Class RMSProp
java.lang.Object
org.tribuo.math.optimisers.RMSProp
- All Implemented Interfaces:
com.oracle.labs.mlrg.olcut.config.Configurable
,com.oracle.labs.mlrg.olcut.provenance.Provenancable<com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance>
,StochasticGradientOptimiser
An implementation of the RMSProp gradient optimiser.
Creates one copy of the parameters to store learning rates. Follows the Keras implementation.
See:
Tieleman, T. and Hinton, G. Lecture 6.5 - RMSProp, COURSERA: Neural Networks for Machine Learning. Technical report, 2012.
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptioncopy()
Copies a gradient optimiser with it's configuration.com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance
void
initialise
(Parameters parameters) Initialises the gradient optimiser.void
Used by the OLCUT configuration system, and should not be called by external code.void
reset()
Resets the optimiser so it's ready to optimise a newParameters
.Tensor[]
Take aTensor
array of gradients and transform them according to the current weight and learning rates.toString()
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
Methods inherited from interface org.tribuo.math.StochasticGradientOptimiser
finalise
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Constructor Details
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RMSProp
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RMSProp
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Method Details
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postConfig
Used by the OLCUT configuration system, and should not be called by external code.- Specified by:
postConfig
in interfacecom.oracle.labs.mlrg.olcut.config.Configurable
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initialise
Description copied from interface:StochasticGradientOptimiser
Initialises the gradient optimiser.Configures any learning rate parameters.
- Specified by:
initialise
in interfaceStochasticGradientOptimiser
- Parameters:
parameters
- The parameters to optimise.
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step
Description copied from interface:StochasticGradientOptimiser
Take aTensor
array of gradients and transform them according to the current weight and learning rates.Can return the same
Tensor
array or a new one.- Specified by:
step
in interfaceStochasticGradientOptimiser
- Parameters:
updates
- An array of gradients.weight
- The weight for the current gradients.- Returns:
- A
Tensor
array of gradients.
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toString
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reset
Description copied from interface:StochasticGradientOptimiser
Resets the optimiser so it's ready to optimise a newParameters
.- Specified by:
reset
in interfaceStochasticGradientOptimiser
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copy
Description copied from interface:StochasticGradientOptimiser
Copies a gradient optimiser with it's configuration. Usually calls the copy constructor.- Specified by:
copy
in interfaceStochasticGradientOptimiser
- Returns:
- A gradient optimiser with the same configuration, but independent state.
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getProvenance
- Specified by:
getProvenance
in interfacecom.oracle.labs.mlrg.olcut.provenance.Provenancable<com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance>
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