Uses of Package
org.tensorflow.op.train

Packages that use org.tensorflow.op.train

Package	Description
org.tensorflow.op
org.tensorflow.op.train

Classes in org.tensorflow.op.train used by org.tensorflow.op

Class and Description
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 Extracts the average gradient in the given ConditionalAccumulator.
ApplyAdadelta Update '*var' according to the adadelta scheme.
ApplyAdadelta.Options Optional attributes for ApplyAdadelta
ApplyAdagrad Update '*var' according to the adagrad scheme.
ApplyAdagrad.Options Optional attributes for ApplyAdagrad
ApplyAdagradDa Update '*var' according to the proximal adagrad scheme.
ApplyAdagradDa.Options Optional attributes for ApplyAdagradDa
ApplyAdam Update '*var' according to the Adam algorithm.
ApplyAdam.Options Optional attributes for ApplyAdam
ApplyAddSign Update '*var' according to the AddSign update.
ApplyAddSign.Options Optional attributes for ApplyAddSign
ApplyCenteredRmsProp Update '*var' according to the centered RMSProp algorithm.
ApplyCenteredRmsProp.Options Optional attributes for ApplyCenteredRmsProp
ApplyFtrl Update '*var' according to the Ftrl-proximal scheme.
ApplyFtrl.Options Optional attributes for ApplyFtrl
ApplyGradientDescent Update '*var' by subtracting 'alpha' * 'delta' from it.
ApplyGradientDescent.Options Optional attributes for ApplyGradientDescent
ApplyMomentum Update '*var' according to the momentum scheme.
ApplyMomentum.Options Optional attributes for ApplyMomentum
ApplyPowerSign Update '*var' according to the AddSign update.
ApplyPowerSign.Options Optional attributes for ApplyPowerSign
ApplyProximalAdagrad Update '*var' and '*accum' according to FOBOS with Adagrad learning rate.
ApplyProximalAdagrad.Options Optional attributes for ApplyProximalAdagrad
ApplyProximalGradientDescent Update '*var' as FOBOS algorithm with fixed learning rate.
ApplyProximalGradientDescent.Options Optional attributes for ApplyProximalGradientDescent
ApplyRmsProp Update '*var' according to the RMSProp algorithm.
ApplyRmsProp.Options Optional attributes for ApplyRmsProp
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
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 An identity op that triggers an error if a gradient is requested.
PreventGradient.Options Optional attributes for PreventGradient
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
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
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
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
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
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 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.
SdcaShrinkL1 Applies L1 regularization shrink step on the parameters.
SparseApplyAdadelta var: Should be from a Variable().
SparseApplyAdadelta.Options Optional attributes for SparseApplyAdadelta
SparseApplyAdagrad Update relevant entries in '*var' and '*accum' according to the adagrad scheme.
SparseApplyAdagrad.Options Optional attributes for SparseApplyAdagrad
SparseApplyAdagradDa Update entries in '*var' and '*accum' according to the proximal adagrad scheme.
SparseApplyAdagradDa.Options Optional attributes for SparseApplyAdagradDa
SparseApplyCenteredRmsProp Update '*var' according to the centered RMSProp algorithm.
SparseApplyCenteredRmsProp.Options Optional attributes for SparseApplyCenteredRmsProp
SparseApplyFtrl Update relevant entries in '*var' according to the Ftrl-proximal scheme.
SparseApplyFtrl.Options Optional attributes for SparseApplyFtrl
SparseApplyMomentum Update relevant entries in '*var' and '*accum' according to the momentum scheme.
SparseApplyMomentum.Options Optional attributes for SparseApplyMomentum
SparseApplyProximalAdagrad Sparse update entries in '*var' and '*accum' according to FOBOS algorithm.
SparseApplyProximalAdagrad.Options Optional attributes for SparseApplyProximalAdagrad
SparseApplyProximalGradientDescent Sparse update '*var' as FOBOS algorithm with fixed learning rate.
SparseApplyProximalGradientDescent.Options Optional attributes for SparseApplyProximalGradientDescent
SparseApplyRmsProp Update '*var' according to the RMSProp algorithm.
SparseApplyRmsProp.Options Optional attributes for SparseApplyRmsProp
TileGrad Returns the gradient of `Tile`.

Classes in org.tensorflow.op.train used by org.tensorflow.op.train

Class and Description
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 Extracts the average gradient in the given ConditionalAccumulator.
ApplyAdadelta Update '*var' according to the adadelta scheme.
ApplyAdadelta.Options Optional attributes for ApplyAdadelta
ApplyAdagrad Update '*var' according to the adagrad scheme.
ApplyAdagrad.Options Optional attributes for ApplyAdagrad
ApplyAdagradDa Update '*var' according to the proximal adagrad scheme.
ApplyAdagradDa.Options Optional attributes for ApplyAdagradDa
ApplyAdam Update '*var' according to the Adam algorithm.
ApplyAdam.Options Optional attributes for ApplyAdam
ApplyAdaMax Update '*var' according to the AdaMax algorithm.
ApplyAdaMax.Options Optional attributes for ApplyAdaMax
ApplyAddSign Update '*var' according to the AddSign update.
ApplyAddSign.Options Optional attributes for ApplyAddSign
ApplyCenteredRmsProp Update '*var' according to the centered RMSProp algorithm.
ApplyCenteredRmsProp.Options Optional attributes for ApplyCenteredRmsProp
ApplyFtrl Update '*var' according to the Ftrl-proximal scheme.
ApplyFtrl.Options Optional attributes for ApplyFtrl
ApplyGradientDescent Update '*var' by subtracting 'alpha' * 'delta' from it.
ApplyGradientDescent.Options Optional attributes for ApplyGradientDescent
ApplyMomentum Update '*var' according to the momentum scheme.
ApplyMomentum.Options Optional attributes for ApplyMomentum
ApplyPowerSign Update '*var' according to the AddSign update.
ApplyPowerSign.Options Optional attributes for ApplyPowerSign
ApplyProximalAdagrad Update '*var' and '*accum' according to FOBOS with Adagrad learning rate.
ApplyProximalAdagrad.Options Optional attributes for ApplyProximalAdagrad
ApplyProximalGradientDescent Update '*var' as FOBOS algorithm with fixed learning rate.
ApplyProximalGradientDescent.Options Optional attributes for ApplyProximalGradientDescent
ApplyRmsProp Update '*var' according to the RMSProp algorithm.
ApplyRmsProp.Options Optional attributes for ApplyRmsProp
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
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 An identity op that triggers an error if a gradient is requested.
PreventGradient.Options Optional attributes for PreventGradient
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
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
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
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
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
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 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
SdcaOptimizer.Options Optional attributes for SdcaOptimizer
SdcaShrinkL1 Applies L1 regularization shrink step on the parameters.
SparseApplyAdadelta var: Should be from a Variable().
SparseApplyAdadelta.Options Optional attributes for SparseApplyAdadelta
SparseApplyAdagrad Update relevant entries in '*var' and '*accum' according to the adagrad scheme.
SparseApplyAdagrad.Options Optional attributes for SparseApplyAdagrad
SparseApplyAdagradDa Update entries in '*var' and '*accum' according to the proximal adagrad scheme.
SparseApplyAdagradDa.Options Optional attributes for SparseApplyAdagradDa
SparseApplyCenteredRmsProp Update '*var' according to the centered RMSProp algorithm.
SparseApplyCenteredRmsProp.Options Optional attributes for SparseApplyCenteredRmsProp
SparseApplyFtrl Update relevant entries in '*var' according to the Ftrl-proximal scheme.
SparseApplyFtrl.Options Optional attributes for SparseApplyFtrl
SparseApplyMomentum Update relevant entries in '*var' and '*accum' according to the momentum scheme.
SparseApplyMomentum.Options Optional attributes for SparseApplyMomentum
SparseApplyProximalAdagrad Sparse update entries in '*var' and '*accum' according to FOBOS algorithm.
SparseApplyProximalAdagrad.Options Optional attributes for SparseApplyProximalAdagrad
SparseApplyProximalGradientDescent Sparse update '*var' as FOBOS algorithm with fixed learning rate.
SparseApplyProximalGradientDescent.Options Optional attributes for SparseApplyProximalGradientDescent
SparseApplyRmsProp Update '*var' according to the RMSProp algorithm.
SparseApplyRmsProp.Options Optional attributes for SparseApplyRmsProp
TileGrad Returns the gradient of `Tile`.