simonkamronn

# https://people.eecs.berkeley.edu/~kjamieson/hyperband.html
# you need to write the following hooks for your custom problem
from problem import get_random_hyperparameter_configuration,run_then_return_val_loss

max_iter = 81  # maximum iterations/epochs per configuration
eta = 3 # defines downsampling rate (default=3)
logeta = lambda x: log(x)/log(eta)
s_max = int(logeta(max_iter))  # number of unique executions of Successive Halving (minus one)
B = (s_max+1)*max_iter  # total number of iterations (without reuse) per execution of Succesive Halving (n,r)

udibr

import numpy as np
from keras.layers import GRU, initializations, K
from collections import OrderedDict

class GRULN(GRU):
    '''Gated Recurrent Unit with Layer Normalization
    Current impelemtation only works with consume_less = 'gpu' which is already
    set.

    # Arguments