def main(args):
if args.resume:
conf_file = os.path.join(args.debugging_folder, 'args.json')
assert os.path.exists(
conf_file
), "Could not find an args.json file in the debugging folder"
for k, v in logger_utils.load_args(args.debugging_folder).items():
setattr(args, k, v)
logger.debug('Configuration: {}'.format(args))
logger_utils.save_args(args, args.debugging_folder)
if 'gpu' in args.device:
agent_gpu = str(misc_utils.pick_gpu_lowest_memory())
os.environ["CUDA_VISIBLE_DEVICES"] = agent_gpu
logger.debug('Agent will be run on device /gpu:{}'.format(agent_gpu))
args.random_seed = 3 # random_seed
env_creator = environment_creator.EnvironmentCreator(args)
args.num_actions = env_creator.num_actions
args.state_shape = env_creator.state_shape
import numpy as np
# Create a set of arrays (as many as emulators) to exchange states, rewards, etc. between the agent and the emulator
n_emulators = args.n_emulator_runners * args.n_emulators_per_emulator_runner
variables = {
"s": np.zeros((n_emulators, ) + args.state_shape, dtype=np.float32),
"a": np.zeros((n_emulators), dtype=np.int32), # Actions
"r": np.zeros((n_emulators), dtype=np.float32), # Rewards
"done": np.zeros((n_emulators), dtype=np.bool)
} # Dones
sim_coordinator = SimulatorsCoordinator(
env_creator, args.n_emulators_per_emulator_runner,
args.n_emulator_runners, variables)
# Start all simulator processes
sim_coordinator.start()
network = QNetwork
def network_creator(name='value_learning', learning_network=None):
nonlocal args
args.name = name
return network(args, learning_network=learning_network)
learner = PDQFDLearner(network_creator, env_creator, args, sim_coordinator)
setup_kill_signal_handler(learner)
logger.info('Starting training')
learner.train()
logger.info('Finished training')
return memory
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('-f', '--folder', type=str, help="Folder where to save the debugging information.", dest="folder", required=True)
parser.add_argument('-tc', '--test_count', default='1', type=int, help="The amount of tests to run on the given network", dest="test_count")
parser.add_argument('-np', '--noops', default=30, type=int, help="Maximum amount of no-ops to use", dest="noops")
parser.add_argument('-gn', '--gif_name', default=None, type=str, help="If provided, a gif will be produced and stored with this name", dest="gif_name")
parser.add_argument('-gf', '--gif_folder', default='', type=str, help="The folder where to save gifs.", dest="gif_folder")
parser.add_argument('-d', '--device', default='/gpu:0', type=str, help="Device to be used ('/cpu:0', '/gpu:0', '/gpu:1',...)", dest="device")
args = parser.parse_args()
arg_file = os.path.join(args.folder, 'args.json')
device = args.device
for k, v in logger_utils.load_args(arg_file).items():
setattr(args, k, v)
args.max_global_steps = 0
df = args.folder
args.debugging_folder = '/tmp/logs'
args.device = device
args.random_start = False
args.single_life_episodes = False
if args.gif_name:
args.visualize = 1
args.actor_id = 0
rng = np.random.RandomState(int(time.time()))
args.random_seed = rng.randint(1000)