org.tensorflow.op.train

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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  
ApplyAdagrad<T extends TType> Update '*var' according to the adagrad scheme. 
ApplyAdagrad.Options Optional attributes for ApplyAdagrad  
ApplyAdagradDa<T extends TType> Update '*var' according to the proximal adagrad scheme. 
ApplyAdagradDa.Options Optional attributes for ApplyAdagradDa  
ApplyAdagradV2<T extends TType> Update '*var' according to the adagrad scheme. 
ApplyAdagradV2.Options Optional attributes for ApplyAdagradV2  
ApplyAdam<T extends TType> Update '*var' according to the Adam algorithm. 
ApplyAdam.Options Optional attributes for ApplyAdam  
ApplyAdaMax<T extends TType> Update '*var' according to the AdaMax algorithm. 
ApplyAdaMax.Options Optional attributes for ApplyAdaMax  
ApplyAddSign<T extends TType> Update '*var' according to the AddSign update. 
ApplyAddSign.Options Optional attributes for ApplyAddSign  
ApplyCenteredRmsProp<T extends TType> Update '*var' according to the centered RMSProp algorithm. 
ApplyCenteredRmsProp.Options Optional attributes for ApplyCenteredRmsProp  
ApplyFtrl<T extends TType> Update '*var' according to the Ftrl-proximal scheme. 
ApplyFtrl.Options Optional attributes for ApplyFtrl  
ApplyGradientDescent<T extends TType> Update '*var' by subtracting 'alpha' * 'delta' from it. 
ApplyGradientDescent.Options Optional attributes for ApplyGradientDescent  
ApplyMomentum<T extends TType> Update '*var' according to the momentum scheme. 
ApplyMomentum.Options Optional attributes for ApplyMomentum  
ApplyPowerSign<T extends TType> Update '*var' according to the AddSign update. 
ApplyPowerSign.Options Optional attributes for ApplyPowerSign  
ApplyProximalAdagrad<T extends TType> Update '*var' and '*accum' according to FOBOS with Adagrad learning rate. 
ApplyProximalAdagrad.Options Optional attributes for ApplyProximalAdagrad  
ApplyProximalGradientDescent<T extends TType> Update '*var' as FOBOS algorithm with fixed learning rate. 
ApplyProximalGradientDescent.Options Optional attributes for ApplyProximalGradientDescent  
ApplyRmsProp<T extends TType> Update '*var' according to the RMSProp algorithm. 
ApplyRmsProp.Options Optional attributes for ApplyRmsProp  
BatchMatMul<T extends TType> Multiplies slices of two tensors in batches. 
BatchMatMul.Options Optional attributes for BatchMatMul  
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  
MergeV2Checkpoints V2 format specific: merges the metadata files of sharded checkpoints. 
MergeV2Checkpoints.Options Optional attributes for MergeV2Checkpoints  
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  
ResourceAccumulatorApplyGradient Applies a gradient to a given accumulator. 
ResourceAccumulatorNumAccumulated Returns the number of gradients aggregated in the given accumulators. 
ResourceAccumulatorSetGlobalStep Updates the accumulator with a new value for global_step. 
ResourceAccumulatorTakeGradient<T extends TType> Extracts the average gradient in the given ConditionalAccumulator. 
ResourceApplyAdadelta Update '*var' according to the adadelta scheme. 
ResourceApplyAdadelta.Options Optional attributes for ResourceApplyAdadelta  
ResourceApplyAdagrad Update '*var' according to the adagrad scheme. 
ResourceApplyAdagrad.Options Optional attributes for ResourceApplyAdagrad  
ResourceApplyAdagradDa Update '*var' according to the proximal adagrad scheme. 
ResourceApplyAdagradDa.Options Optional attributes for ResourceApplyAdagradDa  
ResourceApplyAdam Update '*var' according to the Adam algorithm. 
ResourceApplyAdam.Options Optional attributes for ResourceApplyAdam  
ResourceApplyAdaMax Update '*var' according to the AdaMax algorithm. 
ResourceApplyAdaMax.Options Optional attributes for ResourceApplyAdaMax  
ResourceApplyAdamWithAmsgrad Update '*var' according to the Adam algorithm. 
ResourceApplyAdamWithAmsgrad.Options Optional attributes for ResourceApplyAdamWithAmsgrad  
ResourceApplyAddSign Update '*var' according to the AddSign update. 
ResourceApplyAddSign.Options Optional attributes for ResourceApplyAddSign  
ResourceApplyCenteredRmsProp Update '*var' according to the centered RMSProp algorithm. 
ResourceApplyCenteredRmsProp.Options Optional attributes for ResourceApplyCenteredRmsProp  
ResourceApplyFtrl Update '*var' according to the Ftrl-proximal scheme. 
ResourceApplyFtrl.Options Optional attributes for ResourceApplyFtrl  
ResourceApplyGradientDescent Update '*var' by subtracting 'alpha' * 'delta' from it. 
ResourceApplyGradientDescent.Options Optional attributes for ResourceApplyGradientDescent  
ResourceApplyKerasMomentum Update '*var' according to the momentum scheme. 
ResourceApplyKerasMomentum.Options Optional attributes for ResourceApplyKerasMomentum  
ResourceApplyMomentum Update '*var' according to the momentum scheme. 
ResourceApplyMomentum.Options Optional attributes for ResourceApplyMomentum  
ResourceApplyPowerSign Update '*var' according to the AddSign update. 
ResourceApplyPowerSign.Options Optional attributes for ResourceApplyPowerSign  
ResourceApplyProximalAdagrad Update '*var' and '*accum' according to FOBOS with Adagrad learning rate. 
ResourceApplyProximalAdagrad.Options Optional attributes for ResourceApplyProximalAdagrad  
ResourceApplyProximalGradientDescent Update '*var' as FOBOS algorithm with fixed learning rate. 
ResourceApplyProximalGradientDescent.Options Optional attributes for ResourceApplyProximalGradientDescent  
ResourceApplyRmsProp Update '*var' according to the RMSProp algorithm. 
ResourceApplyRmsProp.Options Optional attributes for ResourceApplyRmsProp  
ResourceConditionalAccumulator A conditional accumulator for aggregating gradients. 
ResourceConditionalAccumulator.Options Optional attributes for ResourceConditionalAccumulator  
ResourceSparseApplyAdadelta var: Should be from a Variable(). 
ResourceSparseApplyAdadelta.Options Optional attributes for ResourceSparseApplyAdadelta  
ResourceSparseApplyAdagrad Update relevant entries in '*var' and '*accum' according to the adagrad scheme. 
ResourceSparseApplyAdagrad.Options Optional attributes for ResourceSparseApplyAdagrad  
ResourceSparseApplyAdagradDa Update entries in '*var' and '*accum' according to the proximal adagrad scheme. 
ResourceSparseApplyAdagradDa.Options Optional attributes for ResourceSparseApplyAdagradDa  
ResourceSparseApplyAdagradV2 Update relevant entries in '*var' and '*accum' according to the adagrad scheme. 
ResourceSparseApplyAdagradV2.Options Optional attributes for ResourceSparseApplyAdagradV2  
ResourceSparseApplyCenteredRmsProp Update '*var' according to the centered RMSProp algorithm. 
ResourceSparseApplyCenteredRmsProp.Options Optional attributes for ResourceSparseApplyCenteredRmsProp  
ResourceSparseApplyFtrl Update relevant entries in '*var' according to the Ftrl-proximal scheme. 
ResourceSparseApplyFtrl.Options Optional attributes for ResourceSparseApplyFtrl  
ResourceSparseApplyKerasMomentum Update relevant entries in '*var' and '*accum' according to the momentum scheme. 
ResourceSparseApplyKerasMomentum.Options Optional attributes for ResourceSparseApplyKerasMomentum  
ResourceSparseApplyMomentum Update relevant entries in '*var' and '*accum' according to the momentum scheme. 
ResourceSparseApplyMomentum.Options Optional attributes for ResourceSparseApplyMomentum  
ResourceSparseApplyProximalAdagrad Sparse update entries in '*var' and '*accum' according to FOBOS algorithm. 
ResourceSparseApplyProximalAdagrad.Options Optional attributes for ResourceSparseApplyProximalAdagrad  
ResourceSparseApplyProximalGradientDescent Sparse update '*var' as FOBOS algorithm with fixed learning rate. 
ResourceSparseApplyProximalGradientDescent.Options Optional attributes for ResourceSparseApplyProximalGradientDescent  
ResourceSparseApplyRmsProp Update '*var' according to the RMSProp algorithm. 
ResourceSparseApplyRmsProp.Options Optional attributes for ResourceSparseApplyRmsProp  
Restore Restores tensors from a V2 checkpoint. 
RestoreSlice<T extends TType> Restores a tensor from checkpoint files. 
RestoreSlice.Options Optional attributes for RestoreSlice  
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  
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  
SparseApplyAdagrad<T extends TType> Update relevant entries in '*var' and '*accum' according to the adagrad scheme. 
SparseApplyAdagrad.Options Optional attributes for SparseApplyAdagrad  
SparseApplyAdagradDa<T extends TType> Update entries in '*var' and '*accum' according to the proximal adagrad scheme. 
SparseApplyAdagradDa.Options Optional attributes for SparseApplyAdagradDa  
SparseApplyCenteredRmsProp<T extends TType> Update '*var' according to the centered RMSProp algorithm. 
SparseApplyCenteredRmsProp.Options Optional attributes for SparseApplyCenteredRmsProp  
SparseApplyFtrl<T extends TType> Update relevant entries in '*var' according to the Ftrl-proximal scheme. 
SparseApplyFtrl.Options Optional attributes for SparseApplyFtrl  
SparseApplyMomentum<T extends TType> Update relevant entries in '*var' and '*accum' according to the momentum scheme. 
SparseApplyMomentum.Options Optional attributes for SparseApplyMomentum  
SparseApplyProximalAdagrad<T extends TType> Sparse update entries in '*var' and '*accum' according to FOBOS algorithm. 
SparseApplyProximalAdagrad.Options Optional attributes for SparseApplyProximalAdagrad  
SparseApplyProximalGradientDescent<T extends TType> Sparse update '*var' as FOBOS algorithm with fixed learning rate. 
SparseApplyProximalGradientDescent.Options Optional attributes for SparseApplyProximalGradientDescent  
SparseApplyRmsProp<T extends TType> Update '*var' according to the RMSProp algorithm. 
SparseApplyRmsProp.Options Optional attributes for SparseApplyRmsProp  
TileGrad<T extends TType> Returns the gradient of `Tile`.