def __init__(self, env_name, atari_wrapper=False, test=False):
if atari_wrapper:
clip_rewards = not test
self.env = make_wrap_atari(env_name, clip_rewards)
else:
self.env = gym.make(env_name)
self.action_space = self.env.action_space
self.observation_space = self.env.observation_space
def run(args):
if args.train:
from agent_dir.agent_dqn import Agent_DQN
env = make_wrap_atari(args.env_id, clip_rewards=True)
#env = gym.make('LunarLander-v2')
agent = Agent_DQN(args, env)
if args.n_steps > 1:
agent.nsteps_train()
else:
agent.train()
def __init__(self, env_name, args, atari_wrapper=False, test=False):
if atari_wrapper:
clip_rewards = not test
self.env = make_wrap_atari(env_name, clip_rewards)
else:
self.env = gym.make(env_name)
self.action_space = self.env.action_space
self.observation_space = self.env.observation_space
self.env = gym.wrappers.Monitor(self.env, './render', force=True)
def run(args):
if args.test_pg:
env = gym.make('Pong-v0')
from agent_dir.agent_pg import Agent_PG
agent = Agent_PG(env, args)
test(agent, env)
if args.test_dqn:
env = make_wrap_atari(args.env_id, clip_rewards=False)
from agent_dir.agent_dqn import Agent_DQN
agent = Agent_DQN(args, env)
test(agent, env, total_episodes=100)
def __init__(self, env_name, args, atari_wrapper=False, test=False):
if atari_wrapper:
clip_rewards = not test # if not test, clip reward, else not clip reward
self.env = make_wrap_atari(env_name, clip_rewards)
else:
self.env = gym.make(env_name)
self.action_space = self.env.action_space
self.observation_space = self.env.observation_space
self.do_render = args.do_render
if args.video_dir:
self.env = gym.wrappers.Monitor(self.env,
args.video_dir,
force=True)
def __init__(self, env_name, args, atari_wrapper=False, test=False):
if env_name.find('Mario') != -1:
from mario_env import create_mario_env
self.env = create_mario_env(env_name)
elif atari_wrapper:
clip_rewards = not test
self.env = make_wrap_atari(env_name, clip_rewards)
else:
self.env = gym.make(env_name)
self.action_space = self.env.action_space
self.observation_space = self.env.observation_space
self.do_render = args.do_render
if args.video_dir:
self.env = gym.wrappers.Monitor(self.env, args.video_dir, force=True)
def __init__(self,
env_name,
args,
atari_wrapper=False,
test=False,
frame_stack_and_origin=False):
if atari_wrapper:
clip_rewards = not test
self.frame_stack_and_origin = frame_stack_and_origin
self.env = make_wrap_atari(env_name, clip_rewards,
frame_stack_and_origin)
else:
self.env = gym.make(env_name)
self.action_space = self.env.action_space
self.observation_space = self.env.observation_space
self.do_render = args.do_render
if args.video_dir:
self.env = gym.wrappers.Monitor(self.env,
args.video_dir,
force=True)
print(" ")
print("--------------")
print(" ")
agent.flag = False
### parsing the input from the command line
#######################################################################################################
parser = argparse.ArgumentParser(description="DQN Breakout")
parser.add_argument('--train_dqn', action='store_true', help='whether train DQN')
parser.add_argument('--test_dqn', action='store_true', help='whether test DQN')
parser.add_argument('--render', action='store_true', help='whether render environment or not')
parser.add_argument('--episodes', type=int, default = 50000, help='Number of episodes to run')
args = parser.parse_args()
#######################################################################################################
### I know globals are bad, but I think I can get away with a few!
env = make_wrap_atari('BreakoutNoFrameskip-v4')
batch_size = 32
model_check = 10
EPSILON_START = 1.0
video_width = 84
video_height = 84
stack_images = 4
agent = DQN_Agent(env.observation_space.shape,env.action_space.n)
agent.run_experient(args)
