoolGrad.Options |
|
| MaxPoolGradGrad<T extends TNumber> |
Computes second-order gradients of the maxpooling function.
|
| MaxPoolGradGrad.Inputs<T extends TNumber> |
|
| MaxPoolGradGrad.Options |
|
| MaxPoolGradGradWithArgmax<T extends TNumber> |
Computes second-order gradients of the maxpooling function.
|
| MaxPoolGradGradWithArgmax.Inputs<T extends TNumber> |
|
| MaxPoolGradGradWithArgmax.Options |
|
| MaxPoolGradWithArgmax<T extends TNumber> |
Computes gradients of the maxpooling function.
|
| MaxPoolGradWithArgmax.Inputs<T extends TNumber> |
|
| MaxPoolGradWithArgmax.Options |
|
| MaxPoolWithArgmax<T extends TNumber,U extends TNumber> |
Performs max pooling on the input and outputs both max values and indices.
|
| MaxPoolWithArgmax.Inputs<T extends TNumber> |
|
| MaxPoolWithArgmax.Options |
|
| Mean<T extends TType> |
Computes the mean of elements across dimensions of a tensor.
|
| Mean.Inputs<T extends TType> |
|
| Mean.Options |
Optional attributes for Mean |
| MemAllocatorStats |
Some of the data from AllocatorStats
|
| MemAllocatorStats.Builder |
Some of the data from AllocatorStats
|
| 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.
|
| Merge.Inputs<T extends TType> |
|
| MergeSummary |
Merges summaries.
|
| MergeSummary.Inputs |
|
| MergeV2Checkpoints |
V2 format specific: merges the metadata files of sharded checkpoints.
|
| MergeV2Checkpoints.Inputs |
|
| MergeV2Checkpoints.Options |
|
| MetaGraphDef |
Protocol buffer containing the following which are necessary to restart
training, run inference.
|
| MetaGraphDef.Builder |
Protocol buffer containing the following which are necessary to restart
training, run inference.
|
| 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 |
|
| MetricEntry |
Protobuf type tensorflow.MetricEntry
|
| MetricEntry.Builder |
Protobuf type tensorflow.MetricEntry
|
| MetricEntryOrBuilder |
|
| Mfcc |
Transforms a spectrogram into a form that's useful for speech recognition.
|
| Mfcc.Inputs |
|
| Mfcc.Options |
Optional attributes for Mfcc |
| Min<T extends TNumber> |
Computes the minimum of elements across dimensions of a tensor.
|
| Min.Inputs<T extends TNumber> |
|
| Min.Options |
Optional attributes for Min |
| Minimum<T extends TNumber> |
Returns the min of x and y (i.e.
|
| Minimum.Inputs<T extends TNumber> |
|
| MirrorPad<T extends TType> |
Pads a tensor with mirrored values.
|
| MirrorPad.Inputs<T extends TType> |
|
| MirrorPadGrad<T extends TType> |
Gradient op for MirrorPad op.
|
| MirrorPadGrad.Inputs<T extends TType> |
|
| MlirPassthroughOp |
Wraps an arbitrary MLIR computation expressed as a module with a main() function.
|
| MlirPassthroughOp.Inputs |
|
| Mod<T extends TNumber> |
Returns element-wise remainder of division.
|
| Mod.Inputs<T extends TNumber> |
|
| ModelDataset |
Identity transformation that models performance.
|
| ModelDataset.Inputs |
|
| ModelDataset.Options |
|
| ModelProto |
Protocol buffer representing the data used by the autotuning modeling
framework.
|
| ModelProto.Builder |
Protocol buffer representing the data used by the autotuning modeling
framework.
|
| ModelProto.Node |
General representation of a node in the model.
|
| ModelProto.Node.Builder |
General representation of a node in the model.
|
| ModelProto.Node.Parameter |
Represents a node parameter.
|
| ModelProto.Node.Parameter.Builder |
Represents a node parameter.
|
| ModelProto.Node.ParameterOrBuilder |
|
| ModelProto.NodeOrBuilder |
|
| ModelProto.OptimizationParams |
Contains parameters of the model autotuning optimization.
|
| ModelProto.OptimizationParams.Builder |
Contains parameters of the model autotuning optimization.
|
| ModelProto.OptimizationParamsOrBuilder |
|
| ModelProtoOrBuilder |
|
| ModelProtos |
|
| Mul<T extends TType> |
Returns x * y element-wise.
|
| Mul.Inputs<T extends TType> |
|
| MulNoNan<T extends TType> |
Returns x * y element-wise.
|
| MulNoNan.Inputs<T extends TType> |
|
| MultiDeviceIterator |
Creates a MultiDeviceIterator resource.
|
| MultiDeviceIterator.Inputs |
|
| MultiDeviceIteratorFromStringHandle |
Generates a MultiDeviceIterator resource from its provided string handle.
|
| MultiDeviceIteratorFromStringHandle.Inputs |
|
| MultiDeviceIteratorFromStringHandle.Options |
|
| MultiDeviceIteratorGetNextFromShard |
Gets next element for the provided shard number.
|
| MultiDeviceIteratorGetNextFromShard.Inputs |
|
| MultiDeviceIteratorInit |
Initializes the multi device iterator with the given dataset.
|
| MultiDeviceIteratorInit.Inputs |
|
| MultiDeviceIteratorToStringHandle |
Produces a string handle for the given MultiDeviceIterator.
|
| MultiDeviceIteratorToStringHandle.Inputs |
|
| Multinomial<U extends TNumber> |
Draws samples from a multinomial distribution.
|
| Multinomial.Inputs |
|
| Multinomial.Options |
|
| MutableDenseHashTable |
Creates an empty hash table that uses tensors as the backing store.
|
| MutableDenseHashTable.Inputs<T extends TType> |
|
| MutableDenseHashTable.Options |
|
| MutableHashTable |
Creates an empty hash table.
|
| MutableHashTable.Inputs |
|
| MutableHashTable.Options |
|
| MutableHashTableOfTensors |
Creates an empty hash table.
|
| MutableHashTableOfTensors.Inputs |
|
| MutableHashTableOfTensors.Options |
|
| Mutex |
Creates a Mutex resource that can be locked by MutexLock.
|
| Mutex.Inputs |
|
| Mutex.Options |
Optional attributes for Mutex |
| MutexLock |
Locks a mutex resource.
|
| MutexLock.Inputs |
|
| 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 |
|
| NameMap |
|
| NameMap.Iterator |
|
| NativeGraphPointer |
|
| NativeOperation |
\addtogroup core
\{
|
| NativeOutput |
Represents a tensor value produced by an Operation.
|
| NativeOutputVector |
|
| NativeOutputVector.Iterator |
|
| NativeStatus |
\ingroup core
Denotes success or failure of a call in Tensorflow.
|
| NcclAllReduce<T extends TNumber> |
Deprecated.
|
| NcclAllReduce<T extends TNumber> |
Outputs a tensor containing the reduction across all input tensors.
|
| NcclAllReduce.Inputs<T extends TNumber> |
|
| NcclAllReduce.Inputs<T extends TNumber> |
|
| NcclBroadcast<T extends TNumber> |
Deprecated.
|
| NcclBroadcast<T extends TNumber> |
Sends input to all devices that are connected to the output.
|
| NcclBroadcast.Inputs<T extends TNumber> |
|
| NcclBroadcast.Inputs<T extends TNumber> |
|
| NcclReduce<T extends TNumber> |
Deprecated.
|
| NcclReduce<T extends TNumber> |
Reduces input from num_devices using reduction to a single device.
|
| NcclReduce.Inputs<T extends TNumber> |
|
| NcclReduce.Inputs<T extends TNumber> |
|
| Ndtri<T extends TNumber> |
The Ndtri operation
|
| Ndtri.Inputs<T extends TNumber> |
|
| NearestNeighbors |
Selects the k nearest centers for each point.
|
| NearestNeighbors.Inputs |
|
| Neg<T extends TType> |
Computes numerical negative value element-wise.
|
| Neg.Inputs<T extends TType> |
|
| NegTrain |
Training via negative sampling.
|
| NegTrain.Inputs |
|
| NextAfter<T extends TNumber> |
Returns the next representable value of x1 in the direction of x2, element-wise.
|
| NextAfter.Inputs<T extends TNumber> |
|
| NextIteration<T extends TType> |
Makes its input available to the next iteration.
|
| NextIteration.Inputs<T extends TType> |
|
| NnOps |
An API for building nn operations as Ops |
| Node |
|
| NodeBuilder |
|
| NodeClass |
Class of a node in the performance model.
|
| 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.
|
| NonDeterministicInts.Inputs |
|
| 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.Inputs<T extends TNumber> |
|
| NonMaxSuppression.Options |
|
| NonMaxSuppressionWithOverlaps |
Greedily selects a subset of bounding boxes in descending order of score,
pruning away boxes that have high overlaps
with previously selected boxes.
|
| NonMaxSuppressionWithOverlaps.Inputs |
|
| NonSerializableDataset |
The ExperimentalNonSerializableDataset operation
|
| NonSerializableDataset |
The NonSerializableDataset operation
|
| NonSerializableDataset.Inputs |
|
| NonSerializableDataset.Inputs |
|
| NoOp |
Does nothing.
|
| NoOp.Inputs |
|
| NormalDistribution |
Protobuf type tensorflow.NormalDistribution
|
| NormalDistribution.Builder |
Protobuf type tensorflow.NormalDistribution
|
| NormalDistributionOrBuilder |
|
| NotEqual |
Returns the truth value of (x != y) element-wise.
|
| NotEqual.Inputs<T extends TType> |
|
| NotEqual.Options |
|
| NthElement<T extends TNumber> |
Finds values of the n-th order statistic for the last dimension.
|
| NthElement.Inputs<T extends TNumber> |
|
| NthElement.Options |
|
| OneHot<U extends TType> |
Returns a one-hot tensor.
|
| OneHot.Inputs<U extends TType> |
|
| OneHot.Options |
Optional attributes for OneHot |
| Ones<T extends TType> |
An operator creating a constant initialized with ones of the shape given by `dims`.
|
| OneShotIterator |
Makes a "one-shot" iterator that can be iterated only once.
|
| OneShotIterator.Inputs |
|
| OneShotIterator.Options |
|
| OnesLike<T extends TType> |
Returns a tensor of ones with the same shape and type as x.
|
| OnesLike.Inputs<T extends TType> |
|
| 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 op
|
| OpDeprecation.Builder |
Information about version-dependent deprecation of an op
|
| 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.
|
| OperationAttributeInspector |
Helper type for attribute getters, so we don't clutter the operation classes too much.
|
| OperationBuilder |
|
| Operator |
Annotation used by classes to make TensorFlow operations conveniently accessible via
org.tensorflow.op.Ops or one of its groups.
|
| OpInfo |
Description of an operation as well as the parameters expected to impact its
performance.
|
| OpInfo.Builder |
Description of an operation as well as the parameters expected to impact its
performance.
|
| OpInfo.TensorProperties |
Input data types, shapes and values if known.
|
| OpInfo.TensorProperties.Builder |
Input data types, shapes and values if known.
|
| OpInfo.TensorPropertiesOrBuilder |
|
| OpInfoOrBuilder |
|
| OpInputsMetadata |
An annotation to provide metadata about an op inputs accessor class.
|
| OpList |
A collection of OpDefs
|
| OpList.Builder |
A collection of OpDefs
|
| OpListOrBuilder |
|
| OpMetadata |
An annotation to provide metadata about an op.
|
| OpPerformance |
Performance data for tensorflow operations
|
| OpPerformance.Builder |
Performance data for tensorflow operations
|
| OpPerformance.ExecutionTimeCase |
|
| OpPerformance.OpMemory |
Memory usage data for a tensorflow operation.
|
| OpPerformance.OpMemory.Builder |
Memory usage data for a tensorflow operation.
|
| OpPerformance.OpMemoryOrBuilder |
|
| OpPerformanceDataProtos |
|
| OpPerformanceList |
A collection of OpPerformance data points.
|
| OpPerformanceList.Builder |
A collection of OpPerformance data points.
|
| OpPerformanceListOrBuilder |
|
| OpPerformanceOrBuilder |
|
| Ops |
An API for building operations as Ops |
| OpScope |
A Java implementation of Scope. |
| OptimizationBarrier |
Wraps the XLA OptimizationBarrier operator.
|
| OptimizationBarrier.Inputs |
|
| OptimizationOptions |
next: 20
|
| OptimizationOptions.Builder |
next: 20
|
| OptimizationOptions.OptionalApplyDefaultOptimizationsCase |
|
| OptimizationOptions.OptionalFilterFusionCase |
|
| OptimizationOptions.OptionalFilterParallelizationCase |
|
| OptimizationOptions.OptionalInjectPrefetchCase |
|
| OptimizationOptions.OptionalMapAndBatchFusionCase |
|
| OptimizationOptions.OptionalMapAndFilterFusionCase |
|
| OptimizationOptions.OptionalMapFusionCase |
|
| OptimizationOptions.OptionalMapParallelizationCase |
|
| OptimizationOptions.OptionalNoopEliminationCase |
|
| OptimizationOptions.OptionalParallelBatchCase |
|
| OptimizationOptions.OptionalShuffleAndRepeatFusionCase |
|
| OptimizationOptionsOrBuilder |
|
| OptimizeDataset |
Creates a dataset by applying related optimizations to input_dataset.
|
| OptimizeDataset.Inputs |
|
| OptimizeDataset.Options |
|
| OptimizerOptions |
Options passed to the graph optimizer
|
| OptimizerOptions.Builder |
Options passed to the graph optimizer
|
| OptimizerOptions.GlobalJitLevel |
Control the use of the compiler/jit.
|
| OptimizerOptions.Level |
Optimization level
|
| OptimizerOptionsOrBuilder |
|
| OptionalFromValue |
Constructs an Optional variant from a tuple of tensors.
|
| OptionalFromValue.Inputs |
|
| OptionalGetValue |
Returns the value stored in an Optional variant or raises an error if none exists.
|
| OptionalGetValue.Inputs |
|
| OptionalHasValue |
Returns true if and only if the given Optional variant has a value.
|
| OptionalHasValue.Inputs |
|
| OptionalNone |
Creates an Optional variant with no value.
|
| OptionalNone.Inputs |
|
| Options |
Message stored with Dataset objects to control how datasets are processed and
optimized.
|
| Options.Builder |
Message stored with Dataset objects to control how datasets are processed and
optimized.
|
| Options.OptionalDeterministicCase |
|
| Options.OptionalExternalStatePolicyCase |
|
| Options.OptionalSlackCase |
|
| OptionsDataset |
Creates a dataset by attaching tf.data.Options to input_dataset.
|
| OptionsDataset.Inputs |
|
| OptionsDataset.Options |
|
| OptionsOrBuilder |
|
| OrderedMapClear |
Op removes all elements in the underlying container.
|
| OrderedMapClear.Inputs |
|
| OrderedMapClear.Options |
|
| OrderedMapIncompleteSize |
Op returns the number of incomplete elements in the underlying container.
|
| OrderedMapIncompleteSize.Inputs |
|
| OrderedMapIncompleteSize.Options |
|
| OrderedMapPeek |
Op peeks at the values at the specified key.
|
| OrderedMapPeek.Inputs |
|
| OrderedMapPeek.Options |
|
| OrderedMapSize |
Op returns the number of elements in the underlying container.
|
| OrderedMapSize.Inputs |
|
| OrderedMapSize.Options |
|
| OrderedMapStage |
Stage (key, values) in the underlying container which behaves like a ordered
associative container.
|
| OrderedMapStage.Inputs |
|
| OrderedMapStage.Options |
|
| OrderedMapUnstage |
Op removes and returns the values associated with the key
from the underlying container.
|
| OrderedMapUnstage.Inputs |
|
| OrderedMapUnstage.Options |
|
| OrderedMapUnstageNoKey |
Op removes and returns the (key, value) element with the smallest
key from the underlying container.
|
| OrderedMapUnstageNoKey.Inputs |
|
| OrderedMapUnstageNoKey.Options |
|
| OrdinalSelector |
A TPU core selector Op.
|
| OrdinalSelector.Inputs |
|
| OutfeedDequeue<T extends TType> |
Retrieves a single tensor from the computation outfeed.
|
| OutfeedDequeue.Inputs |
|
| OutfeedDequeue.Options |
|
| OutfeedDequeueTuple |
Retrieve multiple values from the computation outfeed.
|
| OutfeedDequeueTuple.Inputs |
|
| OutfeedDequeueTuple.Options |
|
| OutfeedDequeueTupleV2 |
Retrieve multiple values from the computation outfeed.
|
| OutfeedDequeueTupleV2.Inputs |
|
| OutfeedDequeueV2<T extends TType> |
Retrieves a single tensor from the computation outfeed.
|
| OutfeedDequeueV2.Inputs |
|
| OutfeedEnqueue |
Enqueue a Tensor on the computation outfeed.
|
| OutfeedEnqueue.Inputs |
|
| OutfeedEnqueueTuple |
Enqueue multiple Tensor values on the computation outfeed.
|
| OutfeedEnqueueTuple.Inputs |
|
| Output<T extends TType> |
A symbolic handle to a tensor produced by an Operation. |
| 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
.
|
| Pad.Inputs<T extends TType> |
|
| Pad.Inputs<T extends TType,U extends TNumber> |
|
| PaddedBatchDataset |
Creates a dataset that batches and pads batch_size elements from the input.
|
| PaddedBatchDataset.Inputs |
|
| PaddedBatchDataset.Options |
|
| PaddingFifoQueue |
A queue that produces elements in first-in first-out order.
|
| PaddingFifoQueue.Inputs |
|
| PaddingFifoQueue.Options |
|
| PairValue |
Represents a (key, value) pair.
|
| PairValue.Builder |
Represents a (key, value) pair.
|
| PairValueOrBuilder |
|
| ParallelBatchDataset |
The ParallelBatchDataset operation
|
| ParallelBatchDataset.Inputs |
|
| ParallelBatchDataset.Options |
|
| ParallelConcat<T extends TType> |
Concatenates a list of N tensors along the first dimension.
|
| ParallelConcat.Inputs<T extends TType> |
|
| ParallelDynamicStitch<T extends TType> |
Interleave the values from the data tensors into a single tensor.
|
| ParallelDynamicStitch.Inputs<T extends TType> |
|
| ParallelFilterDataset |
Creates a dataset containing elements of input_dataset matching predicate.
|
| ParallelFilterDataset.Inputs |
|
| ParallelFilterDataset.Options |
|
| ParallelInterleaveDataset |
Creates a dataset that applies f to the outputs of input_dataset.
|
| ParallelInterleaveDataset |
Creates a dataset that applies f to the outputs of input_dataset.
|
| ParallelInterleaveDataset.Inputs |
|
| ParallelInterleaveDataset.Inputs |
|
| ParallelInterleaveDataset.Options |
|
| ParallelMapDataset |
Creates a dataset that applies f to the outputs of input_dataset.
|
| ParallelMapDataset.Inputs |
|
| ParallelMapDataset.Options |
|
| ParameterizedTruncatedNormal<U extends TNumber> |
Outputs random values from a normal distribution.
|
| ParameterizedTruncatedNormal.Inputs<U extends TNumber> |
|
| ParameterizedTruncatedNormal.Options |
|
| ParseExample |
Transforms a vector of tf.Example protos (as strings) into typed tensors.
|
| ParseExample.Inputs |
|
| 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 |
Transforms input_dataset containing Example protos as vectors of DT_STRING into a dataset of Tensor or SparseTensor objects representing the parsed features.
|
| ParseExampleDataset.Inputs |
|
| ParseExampleDataset.Inputs |
|
| ParseExampleDataset.Options |
|
| ParseExampleDataset.Options |
|
| ParseSequenceExample |
Transforms a vector of tf.io.SequenceExample protos (as strings) into
typed tensors.
|
| ParseSequenceExample.Inputs |
|
| ParseSequenceExample.Options |
|
| ParseSingleExample |
Transforms a tf.Example proto (as a string) into typed tensors.
|
| ParseSingleExample.Inputs |
|
| ParseSingleSequenceExample |
Transforms a scalar brain.SequenceExample proto (as strings) into typed tensors.
|
| ParseSingleSequenceExample.Inputs |
|
| ParseSingleSequenceExample.Options |
|
| ParseTensor<T extends TType> |
Transforms a serialized tensorflow.TensorProto proto into a Tensor.
|
| ParseTensor.Inputs |
|
| PartitionedCall |
returns f(inputs), where f's body is placed and partitioned.
|
| PartitionedCall |
Calls a function placed on a specified TPU device.
|
| PartitionedCall.Inputs |
|
| PartitionedCall.Options |
|
| PartitionedCall.Options |
|
| PartitionedInput<T extends TType> |
An op that groups a list of partitioned inputs together.
|
| PartitionedInput.Inputs<T extends TType> |
|
| PartitionedInput.Options |
|
| 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.Inputs<T extends TType> |
|
| PartitionedOutput.Options |
|
| Placeholder<T extends TType> |
A placeholder op for a value that will be fed into the computation.
|
| Placeholder.Inputs |
|
| Placeholder.Options |
|
| PlaceholderWithDefault<T extends TType> |
A placeholder op that passes through input when its output is not fed.
|
| PlaceholderWithDefault.Inputs<T extends TType> |
|
| PlatformInfo |
Protobuf type tensorflow.PlatformInfo
|
| PlatformInfo.Builder |
Protobuf type tensorflow.PlatformInfo
|
| PlatformInfoOrBuilder |
|
| Polygamma<T extends TNumber> |
Compute the polygamma function \(\psi^{(n)}(x)\).
|
| Polygamma.Inputs<T extends TNumber> |
|
| PopulationCount |
Computes element-wise population count (a.k.a.
|
| PopulationCount.Inputs |
|
| Pow<T extends TType> |
Computes the power of one value to another.
|
| Pow.Inputs<T extends TType> |
|
| PrefetchDataset |
Creates a dataset that asynchronously prefetches elements from input_dataset.
|
| PrefetchDataset.Inputs |
|
| PrefetchDataset.Options |
|
| Prelinearize |
An op which linearizes one Tensor value to an opaque variant tensor.
|
| Prelinearize.Inputs |
|
| Prelinearize.Options |
|
| PrelinearizeTuple |
An op which linearizes multiple Tensor values to an opaque variant tensor.
|
| PrelinearizeTuple.Inputs |
|
| PrelinearizeTuple.Options |
|
| PreventGradient<T extends TType> |
An identity op that triggers an error if a gradient is requested.
|
| PreventGradient.Inputs<T extends TType> |
|
| PreventGradient.Options |
|
| Print |
Prints a string scalar.
|
| Print.Inputs |
|
| Print.Options |
Optional attributes for Print |
| PriorityQueue |
A queue that produces elements sorted by the first component value.
|
| PriorityQueue.Inputs |
|
| PriorityQueue.Options |
|
| 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.
|
| PrivateThreadPoolDataset.Inputs |
|
| PrivateThreadPoolDataset.Inputs |
|
| Prod<T extends TType> |
Computes the product of elements across dimensions of a tensor.
|
| Prod.Inputs<T extends TType> |
|
| Prod.Options |
Optional attributes for Prod |
| ProfileOptions |
Next ID: 11
|
| ProfileOptions.Builder |
Next ID: 11
|
| ProfileOptions.DeviceType |
Protobuf enum tensorflow.ProfileOptions.DeviceType
|
| ProfileOptionsOrBuilder |
|
| ProfilerOptionsProtos |
|
| Qr<T extends TType> |
Computes the QR decompositions of one or more matrices.
|
| Qr.Inputs<T extends TType> |
|
| Qr.Options |
Optional attributes for Qr |
| QuantizationOps |
An API for building quantization operations as Ops |
| Quantize<T extends TNumber> |
Quantize the 'input' tensor of type float to 'output' tensor of type 'T'.
|
| Quantize.Inputs |
|
| Quantize.Options |
|
| QuantizeAndDequantize<T extends TNumber> |
Quantizes then dequantizes a tensor.
|
| QuantizeAndDequantize.Inputs<T extends TNumber> |
|
| QuantizeAndDequantize.Options |
|
| QuantizeAndDequantizeV3<T extends TNumber> |
Quantizes then dequantizes a tensor.
|
| QuantizeAndDequantizeV3.Inputs<T extends TNumber> |
|
| QuantizeAndDequantizeV3.Options |
|
| QuantizeAndDequantizeV4<T extends TNumber> |
Quantizes then dequantizes a tensor.
|
| QuantizeAndDequantizeV4.Inputs<T extends TNumber> |
|
| QuantizeAndDequantizeV4.Options |
|
| QuantizeAndDequantizeV4Grad<T extends TNumber> |
Returns the gradient of QuantizeAndDequantizeV4.
|
| QuantizeAndDequantizeV4Grad.Inputs<T extends TNumber> |
|
| QuantizeAndDequantizeV4Grad.Options |
|
| QuantizedAdd<V extends TNumber> |
Returns x + y element-wise, working on quantized buffers.
|
| QuantizedAdd.Inputs |
|
| QuantizedAvgPool<T extends TNumber> |
Produces the average pool of the input tensor for quantized types.
|
| QuantizedAvgPool.Inputs<T extends TNumber> |
|
| QuantizedBatchNormWithGlobalNormalization<U extends TNumber> |
Quantized Batch normalization.
|
| QuantizedBatchNormWithGlobalNormalization.Inputs<T extends TNumber> |
|
| QuantizedBiasAdd<V extends TNumber> |
Adds Tensor 'bias' to Tensor 'input' for Quantized types.
|
| QuantizedBiasAdd.Inputs |
|
| QuantizedConcat<T extends TType> |
Concatenates quantized tensors along one dimension.
|
| QuantizedConcat.Inputs<T extends TType> |
|
| QuantizedConv2d<V extends TNumber> |
Computes a 2D convolution given quantized 4D input and filter tensors.
|
| QuantizedConv2d.Inputs |
|
| QuantizedConv2d.Options |
|
| QuantizedConv2DAndRelu<V extends TNumber> |
The QuantizedConv2DAndRelu operation
|
| QuantizedConv2DAndRelu.Inputs |
|
| QuantizedConv2DAndRelu.Options |
|
| QuantizedConv2DAndReluAndRequantize<V extends TNumber> |
The QuantizedConv2DAndReluAndRequantize operation
|
| QuantizedConv2DAndReluAndRequantize.Inputs |
|
| QuantizedConv2DAndReluAndRequantize.Options |
|
| QuantizedConv2DAndRequantize<V extends TNumber> |
The QuantizedConv2DAndRequantize operation
|
| QuantizedConv2DAndRequantize.Inputs |
|
| QuantizedConv2DAndRequantize.Options |
|
| QuantizedConv2DPerChannel<V extends TNumber> |
Computes QuantizedConv2D per channel.
|
| QuantizedConv2DPerChannel.Inputs |
|
| QuantizedConv2DPerChannel.Options |
|
| QuantizedConv2DWithBias<V extends TNumber> |
The QuantizedConv2DWithBias operation
|
| QuantizedConv2DWithBias.Inputs |
|
| QuantizedConv2DWithBias.Options |
|
| QuantizedConv2DWithBiasAndRelu<V extends TNumber> |
The QuantizedConv2DWithBiasAndRelu operation
|
| QuantizedConv2DWithBiasAndRelu.Inputs |
|
| QuantizedConv2DWithBiasAndRelu.Options |
|
| QuantizedConv2DWithBiasAndReluAndRequantize<W extends TNumber> |
The QuantizedConv2DWithBiasAndReluAndRequantize operation
|
| QuantizedConv2DWithBiasAndReluAndRequantize.Inputs |
|
| QuantizedConv2DWithBiasAndReluAndRequantize.Options |
|
| QuantizedConv2DWithBiasAndRequantize<W extends TNumber> |
The QuantizedConv2DWithBiasAndRequantize operation
|
| QuantizedConv2DWithBiasAndRequantize.Inputs |
|
| QuantizedConv2DWithBiasAndRequantize.Options |
|
| QuantizedConv2DWithBiasSignedSumAndReluAndRequantize<X extends TNumber> |
The QuantizedConv2DWithBiasSignedSumAndReluAndRequantize operation
|
| QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.Inputs |
|
| QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.Options |
|
| QuantizedConv2DWithBiasSumAndRelu<V extends TNumber> |
The QuantizedConv2DWithBiasSumAndRelu operation
|
| QuantizedConv2DWithBiasSumAndRelu.Inputs |
|
| QuantizedConv2DWithBiasSumAndRelu.Options |
|
| QuantizedConv2DWithBiasSumAndReluAndRequantize<X extends TNumber> |
The QuantizedConv2DWithBiasSumAndReluAndRequantize operation
|
| QuantizedConv2DWithBiasSumAndReluAndRequantize.Inputs |
|
| QuantizedConv2DWithBiasSumAndReluAndRequantize.Options |
|
| QuantizedDepthwiseConv2D<V extends TNumber> |
Computes quantized depthwise Conv2D.
|
| QuantizedDepthwiseConv2D.Inputs |
|
| QuantizedDepthwiseConv2D.Options |
|
| QuantizedDepthwiseConv2DWithBias<V extends TNumber> |
Computes quantized depthwise Conv2D with Bias.
|
| QuantizedDepthwiseConv2DWithBias.Inputs |
|
| QuantizedDepthwiseConv2DWithBias.Options |
|
| QuantizedDepthwiseConv2DWithBiasAndRelu<V extends TNumber> |
Computes quantized depthwise Conv2D with Bias and Relu.
|
| QuantizedDepthwiseConv2DWithBiasAndRelu.Inputs |
|
| QuantizedDepthwiseConv2DWithBiasAndRelu.Options |
|
| QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize<W extends TNumber> |
Computes quantized depthwise Conv2D with Bias, Relu and Requantize.
|
| QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.Inputs |
|
| QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.Options |
|
| QuantizedInstanceNorm<T extends TNumber> |
Quantized Instance normalization.
|
| QuantizedInstanceNorm.Inputs<T extends TNumber> |
|
| QuantizedInstanceNorm.Options |
|
| QuantizedMatMul<V extends TNumber> |
Perform a quantized matrix multiplication of a by the matrix b.
|
| QuantizedMatMul.Inputs |
|
| QuantizedMatMul.Options |
|
| QuantizedMatMulWithBias<W extends TNumber> |
Performs a quantized matrix multiplication of a by the matrix b with bias
add.
|
| QuantizedMatMulWithBias.Inputs |
|
| QuantizedMatMulWithBias.Options |
|
| QuantizedMatMulWithBiasAndDequantize<W extends TNumber> |
The QuantizedMatMulWithBiasAndDequantize operation
|
| QuantizedMatMulWithBiasAndDequantize.Inputs |
|
| QuantizedMatMulWithBiasAndDequantize.Options |
|
| QuantizedMatMulWithBiasAndRelu<V extends TNumber> |
Perform a quantized matrix multiplication of a by the matrix b with bias
add and relu fusion.
|
| QuantizedMatMulWithBiasAndRelu.Inputs |
|
| QuantizedMatMulWithBiasAndRelu.Options |
|
| QuantizedMatMulWithBiasAndReluAndRequantize<W extends TNumber> |
Perform a quantized matrix multiplication of a by the matrix b with bias
add and relu and requantize fusion.
|
| QuantizedMatMulWithBiasAndReluAndRequantize.Inputs |
|
| QuantizedMatMulWithBiasAndReluAndRequantize.Options |
|
| QuantizedMatMulWithBiasAndRequantize<W extends TNumber> |
The QuantizedMatMulWithBiasAndRequantize operation
|
| QuantizedMatMulWithBiasAndRequantize.Inputs |
|
| QuantizedMatMulWithBiasAndRequantize.Options |
|
| QuantizedMaxPool<T extends TNumber> |
Produces the max pool of the input tensor for quantized types.
|
| QuantizedMaxPool.Inputs<T extends TNumber> |
|
| QuantizedMul<V extends TNumber> |
Returns x * y element-wise, working on quantized buffers.
|
| QuantizedMul.Inputs |
|
| QuantizeDownAndShrinkRange<U extends TNumber> |
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.
|
| QuantizeDownAndShrinkRange.Inputs |
|
| QuantizedRelu<U extends TNumber> |
Computes Quantized Rectified Linear: max(features, 0)
|
| QuantizedRelu.Inputs |
|
| QuantizedRelu6<U extends TNumber> |
Computes Quantized Rectified Linear 6: min(max(features, 0), 6)
|
| QuantizedRelu6.Inputs |
|
| QuantizedReluX<U extends TNumber> |
Computes Quantized Rectified Linear X: min(max(features, 0), max_value)
|
| QuantizedReluX.Inputs |
|
| QuantizedReshape<T extends TType> |
Reshapes a quantized tensor as per the Reshape op.
|
| QuantizedReshape.Inputs<T extends TType> |
|
| QuantizedResizeBilinear<T extends TNumber> |
Resize quantized images to size using quantized bilinear interpolation.
|
| QuantizedResizeBilinear.Inputs<T extends TNumber> |
|
| QuantizedResizeBilinear.Options |
|
| QueueClose |
Closes the given queue.
|
| QueueClose.Inputs |
|
| QueueClose.Options |
|
| QueueDequeue |
Dequeues a tuple of one or more tensors from the given queue.
|
| QueueDequeue.Inputs |
|
| QueueDequeue.Options |
|
| QueueDequeueMany |
Dequeues n tuples of one or more tensors from the given queue.
|
| QueueDequeueMany.Inputs |
|
| QueueDequeueMany.Options |
|
| QueueDequeueUpTo |
Dequeues n tuples of one or more tensors from the given queue.
|
| QueueDequeueUpTo.Inputs |
|
| QueueDequeueUpTo.Options |
|
| QueueEnqueue |
Enqueues a tuple of one or more tensors in the given queue.
|
| QueueEnqueue.Inputs |
|
| QueueEnqueue.Options |
|
| QueueEnqueueMany |
Enqueues zero or more tuples of one or more tensors in the given queue.
|
| QueueEnqueueMany.Inputs |
|
| QueueEnqueueMany.Options |
|
| QueueIsClosed |
Returns true if queue is closed.
|
| QueueIsClosed.Inputs |
|
| 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.
|
| QueueSize.Inputs |
|
| RaggedBincount<U extends TNumber> |
Counts the number of occurrences of each value in an integer array.
|
| RaggedBincount.Inputs<T extends TNumber,U extends TNumber> |
|
| RaggedBincount.Options |
|
| RaggedCountSparseOutput<U extends TNumber> |
Performs sparse-output bin counting for a ragged tensor input.
|
| RaggedCountSparseOutput.Inputs<U extends TNumber> |
|
| RaggedCountSparseOutput.Options |
|
| RaggedCross<T extends TType,U extends TNumber> |
Generates a feature cross from a list of tensors, and returns it as a
RaggedTensor.
|
| RaggedCross.Inputs |
|
| RaggedGather<T extends TNumber,U extends TType> |
Gather ragged slices from params axis 0 according to indices.
|
| RaggedGather.Inputs<T extends TNumber,U extends TType> |
|
| RaggedOps |
An API for building ragged operations as Ops |
| RaggedRange<U extends TNumber,T extends TNumber> |
Returns a RaggedTensor containing the specified sequences of numbers.
|
| RaggedRange.Inputs<T extends TNumber> |
|
| RaggedTensorFromVariant<T extends TNumber,U extends TType> |
Decodes a variant Tensor into a RaggedTensor.
|
| RaggedTensorFromVariant.Inputs |
|
| RaggedTensorToSparse<U extends TType> |
Converts a RaggedTensor into a SparseTensor with the same values.
|
| RaggedTensorToSparse.Inputs<U extends TType> |
|
| RaggedTensorToTensor<U extends TType> |
Create a dense tensor from a ragged tensor, possibly altering its shape.
|
| RaggedTensorToTensor.Inputs<U extends TType> |
|
| RaggedTensorToVariant |
Encodes a RaggedTensor into a variant Tensor.
|
| RaggedTensorToVariant.Inputs |
|
| RaggedTensorToVariantGradient<U extends TType> |
Helper used to compute the gradient for RaggedTensorToVariant.
|
| RaggedTensorToVariantGradient.Inputs |
|
| RandomCrop<T extends TNumber> |
Randomly crop image.
|
| RandomCrop.Inputs<T extends TNumber> |
|
| RandomCrop.Options |
|
| RandomDataset |
Creates a Dataset that returns pseudorandom numbers.
|
| RandomDataset |
Creates a Dataset that returns pseudorandom numbers.
|
| RandomDataset.Inputs |
|
| RandomDataset.Inputs |
|
| RandomDataset.Options |
|
| RandomGamma<U extends TNumber> |
Outputs random values from the Gamma distribution(s) described by alpha.
|
| RandomGamma.Inputs<U extends TNumber> |
|
| RandomGamma.Options |
|
| RandomGammaGrad<T extends TNumber> |
Computes the derivative of a Gamma random sample w.r.t.
|
| RandomGammaGrad.Inputs<T extends TNumber> |
|
| RandomIndexShuffle<T extends TNumber> |
Outputs the position of value in a permutation of [0, ..., max_index].
|
| RandomIndexShuffle.Inputs<T extends TNumber> |
|
| RandomOps |
An API for building random operations as Ops |
| RandomPoisson<V extends TNumber> |
Outputs random values from the Poisson distribution(s) described by rate.
|
| RandomPoisson.Inputs |
|
| RandomPoisson.Options |
|
| RandomShuffle<T extends TType> |
Randomly shuffles a tensor along its first dimension.
|
| RandomShuffle.Inputs<T extends TType> |
|
| RandomShuffle.Options |
|
| RandomShuffleQueue |
A queue that randomizes the order of elements.
|
| RandomShuffleQueue.Inputs |
|
| RandomShuffleQueue.Options |
|
| RandomStandardNormal<U extends TNumber> |
Outputs random values from a normal distribution.
|
| RandomStandardNormal.Inputs |
|
| RandomStandardNormal.Options |
|
| RandomUniform<U extends TNumber> |
Outputs random values from a uniform distribution.
|
| RandomUniform.Inputs |
|
| RandomUniform.Options |
|
| RandomUniformInt<U extends TNumber> |
Outputs random integers from a uniform distribution.
|
| RandomUniformInt.Inputs<U extends TNumber> |
|
| RandomUniformInt.Options |
|
| Range<T extends TNumber> |
Creates a sequence of numbers.
|
| Range.Inputs<T extends TNumber> |
|
| RangeDataset |
Creates a dataset with a range of values.
|
| RangeDataset.Inputs |
|
| RangeDataset.Options |
|
| Rank |
Returns the rank of a tensor.
|
| Rank.Inputs |
|
| RawCustomGradient |
A custom gradient for an op of unspecified type.
|
| RawOp |
A base class for Op implementations that are backed by a single Operation. |
| RawOpInputs<T extends RawOp> |
A base class for operation input accessors.
|
| 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.
|
| ReaderNumRecordsProduced.Inputs |
|
| ReaderNumWorkUnitsCompleted |
Returns the number of work units this Reader has finished processing.
|
| ReaderNumWorkUnitsCompleted.Inputs |
|
| ReaderRead |
Returns the next record (key, value pair) produced by a Reader.
|
| ReaderRead.Inputs |
|
| ReaderReadUpTo |
Returns up to num_records (key, value) pairs produced by a Reader.
|
| ReaderReadUpTo.Inputs |
|
| ReaderReset |
Restore a Reader to its initial clean state.
|
| ReaderReset.Inputs |
|
| ReaderRestoreState |
Restore a reader to a previously saved state.
|
| ReaderRestoreState.Inputs |
|
| ReaderSerializeState |
Produce a string tensor that encodes the state of a Reader.
|
| ReaderSerializeState.Inputs |
|
| ReadFile |
Reads and outputs the entire contents of the input filename.
|
| ReadFile.Inputs |
|
| ReadVariableOp<T extends TType> |
Reads the value of a variable.
|
| ReadVariableOp.Inputs |
|
| ReadVariableSplitND<T extends TType> |
Splits resource variable input tensor across all dimensions.
|
| ReadVariableSplitND.Inputs |
|
| ReadVariableSplitND.Options |
|
| Real<U extends TNumber> |
Returns the real part of a complex number.
|
| Real.Inputs |
|
| RealDiv<T extends TType> |
Returns x / y element-wise for real types.
|
| RealDiv.Inputs<T extends TType> |
|
| RebatchDataset |
Creates a dataset that changes the batch size.
|
| RebatchDataset.Inputs |
|
| RebatchDataset.Options |
|
| RebatchDatasetV2 |
Creates a dataset that changes the batch size.
|
| RebatchDatasetV2.Inputs |
|
| Reciprocal<T extends TType> |
Computes the reciprocal of x element-wise.
|
| Reciprocal.Inputs<T extends TType> |
|
| ReciprocalGrad<T extends TType> |
Computes the gradient for the inverse of x wrt its input.
|
| ReciprocalGrad.Inputs<T extends TType> |
|
| RecordInput |
Emits randomized records.
|
| RecordInput.Inputs |
|
| RecordInput.Options |
|
| 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.Inputs |
|
| Recv.Inputs |
|
| Recv.Options |
Optional attributes for Recv |
| RecvTPUEmbeddingActivations |
An op that receives embedding activations on the TPU.
|
| RecvTPUEmbeddingActivations.Inputs |
|
| Reduce<T extends TType> |
Wraps the XLA Reduce operator, documented at
https://www.tensorflow.org/performance/xla/operation_semantics#reduce .
|
| Reduce.Inputs<T extends TType> |
|
| ReduceAll |
Computes the "logical and" of elements across dimensions of a tensor.
|
| ReduceAll.Inputs |
|
| ReduceAll.Options |
|
| ReduceAny |
Computes the "logical or" of elements across dimensions of a tensor.
|
| ReduceAny.Inputs |
|
| ReduceAny.Options |
|
| ReduceDataset |
Reduces the input dataset to a singleton using a reduce function.
|
| ReduceDataset.Inputs |
|
| ReduceDataset.Options |
|
| ReduceJoin |
Joins a string Tensor across the given dimensions.
|
| ReduceJoin.Inputs |
|
| ReduceJoin.Options |
|
| ReduceMax<T extends TNumber> |
Computes the maximum of elements across dimensions of a tensor.
|
| ReduceMax.Inputs<T extends TNumber> |
|
| ReduceMax.Options |
|
| ReduceMin<T extends TNumber> |
Computes the minimum of elements across dimensions of a tensor.
|
| ReduceMin.Inputs<T extends TNumber> |
|
| ReduceMin.Options |
|
| ReduceProd<T extends TType> |
Computes the product of elements across dimensions of a tensor.
|
| ReduceProd.Inputs<T extends TType> |
|
| ReduceProd.Options |
|
| ReduceScatter<T extends TNumber> |
Wraps the XLA ReduceScatter operator
documented at https://www.tensorflow.org/xla/operation_semantics#reducescatter.
|
| ReduceScatter.Inputs<T extends TNumber> |
|
| ReduceSum<T extends TType> |
Computes the sum of elements across dimensions of a tensor.
|
| ReduceSum.Inputs<T extends TType> |
|
| ReduceSum.Options |
|
| ReduceWindow<T extends TType> |
Wraps the XLA ReduceWindow operator, documented at
https://www.tensorflow.org/performance/xla/operation_semantics#reducewindow .
|
| ReduceWindow.Inputs<T extends TType,U extends TNumber> |
|
| RefEnter<T extends TType> |
Creates or finds a child frame, and makes data available to the child frame.
|
| RefEnter.Inputs<T extends TType> |
|
| RefEnter.Options |
|
| RefExit<T extends TType> |
Exits the current frame to its parent frame.
|
| RefExit.Inputs<T extends TType> |
|
| RefIdentity<T extends TType> |
Return the same ref tensor as the input ref tensor.
|
| RefIdentity.Inputs<T extends TType> |
|
| RefMerge<T extends TType> |
Forwards the value of an available tensor from inputs to output.
|
| RefMerge.Inputs<T extends TType> |
|
| RefNextIteration<T extends TType> |
Makes its input available to the next iteration.
|
| RefNextIteration.Inputs<T extends TType> |
|
| RefSelect<T extends TType> |
Forwards the indexth element of inputs to output.
|
| RefSelect.Inputs<T extends TType> |
|
| RefSwitch<T extends TType> |
Forwards the ref tensor data to the output port determined by pred.
|
| RefSwitch.Inputs<T extends TType> |
|
| RegexFullMatch |
Check if the input matches the regex pattern.
|
| RegexFullMatch.Inputs |
|
| RegexReplace |
Replaces matches of the pattern regular expression in input with the
replacement string provided in rewrite.
|
| RegexReplace.Inputs |
|
| RegexReplace.Options |
|
| RegisterDataset |
Registers a dataset with the tf.data service.
|
| RegisterDataset.Inputs |
|
| RegisterDataset.Options |
|
| RegisteredGradient |
RegisteredGradient stores a gradient function that is registered in the
gradients library and used in the ops of a function in the function library.
|
| RegisteredGradient.Builder |
RegisteredGradient stores a gradient function that is registered in the
gradients library and used in the ops of a function in the function library.
|
| RegisteredGradientOrBuilder |
|
| RegisteredSaver |
Protobuf type tensorflow.RegisteredSaver
|
| RegisteredSaver.Builder |
Protobuf type tensorflow.RegisteredSaver
|
| RegisteredSaverOrBuilder |
|
| Relayout<T extends TType> |
The Relayout operation
|
| Relayout.Inputs<T extends TType> |
|
| Relu<T extends TNumber> |
Computes rectified linear: max(features, 0).
|
| Relu.Inputs<T extends TNumber> |
|
| Relu6<T extends TNumber> |
Computes rectified linear 6: min(max(features, 0), 6).
|
| Relu6.Inputs<T extends TNumber> |
|
| Relu6Grad<T extends TNumber> |
Computes rectified linear 6 gradients for a Relu6 operation.
|
| Relu6Grad.Inputs<T extends TNumber> |
|
| ReluGrad<T extends TNumber> |
Computes rectified linear gradients for a Relu operation.
|
| ReluGrad.Inputs<T extends TNumber> |
|
| RemoteCall |
Runs function f on a remote device indicated by target.
|
| RemoteCall.Inputs |
|
| 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 |
|
| RemoveDynamicDimensionSize<T extends TType> |
Inverse of XlaSetDynamicDimensionSize.
|
| RemoveDynamicDimensionSize.Inputs<T extends TType> |
|
| RepeatDataset |
Creates a dataset that emits the outputs of input_dataset count times.
|
| RepeatDataset.Inputs |
|
| RepeatDataset.Options |
|
| ReplicaId |
Replica ID.
|
| ReplicaId.Inputs |
|
| ReplicatedInput<T extends TType> |
Connects N inputs to an N-way replicated TPU computation.
|
| ReplicatedInput.Inputs<T extends TType> |
|
| ReplicatedInput.Options |
|
| ReplicatedOutput<T extends TType> |
Connects N outputs from an N-way replicated TPU computation.
|
| ReplicatedOutput.Inputs<T extends TType> |
|
| ReplicateMetadata |
Metadata indicating how the TPU computation should be replicated.
|
| ReplicateMetadata.Inputs |
|
| ReplicateMetadata.Options |
|
| RequantizationRange |
Computes a range that covers the actual values present in a quantized tensor.
|
| RequantizationRange.Inputs |
|
| RequantizationRangePerChannel |
Computes requantization range per channel.
|
| RequantizationRangePerChannel.Inputs |
|
| Requantize<U extends TNumber> |
Converts the quantized input tensor into a lower-precision output.
|
| Requantize.Inputs |
|
| RequantizePerChannel<U extends TNumber> |
Requantizes input with min and max values known per channel.
|
| RequantizePerChannel.Inputs |
|
| RequestedExitCode |
Protobuf type tensorflow.RequestedExitCode
|
| RequestedExitCode.Builder |
Protobuf type tensorflow.RequestedExitCode
|
| RequestedExitCodeOrBuilder |
|
| Reshape<T extends TType> |
Reshapes a tensor.
|
| Reshape.Inputs<T extends TType> |
|
| ResizeArea |
Resize images to size using area interpolation.
|
| ResizeArea.Inputs |
|
| ResizeArea.Options |
|
| ResizeBicubic |
Resize images to size using bicubic interpolation.
|
| ResizeBicubic.Inputs |
|
| ResizeBicubic.Options |
|
| ResizeBicubicGrad<T extends TNumber> |
Computes the gradient of bicubic interpolation.
|
| ResizeBicubicGrad.Inputs<T extends TNumber> |
|
| ResizeBicubicGrad.Options |
|
| ResizeBilinear |
Resize images to size using bilinear interpolation.
|
| ResizeBilinear.Inputs |
|
| ResizeBilinear.Options |
|
| ResizeBilinearGrad<T extends TNumber> |
Computes the gradient of bilinear interpolation.
|
| ResizeBilinearGrad.Inputs<T extends TNumber> |
|
| ResizeBilinearGrad.Options |
|
| ResizeNearestNeighbor<T extends TNumber> |
Resize images to size using nearest neighbor interpolation.
|
| ResizeNearestNeighbor.Inputs<T extends TNumber> |
|
| ResizeNearestNeighbor.Options |
|
| ResizeNearestNeighborGrad<T extends TNumber> |
Computes the gradient of nearest neighbor interpolation.
|
| ResizeNearestNeighborGrad.Inputs<T extends TNumber> |
|
| ResizeNearestNeighborGrad.Options |
|
| ResourceAccumulatorApplyGradient |
Applies a gradient to a given accumulator.
|
| ResourceAccumulatorApplyGradient.Inputs |
|
| ResourceAccumulatorNumAccumulated |
Returns the number of gradients aggregated in the given accumulators.
|
| ResourceAccumulatorNumAccumulated.Inputs |
|
| ResourceAccumulatorSetGlobalStep |
Updates the accumulator with a new value for global_step.
|
| ResourceAccumulatorSetGlobalStep.Inputs |
|
| ResourceAccumulatorTakeGradient<T extends TType> |
Extracts the average gradient in the given ConditionalAccumulator.
|
| ResourceAccumulatorTakeGradient.Inputs |
|
| ResourceApplyAdadelta |
Update '*var' according to the adadelta scheme.
|
| ResourceApplyAdadelta.Inputs<T extends TType> |
|
| ResourceApplyAdadelta.Options |
|
| ResourceApplyAdagrad |
Update '*var' according to the adagrad scheme.
|
| ResourceApplyAdagrad.Inputs<T extends TType> |
|
| ResourceApplyAdagrad.Options |
|
| ResourceApplyAdagradDa |
Update '*var' according to the proximal adagrad scheme.
|
| ResourceApplyAdagradDa.Inputs<T extends TType> |
|
| ResourceApplyAdagradDa.Options |
|
| ResourceApplyAdam |
Update '*var' according to the Adam algorithm.
|
| ResourceApplyAdam.Inputs<T extends TType> |
|
| ResourceApplyAdam.Options |
|
| ResourceApplyAdaMax |
Update '*var' according to the AdaMax algorithm.
|
| ResourceApplyAdaMax.Inputs<T extends TType> |
|
| ResourceApplyAdaMax.Options |
|
| ResourceApplyAdamWithAmsgrad |
Update '*var' according to the Adam algorithm.
|
| ResourceApplyAdamWithAmsgrad.Inputs<T extends TType> |
|
| ResourceApplyAdamWithAmsgrad.Options |
|
| ResourceApplyAddSign |
Update '*var' according to the AddSign update.
|
| ResourceApplyAddSign.Inputs<T extends TType> |
|
| ResourceApplyAddSign.Options |
|
| ResourceApplyCenteredRmsProp |
Update '*var' according to the centered RMSProp algorithm.
|
| ResourceApplyCenteredRmsProp.Inputs<T extends TType> |
|
| ResourceApplyCenteredRmsProp.Options |
|
| ResourceApplyFtrl |
Update '*var' according to the Ftrl-proximal scheme.
|
| ResourceApplyFtrl.Inputs<T extends TType> |
|
| ResourceApplyFtrl.Options |
|
| ResourceApplyGradientDescent |
Update '*var' by subtracting 'alpha' * 'delta' from it.
|
| ResourceApplyGradientDescent.Inputs<T extends TType> |
|
| ResourceApplyGradientDescent.Options |
|
| ResourceApplyKerasMomentum |
Update '*var' according to the momentum scheme.
|
| ResourceApplyKerasMomentum.Inputs<T extends TType> |
|
| ResourceApplyKerasMomentum.Options |
|
| ResourceApplyMomentum |
Update '*var' according to the momentum scheme.
|
| ResourceApplyMomentum.Inputs<T extends TType> |
|
| ResourceApplyMomentum.Options |
|
| ResourceApplyPowerSign |
Update '*var' according to the AddSign update.
|
| ResourceApplyPowerSign.Inputs<T extends TType> |
|
| ResourceApplyPowerSign.Options |
|
| ResourceApplyProximalAdagrad |
Update '*var' and '*accum' according to FOBOS with Adagrad learning rate.
|
| ResourceApplyProximalAdagrad.Inputs<T extends TType> |
|
| ResourceApplyProximalAdagrad.Options |
|
| ResourceApplyProximalGradientDescent |
Update '*var' as FOBOS algorithm with fixed learning rate.
|
| ResourceApplyProximalGradientDescent.Inputs<T extends TType> |
|
| ResourceApplyProximalGradientDescent.Options |
|
| ResourceApplyRmsProp |
Update '*var' according to the RMSProp algorithm.
|
| ResourceApplyRmsProp.Inputs<T extends TType> |
|
| ResourceApplyRmsProp.Options |
|
| ResourceConditionalAccumulator |
A conditional accumulator for aggregating gradients.
|
| ResourceConditionalAccumulator.Inputs |
|
| ResourceConditionalAccumulator.Options |
|
| ResourceCountUpTo<T extends TNumber> |
Increments variable pointed to by 'resource' until it reaches 'limit'.
|
| ResourceCountUpTo.Inputs |
|
| 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.Inputs |
|
| ResourceGather.Options |
|
| ResourceGatherNd<U extends TType> |
The ResourceGatherNd operation
|
| ResourceGatherNd.Inputs |
|
| 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.
|
| ResourceScatterAdd.Inputs |
|
| ResourceScatterDiv |
Divides sparse updates into the variable referenced by resource.
|
| ResourceScatterDiv.Inputs |
|
| ResourceScatterMax |
Reduces sparse updates into the variable referenced by resource using the max operation.
|
| ResourceScatterMax.Inputs |
|
| ResourceScatterMin |
Reduces sparse updates into the variable referenced by resource using the min operation.
|
| ResourceScatterMin.Inputs |
|
| ResourceScatterMul |
Multiplies sparse updates into the variable referenced by resource.
|
| ResourceScatterMul.Inputs |
|
| ResourceScatterNdAdd |
Applies sparse addition to individual values or slices in a Variable.
|
| ResourceScatterNdAdd.Inputs |
|
| ResourceScatterNdAdd.Options |
|
| ResourceScatterNdMax |
The ResourceScatterNdMax operation
|
| ResourceScatterNdMax.Inputs |
|
| ResourceScatterNdMax.Options |
|
| ResourceScatterNdMin |
The ResourceScatterNdMin operation
|
| ResourceScatterNdMin.Inputs |
|
| ResourceScatterNdMin.Options |
|
| ResourceScatterNdSub |
Applies sparse subtraction to individual values or slices in a Variable.
|
| ResourceScatterNdSub.Inputs |
|
| ResourceScatterNdSub.Options |
|
| ResourceScatterNdUpdate |
Applies sparse updates to individual values or slices within a given
variable according to indices.
|
| ResourceScatterNdUpdate.Inputs |
|
| ResourceScatterNdUpdate.Options |
|
| ResourceScatterSub |
Subtracts sparse updates from the variable referenced by resource.
|
| ResourceScatterSub.Inputs |
|
| ResourceScatterUpdate |
Assigns sparse updates to the variable referenced by resource.
|
| ResourceScatterUpdate.Inputs |
|
| ResourceSparseApplyAdadelta |
var: Should be from a Variable().
|
| ResourceSparseApplyAdadelta.Inputs<T extends TType> |
|
| ResourceSparseApplyAdadelta.Options |
|
| ResourceSparseApplyAdagrad |
Update relevant entries in '*var' and '*accum' according to the adagrad scheme.
|
| ResourceSparseApplyAdagrad.Inputs<T extends TType> |
|
| ResourceSparseApplyAdagrad.Options |
|
| ResourceSparseApplyAdagradDa |
Update entries in '*var' and '*accum' according to the proximal adagrad scheme.
|
| ResourceSparseApplyAdagradDa.Inputs<T extends TType> |
|
| ResourceSparseApplyAdagradDa.Options |
|
| ResourceSparseApplyAdagradV2 |
Update relevant entries in '*var' and '*accum' according to the adagrad scheme.
|
| ResourceSparseApplyAdagradV2.Inputs<T extends TType> |
|
| ResourceSparseApplyAdagradV2.Options |
|
| ResourceSparseApplyCenteredRmsProp |
Update '*var' according to the centered RMSProp algorithm.
|
| ResourceSparseApplyCenteredRmsProp.Inputs<T extends TType> |
|
| ResourceSparseApplyCenteredRmsProp.Options |
|
| ResourceSparseApplyFtrl |
Update relevant entries in '*var' according to the Ftrl-proximal scheme.
|
| ResourceSparseApplyFtrl.Inputs<T extends TType> |
|
| ResourceSparseApplyFtrl.Options |
|
| ResourceSparseApplyKerasMomentum |
Update relevant entries in '*var' and '*accum' according to the momentum scheme.
|
| ResourceSparseApplyKerasMomentum.Inputs<T extends TType> |
|
| ResourceSparseApplyKerasMomentum.Options |
|
| ResourceSparseApplyMomentum |
Update relevant entries in '*var' and '*accum' according to the momentum scheme.
|
| ResourceSparseApplyMomentum.Inputs<T extends TType> |
|
| ResourceSparseApplyMomentum.Options |
|
| ResourceSparseApplyProximalAdagrad |
Sparse update entries in '*var' and '*accum' according to FOBOS algorithm.
|
| ResourceSparseApplyProximalAdagrad.Inputs<T extends TType> |
|
| ResourceSparseApplyProximalAdagrad.Options |
|
| ResourceSparseApplyProximalGradientDescent |
Sparse update '*var' as FOBOS algorithm with fixed learning rate.
|
| ResourceSparseApplyProximalGradientDescent.Inputs<T extends TType> |
|
| ResourceSparseApplyProximalGradientDescent.Options |
|
| ResourceSparseApplyRmsProp |
Update '*var' according to the RMSProp algorithm.
|
| ResourceSparseApplyRmsProp.Inputs<T extends TType> |
|
| ResourceSparseApplyRmsProp.Options |
|
| ResourceStridedSliceAssign |
Assign value to the sliced l-value reference of ref.
|
| ResourceStridedSliceAssign.Inputs<T extends TNumber> |
|
| ResourceStridedSliceAssign.Options |
|
| Restore |
Restores tensors from a V2 checkpoint.
|
| Restore.Inputs |
|
| RestoreSlice<T extends TType> |
Restores a tensor from checkpoint files.
|
| RestoreSlice.Inputs |
|
| RestoreSlice.Options |
|
| Result |
|
| RetrieveAllTPUEmbeddingParameters |
An op that retrieves optimization parameters from embedding to host memory.
|
| RetrieveAllTPUEmbeddingParameters.Inputs |
|
| RetrieveTPUEmbeddingAdadeltaParameters |
Retrieve Adadelta embedding parameters.
|
| RetrieveTPUEmbeddingAdadeltaParameters.Inputs |
|
| RetrieveTPUEmbeddingAdadeltaParameters.Options |
|
| RetrieveTPUEmbeddingAdagradMomentumParameters |
Retrieve Adagrad Momentum embedding parameters.
|
| RetrieveTPUEmbeddingAdagradMomentumParameters.Inputs |
|
| RetrieveTPUEmbeddingAdagradMomentumParameters.Options |
|
| RetrieveTPUEmbeddingAdagradParameters |
Retrieve Adagrad embedding parameters.
|
| RetrieveTPUEmbeddingAdagradParameters.Inputs |
|
| RetrieveTPUEmbeddingAdagradParameters.Options |
|
| RetrieveTPUEmbeddingADAMParameters |
Retrieve ADAM embedding parameters.
|
| RetrieveTPUEmbeddingADAMParameters.Inputs |
|
| RetrieveTPUEmbeddingADAMParameters.Options |
|
| RetrieveTPUEmbeddingCenteredRMSPropParameters |
Retrieve centered RMSProp embedding parameters.
|
| RetrieveTPUEmbeddingCenteredRMSPropParameters.Inputs |
|
| RetrieveTPUEmbeddingCenteredRMSPropParameters.Options |
|
| RetrieveTPUEmbeddingFrequencyEstimatorParameters |
Retrieve frequency estimator embedding parameters.
|
| RetrieveTPUEmbeddingFrequencyEstimatorParameters.Inputs |
|
| RetrieveTPUEmbeddingFrequencyEstimatorParameters.Options |
|
| RetrieveTPUEmbeddingFTRLParameters |
Retrieve FTRL embedding parameters.
|
| RetrieveTPUEmbeddingFTRLParameters.Inputs |
|
| RetrieveTPUEmbeddingFTRLParameters.Options |
|
| RetrieveTPUEmbeddingMDLAdagradLightParameters |
Retrieve MDL Adagrad Light embedding parameters.
|
| RetrieveTPUEmbeddingMDLAdagradLightParameters.Inputs |
|
| RetrieveTPUEmbeddingMDLAdagradLightParameters.Options |
|
| RetrieveTPUEmbeddingMomentumParameters |
Retrieve Momentum embedding parameters.
|
| RetrieveTPUEmbeddingMomentumParameters.Inputs |
|
| RetrieveTPUEmbeddingMomentumParameters.Options |
|
| RetrieveTPUEmbeddingProximalAdagradParameters |
Retrieve proximal Adagrad embedding parameters.
|
| RetrieveTPUEmbeddingProximalAdagradParameters.Inputs |
|
| RetrieveTPUEmbeddingProximalAdagradParameters.Options |
|
| RetrieveTPUEmbeddingProximalYogiParameters |
The RetrieveTPUEmbeddingProximalYogiParameters operation
|
| RetrieveTPUEmbeddingProximalYogiParameters.Inputs |
|
| RetrieveTPUEmbeddingProximalYogiParameters.Options |
|
| RetrieveTPUEmbeddingRMSPropParameters |
Retrieve RMSProp embedding parameters.
|
| RetrieveTPUEmbeddingRMSPropParameters.Inputs |
|
| RetrieveTPUEmbeddingRMSPropParameters.Options |
|
| RetrieveTPUEmbeddingStochasticGradientDescentParameters |
Retrieve SGD embedding parameters.
|
| RetrieveTPUEmbeddingStochasticGradientDescentParameters.Inputs |
|
| RetrieveTPUEmbeddingStochasticGradientDescentParameters.Options |
|
| Reverse<T extends TType> |
Reverses specific dimensions of a tensor.
|
| Reverse.Inputs<T extends TType> |
|
| ReverseSequence<T extends TType> |
Reverses variable length slices.
|
| ReverseSequence.Inputs<T extends TType> |
|
| ReverseSequence.Options |
|
| RewriteDataset |
The RewriteDataset operation
|
| RewriteDataset.Inputs |
|
| 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 parameters
|
| RewriterConfig.CustomGraphOptimizer.Builder |
Message to describe custom graph optimizer and its parameters
|
| 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.
|
| Rfft.Inputs |
|
| Rfft2d<U extends TType> |
2D real-valued fast Fourier transform.
|
| Rfft2d.Inputs |
|
| Rfft3d<U extends TType> |
3D real-valued fast Fourier transform.
|
| Rfft3d.Inputs |
|
| RgbToHsv<T extends TNumber> |
Converts one or more images from RGB to HSV.
|
| RgbToHsv.Inputs<T extends TNumber> |
|
| RightShift<T extends TNumber> |
Elementwise computes the bitwise right-shift of x and y.
|
| RightShift.Inputs<T extends TNumber> |
|
| Rint<T extends TNumber> |
Returns element-wise integer closest to x.
|
| Rint.Inputs<T extends TNumber> |
|
| RiscAbs<T extends TNumber> |
The RiscAbs operation
|
| RiscAbs.Inputs<T extends TNumber> |
|
| RiscAdd<T extends TNumber> |
Returns x + y element-wise.
|
| RiscAdd.Inputs<T extends TNumber> |
|
| RiscBinaryArithmetic<T extends TNumber> |
The RiscBinaryArithmetic operation
|
| RiscBinaryArithmetic.Inputs<T extends TNumber> |
|
| RiscBinaryComparison |
The RiscBinaryComparison operation
|
| RiscBinaryComparison.Inputs<T extends TNumber> |
|
| RiscBitcast<U extends TType> |
The RiscBitcast operation
|
| RiscBitcast.Inputs |
|
| RiscBroadcast<T extends TType> |
The RiscBroadcast operation
|
| RiscBroadcast.Inputs<T extends TType> |
|
| RiscCast<U extends TType> |
The RiscCast operation
|
| RiscCast.Inputs |
|
| RiscCeil<T extends TNumber> |
The RiscCeil operation
|
| RiscCeil.Inputs<T extends TNumber> |
|
| RiscCholesky<T extends TNumber> |
The RiscCholesky operation
|
| RiscCholesky.Inputs<T extends TNumber> |
|
| RiscConcat<T extends TType> |
The RiscConcat operation
|
| RiscConcat.Inputs<T extends TType> |
|
| RiscCondition<U extends TNumber> |
The RiscCondition operation
|
| RiscCondition.Inputs<T extends TNumber> |
|
| RiscConv<T extends TNumber> |
The RiscConv operation
|
| RiscConv.Inputs<T extends TNumber> |
|
| RiscConv.Options |
|
| RiscCos<T extends TNumber> |
The RiscCos operation
|
| RiscCos.Inputs<T extends TNumber> |
|
| RiscDiv<T extends TNumber> |
The RiscDiv operation
|
| RiscDiv.Inputs<T extends TNumber> |
|
| RiscDot<T extends TNumber> |
The RiscDot operation
|
| RiscDot.Inputs<T extends TNumber> |
|
| RiscDot.Options |
|
| RiscExp<T extends TNumber> |
The RiscExp operation
|
| RiscExp.Inputs<T extends TNumber> |
|
| RiscFft<T extends TType> |
The RiscFft operation
|
| RiscFft.Inputs<T extends TType> |
|
| RiscFloor<T extends TNumber> |
The RiscFloor operation
|
| RiscFloor.Inputs<T extends TNumber> |
|
| RiscGather<T extends TType> |
The RiscGather operation
|
| RiscGather.Inputs<T extends TType> |
|
| RiscGather.Options |
|
| RiscImag<U extends TNumber> |
The RiscImag operation
|
| RiscImag.Inputs |
|
| RiscIsFinite |
The RiscIsFinite operation
|
| RiscIsFinite.Inputs |
|
| RiscLog<T extends TNumber> |
The RiscLog operation
|
| RiscLog.Inputs<T extends TNumber> |
|
| RiscLogicalAnd |
The RiscLogicalAnd operation
|
| RiscLogicalAnd.Inputs |
|
| RiscLogicalNot |
The RiscLogicalNot operation
|
| RiscLogicalNot.Inputs |
|
| RiscLogicalOr |
The RiscLogicalOr operation
|
| RiscLogicalOr.Inputs |
|
| RiscMax<T extends TNumber> |
Returns max(x, y) element-wise.
|
| RiscMax.Inputs<T extends TNumber> |
|
| RiscMin<T extends TNumber> |
The RiscMin operation
|
| RiscMin.Inputs<T extends TNumber> |
|
| RiscMul<T extends TNumber> |
The RiscMul operation
|
| RiscMul.Inputs<T extends TNumber> |
|
| RiscNeg<T extends TNumber> |
The RiscNeg operation
|
| RiscNeg.Inputs<T extends TNumber> |
|
| RiscPad<T extends TNumber> |
The RiscPad operation
|
| RiscPad.Inputs<T extends TNumber> |
|
| RiscPool<T extends TNumber> |
The RiscPool operation
|
| RiscPool.Inputs<T extends TNumber> |
|
| RiscPool.Options |
|
| RiscPow<T extends TNumber> |
The RiscPow operation
|
| RiscPow.Inputs<T extends TNumber> |
|
| RiscRandomUniform |
The RiscRandomUniform operation
|
| RiscRandomUniform.Inputs |
|
| RiscRandomUniform.Options |
|
| RiscReal<U extends TNumber> |
The RiscReal operation
|
| RiscReal.Inputs |
|
| RiscReduce<T extends TNumber> |
The RiscReduce operation
|
| RiscReduce.Inputs<T extends TNumber> |
|
| RiscRem<T extends TNumber> |
The RiscRem operation
|
| RiscRem.Inputs<T extends TNumber> |
|
| RiscReshape<T extends TNumber> |
The RiscReshape operation
|
| RiscReshape.Inputs<T extends TNumber> |
|
| RiscReverse<T extends TNumber> |
The RiscReverse operation
|
| RiscReverse.Inputs<T extends TNumber> |
|
| RiscScatter<U extends TNumber> |
The RiscScatter operation
|
| RiscScatter.Inputs<T extends TNumber,U extends TNumber> |
|
| RiscShape<U extends TNumber> |
The RiscShape operation
|
| RiscShape.Inputs |
|
| RiscSign<T extends TNumber> |
The RiscSign operation
|
| RiscSign.Inputs<T extends TNumber> |
|
| RiscSlice<T extends TNumber> |
The RiscSlice operation
|
| RiscSlice.Inputs<T extends TNumber,U extends TNumber> |
|
| RiscSort<T extends TNumber> |
The RiscSort operation
|
| RiscSort.Inputs<T extends TNumber> |
|
| RiscSqueeze<T extends TType> |
The RiscSqueeze operation
|
| RiscSqueeze.Inputs<T extends TType> |
|
| RiscSqueeze.Options |
|
| RiscSub<T extends TNumber> |
The RiscSub operation
|
| RiscSub.Inputs<T extends TNumber> |
|
| RiscTranspose<T extends TType> |
The RiscTranspose operation
|
| RiscTranspose.Inputs<T extends TType> |
|
| RiscTriangularSolve<T extends TNumber> |
The RiscTriangularSolve operation
|
| RiscTriangularSolve.Inputs<T extends TNumber> |
|
| RiscTriangularSolve.Options |
|
| RiscUnary<T extends TNumber> |
The RiscUnary operation
|
| RiscUnary.Inputs<T extends TNumber> |
|
| RiscWhile |
The RiscWhile operation
|
| RiscWhile.Inputs |
|
| RiscWhile.Options |
|
| RngBitGenerator<U extends TNumber> |
Stateless PRNG bit generator.
|
| RngBitGenerator.Inputs |
|
| RngReadAndSkip |
Advance the counter of a counter-based RNG.
|
| RngReadAndSkip.Inputs |
|
| RngSkip |
Advance the counter of a counter-based RNG.
|
| RngSkip.Inputs |
|
| Roll<T extends TType> |
Rolls the elements of a tensor along an axis.
|
| Roll.Inputs<T extends TType> |
|
| Round<T extends TType> |
Rounds the values of a tensor to the nearest integer, element-wise.
|
| Round.Inputs<T extends TType> |
|
| 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.
|
| Rsqrt.Inputs<T extends TType> |
|
| RsqrtGrad<T extends TType> |
Computes the gradient for the rsqrt of x wrt its input.
|
| RsqrtGrad.Inputs<T extends TType> |
|
| 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?
|
| RunOptionsOrBuilder |
|
| SampleDistortedBoundingBox<T extends TNumber> |
Generate a single randomly distorted bounding box for an image.
|
| SampleDistortedBoundingBox.Inputs<T extends TNumber> |
|
| SampleDistortedBoundingBox.Options |
|
| SamplingDataset |
Creates a dataset that takes a Bernoulli sample of the contents of another dataset.
|
| SamplingDataset.Inputs |
|
| Save |
Saves tensors in V2 checkpoint format.
|
| Save.Inputs |
|
| 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 |
|
| SaveDataset |
The SaveDatasetV2 operation
|
| SaveDataset.Inputs |
|
| SaveDataset.Options |
|
| 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.
|
| SaveSlices.Inputs |
|
| ScalarSummary |
Outputs a Summary protocol buffer with scalar values.
|
| ScalarSummary.Inputs |
|
| ScaleAndTranslate |
The ScaleAndTranslate operation
|
| ScaleAndTranslate.Inputs |
|
| ScaleAndTranslate.Options |
|
| ScaleAndTranslateGrad<T extends TNumber> |
The ScaleAndTranslateGrad operation
|
| ScaleAndTranslateGrad.Inputs<T extends TNumber> |
|
| ScaleAndTranslateGrad.Options |
|
| ScanDataset |
Creates a dataset successively reduces f over the elements of input_dataset.
|
| ScanDataset |
Creates a dataset successively reduces f over the elements of input_dataset.
|
| ScanDataset.Inputs |
|
| ScanDataset.Inputs |
|
| ScanDataset.Options |
|
| ScanDataset.Options |
|
| Scatter<T extends TType> |
Wraps the XLA Scatter operator documented at
https://www.tensorflow.org/xla/operation_semantics#scatter.
|
| Scatter.Inputs<T extends TType> |
|
| ScatterAdd<T extends TType> |
Adds sparse updates to a variable reference.
|
| ScatterAdd.Inputs<T extends TType> |
|
| ScatterAdd.Options |
|
| ScatterDiv<T extends TType> |
Divides a variable reference by sparse updates.
|
| ScatterDiv.Inputs<T extends TType> |
|
| ScatterDiv.Options |
|
| ScatterMax<T extends TNumber> |
Reduces sparse updates into a variable reference using the max operation.
|
| ScatterMax.Inputs<T extends TNumber> |
|
| ScatterMax.Options |
|
| ScatterMin<T extends TNumber> |
Reduces sparse updates into a variable reference using the min operation.
|
| ScatterMin.Inputs<T extends TNumber> |
|
| ScatterMin.Options |
|
| ScatterMul<T extends TType> |
Multiplies sparse updates into a variable reference.
|
| ScatterMul.Inputs<T extends TType> |
|
| ScatterMul.Options |
|
| ScatterNd<U extends TType> |
Scatters updates into a tensor of shape shape according to indices.
|
| ScatterNd.Inputs<T extends TNumber,U extends TType> |
|
| ScatterNdAdd<T extends TType> |
Applies sparse addition to individual values or slices in a Variable.
|
| ScatterNdAdd.Inputs<T extends TType> |
|
| ScatterNdAdd.Options |
|
| ScatterNdMax<T extends TType> |
Computes element-wise maximum.
|
| ScatterNdMax.Inputs<T extends TType> |
|
| ScatterNdMax.Options |
|
| ScatterNdMin<T extends TType> |
Computes element-wise minimum.
|
| ScatterNdMin.Inputs<T extends TType> |
|
| ScatterNdMin.Options |
|
| ScatterNdNonAliasingAdd<T extends TType> |
Applies sparse addition to input using individual values or slices
from updates according to indices indices.
|
| ScatterNdNonAliasingAdd.Inputs<T extends TType> |
|
| ScatterNdSub<T extends TType> |
Applies sparse subtraction to individual values or slices in a Variable.
|
| ScatterNdSub.Inputs<T extends TType> |
|
| ScatterNdSub.Options |
|
| ScatterNdUpdate<T extends TType> |
Applies sparse updates to individual values or slices within a given
variable according to indices.
|
| ScatterNdUpdate.Inputs<T extends TType> |
|
| ScatterNdUpdate.Options |
|
| ScatterSub<T extends TType> |
Subtracts sparse updates to a variable reference.
|
| ScatterSub.Inputs<T extends TType> |
|
| ScatterSub.Options |
|
| ScatterUpdate<T extends TType> |
Applies sparse updates to a variable reference.
|
| ScatterUpdate.Inputs<T extends TType> |
|
| ScatterUpdate.Options |
|
| 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.
|
| SdcaFprint.Inputs |
|
| SdcaOptimizer |
Distributed version of Stochastic Dual Coordinate Ascent (SDCA) optimizer for
linear models with L1 + L2 regularization.
|
| SdcaOptimizer.Inputs |
|
| SdcaOptimizer.Options |
|
| SdcaShrinkL1 |
Applies L1 regularization shrink step on the parameters.
|
| SdcaShrinkL1.Inputs |
|
| SegmentMax<T extends TNumber> |
Computes the maximum along segments of a tensor.
|
| SegmentMax.Inputs<T extends TNumber> |
|
| SegmentMean<T extends TType> |
Computes the mean along segments of a tensor.
|
| SegmentMean.Inputs<T extends TType> |
|
| SegmentMin<T extends TNumber> |
Computes the minimum along segments of a tensor.
|
| SegmentMin.Inputs<T extends TNumber> |
|
| SegmentProd<T extends TType> |
Computes the product along segments of a tensor.
|
| SegmentProd.Inputs<T extends TType> |
|
| SegmentSum<T extends TType> |
Computes the sum along segments of a tensor.
|
| SegmentSum.Inputs<T extends TType> |
|
| Select<T extends TType> |
The SelectV2 operation
|
| Select.Inputs<T extends TType> |
|
| SelectAndScatter<T extends TType> |
Wraps the XLA SelectAndScatter operator, documented at
https://www.tensorflow.org/performance/xla/operation_semantics#selectandscatter
.
|
| SelectAndScatter.Inputs<T extends TType,U extends TNumber> |
|
| 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.Inputs<T extends TType> |
|
| SelfAdjointEig.Inputs<T extends TType> |
|
| SelfAdjointEig.Options |
|
| Selu<T extends TNumber> |
Computes scaled exponential linear: scale * alpha * (exp(features) - 1)
if < 0, scale * features otherwise.
|
| Selu.Inputs<T extends TNumber> |
|
| SeluGrad<T extends TNumber> |
Computes gradients for the scaled exponential linear (Selu) operation.
|
| SeluGrad.Inputs<T extends TNumber> |
|
| Send |
Sends the named tensor from send_device to recv_device.
|
| Send |
Sends the named tensor to another XLA computation.
|
| Send.Inputs |
|
| Send.Inputs |
|
| Send.Options |
Optional attributes for Send |
| SendTPUEmbeddingGradients |
Performs gradient updates of embedding tables.
|
| SendTPUEmbeddingGradients.Inputs |
|
| SendTPUEmbeddingGradients.Options |
|
| SequenceExample |
Protobuf type tensorflow.SequenceExample
|
| SequenceExample.Builder |
Protobuf type tensorflow.SequenceExample
|
| SequenceExampleOrBuilder |
|
| SerializedDType |
Represents a serialized tf.dtypes.Dtype
|
| SerializedDType.Builder |
Represents a serialized tf.dtypes.Dtype
|
| SerializedDTypeOrBuilder |
|
| SerializeIterator |
Converts the given resource_handle representing an iterator to a variant tensor.
|
| SerializeIterator.Inputs |
|
| SerializeIterator.Options |
|
| SerializeManySparse<U extends TType> |
Serialize an N-minibatch SparseTensor into an [N, 3] Tensor object.
|
| SerializeManySparse.Inputs |
|
| SerializeSparse<U extends TType> |
Serialize a SparseTensor into a [3] Tensor object.
|
| SerializeSparse.Inputs |
|
| SerializeTensor |
Transforms a Tensor into a serialized TensorProto proto.
|
| SerializeTensor.Inputs |
|
| 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. |
| SessionFunction |
A callable function backed by a session.
|
| SessionInfo |
Description of the session when an op is run.
|
| SessionInfo.Builder |
Description of the session when an op is run.
|
| SessionInfoOrBuilder |
|
| 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.
|
| SetDiff1d.Inputs<T extends TType> |
|
| SetDynamicDimensionSize<T extends TType> |
Make a static dimension into a xla bounded dynamic dimension.
|
| SetDynamicDimensionSize.Inputs<T extends TType> |
|
| SetSize |
Number of unique elements along last dimension of input set.
|
| SetSize.Inputs |
|
| SetSize.Options |
|
| SetStatsAggregatorDataset |
The ExperimentalSetStatsAggregatorDataset operation
|
| SetStatsAggregatorDataset |
The SetStatsAggregatorDataset operation
|
| SetStatsAggregatorDataset.Inputs |
|
| SetStatsAggregatorDataset.Inputs |
|
| Shape<U extends TNumber> |
Returns the shape of a tensor.
|
| Shape_inference_func_TF_ShapeInferenceContext_TF_Status |
|
| Shape.Inputs |
|
| ShapeN<U extends TNumber> |
Returns shape of tensors.
|
| ShapeN.Inputs |
|
| ShapeOps |
An API for building shape operations as Ops |
| Shapes |
An operator providing methods on org.tensorflow.op.core.Shape tensors and 1d operands that
represent the dimensions of a shape.
|
| ShardDataset |
Creates a Dataset that includes only 1/num_shards of this dataset.
|
| ShardDataset.Inputs |
|
| ShardDataset.Options |
|
| ShardedFilename |
Generate a sharded filename.
|
| ShardedFilename.Inputs |
|
| ShardedFilespec |
Generate a glob pattern matching all sharded file names.
|
| ShardedFilespec.Inputs |
|
| Sharding<T extends TType> |
An op which shards the input based on the given sharding attribute.
|
| Sharding.Inputs<T extends TType> |
|
| Sharding.Options |
|
| ShuffleAndRepeatDataset |
The ShuffleAndRepeatDatasetV2 operation
|
| ShuffleAndRepeatDataset.Inputs |
|
| ShuffleAndRepeatDataset.Options |
|
| ShuffleDataset |
The ShuffleDatasetV3 operation
|
| ShuffleDataset.Inputs |
|
| ShuffleDataset.Options |
|
| ShutdownDistributedTPU |
Shuts down a running distributed TPU system.
|
| ShutdownDistributedTPU.Inputs |
|
| ShutdownTPUSystem |
An op that shuts down the TPU system.
|
| ShutdownTPUSystem.Inputs |
|
| Sigmoid<T extends TType> |
Computes sigmoid of x element-wise.
|
| Sigmoid.Inputs<T extends TType> |
|
| SigmoidGrad<T extends TType> |
Computes the gradient of the sigmoid of x wrt its input.
|
| SigmoidGrad.Inputs<T extends TType> |
|
| Sign<T extends TType> |
Returns an element-wise indication of the sign of a number.
|
| Sign.Inputs<T extends TType> |
|
| SignalOps |
An API for building signal operations as Ops |
| 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.
|
| Sin.Inputs<T extends TType> |
|
| Sinh<T extends TType> |
Computes hyperbolic sine of x element-wise.
|
| Sinh.Inputs<T extends TType> |
|
| Size<U extends TNumber> |
Returns the size of a tensor.
|
| Size.Inputs |
|
| SkipDataset |
Creates a dataset that skips count elements from the input_dataset.
|
| SkipDataset.Inputs |
|
| SkipDataset.Options |
|
| Skipgram |
Parses a text file and creates a batch of examples.
|
| Skipgram.Inputs |
|
| Skipgram.Options |
|
| SleepDataset |
The ExperimentalSleepDataset operation
|
| SleepDataset |
The SleepDataset operation
|
| SleepDataset.Inputs |
|
| SleepDataset.Inputs |
|
| Slice<T extends TType> |
Return a slice from 'input'.
|
| Slice.Inputs<T extends TType,U extends TNumber> |
|
| SlidingWindowDataset |
Creates a dataset that passes a sliding window over input_dataset.
|
| SlidingWindowDataset |
Creates a dataset that passes a sliding window over input_dataset.
|
| SlidingWindowDataset.Inputs |
|
| SlidingWindowDataset.Inputs |
|
| SlidingWindowDataset.Options |
|
| Snapshot<T extends TType> |
Returns a copy of the input tensor.
|
| SnapShot |
Protobuf type tensorflow.SnapShot
|
| SnapShot.Builder |
Protobuf type tensorflow.SnapShot
|
| Snapshot.Inputs<T extends TType> |
|
| SnapshotDataset |
Creates a dataset that will write to / read from a snapshot.
|
| SnapshotDataset.Inputs |
|
| SnapshotDataset.Options |
|
| SnapshotDatasetReader |
The SnapshotDatasetReader operation
|
| SnapshotDatasetReader.Inputs |
|
| SnapshotDatasetReader.Options |
|
| SnapshotMetadataRecord |
This stores the metadata information present in each snapshot record.
|
| SnapshotMetadataRecord.Builder |
This stores the metadata information present in each snapshot record.
|
| SnapshotMetadataRecordOrBuilder |
|
| SnapshotNestedDatasetReader |
The SnapshotNestedDatasetReader operation
|
| SnapshotNestedDatasetReader.Inputs |
|
| 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.
|
| SobolSample.Inputs |
|
| Softmax<T extends TNumber> |
Computes softmax activations.
|
| Softmax.Inputs<T extends TNumber> |
|
| SoftmaxCrossEntropyWithLogits<T extends TNumber> |
Computes softmax cross entropy cost and gradients to backpropagate.
|
| SoftmaxCrossEntropyWithLogits.Inputs<T extends TNumber> |
|
| Softplus<T extends TNumber> |
The Softplus operation
|
| Softplus.Inputs<T extends TNumber> |
|
| SoftplusGrad<T extends TNumber> |
Computes softplus gradients for a softplus operation.
|
| SoftplusGrad.Inputs<T extends TNumber> |
|
| Softsign<T extends TNumber> |
Computes softsign: features / (abs(features) + 1).
|
| Softsign.Inputs<T extends TNumber> |
|
| SoftsignGrad<T extends TNumber> |
Computes softsign gradients for a softsign operation.
|
| SoftsignGrad.Inputs<T extends TNumber> |
|
| Solve<T extends TType> |
Solves systems of linear equations.
|
| Solve.Inputs<T extends TType> |
|
| 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
.
|
| Sort.Inputs<T extends TType> |
|
| 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 |
|
| SourceLocation |
|
| SpaceToBatch<T extends TType> |
SpaceToBatch for 4-D tensors of type T.
|
| SpaceToBatch.Inputs<T extends TType> |
|
| SpaceToBatchNd<T extends TType> |
SpaceToBatch for N-D tensors of type T.
|
| SpaceToBatchNd.Inputs<T extends TType> |
|
| SpaceToDepth<T extends TType> |
SpaceToDepth for tensors of type T.
|
| SpaceToDepth.Inputs<T extends TType> |
|
| SpaceToDepth.Options |
|
| SparseAccumulatorApplyGradient |
Applies a sparse gradient to a given accumulator.
|
| SparseAccumulatorApplyGradient.Inputs |
|
| SparseAccumulatorTakeGradient<T extends TType> |
Extracts the average sparse gradient in a SparseConditionalAccumulator.
|
| SparseAccumulatorTakeGradient.Inputs |
|
| SparseAdd<T extends TType> |
Adds two SparseTensor objects to produce another SparseTensor.
|
| SparseAdd.Inputs<T extends TType> |
|
| SparseAddGrad<T extends TType> |
The gradient operator for the SparseAdd op.
|
| SparseAddGrad.Inputs<T extends TType> |
|
| SparseApplyAdadelta<T extends TType> |
var: Should be from a Variable().
|
| SparseApplyAdadelta.Inputs<T extends TType> |
|
| SparseApplyAdadelta.Options |
|
| SparseApplyAdagrad<T extends TType> |
Update relevant entries in '*var' and '*accum' according to the adagrad scheme.
|
| SparseApplyAdagrad.Inputs<T extends TType> |
|
| SparseApplyAdagrad.Options |
|
| SparseApplyAdagradDa<T extends TType> |
Update entries in '*var' and '*accum' according to the proximal adagrad scheme.
|
| SparseApplyAdagradDa.Inputs<T extends TType> |
|
| SparseApplyAdagradDa.Options |
|
| SparseApplyCenteredRmsProp<T extends TType> |
Update '*var' according to the centered RMSProp algorithm.
|
| SparseApplyCenteredRmsProp.Inputs<T extends TType> |
|
| SparseApplyCenteredRmsProp.Options |
|
| SparseApplyFtrl<T extends TType> |
Update relevant entries in '*var' according to the Ftrl-proximal scheme.
|
| SparseApplyFtrl.Inputs<T extends TType> |
|
| SparseApplyFtrl.Options |
|
| SparseApplyMomentum<T extends TType> |
Update relevant entries in '*var' and '*accum' according to the momentum scheme.
|
| SparseApplyMomentum.Inputs<T extends TType> |
|
| SparseApplyMomentum.Options |
|
| SparseApplyProximalAdagrad<T extends TType> |
Sparse update entries in '*var' and '*accum' according to FOBOS algorithm.
|
| SparseApplyProximalAdagrad.Inputs<T extends TType> |
|
| SparseApplyProximalAdagrad.Options |
|
| SparseApplyProximalGradientDescent<T extends TType> |
Sparse update '*var' as FOBOS algorithm with fixed learning rate.
|
| SparseApplyProximalGradientDescent.Inputs<T extends TType> |
|
| SparseApplyProximalGradientDescent.Options |
|
| SparseApplyRmsProp<T extends TType> |
Update '*var' according to the RMSProp algorithm.
|
| SparseApplyRmsProp.Inputs<T extends TType> |
|
| SparseApplyRmsProp.Options |
|
| SparseBincount<U extends TNumber> |
Counts the number of occurrences of each value in an integer array.
|
| SparseBincount.Inputs<T extends TNumber,U extends TNumber> |
|
| SparseBincount.Options |
|
| SparseConcat<T extends TType> |
Concatenates a list of SparseTensor along the specified dimension.
|
| SparseConcat.Inputs<T extends TType> |
|
| SparseConditionalAccumulator |
A conditional accumulator for aggregating sparse gradients.
|
| SparseConditionalAccumulator.Inputs |
|
| SparseConditionalAccumulator.Options |
|
| SparseCountSparseOutput<U extends TNumber> |
Performs sparse-output bin counting for a sparse tensor input.
|
| SparseCountSparseOutput.Inputs<U extends TNumber> |
|
| SparseCountSparseOutput.Options |
|
| SparseCross |
Generates sparse cross from a list of sparse and dense tensors.
|
| SparseCross.Inputs |
|
| SparseCrossHashed |
Generates sparse cross from a list of sparse and dense tensors.
|
| SparseCrossHashed.Inputs |
|
| 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.
|
| SparseDenseCwiseAdd.Inputs<T extends TType> |
|
| SparseDenseCwiseDiv<T extends TType> |
Component-wise divides a SparseTensor by a dense Tensor.
|
| SparseDenseCwiseDiv.Inputs<T extends TType> |
|
| SparseDenseCwiseMul<T extends TType> |
Component-wise multiplies a SparseTensor by a dense Tensor.
|
| SparseDenseCwiseMul.Inputs<T extends TType> |
|
| SparseFillEmptyRows<T extends TType> |
Fills empty rows in the input 2-D SparseTensor with a default value.
|
| SparseFillEmptyRows.Inputs<T extends TType> |
|
| SparseFillEmptyRowsGrad<T extends TType> |
The gradient of SparseFillEmptyRows.
|
| SparseFillEmptyRowsGrad.Inputs<T extends TType> |
|
| SparseMatMul |
Multiply matrix "a" by matrix "b".
|
| SparseMatMul.Inputs |
|
| SparseMatMul.Options |
|
| SparseMatrixAdd |
Sparse addition of two CSR matrices, C = alpha * A + beta * B.
|
| SparseMatrixAdd.Inputs<T extends TType> |
|
| SparseMatrixMatMul<T extends TType> |
Matrix-multiplies a sparse matrix with a dense matrix.
|
| SparseMatrixMatMul.Inputs<T extends TType> |
|
| SparseMatrixMatMul.Options |
|
| SparseMatrixMul |
Element-wise multiplication of a sparse matrix with a dense tensor.
|
| SparseMatrixMul.Inputs |
|
| SparseMatrixNNZ |
Returns the number of nonzeroes of sparse_matrix.
|
| SparseMatrixNNZ.Inputs |
|
| SparseMatrixOrderingAMD |
Computes the Approximate Minimum Degree (AMD) ordering of input.
|
| SparseMatrixOrderingAMD.Inputs |
|
| SparseMatrixSoftmax |
Calculates the softmax of a CSRSparseMatrix.
|
| SparseMatrixSoftmax.Inputs |
|
| SparseMatrixSoftmaxGrad |
Calculates the gradient of the SparseMatrixSoftmax op.
|
| SparseMatrixSoftmaxGrad.Inputs |
|
| SparseMatrixSparseCholesky |
Computes the sparse Cholesky decomposition of input.
|
| SparseMatrixSparseCholesky.Inputs |
|
| SparseMatrixSparseMatMul |
Sparse-matrix-multiplies two CSR matrices a and b.
|
| SparseMatrixSparseMatMul.Inputs |
|
| SparseMatrixSparseMatMul.Options |
|
| SparseMatrixTranspose |
Transposes the inner (matrix) dimensions of a CSRSparseMatrix.
|
| SparseMatrixTranspose.Inputs |
|
| SparseMatrixTranspose.Options |
|
| SparseMatrixZeros |
Creates an all-zeros CSRSparseMatrix with shape dense_shape.
|
| SparseMatrixZeros.Inputs |
|
| SparseOps |
An API for building sparse operations as Ops |
| SparseReduceMax<T extends TNumber> |
Computes the max of elements across dimensions of a SparseTensor.
|
| SparseReduceMax.Inputs<T extends TNumber> |
|
| SparseReduceMax.Options |
|
| SparseReduceMaxSparse<T extends TNumber> |
Computes the max of elements across dimensions of a SparseTensor.
|
| SparseReduceMaxSparse.Inputs<T extends TNumber> |
|
| SparseReduceMaxSparse.Options |
|
| SparseReduceSum<T extends TType> |
Computes the sum of elements across dimensions of a SparseTensor.
|
| SparseReduceSum.Inputs<T extends TType> |
|
| SparseReduceSum.Options |
|
| SparseReduceSumSparse<T extends TType> |
Computes the sum of elements across dimensions of a SparseTensor.
|
| SparseReduceSumSparse.Inputs<T extends TType> |
|
| SparseReduceSumSparse.Options |
|
| SparseReorder<T extends TType> |
Reorders a SparseTensor into the canonical, row-major ordering.
|
| SparseReorder.Inputs<T extends TType> |
|
| SparseReshape |
Reshapes a SparseTensor to represent values in a new dense shape.
|
| SparseReshape.Inputs |
|
| SparseSegmentMean<T extends TNumber> |
Computes the mean along sparse segments of a tensor.
|
| SparseSegmentMean.Inputs<T extends TNumber> |
|
| SparseSegmentMeanGrad<T extends TNumber> |
Computes gradients for SparseSegmentMean.
|
| SparseSegmentMeanGrad.Inputs<T extends TNumber> |
|
| SparseSegmentMeanWithNumSegments<T extends TNumber> |
Computes the mean along sparse segments of a tensor.
|
| SparseSegmentMeanWithNumSegments.Inputs<T extends TNumber> |
|
| SparseSegmentSqrtN<T extends TNumber> |
Computes the sum along sparse segments of a tensor divided by the sqrt of N.
|
| SparseSegmentSqrtN.Inputs<T extends TNumber> |
|
| SparseSegmentSqrtNGrad<T extends TNumber> |
Computes gradients for SparseSegmentSqrtN.
|
| SparseSegmentSqrtNGrad.Inputs<T extends TNumber> |
|
| SparseSegmentSqrtNWithNumSegments<T extends TNumber> |
Computes the sum along sparse segments of a tensor divided by the sqrt of N.
|
| SparseSegmentSqrtNWithNumSegments.Inputs<T extends TNumber> |
|
| SparseSegmentSum<T extends TNumber> |
Computes the sum along sparse segments of a tensor.
|
| SparseSegmentSum.Inputs<T extends TNumber> |
|
| SparseSegmentSumGrad<T extends TNumber> |
Computes gradients for SparseSegmentSum.
|
| SparseSegmentSumGrad.Inputs<T extends TNumber> |
|
| SparseSegmentSumWithNumSegments<T extends TNumber> |
Computes the sum along sparse segments of a tensor.
|
| SparseSegmentSumWithNumSegments.Inputs<T extends TNumber> |
|
| SparseSlice<T extends TType> |
Slice a SparseTensor based on the start and size.
|
| SparseSlice.Inputs<T extends TType> |
|
| SparseSliceGrad<T extends TType> |
The gradient operator for the SparseSlice op.
|
| SparseSliceGrad.Inputs<T extends TType> |
|
| SparseSoftmax<T extends TNumber> |
Applies softmax to a batched N-D SparseTensor.
|
| SparseSoftmax.Inputs<T extends TNumber> |
|
| SparseSoftmaxCrossEntropyWithLogits<T extends TNumber> |
Computes softmax cross entropy cost and gradients to backpropagate.
|
| SparseSoftmaxCrossEntropyWithLogits.Inputs<T extends TNumber> |
|
| SparseSparseMaximum<T extends TNumber> |
Returns the element-wise max of two SparseTensors.
|
| SparseSparseMaximum.Inputs<T extends TNumber> |
|
| SparseSparseMinimum<T extends TType> |
Returns the element-wise min of two SparseTensors.
|
| SparseSparseMinimum.Inputs<T extends TType> |
|
| SparseSplit<T extends TType> |
Split a SparseTensor into num_split tensors along one dimension.
|
| SparseSplit.Inputs<T extends TType> |
|
| SparseTensor<T extends TType> |
A virtual type of Tensor composed of three dense tensors (indices, values and dimensions)
used to represent the sparse data into a multi-dimensional dense space. |
| SparseTensorDenseAdd<U extends TType> |
Adds up a SparseTensor and a dense Tensor, producing a dense Tensor.
|
| SparseTensorDenseAdd.Inputs<T extends TNumber,U extends TType> |
|
| SparseTensorDenseMatMul<U extends TType> |
Multiply SparseTensor (of rank 2) "A" by dense matrix "B".
|
| SparseTensorDenseMatMul.Inputs<U extends TType> |
|
| SparseTensorDenseMatMul.Options |
|
| SparseTensorSliceDataset |
Creates a dataset that splits a SparseTensor into elements row-wise.
|
| SparseTensorSliceDataset.Inputs |
|
| SparseTensorToCSRSparseMatrix |
Converts a SparseTensor to a (possibly batched) CSRSparseMatrix.
|
| SparseTensorToCSRSparseMatrix.Inputs |
|
| SparseToDense<U extends TType> |
Converts a sparse representation into a dense tensor.
|
| SparseToDense.Inputs<T extends TNumber,U extends TType> |
|
| SparseToDense.Options |
|
| SparseToSparseSetOperation<T extends TType> |
Applies set operation along last dimension of 2 SparseTensor inputs.
|
| SparseToSparseSetOperation.Inputs<T extends TType> |
|
| SparseToSparseSetOperation.Options |
|
| Spence<T extends TNumber> |
The Spence operation
|
| Spence.Inputs<T extends TNumber> |
|
| Split<T extends TType> |
Splits a tensor into num_split tensors along one dimension.
|
| Split.Inputs<T extends TType> |
|
| SplitND<T extends TType> |
Splits input tensor across all dimensions.
|
| SplitND.Inputs<T extends TType> |
|
| SplitND.Options |
|
| SplitV<T extends TType> |
Splits a tensor into num_split tensors along one dimension.
|
| SplitV.Inputs<T extends TType> |
|
| SpmdFullToShardShape<T extends TType> |
An op used by XLA SPMD partitioner to switch from automatic partitioning to
manual partitioning.
|
| SpmdFullToShardShape.Inputs<T extends TType> |
|
| SpmdFullToShardShape.Options |
|
| SpmdShardToFullShape<T extends TType> |
An op used by XLA SPMD partitioner to switch from manual partitioning to
automatic partitioning.
|
| SpmdShardToFullShape.Inputs<T extends TType> |
|
| SpmdShardToFullShape.Options |
|
| 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.
|
| SqlDataset.Inputs |
|
| SqlDataset.Inputs |
|
| Sqrt<T extends TType> |
Computes square root of x element-wise.
|
| Sqrt.Inputs<T extends TType> |
|
| SqrtGrad<T extends TType> |
Computes the gradient for the sqrt of x wrt its input.
|
| SqrtGrad.Inputs<T extends TType> |
|
| Sqrtm<T extends TType> |
Computes the matrix square root of one or more square matrices:
matmul(sqrtm(A), sqrtm(A)) = A
|
| Sqrtm.Inputs<T extends TType> |
|
| Square<T extends TType> |
Computes square of x element-wise.
|
| Square.Inputs<T extends TType> |
|
| SquaredDifference<T extends TType> |
Returns conj(x - y)(x - y) element-wise.
|
| SquaredDifference.Inputs<T extends TType> |
|
| Squeeze<T extends TType> |
Removes dimensions of size 1 from the shape of a tensor.
|
| Squeeze.Inputs<T extends TType> |
|
| Squeeze.Options |
|
| Stack<T extends TType> |
Packs a list of N rank-R tensors into one rank-(R+1) tensor.
|
| Stack.Inputs<T extends TType> |
|
| 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.Inputs |
|
| Stage.Options |
Optional attributes for Stage |
| StageClear |
Op removes all elements in the underlying container.
|
| StageClear.Inputs |
|
| StageClear.Options |
|
| StagePeek |
Op peeks at the values at the specified index.
|
| StagePeek.Inputs |
|
| StagePeek.Options |
|
| StageSize |
Op returns the number of elements in the underlying container.
|
| StageSize.Inputs |
|
| StageSize.Options |
|
| StatefulCase |
An n-way switch statement which calls a single branch function.
|
| StatefulCase.Inputs |
|
| StatefulIf |
output = cond ? then_branch(input) : else_branch(input)
|
| StatefulIf.Inputs |
|
| StatefulPartitionedCall |
returns f(inputs), where f's body is placed and partitioned.
|
| StatefulPartitionedCall.Inputs |
|
| StatefulRandomBinomial<V extends TNumber> |
The StatefulRandomBinomial operation
|
| StatefulRandomBinomial.Inputs<U extends TNumber> |
|
| StatefulStandardNormal<U extends TType> |
Outputs random values from a normal distribution.
|
| StatefulStandardNormal.Inputs |
|
| StatefulTruncatedNormal<U extends TType> |
Outputs random values from a truncated normal distribution.
|
| StatefulTruncatedNormal.Inputs |
|
| StatefulUniform<U extends TType> |
Outputs random values from a uniform distribution.
|
| StatefulUniform.Inputs |
|
| StatefulUniformFullInt<U extends TType> |
Outputs random integers from a uniform distribution.
|
| StatefulUniformFullInt.Inputs |
|
| StatefulUniformInt<U extends TType> |
Outputs random integers from a uniform distribution.
|
| StatefulUniformInt.Inputs<U extends TType> |
|
| StatefulWhile |
output = input; While (Cond(output)) { output = Body(output) }
|
| StatefulWhile.Inputs |
|
| StatelessCase |
An n-way switch statement which calls a single branch function.
|
| StatelessCase.Inputs |
|
| StatelessIf |
output = cond ? then_branch(input) : else_branch(input)
|
| StatelessIf.Inputs |
|
| StatelessMultinomial<V extends TNumber> |
Draws samples from a multinomial distribution.
|
| StatelessMultinomial.Inputs |
|
| StatelessParameterizedTruncatedNormal<V extends TNumber> |
The StatelessParameterizedTruncatedNormal operation
|
| StatelessParameterizedTruncatedNormal.Inputs<V extends TNumber> |
|
| StatelessPartitionedCall |
returns f(inputs), where f's body is placed and partitioned.
|
| StatelessPartitionedCall.Inputs |
|
| StatelessRandomBinomial<W extends TNumber> |
Outputs deterministic pseudorandom random numbers from a binomial distribution.
|
| StatelessRandomBinomial.Inputs<V extends TNumber> |
|
| StatelessRandomGamma<V extends TNumber> |
Outputs deterministic pseudorandom random numbers from a gamma distribution.
|
| StatelessRandomGamma.Inputs<V extends TNumber> |
|
| StatelessRandomGetAlg |
Picks the best counter-based RNG algorithm based on device.
|
| StatelessRandomGetAlg.Inputs |
|
| StatelessRandomGetKeyCounter |
Scrambles seed into key and counter, using the best algorithm based on device.
|
| StatelessRandomGetKeyCounter.Inputs |
|
| StatelessRandomGetKeyCounterAlg |
Picks the best algorithm based on device, and scrambles seed into key and counter.
|
| StatelessRandomGetKeyCounterAlg.Inputs |
|
| StatelessRandomNormal<V extends TNumber> |
Outputs deterministic pseudorandom values from a normal distribution.
|
| StatelessRandomNormal.Inputs |
|
| StatelessRandomNormalV2<U extends TNumber> |
Outputs deterministic pseudorandom values from a normal distribution.
|
| StatelessRandomNormalV2.Inputs |
|
| StatelessRandomPoisson<W extends TNumber> |
Outputs deterministic pseudorandom random numbers from a Poisson distribution.
|
| StatelessRandomPoisson.Inputs |
|
| StatelessRandomUniform<V extends TNumber> |
Outputs deterministic pseudorandom random values from a uniform distribution.
|
| StatelessRandomUniform.Inputs |
|
| StatelessRandomUniformFullInt<V extends TNumber> |
Outputs deterministic pseudorandom random integers from a uniform distribution.
|
| StatelessRandomUniformFullInt.Inputs |
|
| StatelessRandomUniformFullIntV2<U extends TNumber> |
Outputs deterministic pseudorandom random integers from a uniform distribution.
|
| StatelessRandomUniformFullIntV2.Inputs |
|
| StatelessRandomUniformInt<V extends TNumber> |
Outputs deterministic pseudorandom random integers from a uniform distribution.
|
| StatelessRandomUniformInt.Inputs<V extends TNumber> |
|
| StatelessRandomUniformIntV2<U extends TNumber> |
Outputs deterministic pseudorandom random integers from a uniform distribution.
|
| StatelessRandomUniformIntV2.Inputs<U extends TNumber> |
|
| StatelessRandomUniformV2<U extends TNumber> |
Outputs deterministic pseudorandom random values from a uniform distribution.
|
| StatelessRandomUniformV2.Inputs |
|
| StatelessSampleDistortedBoundingBox<T extends TNumber> |
Generate a randomly distorted bounding box for an image deterministically.
|
| StatelessSampleDistortedBoundingBox.Inputs<T extends TNumber> |
|
| StatelessSampleDistortedBoundingBox.Options |
|
| StatelessShuffle<T extends TType> |
Randomly and deterministically shuffles a tensor along its first dimension.
|
| StatelessShuffle.Inputs<T extends TType> |
|
| StatelessTruncatedNormal<V extends TNumber> |
Outputs deterministic pseudorandom values from a truncated normal distribution.
|
| StatelessTruncatedNormal.Inputs |
|
| StatelessTruncatedNormalV2<U extends TNumber> |
Outputs deterministic pseudorandom values from a truncated normal distribution.
|
| StatelessTruncatedNormalV2.Inputs |
|
| StatelessWhile |
output = input; While (Cond(output)) { output = Body(output) }
|
| StatelessWhile.Inputs |
|
| StaticRegexFullMatch |
Check if the input matches the regex pattern.
|
| StaticRegexFullMatch.Inputs |
|
| StaticRegexReplace |
Replaces the match of pattern in input with rewrite.
|
| StaticRegexReplace.Inputs |
|
| StaticRegexReplace.Options |
|
| StatsAggregatorHandle |
Creates a statistics manager resource.
|
| StatsAggregatorHandle |
The StatsAggregatorHandleV2 operation
|
| StatsAggregatorHandle.Inputs |
|
| StatsAggregatorHandle.Inputs |
|
| StatsAggregatorHandle.Options |
|
| StatsAggregatorHandle.Options |
|
| StatsAggregatorSetSummaryWriter |
Set a summary_writer_interface to record statistics using given stats_aggregator.
|
| StatsAggregatorSetSummaryWriter.Inputs |
|
| 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.
|
| StatsAggregatorSummary.Inputs |
|
| StatsAggregatorSummary.Inputs |
|
| Status |
|
| Status.DerivedStatus |
If included as a payload, this message flags the Status to be a "derived"
Status.
|
| Status.DerivedStatus.Builder |
If included as a payload, this message flags the Status to be a "derived"
Status.
|
| Status.DerivedStatusOrBuilder |
|
| Status.StackTracePayload |
If included as a payload, this message contains associated source location
for the error Status.
|
| Status.StackTracePayload.Builder |
If included as a payload, this message contains associated source location
for the error Status.
|
| Status.StackTracePayload.StackFrame |
Protobuf type tensorflow.StackTracePayload.StackFrame
|
| Status.StackTracePayload.StackFrame.Builder |
Protobuf type tensorflow.StackTracePayload.StackFrame
|
| Status.StackTracePayload.StackFrameOrBuilder |
|
| Status.StackTracePayloadOrBuilder |
|
| StepStats |
Protobuf type tensorflow.StepStats
|
| StepStats.Builder |
Protobuf type tensorflow.StepStats
|
| StepStatsOrBuilder |
|
| StepStatsProtos |
|
| StopGradient<T extends TType> |
Stops gradient computation.
|
| StopGradient.Inputs<T extends TType> |
|
| StridedSlice<T extends TType> |
Return a strided slice from input.
|
| StridedSlice.Inputs<T extends TType,U extends TNumber> |
|
| StridedSlice.Options |
|
| StridedSliceAssign<T extends TType> |
Assign value to the sliced l-value reference of ref.
|
| StridedSliceAssign.Inputs<T extends TType,U extends TNumber> |
|
| StridedSliceAssign.Options |
|
| StridedSliceGrad<U extends TType> |
Returns the gradient of StridedSlice.
|
| StridedSliceGrad.Inputs<T extends TNumber,U extends TType> |
|
| StridedSliceGrad.Options |
|
| StridedSliceHelper |
Helper endpoint methods for Python like indexing.
|
| StringFormat |
Formats a string template using a list of tensors.
|
| StringFormat.Inputs |
|
| StringFormat.Options |
|
| StringLength |
String lengths of input.
|
| StringLength.Inputs |
|
| StringLength.Options |
|
| StringNGrams<T extends TNumber> |
Creates ngrams from ragged string data.
|
| StringNGrams.Inputs<T extends TNumber> |
|
| StringsOps |
An API for building strings operations as Ops |
| StringSplit |
Split elements of source based on sep into a SparseTensor.
|
| StringSplit.Inputs |
|
| StringSplit.Options |
|
| Strip |
Strip leading and trailing whitespaces from the Tensor.
|
| Strip.Inputs |
|
| 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.
|
| Sub.Inputs<T extends TType> |
|
| Substr |
Return substrings from Tensor of strings.
|
| Substr.Inputs<T extends TNumber> |
|
| Substr.Options |
Optional attributes for Substr |
| Sum<T extends TType> |
Computes the sum of elements across dimensions of a tensor.
|
| Sum.Inputs<T extends TType> |
|
| 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 data
|
| SummaryDescription.Builder |
Metadata associated with a series of Summary data
|
| 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 |
|
| SummaryOps |
An API for building summary operations as Ops |
| SummaryOrBuilder |
|
| SummaryProtos |
|
| SummaryWriter |
The SummaryWriter operation
|
| SummaryWriter.Inputs |
|
| SummaryWriter.Options |
|
| 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.Inputs<T extends TType> |
|
| Svd.Inputs<T extends TType> |
|
| Svd.Options |
Optional attributes for Svd |
| SwitchCond<T extends TType> |
Forwards data to the output port determined by pred.
|
| SwitchCond.Inputs<T extends TType> |
|
| SymbolicGradient |
Computes the gradient function for function f via backpropagation.
|
| SymbolicGradient.Inputs |
|
| 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 |
Creates a dataset that contains count elements from the input_dataset.
|
| TakeDataset.Inputs |
|
| TakeDataset.Options |
|
| TakeManySparseFromTensorsMap<T extends TType> |
Read SparseTensors from a SparseTensorsMap and concatenate them.
|
| TakeManySparseFromTensorsMap.Inputs |
|
| TakeManySparseFromTensorsMap.Options |
|
| TakeWhileDataset |
Creates a dataset that stops iteration when predicate` is false.
|
| TakeWhileDataset |
Creates a dataset that stops iteration when predicate` is false.
|
| TakeWhileDataset.Inputs |
|
| TakeWhileDataset.Inputs |
|
| TakeWhileDataset.Options |
|
| Tan<T extends TType> |
Computes tan of x element-wise.
|
| Tan.Inputs<T extends TType> |
|
| Tanh<T extends TType> |
Computes hyperbolic tangent of x element-wise.
|
| Tanh.Inputs<T extends TType> |
|
| TanhGrad<T extends TType> |
Computes the gradient for the tanh of x wrt its input.
|
| TanhGrad.Inputs<T extends TType> |
|
| 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.
|
| TBool |
Boolean tensor type.
|
| TemporaryVariable<T extends TType> |
Returns a tensor that may be mutated, but only persists within a single step.
|
| TemporaryVariable.Inputs |
|
| TemporaryVariable.Options |
|
| Tensor |
|
| Tensor |
A statically typed multi-dimensional array.
|
| TensorArray |
An array of Tensors of given size.
|
| TensorArray.Inputs |
|
| TensorArray.Options |
|
| TensorArrayClose |
Delete the TensorArray from its resource container.
|
| TensorArrayClose.Inputs |
|
| TensorArrayConcat<T extends TType> |
Concat the elements from the TensorArray into value value.
|
| TensorArrayConcat.Inputs |
|
| TensorArrayConcat.Options |
|
| TensorArrayGather<T extends TType> |
Gather specific elements from the TensorArray into output value.
|
| TensorArrayGather.Inputs |
|
| TensorArrayGather.Options |
|
| TensorArrayGrad |
Creates a TensorArray for storing the gradients of values in the given handle.
|
| TensorArrayGrad.Inputs |
|
| TensorArrayGradWithShape |
Creates a TensorArray for storing multiple gradients of values in the given handle.
|
| TensorArrayGradWithShape.Inputs |
|
| TensorArrayPack<T extends TType> |
The TensorArrayPack operation
|
| TensorArrayPack.Inputs |
|
| TensorArrayPack.Options |
|
| TensorArrayRead<T extends TType> |
Read an element from the TensorArray into output value.
|
| TensorArrayRead.Inputs |
|
| TensorArrayScatter |
Scatter the data from the input value into specific TensorArray elements.
|
| TensorArrayScatter.Inputs |
|
| TensorArraySize |
Get the current size of the TensorArray.
|
| TensorArraySize.Inputs |
|
| TensorArraySplit |
Split the data from the input value into TensorArray elements.
|
| TensorArraySplit.Inputs |
|
| TensorArrayUnpack |
The TensorArrayUnpack operation
|
| TensorArrayUnpack.Inputs |
|
| TensorArrayWrite |
Push an element onto the tensor_array.
|
| TensorArrayWrite.Inputs |
|
| 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.
|
| TensorDataset.Inputs |
|
| TensorDataset.Options |
|
| 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.
|
| TensorDiag.Inputs<T extends TType> |
|
| TensorDiagPart<T extends TType> |
Returns the diagonal part of the tensor.
|
| TensorDiagPart.Inputs<T extends TType> |
|
| tensorflow |
|
| TensorFlow |
Static utility methods describing the TensorFlow runtime.
|
| TensorFlowException |
Unchecked exception thrown by TensorFlow core classes
|
| TensorFunction |
A function that can be called with tensors.
|
| 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.
|
| TensorListConcat.Inputs |
|
| TensorListConcatLists |
The TensorListConcatLists operation
|
| TensorListConcatLists.Inputs |
|
| TensorListElementShape<T extends TNumber> |
The shape of the elements of the given list, as a tensor.
|
| TensorListElementShape.Inputs |
|
| TensorListFromTensor |
Creates a TensorList which, when stacked, has the value of tensor.
|
| TensorListFromTensor.Inputs |
|
| TensorListGather<T extends TType> |
Creates a Tensor by indexing into the TensorList.
|
| TensorListGather.Inputs |
|
| TensorListGetItem<T extends TType> |
The TensorListGetItem operation
|
| TensorListGetItem.Inputs |
|
| TensorListLength |
Returns the number of tensors in the input tensor list.
|
| TensorListLength.Inputs |
|
| TensorListPopBack<T extends TType> |
Returns the last element of the input list as well as a list with all but that element.
|
| TensorListPopBack.Inputs |
|
| TensorListPushBack |
Returns a list which has the passed-in Tensor as last element and the other elements of the given list in input_handle.
|
| TensorListPushBack.Inputs |
|
| TensorListPushBackBatch |
The TensorListPushBackBatch operation
|
| TensorListPushBackBatch.Inputs |
|
| TensorListReserve |
List of the given size with empty elements.
|
| TensorListReserve.Inputs |
|
| TensorListResize |
Resizes the list.
|
| TensorListResize.Inputs |
|
| TensorListScatter |
Creates a TensorList by indexing into a Tensor.
|
| TensorListScatter.Inputs |
|
| TensorListScatterIntoExistingList |
Scatters tensor at indices in an input list.
|
| TensorListScatterIntoExistingList.Inputs |
|
| TensorListSetItem |
The TensorListSetItem operation
|
| TensorListSetItem.Inputs |
|
| TensorListSplit |
Splits a tensor into a list.
|
| TensorListSplit.Inputs |
|
| TensorListStack<T extends TType> |
Stacks all tensors in the list.
|
| TensorListStack.Inputs |
|
| TensorListStack.Options |
|
| TensorMapErase |
Returns a tensor map with item from given key erased.
|
| TensorMapErase.Inputs |
|
| TensorMapHasKey |
Returns whether the given key exists in the map.
|
| TensorMapHasKey.Inputs |
|
| TensorMapInsert |
Returns a map that is the 'input_handle' with the given key-value pair inserted.
|
| TensorMapInsert.Inputs |
|
| TensorMapLookup<U extends TType> |
Returns the value from a given key in a tensor map.
|
| TensorMapLookup.Inputs |
|
| 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.
|
| TensorMapSize.Inputs |
|
| TensorMapStackKeys<T extends TType> |
Returns a Tensor stack of all keys in a tensor map.
|
| TensorMapStackKeys.Inputs |
|
| 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.
|
| TensorScatterNdAdd.Inputs<T extends TType> |
|
| TensorScatterNdMax<T extends TType> |
Apply a sparse update to a tensor taking the element-wise maximum.
|
| TensorScatterNdMax.Inputs<T extends TType> |
|
| TensorScatterNdMin<T extends TType> |
The TensorScatterMin operation
|
| TensorScatterNdMin.Inputs<T extends TType> |
|
| TensorScatterNdSub<T extends TType> |
Subtracts sparse updates from an existing tensor according to indices.
|
| TensorScatterNdSub.Inputs<T extends TType> |
|
| TensorScatterNdUpdate<T extends TType> |
Scatter updates into an existing tensor according to indices.
|
| TensorScatterNdUpdate.Inputs<T extends TType> |
|
| 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 |
Creates a dataset that emits each dim-0 slice of components once.
|
| TensorSliceDataset.Inputs |
|
| TensorSliceDataset.Options |
|
| 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.Inputs<T extends TType,U extends TNumber> |
|
| TensorStridedSliceUpdate.Options |
|
| TensorSummary |
Outputs a Summary protocol buffer with a tensor and per-plugin data.
|
| TensorSummary.Inputs |
|
| TensorType |
Annotation for all 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 |
Creates a dataset that emits the lines of one or more text files.
|
| TextLineDataset.Inputs |
|
| TextLineDataset.Options |
|
| TextLineReader |
A Reader that outputs the lines of a file delimited by '\n'.
|
| TextLineReader.Inputs |
|
| TextLineReader.Options |
|
| 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_Scope |
\addtogroup core
\{
|
| TF_Scope.Impl |
If status() is Status::OK(), construct a Graph object using opts as the
GraphConstructorOptions, and return Status::OK if graph construction was
successful.
|
| 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_OpAttrs |
|
| TFE_TensorDebugInfo |
|
| TFE_TensorHandle |
|
| TFFailedPreconditionException |
|
| TFInvalidArgumentException |
|
| TFloat16 |
IEEE-754 half-precision 16-bit float tensor type.
|
| TFloat32 |
IEEE-754 single-precision 32-bit float tensor type.
|
| TFloat64 |
IEEE-754 double-precision 64-bit float tensor type.
|
| 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.Inputs |
|
| TfRecordDataset.Options |
|
| TfRecordReader |
A Reader that outputs the records from a TensorFlow Records file.
|
| TfRecordReader.Inputs |
|
| TfRecordReader.Options |
|
| TFResourceExhaustedException |
|
| TFUnauthenticatedException |
|
| TFUnimplementedException |
|
| ThreadingOptions |
next: 3
|
| ThreadingOptions.Builder |
next: 3
|
| ThreadingOptions.OptionalMaxIntraOpParallelismCase |
|
| ThreadingOptions.OptionalPrivateThreadpoolSizeCase |
|
| ThreadingOptionsOrBuilder |
|
| 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.
|
| ThreadPoolDataset.Inputs |
|
| ThreadPoolDataset.Inputs |
|
| 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.Inputs |
|
| ThreadPoolHandle.Inputs |
|
| ThreadPoolHandle.Options |
|
| ThreadPoolHandle.Options |
|
| ThreadPoolOptionProto |
Protobuf type tensorflow.ThreadPoolOptionProto
|
| ThreadPoolOptionProto.Builder |
Protobuf type tensorflow.ThreadPoolOptionProto
|
| ThreadPoolOptionProtoOrBuilder |
|
| Tile<T extends TType> |
Constructs a tensor by tiling a given tensor.
|
| Tile.Inputs<T extends TType> |
|
| TileGrad<T extends TType> |
Returns the gradient of Tile.
|
| TileGrad.Inputs<T extends TType> |
|
| Timestamp |
Provides the time since epoch in seconds.
|
| Timestamp.Inputs |
|
| TInt32 |
32-bit signed integer tensor type.
|
| TInt64 |
64-bit signed integer tensor type.
|
| TIntegral |
Common interface for all integral numeric tensors.
|
| TNumber |
Common interface for all numeric tensors.
|
| ToBool |
Converts a tensor to a scalar predicate.
|
| ToBool.Inputs |
|
| ToHashBucket |
Converts each string in the input Tensor to its hash mod by a number of buckets.
|
| ToHashBucket.Inputs |
|
| ToHashBucketFast |
Converts each string in the input Tensor to its hash mod by a number of buckets.
|
| ToHashBucketFast.Inputs |
|
| ToHashBucketStrong |
Converts each string in the input Tensor to its hash mod by a number of buckets.
|
| ToHashBucketStrong.Inputs |
|
| ToNumber<T extends TNumber> |
Converts each string in the input Tensor to the specified numeric type.
|
| ToNumber.Inputs |
|
| TopK<T extends TNumber> |
Finds values and indices of the k largest elements for the last dimension.
|
| TopK.Inputs<T extends TNumber> |
|
| TopK.Options |
Optional attributes for TopK |
| TopKUnique |
Returns the TopK unique values in the array in sorted order.
|
| TopKUnique.Inputs |
|
| TopKWithUnique |
Returns the TopK values in the array in sorted order.
|
| TopKWithUnique.Inputs |
|
| TPUCompilationResult |
Deprecated.
|
| TPUCompilationResult.Inputs |
|
| TPUEmbeddingActivations |
Deprecated.
|
| TPUEmbeddingActivations.Inputs |
|
| TpuHandleToProtoKey |
Converts XRT's uid handles to TensorFlow-friendly input format.
|
| TpuHandleToProtoKey.Inputs |
|
| TpuOps |
An API for building tpu operations as Ops |
| TPUReplicatedInput<T extends TType> |
Deprecated.
|
| TPUReplicatedInput.Inputs<T extends TType> |
|
| TPUReplicatedInput.Options |
|
| TPUReplicatedOutput<T extends TType> |
Deprecated.
|
| TPUReplicatedOutput.Inputs<T extends TType> |
|
| TPUReplicateMetadata |
Deprecated.
|
| TPUReplicateMetadata.Inputs |
|
| TPUReplicateMetadata.Options |
|
| TPUReshardVariables |
Op that reshards on-device TPU variables to specified state.
|
| TPUReshardVariables.Inputs |
|
| TPURoundRobin |
Round-robin load balancing on TPU cores.
|
| TPURoundRobin.Inputs |
|
| 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 |
|
| TrainOps |
An API for building train operations as Ops |
| 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.
|
| Transpose.Inputs<T extends TType> |
|
| TriangularSolve<T extends TType> |
Solves systems of linear equations with upper or lower triangular matrices by backsubstitution.
|
| TriangularSolve.Inputs<T extends TType> |
|
| TriangularSolve.Options |
|
| TridiagonalMatMul<T extends TType> |
Calculate product with tridiagonal matrix.
|
| TridiagonalMatMul.Inputs<T extends TType> |
|
| TridiagonalSolve<T extends TType> |
Solves tridiagonal systems of equations.
|
| TridiagonalSolve.Inputs<T extends TType> |
|
| TridiagonalSolve.Options |
|
| TruncateDiv<T extends TType> |
Returns x / y element-wise for integer types.
|
| TruncateDiv.Inputs<T extends TType> |
|
| TruncatedNormal<U extends TNumber> |
Outputs random values from a truncated normal distribution.
|
| TruncatedNormal.Inputs |
|
| TruncatedNormal.Options |
|
| TruncateMod<T extends TNumber> |
Returns element-wise remainder of division.
|
| TruncateMod.Inputs<T extends TNumber> |
|
| TString |
String type.
|
| TType |
Common interface for all typed tensors.
|
| TUint16 |
16-bit unsigned integer tensor type.
|
| TUint8 |
8-bit unsigned integer tensor type.
|
| TupleValue |
Represents a Python tuple.
|
| TupleValue.Builder |
Represents a Python tuple.
|
| TupleValueOrBuilder |
|
| TypeSpecProto |
Represents a tf.TypeSpec
|
| TypeSpecProto.Builder |
Represents a tf.TypeSpec
|
| TypeSpecProto.TypeSpecClass |
Protobuf enum tensorflow.TypeSpecProto.TypeSpecClass
|
| TypeSpecProtoOrBuilder |
|
| TypesProtos |
|
| Unbatch<T extends TType> |
Reverses the operation of Batch for a single output Tensor.
|
| Unbatch.Inputs<T extends TType> |
|
| Unbatch.Options |
|
| 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.
|
| UnbatchDataset.Inputs |
|
| UnbatchDataset.Inputs |
|
| UnbatchDataset.Options |
|
| UnbatchGrad<T extends TType> |
Gradient of Unbatch.
|
| UnbatchGrad.Inputs<T extends TType> |
|
| UnbatchGrad.Options |
|
| UncompressElement |
Uncompresses a compressed dataset element.
|
| UncompressElement.Inputs |
|
| UnicodeDecode<T extends TNumber> |
Decodes each string in input into a sequence of Unicode code points.
|
| UnicodeDecode.Inputs |
|
| UnicodeDecode.Options |
|
| UnicodeDecodeWithOffsets<T extends TNumber> |
Decodes each string in input into a sequence of Unicode code points.
|
| UnicodeDecodeWithOffsets.Inputs |
|
| UnicodeDecodeWithOffsets.Options |
|
| UnicodeEncode |
Encode a tensor of ints into unicode strings.
|
| UnicodeEncode.Inputs |
|
| UnicodeEncode.Options |
|
| UnicodeScript |
Determine the script codes of a given tensor of Unicode integer code points.
|
| UnicodeScript.Inputs |
|
| UnicodeTranscode |
Transcode the input text from a source encoding to a destination encoding.
|
| UnicodeTranscode.Inputs |
|
| UnicodeTranscode.Options |
|
| UniformCandidateSampler |
Generates labels for candidate sampling with a uniform distribution.
|
| UniformCandidateSampler.Inputs |
|
| UniformCandidateSampler.Options |
|
| UniformDequantize<U extends TNumber> |
Perform dequantization on the quantized Tensor input.
|
| UniformDequantize.Inputs |
|
| UniformDequantize.Options |
|
| UniformQuantizedDotHybrid<V extends TNumber> |
Perform hybrid quantized dot of float Tensor lhs and quantized Tensor rhs.
|
| UniformQuantizedDotHybrid.Inputs |
|
| UniformQuantizedDotHybrid.Options |
|
| Unique<T extends TType,V extends TNumber> |
Finds unique elements along an axis of a tensor.
|
| Unique.Inputs<T extends TType> |
|
| UniqueDataset |
Creates a dataset that contains the unique elements of input_dataset.
|
| UniqueDataset |
Creates a dataset that contains the unique elements of input_dataset.
|
| UniqueDataset.Inputs |
|
| UniqueDataset.Inputs |
|
| UniqueDataset.Options |
|
| UniqueWithCounts<T extends TType,V extends TNumber> |
Finds unique elements along an axis of a tensor.
|
| UniqueWithCounts.Inputs<T extends TType> |
|
| UnravelIndex<T extends TNumber> |
Converts an array of flat indices into a tuple of coordinate arrays.
|
| UnravelIndex.Inputs<T extends TNumber> |
|
| UnsortedSegmentJoin |
The UnsortedSegmentJoin operation
|
| UnsortedSegmentJoin.Inputs |
|
| UnsortedSegmentJoin.Options |
|
| UnsortedSegmentMax<T extends TNumber> |
Computes the maximum along segments of a tensor.
|
| UnsortedSegmentMax.Inputs<T extends TNumber> |
|
| UnsortedSegmentMin<T extends TNumber> |
Computes the minimum along segments of a tensor.
|
| UnsortedSegmentMin.Inputs<T extends TNumber> |
|
| UnsortedSegmentProd<T extends TType> |
Computes the product along segments of a tensor.
|
| UnsortedSegmentProd.Inputs<T extends TType> |
|
| UnsortedSegmentSum<T extends TType> |
Computes the sum along segments of a tensor.
|
| UnsortedSegmentSum.Inputs<T extends TType> |
|
| Unstack<T extends TType> |
Unpacks a given dimension of a rank-R tensor into num rank-(R-1) tensors.
|
| Unstack.Inputs<T extends TType> |
|
| Unstack.Options |
|
| Unstage |
Op is similar to a lightweight Dequeue.
|
| Unstage.Inputs |
|
| Unstage.Options |
|
| UnwrapDatasetVariant |
The UnwrapDatasetVariant operation
|
| UnwrapDatasetVariant.Inputs |
|
| Upper |
Converts all lowercase characters into their respective uppercase replacements.
|
| Upper.Inputs |
|
| Upper.Options |
Optional attributes for Upper |
| UpperBound<U extends TNumber> |
Applies upper_bound(sorted_search_values, values) along each row.
|
| UpperBound.Inputs<T extends TType> |
|
| 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.Inputs |
|
| VarHandleOp.Options |
|
| Variable<T extends TType> |
Holds state in the form of a tensor that persists across steps.
|
| Variable.Inputs |
|
| Variable.Options |
|
| 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.
|
| VariableShape.Inputs |
|
| VariableSynchronization |
Indicates when a distributed variable will be synced.
|
| 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.
|
| VarIsInitializedOp.Inputs |
|
| 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 |
|
| WatchdogConfig |
Protobuf type tensorflow.WatchdogConfig
|
| WatchdogConfig.Builder |
Protobuf type tensorflow.WatchdogConfig
|
| WatchdogConfigOrBuilder |
|
| Where |
Returns locations of nonzero / true values in a tensor.
|
| Where.Inputs |
|
| While |
output = input; While (Cond(output)) { output = Body(output) }
|
| While |
output = input; While (Cond(output)) { output = Body(output) }
|
| While.Inputs |
|
| While.Options |
Optional attributes for While |
| 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.Inputs |
|
| WholeFileReader.Options |
|
| WindowDataset |
Combines (nests of) input elements into a dataset of (nests of) windows.
|
| WindowDataset.Inputs |
|
| WindowDataset.Options |
|
| WindowOp |
The WindowOp operation
|
| WindowOp.Inputs |
|
| WorkerHealth |
Current health status of a worker.
|
| WorkerHeartbeat |
Worker heartbeat op.
|
| WorkerHeartbeat.Inputs |
|
| 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 |
The WrapDatasetVariant operation
|
| WrapDatasetVariant.Inputs |
|
| WriteAudioSummary |
Writes an audio summary.
|
| WriteAudioSummary.Inputs |
|
| WriteAudioSummary.Options |
|
| WriteFile |
Writes contents to the file at input filename.
|
| WriteFile.Inputs |
|
| WriteGraphSummary |
Writes a graph summary.
|
| WriteGraphSummary.Inputs |
|
| WriteHistogramSummary |
Writes a histogram summary.
|
| WriteHistogramSummary.Inputs |
|
| WriteImageSummary |
Writes an image summary.
|
| WriteImageSummary.Inputs |
|
| WriteImageSummary.Options |
|
| WriteRawProtoSummary |
Writes a serialized proto summary.
|
| WriteRawProtoSummary.Inputs |
|
| WriteScalarSummary |
Writes a scalar summary.
|
| WriteScalarSummary.Inputs |
|
| WriteSummary |
Writes a tensor summary.
|
| WriteSummary.Inputs |
|
| Xdivy<T extends TType> |
Returns 0 if x == 0, and x / y otherwise, elementwise.
|
| Xdivy.Inputs<T extends TType> |
|
| 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 |
|
| XlaCallModule |
Temporary op for experimenting with jax2tf.
|
| XlaCallModule.Inputs |
|
| XlaHostCompute |
A pseudo-op to represent host-side computation in an XLA program.
|
| XlaHostCompute.Inputs |
|
| XlaHostCompute.Options |
|
| XlaLaunch |
XLA Launch Op.
|
| XlaLaunch.Inputs |
|
| XlaOps |
An API for building xla operations as Ops |
| XlaRecvFromHost<T extends TType> |
An op to receive a tensor from the host.
|
| XlaRecvFromHost.Inputs |
|
| XlaRecvTPUEmbeddingActivations |
An op that receives embedding activations on the TPU.
|
| XlaRecvTPUEmbeddingActivations.Inputs |
|
| XlaRecvTPUEmbeddingDeduplicationData |
Receives deduplication data (indices and weights) from the embedding core.
|
| XlaRecvTPUEmbeddingDeduplicationData.Inputs |
|
| XlaSendToHost |
An op to send a tensor to the host.
|
| XlaSendToHost.Inputs |
|
| XlaSendTPUEmbeddingGradients |
An op that performs gradient updates of embedding tables.
|
| XlaSendTPUEmbeddingGradients.Inputs |
|
| XlaSendTPUEmbeddingGradients.Options |
|
| XlaSetBound |
Set a bound for the given input value as a hint to Xla compiler,
|
| XlaSetBound.Inputs |
|
| XlaVariadicReduce |
Wraps the variadic XLA Reduce operator.
|
| XlaVariadicReduce.Inputs |
|
| XlaVariadicSort |
Wraps the XLA Sort operator, documented at
https://www.tensorflow.org/performance/xla/operation_semantics#sort
.
|
| XlaVariadicSort.Inputs |
|
| 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.
|
| Xlog1py.Inputs<T extends TType> |
|
| Xlogy<T extends TType> |
Returns 0 if x == 0, and x * log(y) otherwise, elementwise.
|
| Xlogy.Inputs<T extends TType> |
|
| 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 |
|
| 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.
|
| ZerosLike.Inputs<T extends TType> |
|
| Zeta<T extends TNumber> |
Compute the Hurwitz zeta function \(\zeta(x, q)\).
|
| Zeta.Inputs<T extends TNumber> |
|
| ZipDataset |
Creates a dataset that zips together input_datasets.
|
| ZipDataset.Inputs |
|
| ZipDataset.Options |
|