All Classes Interface Summary Class Summary Enum Summary Annotation Types Summary
| Class |
Description |
| Abort |
Raise a exception to abort the process when called.
|
| Abort.Inputs |
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| Abort.Options |
Optional attributes for Abort |
| Abs<T extends TNumber> |
Computes the absolute value of a tensor.
|
| Abs.Inputs<T extends TNumber> |
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| AbstractGradientAdapter |
Helper base class for custom gradient adapters INTERNAL USE ONLY
|
| AccumulateN<T extends TType> |
Returns the element-wise sum of a list of tensors.
|
| AccumulateN.Inputs<T extends TType> |
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| AccumulatorApplyGradient |
Applies a gradient to a given accumulator.
|
| AccumulatorApplyGradient.Inputs |
|
| AccumulatorNumAccumulated |
Returns the number of gradients aggregated in the given accumulators.
|
| AccumulatorNumAccumulated.Inputs |
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| AccumulatorSetGlobalStep |
Updates the accumulator with a new value for global_step.
|
| AccumulatorSetGlobalStep.Inputs |
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| AccumulatorTakeGradient<T extends TType> |
Extracts the average gradient in the given ConditionalAccumulator.
|
| AccumulatorTakeGradient.Inputs |
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| Acos<T extends TType> |
Computes acos of x element-wise.
|
| Acos.Inputs<T extends TType> |
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| Acosh<T extends TType> |
Computes inverse hyperbolic cosine of x element-wise.
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| Acosh.Inputs<T extends TType> |
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| Add<T extends TType> |
Returns x + y element-wise.
|
| Add.Inputs<T extends TType> |
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| 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> |
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| 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> |
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| AdjustHue<T extends TNumber> |
Adjust the hue of one or more images.
|
| AdjustHue.Inputs<T extends TNumber> |
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| 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 |
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| 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 |
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| AnonymousIterator |
A container for an iterator resource.
|
| AnonymousIterator.Inputs |
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| AnonymousMemoryCache |
The AnonymousMemoryCache operation
|
| AnonymousMemoryCache.Inputs |
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| AnonymousMultiDeviceIterator |
A container for a multi device iterator resource.
|
| AnonymousMultiDeviceIterator.Inputs |
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| AnonymousMutableDenseHashTable |
Creates an empty anonymous mutable hash table that uses tensors as the backing store.
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| AnonymousMutableDenseHashTable.Inputs<T extends TType> |
|
| AnonymousMutableDenseHashTable.Options |
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| AnonymousMutableHashTable |
Creates an empty anonymous mutable hash table.
|
| AnonymousMutableHashTable.Inputs |
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| AnonymousMutableHashTableOfTensors |
Creates an empty anonymous mutable hash table of vector values.
|
| AnonymousMutableHashTableOfTensors.Inputs |
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| AnonymousMutableHashTableOfTensors.Options |
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| AnonymousRandomSeedGenerator |
The AnonymousRandomSeedGenerator operation
|
| AnonymousRandomSeedGenerator.Inputs |
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| AnonymousSeedGenerator |
The AnonymousSeedGenerator operation
|
| AnonymousSeedGenerator.Inputs |
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| Any |
Computes the "logical or" of elements across dimensions of a tensor.
|
| Any.Inputs |
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| Any.Options |
Optional attributes for Any |
| ApplyAdadelta<T extends TType> |
Update '*var' according to the adadelta scheme.
|
| ApplyAdadelta.Inputs<T extends TType> |
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| ApplyAdadelta.Options |
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| ApplyAdagrad<T extends TType> |
Update '*var' according to the adagrad scheme.
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| ApplyAdagrad.Inputs<T extends TType> |
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| ApplyAdagrad.Options |
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| ApplyAdagradDa<T extends TType> |
Update '*var' according to the proximal adagrad scheme.
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| ApplyAdagradDa.Inputs<T extends TType> |
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| ApplyAdagradDa.Options |
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| ApplyAdagradV2<T extends TType> |
Update '*var' according to the adagrad scheme.
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| ApplyAdagradV2.Inputs<T extends TType> |
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| ApplyAdagradV2.Options |
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| ApplyAdam<T extends TType> |
Update '*var' according to the Adam algorithm.
|
| ApplyAdam.Inputs<T extends TType> |
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| ApplyAdam.Options |
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| ApplyAdaMax<T extends TType> |
Update '*var' according to the AdaMax algorithm.
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| ApplyAdaMax.Inputs<T extends TType> |
|
| ApplyAdaMax.Options |
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| ApplyAddSign<T extends TType> |
Update '*var' according to the AddSign update.
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| ApplyAddSign.Inputs<T extends TType> |
|
| ApplyAddSign.Options |
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| ApplyCenteredRmsProp<T extends TType> |
Update '*var' according to the centered RMSProp algorithm.
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| ApplyCenteredRmsProp.Inputs<T extends TType> |
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| ApplyCenteredRmsProp.Options |
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| ApplyFtrl<T extends TType> |
Update '*var' according to the Ftrl-proximal scheme.
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| ApplyFtrl.Inputs<T extends TType> |
|
| ApplyFtrl.Options |
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| ApplyGradientDescent<T extends TType> |
Update '*var' by subtracting 'alpha' * 'delta' from it.
|
| ApplyGradientDescent.Inputs<T extends TType> |
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| ApplyGradientDescent.Options |
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| ApplyMomentum<T extends TType> |
Update '*var' according to the momentum scheme.
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| ApplyMomentum.Inputs<T extends TType> |
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| ApplyMomentum.Options |
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| ApplyPowerSign<T extends TType> |
Update '*var' according to the AddSign update.
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| ApplyPowerSign.Inputs<T extends TType> |
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| ApplyPowerSign.Options |
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| ApplyProximalAdagrad<T extends TType> |
Update '*var' and '*accum' according to FOBOS with Adagrad learning rate.
|
| ApplyProximalAdagrad.Inputs<T extends TType> |
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| ApplyProximalAdagrad.Options |
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| ApplyProximalGradientDescent<T extends TType> |
Update '*var' as FOBOS algorithm with fixed learning rate.
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| ApplyProximalGradientDescent.Inputs<T extends TType> |
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| ApplyProximalGradientDescent.Options |
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| ApplyRmsProp<T extends TType> |
Update '*var' according to the RMSProp algorithm.
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| 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 |
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| 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 |
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| ArgMax<V extends TNumber> |
Returns the index with the largest value across dimensions of a tensor.
|
| ArgMax.Inputs |
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| 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> |
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| Asinh<T extends TType> |
Computes inverse hyperbolic sine of x element-wise.
|
| Asinh.Inputs<T extends TType> |
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| AssertCardinalityDataset |
The AssertCardinalityDataset operation
|
| AssertCardinalityDataset.Inputs |
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| AssertNextDataset |
A transformation that asserts which transformations happen next.
|
| AssertNextDataset |
The ExperimentalAssertNextDataset operation
|
| AssertNextDataset.Inputs |
|
| AssertNextDataset.Inputs |
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| AssertPrevDataset |
A transformation that asserts which transformations happened previously.
|
| AssertPrevDataset.Inputs |
|
| AssertThat |
Asserts that the given condition is true.
|
| AssertThat.Inputs |
|
| AssertThat.Options |
|
| 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 |
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| AssignAddVariableOp |
Adds a value to the current value of a variable.
|
| AssignAddVariableOp.Inputs |
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| 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 |
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| AssignVariableConcatND |
Concats input tensor across all dimensions.
|
| AssignVariableConcatND.Inputs |
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| AssignVariableConcatND.Options |
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| 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.
|
| AudioOps |
An API for building audio operations as Ops |
| AudioSpectrogram |
Produces a visualization of audio data over time.
|
| AudioSpectrogram.Inputs |
|
| AudioSpectrogram.Options |
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| AudioSummary |
Outputs a Summary protocol buffer with audio.
|
| AudioSummary.Inputs |
|
| AudioSummary.Options |
|
| 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 |
|
| 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 |
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| AvgPool3dGrad<T extends TNumber> |
Computes gradients of average pooling function.
|
| AvgPool3dGrad.Inputs<T extends TNumber> |
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| AvgPool3dGrad.Options |
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| AvgPoolGrad<T extends TNumber> |
Computes gradients of the average pooling function.
|
| AvgPoolGrad.Inputs<T extends TNumber> |
|
| AvgPoolGrad.Options |
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| 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 |
|
| 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 |
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| BatchFft |
The BatchFFT operation
|
| BatchFft.Inputs |
|
| BatchFft2d |
The BatchFFT2D operation
|
| BatchFft2d.Inputs |
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| BatchFft3d |
The BatchFFT3D operation
|
| BatchFft3d.Inputs |
|
| BatchFunction |
Batches all the inputs tensors to the computation done by the function.
|
| BatchFunction.Inputs |
|
| BatchFunction.Options |
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| BatchIfft |
The BatchIFFT operation
|
| BatchIfft.Inputs |
|
| BatchIfft2d |
The BatchIFFT2D operation
|
| BatchIfft2d.Inputs |
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| BatchIfft3d |
The BatchIFFT3D operation
|
| BatchIfft3d.Inputs |
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| BatchMatMul<V extends TType> |
Multiplies slices of two tensors in batches.
|
| BatchMatMul.Inputs |
|
| BatchMatMul.Options |
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| BatchMatrixBandPart<T extends TType> |
The BatchMatrixBandPart operation
|
| BatchMatrixBandPart.Inputs<T extends TType> |
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| BatchMatrixDeterminant<T extends TType> |
The BatchMatrixDeterminant operation
|
| BatchMatrixDeterminant.Inputs<T extends TType> |
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| BatchMatrixDiag<T extends TType> |
The BatchMatrixDiag operation
|
| BatchMatrixDiag.Inputs<T extends TType> |
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| BatchMatrixDiagPart<T extends TType> |
The BatchMatrixDiagPart operation
|
| BatchMatrixDiagPart.Inputs<T extends TType> |
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| BatchMatrixInverse<T extends TNumber> |
The BatchMatrixInverse operation
|
| BatchMatrixInverse.Inputs<T extends TNumber> |
|
| BatchMatrixInverse.Options |
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| 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 |
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| 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> |
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| BatchNormWithGlobalNormalizationGrad<T extends TType> |
Gradients for batch normalization.
|
| BatchNormWithGlobalNormalizationGrad.Inputs<T extends TType> |
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| BatchSelfAdjointEig<T extends TNumber> |
The BatchSelfAdjointEigV2 operation
|
| BatchSelfAdjointEig.Inputs<T extends TNumber> |
|
| BatchSelfAdjointEig.Options |
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| 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> |
|
| 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> |
|
| 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> |
|
| 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 |
|
| 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> |
|
| BroadcastTo<T extends TType> |
Broadcast an array for a compatible shape.
|
| BroadcastTo.Inputs<T extends TType> |
|
| Bucketize |
Bucketizes 'input' based on 'boundaries'.
|
| Bucketize.Inputs |
|
| 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 |
|
| 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 |
|
| ClusterOps |
An API for building cluster operations as Ops |
| CollateTPUEmbeddingMemory |
An op that merges the string-encoded memory config protos from all hosts.
|
| CollateTPUEmbeddingMemory.Inputs |
|
| 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 |
|
| CollectiveOps |
An API for building collective operations as Ops |
| 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 |
|
| CollectiveReduceScatter<T extends TNumber> |
Mutually reduces multiple tensors of identical type and shape and scatters the result.
|
| CollectiveReduceScatter.Inputs<T extends TNumber> |
|
| CollectiveReduceScatter.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 |
|
| 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 |
|
| 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 |
|
| 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 |
|
| ComputeDedupDataSize |
An op computes the size of the deduplication data from embedding core and returns the updated config.
|
| ComputeDedupDataSize.Inputs |
|
| ComputeDedupDataTupleMask |
An op computes tuple mask of deduplication data from embedding core.
|
| ComputeDedupDataTupleMask.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 |
|
| ConcatOffset<T extends TNumber> |
Computes offsets of concat inputs within its output.
|
| ConcatOffset.Inputs<T extends TNumber> |
|
| ConcreteFunction |
A graph that can be invoked as a single function, with an input and output signature.
|
| ConditionalAccumulator |
A conditional accumulator for aggregating gradients.
|
| ConditionalAccumulator.Inputs |
|
| ConditionalAccumulator.Options |
|
| ConfigureAndInitializeGlobalTPU |
An op that sets up the centralized structures for a distributed TPU system.
|
| ConfigureAndInitializeGlobalTPU.Inputs |
|
| ConfigureAndInitializeGlobalTPU.Options |
|
| 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 |
|
| ControlTrigger |
Does nothing.
|
| ControlTrigger.Inputs |
|
| Conv<T extends TNumber> |
Computes a N-D convolution given (N+1+batch_dims)-D input and (N+2)-D filter tensors.
|
| Conv.Inputs<T 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 |
|
| Conv2dBackpropFilterV2<T extends TNumber> |
Computes the gradients of convolution with respect to the filter.
|
| Conv2dBackpropFilterV2.Inputs<T extends TNumber> |
|
| Conv2dBackpropFilterV2.Options |
|
| Conv2dBackpropInput<T extends TNumber> |
Computes the gradients of convolution with respect to the input.
|
| Conv2dBackpropInput.Inputs<T extends TNumber> |
|
| Conv2dBackpropInput.Options |
|
| Conv2dBackpropInputV2<T extends TNumber> |
Computes the gradients of convolution with respect to the input.
|
| Conv2dBackpropInputV2.Inputs<T extends TNumber> |
|
| Conv2dBackpropInputV2.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 |
|
| ConvertToCooTensor |
The ConvertToCooTensor operation
|
| ConvertToCooTensor.Inputs |
|
| 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> |
|
| CopyToMeshGrad<T extends TType> |
The CopyToMeshGrad operation
|
| CopyToMeshGrad.Inputs<T extends TType> |
|
| 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> |
|
| CountUpTo<T extends TNumber> |
Increments 'ref' until it reaches 'limit'.
|
| CountUpTo.Inputs<T extends TNumber> |
|
| 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 |
|
| CustomGradient<T extends RawOpInputs> |
|
| DataExperimentalOps |
An API for building data.experimental operations as Ops |
| 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 |
| 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 |
|
| DatasetCardinality.Options |
|
| DatasetFingerprint |
Returns the fingerprint of input_dataset.
|
| DatasetFingerprint.Inputs |
|
| DatasetFromGraph |
Creates a dataset from the given graph_def.
|
| DatasetFromGraph.Inputs |
|
| 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 |
|
| Dawsn<T extends TNumber> |
The Dawsn operation
|
| Dawsn.Inputs<T extends TNumber> |
|
| DebuggingOps |
An API for building debugging operations as Ops |
| 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> |
Provides an identity mapping of the non-Ref type input tensor for debugging.
|
| DebugIdentity.Inputs<T extends TType> |
|
| DebugIdentity.Options |
|
| DebugNanCount |
Debug NaN Value Counter Op.
|
| DebugNanCount.Inputs |
|
| DebugNanCount.Options |
|
| DebugNumericsSummary<U extends TNumber> |
Debug Numeric Summary V2 Op.
|
| DebugNumericsSummary.Inputs |
|
| DebugNumericsSummary.Options |
|
| 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> |
|
| 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.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> |
|
| DeviceIndex |
Return the index of device the op runs.
|
| DeviceIndex.Inputs |
|
| DeviceSpec |
Represents a (possibly partial) specification for a TensorFlow device.
|
| DeviceSpec.Builder |
|
| DeviceSpec.DeviceType |
|
| 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 |
|
| DistributedSave |
The DistributedSave operation
|
| DistributedSave.Inputs |
|
| DistributedSave.Options |
|
| DistributeOps |
An API for building distribute operations as Ops |
| 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> |
|
| DrawBoundingBoxes<T extends TNumber> |
Draw bounding boxes on a batch of images.
|
| DrawBoundingBoxes.Inputs<T extends TNumber> |
|
| DTensorRestore |
The DTensorRestoreV2 operation
|
| DTensorRestore.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 |
|
| DynamicEnqueueTPUEmbeddingRaggedTensorBatch |
The DynamicEnqueueTPUEmbeddingRaggedTensorBatch operation
|
| DynamicEnqueueTPUEmbeddingRaggedTensorBatch.Inputs |
|
| DynamicEnqueueTPUEmbeddingRaggedTensorBatch.Options |
|
| DynamicPartition<T extends TType> |
Partitions data into num_partitions tensors using indices from partitions.
|
| DynamicPartition.Inputs<T extends TType> |
|
| DynamicStitch<T extends TType> |
Interleave the values from the data tensors into a single tensor.
|
| DynamicStitch.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.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 |
| 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> |
|
| EuclideanNorm<T extends TType> |
Computes the euclidean norm of elements across dimensions of a tensor.
|
| EuclideanNorm.Inputs<T extends TType> |
|
| EuclideanNorm.Options |
|
| 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 |
|
| ExecutionEnvironment |
Defines an environment for creating and executing TensorFlow Operations. |
| ExecutionEnvironment.Types |
|
| 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> |
|
| 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 |
|
| FakeParam<T extends TType> |
This op is used as a placeholder in If branch functions.
|
| FakeParam.Inputs |
|
| FakeQuantWithMinMaxArgs |
Fake-quantize the 'inputs' tensor, type float to 'outputs' tensor of same shape and 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 |
|
| FakeQueue |
Deprecated.
|
| FakeQueue.Inputs |
|
| 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> |
|
| FftNd<T extends TType> |
ND fast Fourier transform.
|
| FftNd.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 |
|
| 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 |
|
| 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> |
|
| Function |
|
| 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.Inputs<T extends TType> |
|
| 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 |
|
| GetMinibatchesInCsrWithPhysicalReplica |
The GetMinibatchesInCsrWithPhysicalReplica operation
|
| GetMinibatchesInCsrWithPhysicalReplica.Inputs |
|
| GetMinibatchSplitsWithPhysicalReplica |
The GetMinibatchSplitsWithPhysicalReplica operation
|
| GetMinibatchSplitsWithPhysicalReplica.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 |
|
| GlobalIterId |
The GlobalIterId operation
|
| GlobalIterId.Inputs |
|
| 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 |
|
| 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.
|
| GraphOperation |
|
| GraphOperationBuilder |
|
| 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> |
|
| HistogramSummary |
Outputs a Summary protocol buffer with a histogram.
|
| HistogramSummary.Inputs |
|
| HostConst<T extends TType> |
Returns a constant tensor on the host.
|
| HostConst.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.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> |
|
| IfftNd<T extends TType> |
ND inverse fast Fourier transform.
|
| IfftNd.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> |
|
| 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 |
|
| IrfftNd<U extends TNumber> |
ND inverse real fast Fourier transform.
|
| IrfftNd.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 |
|
| 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 |
| 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 |
| LinalgSparseOps |
An API for building linalg.sparse 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 |
|
| ListSnapshotChunksDataset |
The ListSnapshotChunksDataset operation
|
| ListSnapshotChunksDataset.Inputs |
|
| 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 |
|
| 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> |
|
| 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> |
|
| 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 |
| MathSpecialOps |
An API for building math.special 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 |
|
| MatrixExponential<T extends TType> |
Deprecated, use python implementation tf.linalg.matrix_exponential.
|
| MatrixExponential.Inputs<T extends TType> |
|
| 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 |
| Merge<T extends TType> |
Forwards the value of an available tensor from inputs to output.
|
| Merge.Inputs<T extends TType> |
|
| MergeDedupData |
An op merges elements of integer and float tensors into deduplication data as
XLA tuple.
|
| MergeDedupData.Inputs |
|
| MergeDedupData.Options |
|
| MergeSummary |
Merges summaries.
|
| MergeSummary.Inputs |
|
| MergeV2Checkpoints |
V2 format specific: merges the metadata files of sharded checkpoints.
|
| MergeV2Checkpoints.Inputs |
|
| MergeV2Checkpoints.Options |
|
| 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 |
|
| 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 |
|
| NativeScope |
A Scope implementation backed by a native scope. |
| 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 |
| NonDeterministicInts<U extends TType> |
Non-deterministically generates some integers.
|
| NonDeterministicInts.Inputs |
|
| 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 |
|
| 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.
|
| 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.
|
| OpInputsMetadata |
An annotation to provide metadata about an op inputs accessor class.
|
| OpMetadata |
An annotation to provide metadata about an op.
|
| Ops |
An API for building operations as Ops |
| OpScope |
A Java implementation of Scope. |
| OptimizeDataset |
Creates a dataset by applying related optimizations to input_dataset.
|
| OptimizeDataset.Inputs |
|
| OptimizeDataset.Options |
|
| 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 |
|
| OptionsDataset |
Creates a dataset by attaching tf.data.Options to input_dataset.
|
| OptionsDataset.Inputs |
|
| OptionsDataset.Options |
|
| 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 |
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| OrderedMapUnstageNoKey.Options |
|
| OrdinalSelector |
A TPU core selector Op.
|
| OrdinalSelector.Inputs |
|
| OutfeedDequeue<T extends TType> |
Retrieves a single tensor from the computation outfeed.
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| OutfeedDequeue.Inputs |
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| OutfeedDequeue.Options |
|
| OutfeedDequeueTuple |
Retrieve multiple values from the computation outfeed.
|
| OutfeedDequeueTuple.Inputs |
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| 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.Inputs<T extends TType> |
|
| PaddedBatchDataset |
Creates a dataset that batches and pads batch_size elements from the input.
|
| PaddedBatchDataset.Inputs |
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| PaddedBatchDataset.Options |
|
| PaddingFifoQueue |
A queue that produces elements in first-in first-out order.
|
| PaddingFifoQueue.Inputs |
|
| PaddingFifoQueue.Options |
|
| ParallelBatchDataset |
The ParallelBatchDataset operation
|
| ParallelBatchDataset.Inputs |
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| 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.
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| ParallelDynamicStitch.Inputs<T extends TType> |
|
| ParallelFilterDataset |
Creates a dataset containing elements of input_dataset matching predicate.
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| ParallelFilterDataset.Inputs |
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| 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 |
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| ParallelInterleaveDataset.Inputs |
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| ParallelInterleaveDataset.Options |
|
| ParallelMapDataset |
Creates a dataset that applies f to the outputs of input_dataset.
|
| ParallelMapDataset.Inputs |
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| 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 |
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| ParseExampleDataset.Inputs |
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| ParseExampleDataset.Options |
|
| ParseExampleDataset.Options |
|
| ParseSequenceExample |
Transforms a vector of tf.io.SequenceExample protos (as strings) into
typed tensors.
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| 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 |
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| 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 |
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| 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> |
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| 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> |
|
| Placeholder<T extends TType> |
A placeholder op for a value that will be fed into the computation.
|
| Placeholder.Inputs |
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| Placeholder.Options |
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| PlaceholderWithDefault<T extends TType> |
A placeholder op that passes through input when its output is not fed.
|
| PlaceholderWithDefault.Inputs<T extends TType> |
|
| 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.
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| Pow.Inputs<T extends TType> |
|
| PrefetchDataset |
Creates a dataset that asynchronously prefetches elements from input_dataset.
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| PrefetchDataset.Inputs |
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| PrefetchDataset.Options |
|
| Prelinearize |
An op which linearizes one Tensor value to an opaque variant tensor.
|
| Prelinearize.Inputs |
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| Prelinearize.Options |
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| 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 |
| 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> |
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| 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> |
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| QuantizeAndDequantizeV4.Options |
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| 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 |
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| QuantizedAvgPool<T extends TNumber> |
Produces the average pool of the input tensor for quantized types.
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| QuantizedAvgPool.Inputs<T extends TNumber> |
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| 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 |
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| 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 |
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| QuantizedConv2d.Options |
|
| QuantizedConv2DAndRelu<V extends TNumber> |
The QuantizedConv2DAndRelu operation
|
| QuantizedConv2DAndRelu.Inputs |
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| QuantizedConv2DAndRelu.Options |
|
| QuantizedConv2DAndReluAndRequantize<V extends TNumber> |
The QuantizedConv2DAndReluAndRequantize operation
|
| QuantizedConv2DAndReluAndRequantize.Inputs |
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| QuantizedConv2DAndReluAndRequantize.Options |
|
| QuantizedConv2DAndRequantize<V extends TNumber> |
The QuantizedConv2DAndRequantize operation
|
| QuantizedConv2DAndRequantize.Inputs |
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| QuantizedConv2DAndRequantize.Options |
|
| QuantizedConv2DPerChannel<V extends TNumber> |
Computes QuantizedConv2D per channel.
|
| QuantizedConv2DPerChannel.Inputs |
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| QuantizedConv2DPerChannel.Options |
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| QuantizedConv2DWithBias<V extends TNumber> |
The QuantizedConv2DWithBias operation
|
| QuantizedConv2DWithBias.Inputs |
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| QuantizedConv2DWithBias.Options |
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| QuantizedConv2DWithBiasAndRelu<V extends TNumber> |
The QuantizedConv2DWithBiasAndRelu operation
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| QuantizedConv2DWithBiasAndRelu.Inputs |
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| QuantizedConv2DWithBiasAndRelu.Options |
|
| QuantizedConv2DWithBiasAndReluAndRequantize<W extends TNumber> |
The QuantizedConv2DWithBiasAndReluAndRequantize operation
|
| QuantizedConv2DWithBiasAndReluAndRequantize.Inputs |
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| QuantizedConv2DWithBiasAndReluAndRequantize.Options |
|
| QuantizedConv2DWithBiasAndRequantize<W extends TNumber> |
The QuantizedConv2DWithBiasAndRequantize operation
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| QuantizedConv2DWithBiasAndRequantize.Inputs |
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| QuantizedConv2DWithBiasAndRequantize.Options |
|
| QuantizedConv2DWithBiasSignedSumAndReluAndRequantize<X extends TNumber> |
The QuantizedConv2DWithBiasSignedSumAndReluAndRequantize operation
|
| QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.Inputs |
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| QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.Options |
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| QuantizedConv2DWithBiasSumAndRelu<V extends TNumber> |
The QuantizedConv2DWithBiasSumAndRelu operation
|
| QuantizedConv2DWithBiasSumAndRelu.Inputs |
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| QuantizedConv2DWithBiasSumAndRelu.Options |
|
| QuantizedConv2DWithBiasSumAndReluAndRequantize<X extends TNumber> |
The QuantizedConv2DWithBiasSumAndReluAndRequantize operation
|
| QuantizedConv2DWithBiasSumAndReluAndRequantize.Inputs |
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| 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 |
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| 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> |
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| 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 |
|
| 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 |
|
| RaggedFillEmptyRows<T extends TType> |
The RaggedFillEmptyRows operation
|
| RaggedFillEmptyRows.Inputs<T extends TType> |
|
| RaggedFillEmptyRowsGrad<T extends TType> |
The RaggedFillEmptyRowsGrad operation
|
| RaggedFillEmptyRowsGrad.Inputs<T extends TType> |
|
| 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 |
|
| RandomExperimentalOps |
An API for building random.experimental operations as Ops |
| 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> |
|
| RandomIndexShuffle.Options |
|
| 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.
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| ReaderNumRecordsProduced |
Returns the number of records this Reader has produced.
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| ReaderNumRecordsProduced.Inputs |
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| ReaderNumWorkUnitsCompleted |
Returns the number of work units this Reader has finished processing.
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| ReaderNumWorkUnitsCompleted.Inputs |
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| ReaderRead |
Returns the next record (key, value pair) produced by a Reader.
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| ReaderRead.Inputs |
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| ReaderReadUpTo |
Returns up to num_records (key, value) pairs produced by a Reader.
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| ReaderReadUpTo.Inputs |
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| ReaderReset |
Restore a Reader to its initial clean state.
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| ReaderReset.Inputs |
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| ReaderRestoreState |
Restore a reader to a previously saved state.
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| ReaderRestoreState.Inputs |
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| ReaderSerializeState |
Produce a string tensor that encodes the state of a Reader.
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| ReaderSerializeState.Inputs |
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| ReadFile |
Reads and outputs the entire contents of the input filename.
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| ReadFile.Inputs |
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| ReadVariableOp<T extends TType> |
Reads the value of a variable.
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| ReadVariableOp.Inputs |
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| ReadVariableSplitND<T extends TType> |
Splits resource variable input tensor across all dimensions.
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| ReadVariableSplitND.Inputs |
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| ReadVariableSplitND.Options |
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| Real<U extends TNumber> |
Returns the real part of a complex number.
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| Real.Inputs |
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| RealDiv<T extends TType> |
Returns x / y element-wise for real types.
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| RealDiv.Inputs<T extends TType> |
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| RebatchDataset |
Creates a dataset that changes the batch size.
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| RebatchDataset.Inputs |
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| RebatchDataset.Options |
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| RebatchDatasetV2 |
Creates a dataset that changes the batch size.
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| RebatchDatasetV2.Inputs |
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| Reciprocal<T extends TType> |
Computes the reciprocal of x element-wise.
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| Reciprocal.Inputs<T extends TType> |
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| ReciprocalGrad<T extends TType> |
Computes the gradient for the inverse of x wrt its input.
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| ReciprocalGrad.Inputs<T extends TType> |
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| RecordInput |
Emits randomized records.
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| RecordInput.Inputs |
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| RecordInput.Options |
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| Recv<T extends TType> |
Receives the named tensor from send_device on recv_device.
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| Recv.Inputs |
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| Recv.Options |
Optional attributes for Recv |
| RecvTPUEmbeddingActivations |
An op that receives embedding activations on the TPU.
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| RecvTPUEmbeddingActivations.Inputs |
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| ReduceAll |
Computes the "logical and" of elements across dimensions of a tensor.
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| ReduceAll.Inputs |
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| ReduceAll.Options |
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| ReduceAny |
Computes the "logical or" of elements across dimensions of a tensor.
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| ReduceAny.Inputs |
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| ReduceAny.Options |
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| ReduceDataset |
Reduces the input dataset to a singleton using a reduce function.
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| ReduceDataset.Inputs |
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| ReduceDataset.Options |
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| ReduceJoin |
Joins a string Tensor across the given dimensions.
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| ReduceJoin.Inputs |
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| ReduceJoin.Options |
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| ReduceMax<T extends TNumber> |
Computes the maximum of elements across dimensions of a tensor.
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| ReduceMax.Inputs<T extends TNumber> |
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| ReduceMax.Options |
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| ReduceMin<T extends TNumber> |
Computes the minimum of elements across dimensions of a tensor.
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| ReduceMin.Inputs<T extends TNumber> |
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| ReduceMin.Options |
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| ReduceProd<T extends TType> |
Computes the product of elements across dimensions of a tensor.
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| ReduceProd.Inputs<T extends TType> |
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| ReduceProd.Options |
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| ReduceSum<T extends TType> |
Computes the sum of elements across dimensions of a tensor.
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| ReduceSum.Inputs<T extends TType> |
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| ReduceSum.Options |
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| RefEnter<T extends TType> |
Creates or finds a child frame, and makes data available to the child frame.
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| RefEnter.Inputs<T extends TType> |
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| RefEnter.Options |
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| RefExit<T extends TType> |
Exits the current frame to its parent frame.
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| RefExit.Inputs<T extends TType> |
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| RefIdentity<T extends TType> |
Return the same ref tensor as the input ref tensor.
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| RefIdentity.Inputs<T extends TType> |
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| RefMerge<T extends TType> |
Forwards the value of an available tensor from inputs to output.
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| RefMerge.Inputs<T extends TType> |
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| RefNextIteration<T extends TType> |
Makes its input available to the next iteration.
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| RefNextIteration.Inputs<T extends TType> |
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| RefSelect<T extends TType> |
Forwards the indexth element of inputs to output.
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| RefSelect.Inputs<T extends TType> |
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| RefSwitch<T extends TType> |
Forwards the ref tensor data to the output port determined by pred.
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| RefSwitch.Inputs<T extends TType> |
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| RegexFullMatch |
Check if the input matches the regex pattern.
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| RegexFullMatch.Inputs |
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| RegexReplace |
Replaces matches of the pattern regular expression in input with the
replacement string provided in rewrite.
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| RegexReplace.Inputs |
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| RegexReplace.Options |
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| RegisterDataset |
Registers a dataset with the tf.data service.
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| RegisterDataset.Inputs |
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| RegisterDataset.Options |
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| Relayout<T extends TType> |
The Relayout operation
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| Relayout.Inputs<T extends TType> |
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| RelayoutLike<T extends TType> |
The RelayoutLike operation
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| RelayoutLike.Inputs<T extends TType> |
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| Relu<T extends TNumber> |
Computes rectified linear: max(features, 0).
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| Relu.Inputs<T extends TNumber> |
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| Relu6<T extends TNumber> |
Computes rectified linear 6: min(max(features, 0), 6).
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| Relu6.Inputs<T extends TNumber> |
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| Relu6Grad<T extends TNumber> |
Computes rectified linear 6 gradients for a Relu6 operation.
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| Relu6Grad.Inputs<T extends TNumber> |
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| ReluGrad<T extends TNumber> |
Computes rectified linear gradients for a Relu operation.
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| ReluGrad.Inputs<T extends TNumber> |
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| RemoteCall |
Runs function f on a remote device indicated by target.
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| RemoteCall.Inputs |
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| RepeatDataset |
Creates a dataset that emits the outputs of input_dataset count times.
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| RepeatDataset.Inputs |
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| RepeatDataset.Options |
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| ReplicatedInput<T extends TType> |
Connects N inputs to an N-way replicated TPU computation.
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| ReplicatedInput.Inputs<T extends TType> |
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| ReplicatedInput.Options |
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| ReplicatedOutput<T extends TType> |
Connects N outputs from an N-way replicated TPU computation.
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| ReplicatedOutput.Inputs<T extends TType> |
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| ReplicateMetadata |
Metadata indicating how the TPU computation should be replicated.
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| ReplicateMetadata.Inputs |
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| ReplicateMetadata.Options |
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| RequantizationRange |
Computes a range that covers the actual values present in a quantized tensor.
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| RequantizationRange.Inputs |
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| RequantizationRangePerChannel |
Computes requantization range per channel.
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| RequantizationRangePerChannel.Inputs |
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| Requantize<U extends TNumber> |
Converts the quantized input tensor into a lower-precision output.
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| Requantize.Inputs |
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| RequantizePerChannel<U extends TNumber> |
Requantizes input with min and max values known per channel.
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| RequantizePerChannel.Inputs |
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| Reshape<T extends TType> |
Reshapes a tensor.
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| Reshape.Inputs<T extends TType> |
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| ResizeArea |
Resize images to size using area interpolation.
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| ResizeArea.Inputs |
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| ResizeArea.Options |
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| ResizeBicubic |
Resize images to size using bicubic interpolation.
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| ResizeBicubic.Inputs |
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| ResizeBicubic.Options |
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| ResizeBicubicGrad<T extends TNumber> |
Computes the gradient of bicubic interpolation.
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| ResizeBicubicGrad.Inputs<T extends TNumber> |
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| ResizeBicubicGrad.Options |
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| ResizeBilinear |
Resize images to size using bilinear interpolation.
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| ResizeBilinear.Inputs |
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| ResizeBilinear.Options |
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| ResizeBilinearGrad<T extends TNumber> |
Computes the gradient of bilinear interpolation.
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| ResizeBilinearGrad.Inputs<T extends TNumber> |
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| ResizeBilinearGrad.Options |
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| ResizeNearestNeighbor<T extends TNumber> |
Resize images to size using nearest neighbor interpolation.
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| ResizeNearestNeighbor.Inputs<T extends TNumber> |
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| ResizeNearestNeighbor.Options |
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| ResizeNearestNeighborGrad<T extends TNumber> |
Computes the gradient of nearest neighbor interpolation.
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| ResizeNearestNeighborGrad.Inputs<T extends TNumber> |
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| ResizeNearestNeighborGrad.Options |
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| ResourceAccumulatorApplyGradient |
Applies a gradient to a given accumulator.
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| ResourceAccumulatorApplyGradient.Inputs |
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| ResourceAccumulatorNumAccumulated |
Returns the number of gradients aggregated in the given accumulators.
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| ResourceAccumulatorNumAccumulated.Inputs |
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| ResourceAccumulatorSetGlobalStep |
Updates the accumulator with a new value for global_step.
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| ResourceAccumulatorSetGlobalStep.Inputs |
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| ResourceAccumulatorTakeGradient<T extends TType> |
Extracts the average gradient in the given ConditionalAccumulator.
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| ResourceAccumulatorTakeGradient.Inputs |
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| ResourceApplyAdadelta |
Update '*var' according to the adadelta scheme.
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| ResourceApplyAdadelta.Inputs<T extends TType> |
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| ResourceApplyAdadelta.Options |
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| ResourceApplyAdagrad |
Update '*var' according to the adagrad scheme.
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| ResourceApplyAdagrad.Inputs<T extends TType> |
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| ResourceApplyAdagrad.Options |
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| ResourceApplyAdagradDa |
Update '*var' according to the proximal adagrad scheme.
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| ResourceApplyAdagradDa.Inputs<T extends TType> |
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| ResourceApplyAdagradDa.Options |
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| ResourceApplyAdam |
Update '*var' according to the Adam algorithm.
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| ResourceApplyAdam.Inputs<T extends TType> |
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| ResourceApplyAdam.Options |
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| ResourceApplyAdaMax |
Update '*var' according to the AdaMax algorithm.
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| ResourceApplyAdaMax.Inputs<T extends TType> |
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| ResourceApplyAdaMax.Options |
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| ResourceApplyAdamWithAmsgrad |
Update '*var' according to the Adam algorithm.
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| ResourceApplyAdamWithAmsgrad.Inputs<T extends TType> |
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| ResourceApplyAdamWithAmsgrad.Options |
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| ResourceApplyAddSign |
Update '*var' according to the AddSign update.
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| ResourceApplyAddSign.Inputs<T extends TType> |
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| ResourceApplyAddSign.Options |
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| ResourceApplyCenteredRmsProp |
Update '*var' according to the centered RMSProp algorithm.
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| ResourceApplyCenteredRmsProp.Inputs<T extends TType> |
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| ResourceApplyCenteredRmsProp.Options |
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| ResourceApplyFtrl |
Update '*var' according to the Ftrl-proximal scheme.
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| ResourceApplyFtrl.Inputs<T extends TType> |
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| ResourceApplyFtrl.Options |
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| ResourceApplyGradientDescent |
Update '*var' by subtracting 'alpha' * 'delta' from it.
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| ResourceApplyGradientDescent.Inputs<T extends TType> |
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| ResourceApplyGradientDescent.Options |
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| ResourceApplyKerasMomentum |
Update '*var' according to the momentum scheme.
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| ResourceApplyKerasMomentum.Inputs<T extends TType> |
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| ResourceApplyKerasMomentum.Options |
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| ResourceApplyMomentum |
Update '*var' according to the momentum scheme.
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| ResourceApplyMomentum.Inputs<T extends TType> |
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| ResourceApplyMomentum.Options |
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| ResourceApplyPowerSign |
Update '*var' according to the AddSign update.
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| ResourceApplyPowerSign.Inputs<T extends TType> |
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| ResourceApplyPowerSign.Options |
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| ResourceApplyProximalAdagrad |
Update '*var' and '*accum' according to FOBOS with Adagrad learning rate.
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| ResourceApplyProximalAdagrad.Inputs<T extends TType> |
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| ResourceApplyProximalAdagrad.Options |
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| ResourceApplyProximalGradientDescent |
Update '*var' as FOBOS algorithm with fixed learning rate.
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| ResourceApplyProximalGradientDescent.Inputs<T extends TType> |
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| ResourceApplyProximalGradientDescent.Options |
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| ResourceApplyRmsProp |
Update '*var' according to the RMSProp algorithm.
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| ResourceApplyRmsProp.Inputs<T extends TType> |
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| ResourceApplyRmsProp.Options |
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| ResourceConditionalAccumulator |
A conditional accumulator for aggregating gradients.
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| ResourceConditionalAccumulator.Inputs |
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| ResourceConditionalAccumulator.Options |
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| ResourceCountUpTo<T extends TNumber> |
Increments variable pointed to by 'resource' until it reaches 'limit'.
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| ResourceCountUpTo.Inputs |
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| ResourceGather<U extends TType> |
Gather slices from the variable pointed to by resource according to indices.
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| ResourceGather.Inputs |
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| ResourceGather.Options |
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| ResourceGatherNd<U extends TType> |
The ResourceGatherNd operation
|
| ResourceGatherNd.Inputs |
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| ResourceScatterAdd |
Adds sparse updates to the variable referenced by resource.
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| ResourceScatterAdd.Inputs |
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| ResourceScatterDiv |
Divides sparse updates into the variable referenced by resource.
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| ResourceScatterDiv.Inputs |
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| ResourceScatterMax |
Reduces sparse updates into the variable referenced by resource using the max operation.
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| ResourceScatterMax.Inputs |
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| ResourceScatterMin |
Reduces sparse updates into the variable referenced by resource using the min operation.
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| ResourceScatterMin.Inputs |
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| ResourceScatterMul |
Multiplies sparse updates into the variable referenced by resource.
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| ResourceScatterMul.Inputs |
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| ResourceScatterNdAdd |
Applies sparse addition to individual values or slices in a Variable.
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| ResourceScatterNdAdd.Inputs |
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| ResourceScatterNdAdd.Options |
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| ResourceScatterNdMax |
The ResourceScatterNdMax operation
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| ResourceScatterNdMax.Inputs |
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| ResourceScatterNdMax.Options |
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| ResourceScatterNdMin |
The ResourceScatterNdMin operation
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| ResourceScatterNdMin.Inputs |
|
| ResourceScatterNdMin.Options |
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| ResourceScatterNdSub |
Applies sparse subtraction to individual values or slices in a Variable.
|
| ResourceScatterNdSub.Inputs |
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| ResourceScatterNdSub.Options |
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| ResourceScatterNdUpdate |
Applies sparse updates to individual values or slices within a given
variable according to indices.
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| ResourceScatterNdUpdate.Inputs |
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| ResourceScatterNdUpdate.Options |
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| ResourceScatterSub |
Subtracts sparse updates from the variable referenced by resource.
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| ResourceScatterSub.Inputs |
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| ResourceScatterUpdate |
Assigns sparse updates to the variable referenced by resource.
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| ResourceScatterUpdate.Inputs |
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| ResourceSparseApplyAdadelta |
var: Should be from a Variable().
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| ResourceSparseApplyAdadelta.Inputs<T extends TType> |
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| ResourceSparseApplyAdadelta.Options |
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| ResourceSparseApplyAdagrad |
Update relevant entries in '*var' and '*accum' according to the adagrad scheme.
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| ResourceSparseApplyAdagrad.Inputs<T extends TType> |
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| ResourceSparseApplyAdagrad.Options |
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| ResourceSparseApplyAdagradDa |
Update entries in '*var' and '*accum' according to the proximal adagrad scheme.
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| ResourceSparseApplyAdagradDa.Inputs<T extends TType> |
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| ResourceSparseApplyAdagradDa.Options |
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| ResourceSparseApplyAdagradV2 |
Update relevant entries in '*var' and '*accum' according to the adagrad scheme.
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| ResourceSparseApplyAdagradV2.Inputs<T extends TType> |
|
| ResourceSparseApplyAdagradV2.Options |
|
| ResourceSparseApplyCenteredRmsProp |
Update '*var' according to the centered RMSProp algorithm.
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| ResourceSparseApplyCenteredRmsProp.Inputs<T extends TType> |
|
| ResourceSparseApplyCenteredRmsProp.Options |
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| ResourceSparseApplyFtrl |
Update relevant entries in '*var' according to the Ftrl-proximal scheme.
|
| ResourceSparseApplyFtrl.Inputs<T extends TType> |
|
| ResourceSparseApplyFtrl.Options |
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| ResourceSparseApplyKerasMomentum |
Update relevant entries in '*var' and '*accum' according to the momentum scheme.
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| ResourceSparseApplyKerasMomentum.Inputs<T extends TType> |
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| ResourceSparseApplyKerasMomentum.Options |
|
| ResourceSparseApplyMomentum |
Update relevant entries in '*var' and '*accum' according to the momentum scheme.
|
| ResourceSparseApplyMomentum.Inputs<T extends TType> |
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| ResourceSparseApplyMomentum.Options |
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| ResourceSparseApplyProximalAdagrad |
Sparse update entries in '*var' and '*accum' according to FOBOS algorithm.
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| ResourceSparseApplyProximalAdagrad.Inputs<T extends TType> |
|
| ResourceSparseApplyProximalAdagrad.Options |
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| ResourceSparseApplyProximalGradientDescent |
Sparse update '*var' as FOBOS algorithm with fixed learning rate.
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| ResourceSparseApplyProximalGradientDescent.Inputs<T extends TType> |
|
| ResourceSparseApplyProximalGradientDescent.Options |
|
| ResourceSparseApplyRmsProp |
Update '*var' according to the RMSProp algorithm.
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| ResourceSparseApplyRmsProp.Inputs<T extends TType> |
|
| ResourceSparseApplyRmsProp.Options |
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| ResourceStridedSliceAssign |
Assign value to the sliced l-value reference of ref.
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| ResourceStridedSliceAssign.Inputs<T extends TNumber> |
|
| ResourceStridedSliceAssign.Options |
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| Restore |
Restores tensors from a V2 checkpoint.
|
| Restore.Inputs |
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| RestoreSlice<T extends TType> |
Restores a tensor from checkpoint files.
|
| RestoreSlice.Inputs |
|
| RestoreSlice.Options |
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| Result |
|
| RetrieveAllTPUEmbeddingParameters |
An op that retrieves optimization parameters from embedding to host memory.
|
| RetrieveAllTPUEmbeddingParameters.Inputs |
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| RetrieveTPUEmbeddingAdadeltaParameters |
Retrieve Adadelta embedding parameters.
|
| RetrieveTPUEmbeddingAdadeltaParameters.Inputs |
|
| RetrieveTPUEmbeddingAdadeltaParameters.Options |
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| RetrieveTPUEmbeddingAdagradMomentumParameters |
Retrieve Adagrad Momentum embedding parameters.
|
| RetrieveTPUEmbeddingAdagradMomentumParameters.Inputs |
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| RetrieveTPUEmbeddingAdagradMomentumParameters.Options |
|
| RetrieveTPUEmbeddingAdagradParameters |
Retrieve Adagrad embedding parameters.
|
| RetrieveTPUEmbeddingAdagradParameters.Inputs |
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| RetrieveTPUEmbeddingAdagradParameters.Options |
|
| RetrieveTPUEmbeddingADAMParameters |
Retrieve ADAM embedding parameters.
|
| RetrieveTPUEmbeddingADAMParameters.Inputs |
|
| RetrieveTPUEmbeddingADAMParameters.Options |
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| RetrieveTPUEmbeddingCenteredRMSPropParameters |
Retrieve centered RMSProp embedding parameters.
|
| RetrieveTPUEmbeddingCenteredRMSPropParameters.Inputs |
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| 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 |
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| 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 |
|
| 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 |
|
| RfftNd<U extends TType> |
ND fast real Fourier transform.
|
| RfftNd.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> |
|
| 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> |
|
| 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> |
|
| 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 |
|
| SaveDataset |
The SaveDatasetV2 operation
|
| SaveDataset.Inputs |
|
| SaveDataset.Options |
|
| SavedModelBundle |
SavedModelBundle represents a model loaded from storage.
|
| SavedModelBundle.Exporter |
Options for exporting a SavedModel.
|
| SavedModelBundle.Loader |
Options for loading a SavedModel.
|
| 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 |
|
| 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.
|
| 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> |
|
| SelfAdjointEig<T extends TType> |
Computes the eigen decomposition of one or more square self-adjoint matrices.
|
| 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.Inputs |
|
| Send.Options |
Optional attributes for Send |
| SendTPUEmbeddingGradients |
Performs gradient updates of embedding tables.
|
| SendTPUEmbeddingGradients.Inputs |
|
| SendTPUEmbeddingGradients.Options |
|
| 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.
|
| Session |
Driver for Graph execution. |
| SessionFunction |
A callable function backed by a session.
|
| SetDiff1d<T extends TType,U extends TNumber> |
Computes the difference between two lists of numbers or strings.
|
| SetDiff1d.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.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 |
|
| 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 |
|
| 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.Inputs<T extends TType> |
|
| SnapshotChunkDataset |
The SnapshotChunkDataset operation
|
| SnapshotChunkDataset.Inputs |
|
| SnapshotChunkDataset.Options |
|
| SnapshotDataset |
Creates a dataset that will write to / read from a snapshot.
|
| SnapshotDataset.Inputs |
|
| SnapshotDataset.Options |
|
| SnapshotDatasetReader |
The SnapshotDatasetReader operation
|
| SnapshotDatasetReader.Inputs |
|
| SnapshotDatasetReader.Options |
|
| SnapshotNestedDatasetReader |
The SnapshotNestedDatasetReader operation
|
| SnapshotNestedDatasetReader.Inputs |
|
| 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 |
| 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> |
|
| SparseSegmentMean.Options |
|
| SparseSegmentMeanGrad<T extends TNumber,U extends TNumber> |
Computes gradients for SparseSegmentMean.
|
| SparseSegmentMeanGrad.Inputs<T extends TNumber,U extends TNumber> |
|
| SparseSegmentMeanWithNumSegments<T extends TNumber> |
Computes the mean along sparse segments of a tensor.
|
| SparseSegmentMeanWithNumSegments.Inputs<T extends TNumber> |
|
| SparseSegmentMeanWithNumSegments.Options |
|
| SparseSegmentSqrtN<T extends TNumber> |
Computes the sum along sparse segments of a tensor divided by the sqrt of N.
|
| SparseSegmentSqrtN.Inputs<T extends TNumber> |
|
| SparseSegmentSqrtN.Options |
|
| SparseSegmentSqrtNGrad<T extends TNumber,U extends TNumber> |
Computes gradients for SparseSegmentSqrtN.
|
| SparseSegmentSqrtNGrad.Inputs<T extends TNumber,U 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> |
|
| SparseSegmentSqrtNWithNumSegments.Options |
|
| SparseSegmentSum<T extends TNumber> |
Computes the sum along sparse segments of a tensor.
|
| SparseSegmentSum.Inputs<T extends TNumber> |
|
| SparseSegmentSum.Options |
|
| SparseSegmentSumGrad<T extends TNumber,U extends TNumber> |
Computes gradients for SparseSegmentSum.
|
| SparseSegmentSumGrad.Inputs<T extends TNumber,U extends TNumber> |
|
| SparseSegmentSumWithNumSegments<T extends TNumber> |
Computes the sum along sparse segments of a tensor.
|
| SparseSegmentSumWithNumSegments.Inputs<T extends TNumber> |
|
| SparseSegmentSumWithNumSegments.Options |
|
| 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> |
|
| SplitDedupData<T extends TNumber,U extends TNumber> |
An op splits input deduplication data XLA tuple into integer and floating point
tensors.
|
| SplitDedupData.Inputs |
|
| SplitDedupData.Options |
|
| 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> |
|
| 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 |
| StackClose |
Delete the stack from its resource container.
|
| StackClose.Inputs |
|
| StackCreate |
A stack that produces elements in first-in last-out order.
|
| StackCreate.Inputs |
|
| StackCreate.Options |
|
| StackPop<T extends TType> |
Pop the element at the top of the stack.
|
| StackPop.Inputs |
|
| StackPush<T extends TType> |
Push an element onto the stack.
|
| StackPush.Inputs<T extends TType> |
|
| StackPush.Options |
|
| 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 |
|
| StatefulPartitionedCall.Options |
|
| 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> |
|
| StatelessRandomBinomial<W extends TNumber> |
Outputs deterministic pseudorandom random numbers from a binomial distribution.
|
| StatelessRandomBinomial.Inputs<V extends TNumber> |
|
| StatelessRandomGamma<U extends TNumber> |
Outputs deterministic pseudorandom random numbers from a gamma distribution.
|
| StatelessRandomGamma.Inputs<U 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 |
|
| StochasticCastToInt<U extends TNumber> |
Stochastically cast a given tensor from floats to ints.
|
| StochasticCastToInt.Inputs |
|
| StopGradient<T extends TType> |
Stops gradient computation.
|
| StopGradient.Inputs<T extends TType> |
|
| StoreMinibatchStatisticsInFdo |
The StoreMinibatchStatisticsInFdo operation
|
| StoreMinibatchStatisticsInFdo.Inputs |
|
| 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 |
|
| 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 |
| SummaryOps |
An API for building summary operations as Ops |
| SummaryWriter |
The SummaryWriter operation
|
| SummaryWriter.Inputs |
|
| SummaryWriter.Options |
|
| Svd<T extends TType> |
Computes the singular value decompositions of one or more matrices.
|
| 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 |
|
| SyncDevice |
Synchronizes the device this op is run on.
|
| SyncDevice.Inputs |
|
| 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> |
|
| 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 |
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 |
|
| TensorDataset |
Creates a dataset that emits components as a tuple of tensors once.
|
| TensorDataset.Inputs |
|
| TensorDataset.Options |
|
| 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 |
Static utility methods describing the TensorFlow runtime.
|
| TensorFunction |
A function that can be called with tensors.
|
| 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> |
Returns the item in the list with the given index.
|
| 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 |
Sets the index-th position of the list to contain the given tensor.
|
| TensorListSetItem.Inputs |
|
| TensorListSetItem.Options |
|
| 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 |
|
| 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> |
|
| TensorSliceDataset |
Creates a dataset that emits each dim-0 slice of components once.
|
| TensorSliceDataset.Inputs |
|
| TensorSliceDataset.Options |
|
| 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.
|
| 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 |
|
| 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.
|
| 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 |
|
| 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 |
|
| ThreadUnsafeUnigramCandidateSampler |
Generates labels for candidate sampling with a learned unigram distribution.
|
| ThreadUnsafeUnigramCandidateSampler.Inputs |
|
| ThreadUnsafeUnigramCandidateSampler.Options |
|
| 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,V 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 |
|
| TPUAnnotateTensorsWithDynamicShape |
The TPUAnnotateTensorsWithDynamicShape operation
|
| TPUAnnotateTensorsWithDynamicShape.Inputs |
|
| TPUCompilationResult |
Deprecated.
|
| TPUCompilationResult.Inputs |
|
| TPUCopyWithDynamicShape |
Op that copies host tensor to device with dynamic shape support.
|
| TPUCopyWithDynamicShape.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 |
|
| TrainOps |
An API for building train operations as Ops |
| 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.
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| TridiagonalMatMul.Inputs<T extends TType> |
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| TridiagonalSolve<T extends TType> |
Solves tridiagonal systems of equations.
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| TridiagonalSolve.Inputs<T extends TType> |
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| TridiagonalSolve.Options |
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| TruncateDiv<T extends TType> |
Returns x / y element-wise, rounded towards zero.
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| TruncateDiv.Inputs<T extends TType> |
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| TruncatedNormal<U extends TNumber> |
Outputs random values from a truncated normal distribution.
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| TruncatedNormal.Inputs |
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| TruncatedNormal.Options |
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| TruncateMod<T extends TNumber> |
Returns element-wise remainder of division.
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| TruncateMod.Inputs<T extends TNumber> |
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| TString |
String type.
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| TType |
Common interface for all typed tensors.
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| TUint16 |
16-bit unsigned integer tensor type.
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| TUint8 |
8-bit unsigned integer tensor type.
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| Unbatch<T extends TType> |
Reverses the operation of Batch for a single output Tensor.
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| Unbatch.Inputs<T extends TType> |
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| Unbatch.Options |
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| UnbatchDataset |
A dataset that splits the elements of its input into multiple elements.
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| UnbatchDataset |
A dataset that splits the elements of its input into multiple elements.
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| UnbatchDataset.Inputs |
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| UnbatchDataset.Inputs |
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| UnbatchDataset.Options |
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| UnbatchGrad<T extends TType> |
Gradient of Unbatch.
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| UnbatchGrad.Inputs<T extends TType> |
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| UnbatchGrad.Options |
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| UncompressElement |
Uncompresses a compressed dataset element.
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| UncompressElement.Inputs |
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| UnicodeDecode<T extends TNumber> |
Decodes each string in input into a sequence of Unicode code points.
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| UnicodeDecode.Inputs |
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| UnicodeDecode.Options |
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| UnicodeDecodeWithOffsets<T extends TNumber> |
Decodes each string in input into a sequence of Unicode code points.
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| UnicodeDecodeWithOffsets.Inputs |
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| UnicodeDecodeWithOffsets.Options |
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| UnicodeEncode |
Encode a tensor of ints into unicode strings.
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| UnicodeEncode.Inputs |
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| UnicodeEncode.Options |
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| UnicodeScript |
Determine the script codes of a given tensor of Unicode integer code points.
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| UnicodeScript.Inputs |
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| UnicodeTranscode |
Transcode the input text from a source encoding to a destination encoding.
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| UnicodeTranscode.Inputs |
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| UnicodeTranscode.Options |
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| UniformCandidateSampler |
Generates labels for candidate sampling with a uniform distribution.
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| UniformCandidateSampler.Inputs |
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| UniformCandidateSampler.Options |
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| UniformDequantize<U extends TNumber> |
Perform dequantization on the quantized Tensor input.
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| UniformDequantize.Inputs |
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| UniformDequantize.Options |
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| UniformQuantize<U extends TNumber> |
Perform quantization on Tensor input.
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| UniformQuantize.Inputs |
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| UniformQuantize.Options |
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| UniformQuantizedAdd<T extends TNumber> |
Perform quantized add of quantized Tensor lhs and quantized Tensor rhs to make quantized output.
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| UniformQuantizedAdd.Inputs<T extends TNumber> |
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| UniformQuantizedAdd.Options |
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| UniformQuantizedClipByValue<T extends TNumber> |
Perform clip by value on the quantized Tensor operand.
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| UniformQuantizedClipByValue.Inputs<T extends TNumber> |
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| UniformQuantizedClipByValue.Options |
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| UniformQuantizedConvolution<U extends TNumber> |
Perform quantized convolution of quantized Tensor lhs and quantized Tensor rhs.
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| UniformQuantizedConvolution.Inputs<T extends TNumber> |
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| UniformQuantizedConvolution.Options |
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| UniformQuantizedConvolutionHybrid<V extends TNumber> |
Perform hybrid quantized convolution of float Tensor lhs and quantized Tensor rhs.
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| UniformQuantizedConvolutionHybrid.Inputs |
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| UniformQuantizedConvolutionHybrid.Options |
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| UniformQuantizedDot<U extends TNumber> |
Perform quantized dot of quantized Tensor lhs and quantized Tensor rhs to make quantized output.
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| UniformQuantizedDot.Inputs<T extends TNumber> |
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| UniformQuantizedDot.Options |
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| UniformQuantizedDotHybrid<V extends TNumber> |
Perform hybrid quantized dot of float Tensor lhs and quantized Tensor rhs.
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| UniformQuantizedDotHybrid.Inputs |
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| UniformQuantizedDotHybrid.Options |
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| UniformRequantize<U extends TNumber> |
Given quantized tensor input, requantize it with new quantization parameters.
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| UniformRequantize.Inputs |
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| UniformRequantize.Options |
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| Unique<T extends TType,V extends TNumber> |
Finds unique elements along an axis of a tensor.
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| Unique.Inputs<T extends TType> |
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| UniqueDataset |
Creates a dataset that contains the unique elements of input_dataset.
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| UniqueDataset |
Creates a dataset that contains the unique elements of input_dataset.
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| UniqueDataset.Inputs |
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| UniqueDataset.Inputs |
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| UniqueDataset.Options |
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| UniqueWithCounts<T extends TType,V extends TNumber> |
Finds unique elements along an axis of a tensor.
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| UniqueWithCounts.Inputs<T extends TType> |
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| UnravelIndex<T extends TNumber> |
Converts an array of flat indices into a tuple of coordinate arrays.
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| UnravelIndex.Inputs<T extends TNumber> |
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| UnsortedSegmentJoin |
The UnsortedSegmentJoin operation
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| UnsortedSegmentJoin.Inputs |
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| UnsortedSegmentJoin.Options |
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| UnsortedSegmentMax<T extends TNumber> |
Computes the maximum along segments of a tensor.
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| UnsortedSegmentMax.Inputs<T extends TNumber> |
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| UnsortedSegmentMin<T extends TNumber> |
Computes the minimum along segments of a tensor.
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| UnsortedSegmentMin.Inputs<T extends TNumber> |
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| UnsortedSegmentProd<T extends TType> |
Computes the product along segments of a tensor.
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| UnsortedSegmentProd.Inputs<T extends TType> |
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| UnsortedSegmentSum<T extends TType> |
Computes the sum along segments of a tensor.
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| UnsortedSegmentSum.Inputs<T extends TType> |
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| Unstack<T extends TType> |
Unpacks a given dimension of a rank-R tensor into num rank-(R-1) tensors.
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| Unstack.Inputs<T extends TType> |
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| Unstack.Options |
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| Unstage |
Op is similar to a lightweight Dequeue.
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| Unstage.Inputs |
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| Unstage.Options |
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| UnwrapDatasetVariant |
The UnwrapDatasetVariant operation
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| UnwrapDatasetVariant.Inputs |
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| Upper |
Converts all lowercase characters into their respective uppercase replacements.
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| Upper.Inputs |
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| Upper.Options |
Optional attributes for Upper |
| UpperBound<U extends TNumber> |
Applies upper_bound(sorted_search_values, values) along each row.
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| UpperBound.Inputs<T extends TType> |
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| VarHandleOp |
Creates a handle to a Variable resource.
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| VarHandleOp.Inputs |
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| VarHandleOp.Options |
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| Variable<T extends TType> |
Holds state in the form of a tensor that persists across steps.
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| Variable.Inputs |
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| Variable.Options |
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| VariableShape<T extends TNumber> |
Returns the shape of the variable pointed to by resource.
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| VariableShape.Inputs |
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| VarIsInitializedOp |
Checks whether a resource handle-based variable has been initialized.
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| VarIsInitializedOp.Inputs |
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| Where |
Returns locations of nonzero / true values in a tensor.
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| Where.Inputs |
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| While |
output = input; While (Cond(output)) { output = Body(output) }
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| While.Options |
Optional attributes for While |
| WholeFileReader |
A Reader that outputs the entire contents of a file as a value.
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| WholeFileReader.Inputs |
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| WholeFileReader.Options |
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| WindowDataset |
Combines (nests of) input elements into a dataset of (nests of) windows.
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| WindowDataset.Inputs |
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| WindowDataset.Options |
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| WindowOp |
The WindowOp operation
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| WindowOp.Inputs |
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| WorkerHeartbeat |
Worker heartbeat op.
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| WorkerHeartbeat.Inputs |
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| WrapDatasetVariant |
The WrapDatasetVariant operation
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| WrapDatasetVariant.Inputs |
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| WriteAudioSummary |
Writes an audio summary.
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| WriteAudioSummary.Inputs |
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| WriteAudioSummary.Options |
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| WriteFile |
Writes contents to the file at input filename.
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| WriteFile.Inputs |
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| WriteGraphSummary |
Writes a graph summary.
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| WriteGraphSummary.Inputs |
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| WriteHistogramSummary |
Writes a histogram summary.
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| WriteHistogramSummary.Inputs |
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| WriteImageSummary |
Writes an image summary.
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| WriteImageSummary.Inputs |
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| WriteImageSummary.Options |
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| WriteRawProtoSummary |
Writes a serialized proto summary.
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| WriteRawProtoSummary.Inputs |
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| WriteScalarSummary |
Writes a scalar summary.
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| WriteScalarSummary.Inputs |
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| WriteSummary |
Writes a tensor summary.
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| WriteSummary.Inputs |
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| Xdivy<T extends TType> |
Returns 0 if x == 0, and x / y otherwise, elementwise.
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| Xdivy.Inputs<T extends TType> |
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| XlaHostCompute |
A pseudo-op to represent host-side computation in an XLA program.
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| XlaHostCompute.Inputs |
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| XlaHostCompute.Options |
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| XlaOps |
An API for building xla operations as Ops |
| XlaRecvFromHost<T extends TType> |
An op to receive a tensor from the host.
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| XlaRecvFromHost.Inputs |
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| XlaRecvTPUEmbeddingActivations |
An op that receives embedding activations on the TPU.
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| XlaRecvTPUEmbeddingActivations.Inputs |
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| XlaRecvTPUEmbeddingDeduplicationData |
Receives deduplication data (indices and weights) from the embedding core.
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| XlaRecvTPUEmbeddingDeduplicationData.Inputs |
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| XlaSendToHost |
An op to send a tensor to the host.
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| XlaSendToHost.Inputs |
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| XlaSendTPUEmbeddingGradients |
An op that performs gradient updates of embedding tables.
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| XlaSendTPUEmbeddingGradients.Inputs |
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| XlaSendTPUEmbeddingGradients.Options |
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| XlaSparseCoreAdagrad |
The XlaSparseCoreAdagrad operation
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| XlaSparseCoreAdagrad.Inputs |
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| XlaSparseCoreAdagradMomentum |
The XlaSparseCoreAdagradMomentum operation
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| XlaSparseCoreAdagradMomentum.Inputs |
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| XlaSparseCoreAdam |
The XlaSparseCoreAdam operation
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| XlaSparseCoreAdam.Inputs |
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| XlaSparseCoreFtrl |
The XlaSparseCoreFtrl operation
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| XlaSparseCoreFtrl.Inputs |
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| XlaSparseCoreSgd |
The XlaSparseCoreSgd operation
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| XlaSparseCoreSgd.Inputs |
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| XlaSparseDenseMatmul |
The XlaSparseDenseMatmul operation
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| XlaSparseDenseMatmul.Inputs |
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| XlaSparseDenseMatmulGradWithAdagradAndCsrInput |
The XlaSparseDenseMatmulGradWithAdagradAndCsrInput operation
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| XlaSparseDenseMatmulGradWithAdagradAndCsrInput.Inputs |
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| XlaSparseDenseMatmulGradWithAdagradAndCsrInput.Options |
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| XlaSparseDenseMatmulGradWithAdagradMomentumAndCsrInput |
The XlaSparseDenseMatmulGradWithAdagradMomentumAndCsrInput operation
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| XlaSparseDenseMatmulGradWithAdagradMomentumAndCsrInput.Inputs |
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| XlaSparseDenseMatmulGradWithAdagradMomentumAndCsrInput.Options |
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| XlaSparseDenseMatmulGradWithAdamAndCsrInput |
The XlaSparseDenseMatmulGradWithAdamAndCsrInput operation
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| XlaSparseDenseMatmulGradWithAdamAndCsrInput.Inputs |
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| XlaSparseDenseMatmulGradWithAdamAndCsrInput.Options |
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| XlaSparseDenseMatmulGradWithFtrlAndCsrInput |
The XlaSparseDenseMatmulGradWithFtrlAndCsrInput operation
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| XlaSparseDenseMatmulGradWithFtrlAndCsrInput.Inputs |
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| XlaSparseDenseMatmulGradWithFtrlAndCsrInput.Options |
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| XlaSparseDenseMatmulGradWithSgdAndCsrInput |
The XlaSparseDenseMatmulGradWithSgdAndCsrInput operation
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| XlaSparseDenseMatmulGradWithSgdAndCsrInput.Inputs |
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| XlaSparseDenseMatmulGradWithSgdAndCsrInput.Options |
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| XlaSparseDenseMatmulWithCsrInput |
The XlaSparseDenseMatmulWithCsrInput operation
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| XlaSparseDenseMatmulWithCsrInput.Inputs |
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| Xlog1py<T extends TType> |
Returns 0 if x == 0, and x * log1p(y) otherwise, elementwise.
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| Xlog1py.Inputs<T extends TType> |
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| Xlogy<T extends TType> |
Returns 0 if x == 0, and x * log(y) otherwise, elementwise.
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| Xlogy.Inputs<T extends TType> |
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| Zeros<T extends TType> |
An operator creating a constant initialized with zeros of the shape given by `dims`.
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| ZerosLike<T extends TType> |
Returns a tensor of zeros with the same shape and type as x.
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| ZerosLike.Inputs<T extends TType> |
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| Zeta<T extends TNumber> |
Compute the Hurwitz zeta function \(\zeta(x, q)\).
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| Zeta.Inputs<T extends TNumber> |
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| ZipDataset |
Creates a dataset that zips together input_datasets.
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| ZipDataset.Inputs |
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| ZipDataset.Options |
|