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, )))
