Abstraction for learning a subset of parameters of a learnable function using first order gradient values. For example momentum, AdaGrad, RMSProp, etc. are different types of learners with their own algorithms for learning parameter values using first order gradients. To instantiate a concrete learner, use the factory methods in this module.
Learner(parameters, learning_rate_schedule)
| parameters | – list of network parameters list of parameter associated with this learner |
|---|---|
| learning_rate_schedule | get_learning_rate(learner) |