PBT without MongoDB: Trial parameters are not changed from generation to generation about sherpa HOT 2 CLOSED

Hi Martin,
See my comment on the other issue. So we should only expect the last two trials (in a generataion of 10) to have changed learning rates. However, you're right that K.set_value(model.optimizer.lr, trial.parameters['lr']) actually doesn't work. Keras will happily accept this command but internally it won't actually change the learning rate of the training. Changing the learning rate of a compiled model in Keras is actually non-trivial. Same for dropout. Batch size should be easy. Sherpa should pass a modified batch_size (again only for the bottom 20% of the population) and so long Keras reads the training batchsize from trial.parameters it should be correct.

from sherpa.

In the 11. trial for example, the model from the 6. trial is loaded and modified by the algorithm. However, the learning rate is the same - this is the case for all trials.

from sherpa.