old_contents: 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
  
new_contents: import numpy as np
  from keras.models import Sequential
  from keras.layers import Convolution2D, MaxPooling2D, BatchNormalization
  from keras.layers import Dense, Dropout, Activation
  
  # 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
  
subject: remove genome from file