def test_preserves_previous_hitpoints(self): self.get_mega_name_mock.return_value = 'venusaurmega' pkmn = Pokemon('venusaur', 100) pkmn.hp = 1 pkmn.try_convert_to_mega() self.assertEqual(1, pkmn.hp)
# from tensorflow.keras.models import Model, Sequential import json import numpy as np from keras.models import Sequential from keras.layers import Dense, Activation, Dropout from keras.optimizers import SGD, Adam poke_string = open("data/pokedex.json", "r").read() y = json.loads(poke_string) poke_list = list(y.keys()) pokemon_initializations = 50 x_train = [] y_train = [] for poke_string in poke_list: for i in range(50): pokemon = Pokemon(poke_string, 100) pokemon.hp = np.random.randint(0, 100) try: vector = pokemon.to_vector().numpy() x_train.append(np.array(vector)) y_train.append(np.array(vector)) except: print("pokemon", poke_string, "to_vector does not work") encoding_dim = 50 model = Sequential() model.add(Dense(512, activation="relu", input_shape=(1157, ))) model.add(Dropout(.1)) model.add(Dense(128, activation="relu", input_shape=(1157, ))) model.add(Dropout(.1)) model.add(Dense(encoding_dim, activation='relu')) model.add(Dense(128, activation="relu", input_shape=(1157, ))) model.add(Dense(512, activation="relu", input_shape=(1157, )))