Classes
AccumulatorApplyGradient | Applies a gradient to a given accumulator. |
AccumulatorNumAccumulated | Returns the number of gradients aggregated in the given accumulators. |
AccumulatorSetGlobalStep | Updates the accumulator with a new value for global_step. |
AccumulatorTakeGradient<T extends TType> | Extracts the average gradient in the given ConditionalAccumulator. |
ApplyAdadelta<T extends TType> | Update '*var' according to the adadelta scheme. |
ApplyAdadelta.Options | Optional attributes for ApplyAdadelta
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ApplyAdagrad<T extends TType> | Update '*var' according to the adagrad scheme. |
ApplyAdagrad.Options | Optional attributes for ApplyAdagrad
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ApplyAdagradDa<T extends TType> | Update '*var' according to the proximal adagrad scheme. |
ApplyAdagradDa.Options | Optional attributes for ApplyAdagradDa
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ApplyAdagradV2<T extends TType> | Update '*var' according to the adagrad scheme. |
ApplyAdagradV2.Options | Optional attributes for ApplyAdagradV2
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ApplyAdam<T extends TType> | Update '*var' according to the Adam algorithm. |
ApplyAdam.Options | Optional attributes for ApplyAdam
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ApplyAdaMax<T extends TType> | Update '*var' according to the AdaMax algorithm. |
ApplyAdaMax.Options | Optional attributes for ApplyAdaMax
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ApplyAddSign<T extends TType> | Update '*var' according to the AddSign update. |
ApplyAddSign.Options | Optional attributes for ApplyAddSign
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ApplyCenteredRmsProp<T extends TType> | Update '*var' according to the centered RMSProp algorithm. |
ApplyCenteredRmsProp.Options | Optional attributes for ApplyCenteredRmsProp
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ApplyFtrl<T extends TType> | Update '*var' according to the Ftrl-proximal scheme. |
ApplyFtrl.Options | Optional attributes for ApplyFtrl
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ApplyGradientDescent<T extends TType> | Update '*var' by subtracting 'alpha' * 'delta' from it. |
ApplyGradientDescent.Options | Optional attributes for ApplyGradientDescent
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ApplyMomentum<T extends TType> | Update '*var' according to the momentum scheme. |
ApplyMomentum.Options | Optional attributes for ApplyMomentum
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ApplyPowerSign<T extends TType> | Update '*var' according to the AddSign update. |
ApplyPowerSign.Options | Optional attributes for ApplyPowerSign
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ApplyProximalAdagrad<T extends TType> | Update '*var' and '*accum' according to FOBOS with Adagrad learning rate. |
ApplyProximalAdagrad.Options | Optional attributes for ApplyProximalAdagrad
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ApplyProximalGradientDescent<T extends TType> | Update '*var' as FOBOS algorithm with fixed learning rate. |
ApplyProximalGradientDescent.Options | Optional attributes for ApplyProximalGradientDescent
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ApplyRmsProp<T extends TType> | Update '*var' according to the RMSProp algorithm. |
ApplyRmsProp.Options | Optional attributes for ApplyRmsProp
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BatchMatMul<T extends TType> | Multiplies slices of two tensors in batches. |
BatchMatMul.Options | Optional attributes for BatchMatMul
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ComputeBatchSize | Computes the static batch size of a dataset sans partial batches. |
ConditionalAccumulator | A conditional accumulator for aggregating gradients. |
ConditionalAccumulator.Options | Optional attributes for ConditionalAccumulator
|
GenerateVocabRemapping | Given a path to new and old vocabulary files, returns a remapping Tensor of
length `num_new_vocab`, where `remapping[i]` contains the row number in the old vocabulary that corresponds to row `i` in the new vocabulary (starting at line `new_vocab_offset` and up to `num_new_vocab` entities), or `-1` if entry `i` in the new vocabulary is not in the old vocabulary. |
GenerateVocabRemapping.Options | Optional attributes for GenerateVocabRemapping
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MergeV2Checkpoints | V2 format specific: merges the metadata files of sharded checkpoints. |
MergeV2Checkpoints.Options | Optional attributes for MergeV2Checkpoints
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NegTrain | Training via negative sampling. |
PreventGradient<T extends TType> | An identity op that triggers an error if a gradient is requested. |
PreventGradient.Options | Optional attributes for PreventGradient
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ResourceAccumulatorApplyGradient | Applies a gradient to a given accumulator. |
ResourceAccumulatorNumAccumulated | Returns the number of gradients aggregated in the given accumulators. |
ResourceAccumulatorSetGlobalStep | Updates the accumulator with a new value for global_step. |
ResourceAccumulatorTakeGradient<T extends TType> | Extracts the average gradient in the given ConditionalAccumulator. |
ResourceApplyAdadelta | Update '*var' according to the adadelta scheme. |
ResourceApplyAdadelta.Options | Optional attributes for ResourceApplyAdadelta
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ResourceApplyAdagrad | Update '*var' according to the adagrad scheme. |
ResourceApplyAdagrad.Options | Optional attributes for ResourceApplyAdagrad
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ResourceApplyAdagradDa | Update '*var' according to the proximal adagrad scheme. |
ResourceApplyAdagradDa.Options | Optional attributes for ResourceApplyAdagradDa
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ResourceApplyAdam | Update '*var' according to the Adam algorithm. |
ResourceApplyAdam.Options | Optional attributes for ResourceApplyAdam
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ResourceApplyAdaMax | Update '*var' according to the AdaMax algorithm. |
ResourceApplyAdaMax.Options | Optional attributes for ResourceApplyAdaMax
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ResourceApplyAdamWithAmsgrad | Update '*var' according to the Adam algorithm. |
ResourceApplyAdamWithAmsgrad.Options | Optional attributes for ResourceApplyAdamWithAmsgrad
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ResourceApplyAddSign | Update '*var' according to the AddSign update. |
ResourceApplyAddSign.Options | Optional attributes for ResourceApplyAddSign
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ResourceApplyCenteredRmsProp | Update '*var' according to the centered RMSProp algorithm. |
ResourceApplyCenteredRmsProp.Options | Optional attributes for ResourceApplyCenteredRmsProp
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ResourceApplyFtrl | Update '*var' according to the Ftrl-proximal scheme. |
ResourceApplyFtrl.Options | Optional attributes for ResourceApplyFtrl
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ResourceApplyGradientDescent | Update '*var' by subtracting 'alpha' * 'delta' from it. |
ResourceApplyGradientDescent.Options | Optional attributes for ResourceApplyGradientDescent
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ResourceApplyKerasMomentum | Update '*var' according to the momentum scheme. |
ResourceApplyKerasMomentum.Options | Optional attributes for ResourceApplyKerasMomentum
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ResourceApplyMomentum | Update '*var' according to the momentum scheme. |
ResourceApplyMomentum.Options | Optional attributes for ResourceApplyMomentum
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ResourceApplyPowerSign | Update '*var' according to the AddSign update. |
ResourceApplyPowerSign.Options | Optional attributes for ResourceApplyPowerSign
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ResourceApplyProximalAdagrad | Update '*var' and '*accum' according to FOBOS with Adagrad learning rate. |
ResourceApplyProximalAdagrad.Options | Optional attributes for ResourceApplyProximalAdagrad
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ResourceApplyProximalGradientDescent | Update '*var' as FOBOS algorithm with fixed learning rate. |
ResourceApplyProximalGradientDescent.Options | Optional attributes for ResourceApplyProximalGradientDescent
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ResourceApplyRmsProp | Update '*var' according to the RMSProp algorithm. |
ResourceApplyRmsProp.Options | Optional attributes for ResourceApplyRmsProp
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ResourceConditionalAccumulator | A conditional accumulator for aggregating gradients. |
ResourceConditionalAccumulator.Options | Optional attributes for ResourceConditionalAccumulator
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ResourceSparseApplyAdadelta | var: Should be from a Variable(). |
ResourceSparseApplyAdadelta.Options | Optional attributes for ResourceSparseApplyAdadelta
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ResourceSparseApplyAdagrad | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
ResourceSparseApplyAdagrad.Options | Optional attributes for ResourceSparseApplyAdagrad
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ResourceSparseApplyAdagradDa | Update entries in '*var' and '*accum' according to the proximal adagrad scheme. |
ResourceSparseApplyAdagradDa.Options | Optional attributes for ResourceSparseApplyAdagradDa
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ResourceSparseApplyAdagradV2 | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
ResourceSparseApplyAdagradV2.Options | Optional attributes for ResourceSparseApplyAdagradV2
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ResourceSparseApplyCenteredRmsProp | Update '*var' according to the centered RMSProp algorithm. |
ResourceSparseApplyCenteredRmsProp.Options | Optional attributes for ResourceSparseApplyCenteredRmsProp
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ResourceSparseApplyFtrl | Update relevant entries in '*var' according to the Ftrl-proximal scheme. |
ResourceSparseApplyFtrl.Options | Optional attributes for ResourceSparseApplyFtrl
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ResourceSparseApplyKerasMomentum | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
ResourceSparseApplyKerasMomentum.Options | Optional attributes for ResourceSparseApplyKerasMomentum
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ResourceSparseApplyMomentum | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
ResourceSparseApplyMomentum.Options | Optional attributes for ResourceSparseApplyMomentum
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ResourceSparseApplyProximalAdagrad | Sparse update entries in '*var' and '*accum' according to FOBOS algorithm. |
ResourceSparseApplyProximalAdagrad.Options | Optional attributes for ResourceSparseApplyProximalAdagrad
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ResourceSparseApplyProximalGradientDescent | Sparse update '*var' as FOBOS algorithm with fixed learning rate. |
ResourceSparseApplyProximalGradientDescent.Options | Optional attributes for ResourceSparseApplyProximalGradientDescent
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ResourceSparseApplyRmsProp | Update '*var' according to the RMSProp algorithm. |
ResourceSparseApplyRmsProp.Options | Optional attributes for ResourceSparseApplyRmsProp
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Restore | Restores tensors from a V2 checkpoint. |
RestoreSlice<T extends TType> | Restores a tensor from checkpoint files. |
RestoreSlice.Options | Optional attributes for RestoreSlice
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Save | Saves tensors in V2 checkpoint format. |
SaveSlices | Saves input tensors slices to disk. |
SdcaFprint | Computes fingerprints of the input strings. |
SdcaOptimizer | Distributed version of Stochastic Dual Coordinate Ascent (SDCA) optimizer for
linear models with L1 + L2 regularization. |
SdcaOptimizer.Options | Optional attributes for SdcaOptimizer
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SdcaShrinkL1 | Applies L1 regularization shrink step on the parameters. |
SparseApplyAdadelta<T extends TType> | var: Should be from a Variable(). |
SparseApplyAdadelta.Options | Optional attributes for SparseApplyAdadelta
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SparseApplyAdagrad<T extends TType> | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
SparseApplyAdagrad.Options | Optional attributes for SparseApplyAdagrad
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SparseApplyAdagradDa<T extends TType> | Update entries in '*var' and '*accum' according to the proximal adagrad scheme. |
SparseApplyAdagradDa.Options | Optional attributes for SparseApplyAdagradDa
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SparseApplyCenteredRmsProp<T extends TType> | Update '*var' according to the centered RMSProp algorithm. |
SparseApplyCenteredRmsProp.Options | Optional attributes for SparseApplyCenteredRmsProp
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SparseApplyFtrl<T extends TType> | Update relevant entries in '*var' according to the Ftrl-proximal scheme. |
SparseApplyFtrl.Options | Optional attributes for SparseApplyFtrl
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SparseApplyMomentum<T extends TType> | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
SparseApplyMomentum.Options | Optional attributes for SparseApplyMomentum
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SparseApplyProximalAdagrad<T extends TType> | Sparse update entries in '*var' and '*accum' according to FOBOS algorithm. |
SparseApplyProximalAdagrad.Options | Optional attributes for SparseApplyProximalAdagrad
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SparseApplyProximalGradientDescent<T extends TType> | Sparse update '*var' as FOBOS algorithm with fixed learning rate. |
SparseApplyProximalGradientDescent.Options | Optional attributes for SparseApplyProximalGradientDescent
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SparseApplyRmsProp<T extends TType> | Update '*var' according to the RMSProp algorithm. |
SparseApplyRmsProp.Options | Optional attributes for SparseApplyRmsProp
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TileGrad<T extends TType> | Returns the gradient of `Tile`. |