def test_offpol_sarsa(cls):
data_df = run('offpol_sarsa')
assert isinstance(data_df, pd.DataFrame)
def test_dqn_v1(cls):
data_df = run('dqn_v1')
assert isinstance(data_df, pd.DataFrame)
def test_quickstart_dqn(cls):
data_df = run('quickstart_dqn')
assert isinstance(data_df, pd.DataFrame)
def test_double_dqn(cls):
data_df = run('double_dqn')
assert isinstance(data_df, pd.DataFrame)
def test_lunar_dqn(cls):
data_df = run('lunar_dqn')
assert isinstance(data_df, pd.DataFrame)
def test_q_table(cls):
data_df = run('q_table')
assert isinstance(data_df, pd.DataFrame)
def test_dqn_epsilon(cls):
data_df = run('dqn_epsilon')
assert isinstance(data_df, pd.DataFrame)
def test_acrobot(cls):
data_df = run('acrobot')
assert isinstance(data_df, pd.DataFrame)
def test_pendulum_ddpg(cls):
data_df = run('pendulum_ddpg')
assert isinstance(data_df, pd.DataFrame)
def test_quickstart_dqn(cls):
data_df = run('quickstart_dqn')
assert isinstance(data_df, pd.DataFrame)
def test_breakout_dqn(cls):
data_df = run('breakout_dqn')
assert isinstance(data_df, pd.DataFrame)
def test_walker_ddpg_linearnoise(cls):
data_df = run('walker_ddpg_linearnoise')
assert isinstance(data_df, pd.DataFrame)
def test_lunar_freeze(cls):
data_df = run('lunar_freeze')
assert isinstance(data_df, pd.DataFrame)
def test_pendulum_ddpg_linearnoise(cls):
data_df = run('pendulum_ddpg_linearnoise')
assert isinstance(data_df, pd.DataFrame)
def test_cartpole_ac_argmax(cls):
data_df = run('cartpole_ac_argmax')
assert isinstance(data_df, pd.DataFrame)
def test_exp_sarsa(cls):
data_df = run('exp_sarsa')
assert isinstance(data_df, pd.DataFrame)
def test_dqn_v1(cls):
data_df = run('dqn_v1')
assert isinstance(data_df, pd.DataFrame)
def test_lunar_dqn(cls):
data_df = run('lunar_dqn')
assert isinstance(data_df, pd.DataFrame)
def test_pendulum_ddpg_linearnoise(cls):
data_df = run('pendulum_ddpg_linearnoise')
assert isinstance(data_df, pd.DataFrame)
def test_gym_tour(cls):
data_df = run('dummy')
assert isinstance(data_df, pd.DataFrame)
def test_run_q_table(self):
metrics_df = run('q_table')
assert isinstance(metrics_df, pd.DataFrame)
def test_dqn_pass(cls):
data_df = run('test_dqn_pass')
max_total_rewards = data_df['max_total_rewards_stats_mean'][0]
print(max_total_rewards)
assert max_total_rewards > 50, 'dqn failed to hit max_total_rewards'
def test_run_dqn(self):
metrics_df = run('dqn')
assert isinstance(metrics_df, pd.DataFrame)
def test_dqn_epsilon(cls):
data_df = run('dqn_epsilon')
assert isinstance(data_df, pd.DataFrame)
def test_run_mountain_double_dqn(self):
metrics_df = run('mountain_double_dqn')
assert isinstance(metrics_df, pd.DataFrame)
def test_exp_sarsa(cls):
data_df = run('exp_sarsa')
assert isinstance(data_df, pd.DataFrame)
def test_run_gym_tour(self):
metrics_df = run('dummy')
assert isinstance(metrics_df, pd.DataFrame)
def test_cartpole_ac_argmax(cls):
data_df = run('cartpole_ac_argmax')
assert isinstance(data_df, pd.DataFrame)
from rl.experiment import run
if __name__ == '__main__':
# run('dev_dqn', times=2, param_selection=True)
# run('dqn', times=2, param_selection=False)
run('lunar_dqn', times=5, param_selection=True)
# run('DevCartPole-v0_DQN_HighLowMemoryWithForgetting_BoltzmannPolicy_NoPreProcessor_2017-01-21_191023_e0', plot_only=True)
# run('lunar_dqn', times=3, param_selection=True, line_search=True)
# run('breakout_dqn', times=1, param_selection=True)
def test_acrobot(cls):
data_df = run('acrobot')
assert isinstance(data_df, pd.DataFrame)
def test_dqn(cls):
data_df = run('double_dqn_per')
assert isinstance(data_df, pd.DataFrame)
def test_mountain_dqn(cls):
data_df = run('mountain_dqn')
assert isinstance(data_df, pd.DataFrame)
def test_gym_tour(cls):
data_df = run('dummy')
assert isinstance(data_df, pd.DataFrame)
def test_offpol_sarsa(cls):
data_df = run('offpol_sarsa')
assert isinstance(data_df, pd.DataFrame)
def test_q_table(cls):
data_df = run('q_table')
assert isinstance(data_df, pd.DataFrame)
def test_mountain_dqn(cls):
data_df = run('mountain_dqn')
assert isinstance(data_df, pd.DataFrame)
def test_dqn_pass(cls):
data_df = run('test_dqn_pass')
max_total_rewards = data_df['max_total_rewards_stats_mean'][0]
print(max_total_rewards)
assert max_total_rewards > 50, 'dqn failed to hit max_total_rewards'
def test_breakout_double_dqn(cls):
data_df = run('breakout_double_dqn')
assert isinstance(data_df, pd.DataFrame)
from rl.experiment import run
from rl.util import args
if __name__ == '__main__':
run(args.experiment, **vars(args))
