| 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::ApplyCenteredRMSProp | Update '*var' according to the centered RMSProp algorithm. |
| tensorflow::ops::ApplyFtrl | 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::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::ResourceApplyCenteredRMSProp | Update '*var' according to the centered RMSProp algorithm. |
| tensorflow::ops::ResourceApplyFtrl | Update '*var' according to the Ftrl-proximal scheme. |
| tensorflow::ops::ResourceApplyGradientDescent | Update '*var' by subtracting 'alpha' * 'delta' from it. |
| tensorflow::ops::ResourceApplyMomentum | Update '*var' according to the momentum scheme. |
| 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::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::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. |
© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/cc/group/training-ops