Training Ops

Summary

Classes

tensorflow::ops::ApplyAdadelta

Update '*var' according to the adadelta scheme.

tensorflow::ops::ApplyAdagrad

Update '*var' according to the adagrad scheme.

tensorflow::ops::ApplyAdagradDA

Update '*var' according to the proximal adagrad scheme.

tensorflow::ops::ApplyAdam

Update '*var' according to the Adam algorithm.

tensorflow::ops::ApplyAddSign

Update '*var' according to the AddSign update.

tensorflow::ops::ApplyCenteredRMSProp

Update '*var' according to the centered RMSProp algorithm.

tensorflow::ops::ApplyFtrl

Update '*var' according to the Ftrl-proximal scheme.

tensorflow::ops::ApplyFtrlV2

Update '*var' according to the Ftrl-proximal scheme.

tensorflow::ops::ApplyGradientDescent

Update '*var' by subtracting 'alpha' * 'delta' from it.

tensorflow::ops::ApplyMomentum

Update '*var' according to the momentum scheme.

tensorflow::ops::ApplyPowerSign

Update '*var' according to the AddSign update.

tensorflow::ops::ApplyProximalAdagrad

Update '*var' and '*accum' according to FOBOS with Adagrad learning rate.

tensorflow::ops::ApplyProximalGradientDescent

Update '*var' as FOBOS algorithm with fixed learning rate.

tensorflow::ops::ApplyRMSProp

Update '*var' according to the RMSProp algorithm.

tensorflow::ops::ResourceApplyAdadelta

Update '*var' according to the adadelta scheme.

tensorflow::ops::ResourceApplyAdagrad

Update '*var' according to the adagrad scheme.

tensorflow::ops::ResourceApplyAdagradDA

Update '*var' according to the proximal adagrad scheme.

tensorflow::ops::ResourceApplyAdam

Update '*var' according to the Adam algorithm.

tensorflow::ops::ResourceApplyAdamWithAmsgrad

Update '*var' according to the Adam algorithm.

tensorflow::ops::ResourceApplyAddSign

Update '*var' according to the AddSign update.

tensorflow::ops::ResourceApplyCenteredRMSProp

Update '*var' according to the centered RMSProp algorithm.

tensorflow::ops::ResourceApplyFtrl

Update '*var' according to the Ftrl-proximal scheme.

tensorflow::ops::ResourceApplyFtrlV2

Update '*var' according to the Ftrl-proximal scheme.

tensorflow::ops::ResourceApplyGradientDescent

Update '*var' by subtracting 'alpha' * 'delta' from it.

tensorflow::ops::ResourceApplyKerasMomentum

Update '*var' according to the momentum scheme.

tensorflow::ops::ResourceApplyMomentum

Update '*var' according to the momentum scheme.

tensorflow::ops::ResourceApplyPowerSign

Update '*var' according to the AddSign update.

tensorflow::ops::ResourceApplyProximalAdagrad

Update '*var' and '*accum' according to FOBOS with Adagrad learning rate.

tensorflow::ops::ResourceApplyProximalGradientDescent

Update '*var' as FOBOS algorithm with fixed learning rate.

tensorflow::ops::ResourceApplyRMSProp

Update '*var' according to the RMSProp algorithm.

tensorflow::ops::ResourceSparseApplyAdadelta

var: Should be from a Variable().

tensorflow::ops::ResourceSparseApplyAdagrad

Update relevant entries in '*var' and '*accum' according to the adagrad scheme.

tensorflow::ops::ResourceSparseApplyAdagradDA

Update entries in '*var' and '*accum' according to the proximal adagrad scheme.

tensorflow::ops::ResourceSparseApplyCenteredRMSProp

Update '*var' according to the centered RMSProp algorithm.

tensorflow::ops::ResourceSparseApplyFtrl

Update relevant entries in '*var' according to the Ftrl-proximal scheme.

tensorflow::ops::ResourceSparseApplyFtrlV2

Update relevant entries in '*var' according to the Ftrl-proximal scheme.

tensorflow::ops::ResourceSparseApplyKerasMomentum

Update relevant entries in '*var' and '*accum' according to the momentum scheme.

tensorflow::ops::ResourceSparseApplyMomentum

Update relevant entries in '*var' and '*accum' according to the momentum scheme.

tensorflow::ops::ResourceSparseApplyProximalAdagrad

Sparse update entries in '*var' and '*accum' according to FOBOS algorithm.

tensorflow::ops::ResourceSparseApplyProximalGradientDescent

Sparse update '*var' as FOBOS algorithm with fixed learning rate.

tensorflow::ops::ResourceSparseApplyRMSProp

Update '*var' according to the RMSProp algorithm.

tensorflow::ops::SparseApplyAdadelta

var: Should be from a Variable().

tensorflow::ops::SparseApplyAdagrad

Update relevant entries in '*var' and '*accum' according to the adagrad scheme.

tensorflow::ops::SparseApplyAdagradDA

Update entries in '*var' and '*accum' according to the proximal adagrad scheme.

tensorflow::ops::SparseApplyCenteredRMSProp

Update '*var' according to the centered RMSProp algorithm.

tensorflow::ops::SparseApplyFtrl

Update relevant entries in '*var' according to the Ftrl-proximal scheme.

tensorflow::ops::SparseApplyFtrlV2

Update relevant entries in '*var' according to the Ftrl-proximal scheme.

tensorflow::ops::SparseApplyMomentum

Update relevant entries in '*var' and '*accum' according to the momentum scheme.

tensorflow::ops::SparseApplyProximalAdagrad

Sparse update entries in '*var' and '*accum' according to FOBOS algorithm.

tensorflow::ops::SparseApplyProximalGradientDescent

Sparse update '*var' as FOBOS algorithm with fixed learning rate.

tensorflow::ops::SparseApplyRMSProp

Update '*var' according to the RMSProp algorithm.