def main(argv):
del argv
if FLAGS.seed is not None and FLAGS.set_seed:
print('Seed set to %i.' % FLAGS.seed)
random.seed(FLAGS.seed)
np.random.seed(FLAGS.seed)
tf.set_random_seed(FLAGS.seed)
(agent_type, log_dir, run_name, create_environment_fn,
gin_file) = parse_flags()
print('Flags parsed.')
print('log_dir = {}'.format(log_dir))
print(run_name)
def create_agent_fn(sess, environment, summary_writer):
"""Creates the appropriate agent."""
if agent_type == 'dqn':
return dqn_agent.DQNAgent(
sess=sess,
num_actions=environment.action_space.n,
summary_writer=summary_writer)
if agent_type == 'al_dqn':
return al_dqn.ALDQNAgent(
sess=sess,
num_actions=environment.action_space.n,
alpha=FLAGS.shaping_scale,
persistent=FLAGS.persistent,
summary_writer=summary_writer)
if agent_type == 'm_dqn':
return m_dqn.MunchausenDQNAgent(
sess=sess,
num_actions=environment.action_space.n,
tau=FLAGS.tau,
alpha=FLAGS.alpha,
clip_value_min=FLAGS.clip_value_min,
interact=FLAGS.interact,
summary_writer=summary_writer)
if agent_type == 'm_iqn':
return m_iqn.MunchausenIQNAgent(
sess=sess,
num_actions=environment.action_space.n,
tau=FLAGS.tau,
alpha=FLAGS.alpha,
interact=FLAGS.interact,
clip_value_min=FLAGS.clip_value_min,
summary_writer=summary_writer)
raise ValueError('Wrong agent %s' % agent_type)
if gin_file:
load_gin_configs([gin_file], FLAGS.gin_bindings)
print('lets run!')
runner = run_experiment.TrainRunner(log_dir, create_agent_fn,
create_environment_fn)
print('Agent of type %s created.' % agent_type)
# pylint: disable=protected-access
for k in sorted(runner._agent.__dict__):
if not k.startswith('_'):
print(k, runner._agent.__dict__[k])
print()
# pylint: enable=protected-access
runner.run_experiment()
def main(argv):
del argv
if FLAGS.seed is not None and FLAGS.set_seed:
print('Seed set to %i.' % FLAGS.seed)
random.seed(FLAGS.seed)
np.random.seed(FLAGS.seed)
tf.set_random_seed(FLAGS.seed)
(agent_type, log_dir, run_name, create_environment_fn,
gin_file) = parse_flags()
print('Flags parsed.')
print('log_dir = {}'.format(log_dir))
print(run_name)
def create_agent_fn(sess, environment, summary_writer):
"""Creates the appropriate agent."""
if agent_type == 'dqn':
return dqn_agent.DQNAgent(
sess=sess,
num_actions=environment.action_space.n,
summary_writer=summary_writer)
elif agent_type == 'iqn':
return implicit_quantile_agent.ImplicitQuantileAgent(
sess=sess,
num_actions=environment.action_space.n,
summary_writer=summary_writer)
elif agent_type == 'al_dqn':
return al_dqn.ALDQNAgent(
sess=sess,
num_actions=environment.action_space.n,
summary_writer=summary_writer)
elif agent_type == 'al_iqn':
return al_iqn.ALImplicitQuantileAgent(
sess=sess,
num_actions=environment.action_space.n,
summary_writer=summary_writer)
elif agent_type == 'sail_dqn':
return sail_dqn.SAILDQNAgent(
sess=sess,
num_actions=environment.action_space.n,
summary_writer=summary_writer)
elif agent_type == 'sail_iqn':
return sail_iqn.SAILImplicitQuantileAgent(
sess=sess,
num_actions=environment.action_space.n,
summary_writer=summary_writer)
else:
raise ValueError('Wrong agent %s' % agent_type)
if gin_file:
load_gin_configs([gin_file], FLAGS.gin_bindings)
print('lets run!')
runner = run_experiment.TrainRunner(log_dir, create_agent_fn,
create_environment_fn)
print('Agent of type %s created.' % agent_type)
# pylint: disable=protected-access
for k in sorted(runner._agent.__dict__):
if not k.startswith('_'):
print(k, runner._agent.__dict__[k])
print()
# pylint: enable=protected-access
runner.run_experiment()
def set_seed(seed=0):
tf.set_random_seed(seed)