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)