def testCase1(self):
env = SevenKingEnv()
players = [
AlwaysFoldPlayer(),
AlwaysFoldPlayer(),
AlwaysNotFoldPlayer()
]
env.compete(env, players)
def testRandom(self):
"""
"""
env = SevenKingEnv()
env.num_players = 2
players = [roomai.common.RandomPlayer() for i in range(2)]
for i in range(100):
SevenKingEnv.compete(env, players)
def testScores(self):
"""
"""
env = SevenKingEnv()
env.num_players = 3
print "aaa"
players = [AlwaysFoldPlayer(), AlwaysFoldPlayer(), AlwaysNotFoldPlayer()]
scores = env.compete(env, players)
print scores
self.assertEqual(scores[0],-1)
self.assertEqual(scores[1],-1)
self.assertEqual(scores[2],2)
def testScores(self):
"""
"""
env = SevenKingEnv()
print("aaa")
players = [
AlwaysFoldPlayer(),
AlwaysFoldPlayer(),
AlwaysNotFoldPlayer(),
roomai.common.RandomPlayerChance()
]
scores = env.compete(env, players)
print(scores)
self.assertEqual(scores[0], -1)
self.assertEqual(scores[1], -1)
self.assertEqual(scores[2], 2)
def testScores1(self):
"""
"""
env = SevenKingEnv()
infos, public_state, person_states, private_state = env.init()
self.assertTrue(
"" not in infos[public_state.turn].person_state.available_actions)
self.assertFalse(
env.is_action_valid(SevenKingAction.lookup(""), public_state,
person_states[public_state.turn]))
if __name__ == "__main__":
env = SevenKingEnv()
players = [
AlwaysMaxPlayer(),
AlwaysNotFoldPlayer(),
AlwaysMinPlayer(),
roomai.common.RandomPlayer()
]
import time
start = time.time()
for i in range(10):
scores = env.compete(env, players)
print(scores)
end = time.time()
print(end - start)
'''
if k == BATCH_SIZE:
feed_dict = {
model.xs: batch_x,
model.ys: batch_y,
}
else:
feed_dict = {
model.xs: batch_x,
model.ys: batch_y,
model.cell_init_state: state
}
# print(feed_dict)
_, cost, state, pred = sess.run(
[model.train_op, model.cost, model.cell_final_state, model.pred],
feed_dict=feed_dict)
if math.isnan(cost):
pdb.set_trace()
if i % 100 == 0:
print('cost: ', round(cost, 4))
'''
# player.rnn_model.save_model("./path/")
player2 = skp.AlwaysFoldPlayer()
for i in range(10):
scores = env.compete(env, players=[player, player2])
print(scores)