atari_mutation.py

def _mutation(self, base_offsprings):
        offsprings = []
        for offspring in base_offsprings:
            offspring_mutation = copy.deepcopy(offspring)

            for a in range(0, len(offspring_mutation)):  # 10
                a_layer = offspring_mutation[a]
                for b in range(0, len(a_layer)):  # 8
                    b_layer = a_layer[b]
                    if not isinstance(b_layer, np.ndarray):
                        if np.random.choice([True, False], p=[self.mutation_rate, 1 - self.mutation_rate]):
                            offspring_mutation[a][b] = self._random_weight()
                        continue
                    for c in range(0, len(b_layer)):  # 8
                        c_layer = b_layer[c]
                        if not isinstance(c_layer, np.ndarray):
                            if np.random.choice([True, False], p=[self.mutation_rate, 1 - self.mutation_rate]):
                                offspring_mutation[a][b][c] = self._random_weight()
                            continue
                        for d in range(0, len(c_layer)):  # 4
                            d_layer = c_layer[d]
                            for e in range(0, len(d_layer)):  # 32
                                if np.random.choice([True, False], p=[self.mutation_rate, 1 - self.mutation_rate]):
                                    offspring_mutation[a][b][c][d][e] = self._random_weight()
            offsprings.append(offspring_mutation)
        return offsprings