import numpy as np
from keras.models import Sequential
from keras.layers import Convolution2D, MaxPooling2D, BatchNormalization
from keras.layers import Dense, Dropout, Activation


# Just handles decoding from genome strings into Keras models
class Genome:

    # Returns a compiled keras model
    def decode(self, genome):
        pass
    
    # Returns one randomly create genome
    def generateRandom(self):
        pass

# Our genetic algorithm.
# This will contain methods for fitness, crossover, mutation, etc.
class Evolutions:

    # Run the whole thing
    def run(self):
        pass

    # Evaluate the fitness of a model
    def fitness(self, model):
        pass

    # Crossover two genomes
    def crossover(self, genome1, genome2):
        pass

    # Mutate one gene
    def mutate(self, genome):
        pass

@@ -178,256 +178,8 @@
 on%0A%0A
-%0A# Just handles decoding from genome strings into Keras models%0Aclass Genome:%0A%0A    # Returns a compiled keras model%0A    def decode(self, genome):%0A        pass%0A    %0A    # Returns one randomly create genome%0A    def generateRandom(self):%0A        pass%0A%0A
 # Ou

remove genome from file