# warm up should be less than one epoch
c.ddpg_update_batch_size = 100
c.ddpg_warmup_steps = 200
c.model_save_int = 100 # in episodes
c.profile_int = 50 # in episodes
def policy_noise(action):
return t.clamp(
add_clipped_normal_noise_to_action(action, c.policy_noise_params), -1,
1)
if __name__ == "__main__":
save_env = SaveEnv(c.root_dir, restart_use_trial=c.restart_from_trial)
prep_args(c, save_env)
# save_env.remove_trials_older_than(diff_hour=1)
global_board.init(save_env.get_trial_train_log_dir())
writer = global_board.writer
logger.info("Directories prepared.")
actor = MW(
Actor(observe_dim, action_dim, 1).to(c.device), c.device, c.device)
actor_t = MW(
Actor(observe_dim, action_dim, 1).to(c.device), c.device, c.device)
critic = MW(
Critic(observe_dim, action_dim).to(c.device), c.device, c.device)
critic_t = MW(
Critic(observe_dim, action_dim).to(c.device), c.device, c.device)
critic2 = MW(
load_framework2 = "naive_ppo_parallel"
load_trial1 = "2020_05_06_21_50_57"
load_trial2 = "2020_05_06_21_50_57"
test_root_dir = ""
def load_framework(name):
module = imp.import_module(".magent_" + name)
return module.c, module.create_models, module.run_agents
if __name__ == "__main__":
c1, create_models1, run_agents1 = load_framework(load_framework1)
c2, create_models2, run_agents2 = load_framework(load_framework1)
save_env1 = SaveEnv(c1.root_dir, restart_use_trial=load_trial1)
prep_args(c1, save_env1)
save_env2 = SaveEnv(c2.root_dir, restart_use_trial=load_trial2)
prep_args(c2, save_env2)
c1.restart_from_trial = load_trial1
framework1 = create_models1()
logger.info("Framework 1 initialized")
c2.restart_from_trial = load_trial2
framework2 = create_models2()
logger.info("Framework 2 initialized")
operators = [(framework1, run_agents1, load_framework1),
(framework2, run_agents2, load_framework2)]
# testing