ray.init(ignore_reinit_error=True)
#### Register the environment ##############################
temp_env_name = "this-aviary-v0"
if ARGS.env == 'flock':
register_env(
temp_env_name, lambda _: FlockAviary(
num_drones=ARGS.num_drones,
aggregate_phy_steps=shared_constants.AGGR_PHY_STEPS,
obs=ARGS.obs,
act=ARGS.act))
elif ARGS.env == 'leaderfollower':
register_env(
temp_env_name, lambda _: LeaderFollowerAviary(
num_drones=ARGS.num_drones,
aggregate_phy_steps=shared_constants.AGGR_PHY_STEPS,
obs=ARGS.obs,
act=ARGS.act))
elif ARGS.env == 'meetup':
register_env(
temp_env_name, lambda _: MeetupAviary(
num_drones=ARGS.num_drones,
aggregate_phy_steps=shared_constants.AGGR_PHY_STEPS,
obs=ARGS.obs,
act=ARGS.act))
elif ARGS.env == 'payloadcoop':
register_env(
temp_env_name, lambda _: PayloadCoop(
num_drones=ARGS.num_drones,
aggregate_phy_steps=shared_constants.AGGR_PHY_STEPS,
obs=ARGS.obs,
#### Register the custom centralized critic model ##########
ModelCatalog.register_custom_model("cc_model", CustomTorchCentralizedCriticModel)
#### Register the environment ##############################
temp_env_name = "this-aviary-v0"
if ARGS.exp.split("-")[1] == 'flock':
register_env(temp_env_name, lambda _: FlockAviary(num_drones=NUM_DRONES,
aggregate_phy_steps=shared_constants.AGGR_PHY_STEPS,
obs=OBS,
act=ACT
)
)
elif ARGS.exp.split("-")[1] == 'leaderfollower':
register_env(temp_env_name, lambda _: LeaderFollowerAviary(num_drones=NUM_DRONES,
aggregate_phy_steps=shared_constants.AGGR_PHY_STEPS,
obs=OBS,
act=ACT
)
)
elif ARGS.exp.split("-")[1] == 'meetup':
register_env(temp_env_name, lambda _: MeetupAviary(num_drones=NUM_DRONES,
aggregate_phy_steps=shared_constants.AGGR_PHY_STEPS,
obs=OBS,
act=ACT
)
)
else:
print("[ERROR] environment not yet implemented")
exit()
#### Unused env to extract the act and obs spaces ##########