import minerl
import coloredlogs
import logging
coloredlogs.install(logging.DEBUG)
from minerl.env.malmo import launch_instance_manager
if __name__ == "__main__":
launch_instance_manager()
def main():
malmo_base_port = FLAGS.malmo_base_port
os.environ["CUDA_VISIBLE_DEVICES"] = FLAGS.gpus
malmo.InstanceManager.configure_malmo_base_port(malmo_base_port)
observation_space = CustomObservationSpace(
pov_resolution=FLAGS.pov_resolution,
pov_color_space=FLAGS.pov_color_space)
action_space = CustomActionSpace(
num_camera_actions=FLAGS.num_camera_actions,
camera_max_angle=FLAGS.camera_max_angle)
def combined_actor_critic_agent():
return ResnetLSTMAgent(observation_space=observation_space,
action_space=action_space,
max_step_mul=FLAGS.max_step_mul,
core_hidden_size=FLAGS.lstm_hidden_size,
use_prev_actions=FLAGS.use_prev_actions,
action_embed_type=FLAGS.action_embed_type,
action_embed_size=FLAGS.action_embed_size)
def separate_actor_critic_agent():
return SeparateActorCriticWrapperAgent(
actor=combined_actor_critic_agent(),
critic=combined_actor_critic_agent())
if FLAGS.separate_actor_critic:
agent_fn = separate_actor_critic_agent
else:
agent_fn = combined_actor_critic_agent
log_dir = FLAGS.logdir
# Training Phase
if EVALUATION_STAGE in ['all', 'training']:
# only write out flags when training
pathlib.Path(log_dir).mkdir(parents=True, exist_ok=True)
FLAGS.append_flags_into_file(
f'{log_dir}/flags_{datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S")}.cfg'
)
aicrowd_helper.training_start()
try:
train.main(log_dir=log_dir,
load_dir=FLAGS.loaddir,
observation_space=observation_space,
action_space=action_space,
max_step_mul=FLAGS.max_step_mul,
fixed_step_mul=FLAGS.fixed_step_mul,
step_mul=FLAGS.step_mul,
agent_fn=agent_fn,
seed=FLAGS.train_seed,
malmo_base_port=malmo_base_port)
aicrowd_helper.training_end()
except Exception as e:
aicrowd_helper.training_error()
print(traceback.format_exc())
print(e)
# Testing Phase
if EVALUATION_STAGE in ['all', 'testing']:
if EVALUATION_RUNNING_ON in ['local']:
try:
os.remove(EXITED_SIGNAL_PATH)
except FileNotFoundError:
pass
aicrowd_helper.inference_start()
try:
test.main(log_dir=log_dir,
test_model=FLAGS.test_model,
observation_space=observation_space,
action_space=action_space,
fixed_step_mul=FLAGS.fixed_step_mul,
step_mul=FLAGS.step_mul,
agent_fn=agent_fn)
aicrowd_helper.inference_end()
except Exception as e:
aicrowd_helper.inference_error()
print(traceback.format_exc())
print(e)
if EVALUATION_RUNNING_ON in ['local']:
from pathlib import Path
Path(EXITED_SIGNAL_PATH).touch()
# Launch instance manager
if EVALUATION_STAGE in ['manager']:
from minerl.env.malmo import launch_instance_manager
launch_instance_manager()