Description Usage Arguments Details See Also
Base class of all user-defined learners. To implement your own learning
algorithm, derive from this class and override the update()
.
1 | UserLearner(parameters, lr_schedule, as_matrix = TRUE)
|
parameters |
– list of network parameters |
as_matrix |
|
lr |
(output of learning_rate_schedule()) – learning rate schedule_schedule |
Certain optimizers (such as AdaGrad) require additional storage. This can be allocated and initialized during construction.
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