50a48e6cdd5f2240d2f0c793b3b3991d09c28d03,genome_handler.py,GenomeHandler,mutate,#GenomeHandler#Any#,53

Before Change

        self.dense_layer_size = len(self.dense_layer_shape)

    def mutate(self, genome):
        while True:
            index = np.random.choice(range(1, len(genome)))
            if index < self.convolution_layer_size * self.convolution_layers:
                if genome[index - index % self.convolution_layer_size]:
                    range_index = index % self.convolution_layer_size
                    choice_range = self.convolutional_layer_shape[range_index]
                    genome[index] = np.random.choice(choice_range)
                    break
            elif index != len(genome) - 1:
                offset = self.convolution_layer_size * self.convolution_layers
                new_index = (index - offset)
                present_index = new_index - new_index % self.dense_layer_size
                if genome[present_index + offset]:
                    range_index = new_index % self.dense_layer_size
                    choice_range = self.dense_layer_shape[range_index]
                    genome[index] = np.random.choice(choice_range)
                    break
            else:
                genome[index] = np.random.choice(self.optimizer.keys())
                break
        return genome

    def decode(self, genome):
        model = Sequential()

After Change

        self.dense_layer_size = len(self.dense_layer_shape)

    def mutate(self, genome):
        num_mutations = np.random.choice(range(3))
        for i in range(num_mutations):
            index = np.random.choice(range(1, len(genome)))
            if index < self.convolution_layer_size * self.convolution_layers:
                if genome[index - index % self.convolution_layer_size]:

Instances