Optimizer that implements the RMSProp algorithm.
The gist of RMSprop is to:
- Maintain a moving (discounted) average of the square of gradients
- Divide the gradient by the root of this average
This implementation of RMSprop uses plain momentum, not Nesterov momentum.
The centered version additionally maintains a moving average of the gradients, and uses that average to estimate the variance.
Constants
boolean | CENTERED_DEFAULT | |
float | DECAY_DEFAULT | |
float | EPSILON_DEFAULT | |
float | LEARNING_RATE_DEFAULT | |
String | MG | |
String | MOMENTUM | |
float | MOMENTUM_DEFAULT | |
String | RMS |
Inherited Constants
Public Constructors
Public Methods
String |
getOptimizerName()
Get the Name of the optimizer.
|
String |
toString()
|
Inherited Methods
Constants
public static final boolean CENTERED_DEFAULT
public static final float DECAY_DEFAULT
public static final float EPSILON_DEFAULT
public static final float LEARNING_RATE_DEFAULT
public static final String MG
public static final String MOMENTUM
public static final float MOMENTUM_DEFAULT
public static final String RMS
Public Constructors
public RMSProp (Graph graph, float learningRate)
Creates an RMSPRrop Optimizer
Parameters
graph | the TensorFlow Graph |
---|---|
learningRate | the learning rate |
public RMSProp (Graph graph, float learningRate, float decay, float momentum, float epsilon, boolean centered)
Creates an RMSPRrop Optimizer
Parameters
graph | the TensorFlow Graph |
---|---|
learningRate | the learning rate |
decay | Discounting factor for the history/coming gradient. Defaults to 0.9. |
momentum | the acceleration factor, default is 0. |
epsilon | A small constant for numerical stability |
centered | If true , gradients are normalized by the estimated variance of the
gradient; if false , by the uncentered second moment. Setting this to
true may help with training, but is slightly more expensive in terms of computation
and memory. Defaults to false .
|
public RMSProp (Graph graph, String name, float learningRate)
Creates an RMSPRrop Optimizer
Parameters
graph | the TensorFlow Graph |
---|---|
name | the name of this Optimizer. Defaults to "RMSProp". |
learningRate | the learning rate |
public RMSProp (Graph graph, String name, float learningRate, float decay, float momentum, float epsilon, boolean centered)
Creates an RMSPRrop Optimizer
Parameters
graph | the TensorFlow Graph |
---|---|
name | the name of this Optimizer. Defaults to "RMSProp". |
learningRate | the learning rate |
decay | Discounting factor for the history/coming gradient. Defaults to 0.9. |
momentum | The acceleration factor, default is 0. |
epsilon | A small constant for numerical stability |
centered | If true , gradients are normalized by the estimated variance of the
gradient; if false , by the uncentered second moment. Setting this to
true may help with training, but is slightly more expensive in terms of computation
and memory. Defaults to false .
|
Public Methods
public String getOptimizerName ()
Get the Name of the optimizer.
Returns
- The optimizer name.
public String toString ()