def optimizer_worker(train):
print("Optimizer worker started")
while train.replay_buffer.ready() == False:
sleep(10)
while True:
for _ in range(5):
sampled = train.replay_buffer.get_samples(train.batch_size)
state_batch, action_batch, value_batch = zip(*sampled)
# SB need to read file from state.txt file to prevent json file is too big
states = []
for state_path in state_batch:
world = World(state_path)
state = world.current_state()
states.append(state)
# need change visit count to probability distribution
actions = []
for visit_count in action_batch:
visit_count_array = np.array(visit_count)
total_visit = np.sum(visit_count_array)
probability_distribution = visit_count_array / total_visit
actions.append(probability_distribution)
state_batch_reshaped = np.reshape(
states, (-1, train.obs_shape[1], train.obs_shape[0],
train.obs_shape[2]))
action_batch_reshaped = np.reshape(actions, (-1, train.act_shape))
value_batch_reshaped = np.reshape(value_batch, (-1, 1))
loss, entropy = train.network.train_step(state_batch_reshaped,
action_batch_reshaped,
value_batch_reshaped,
train.learning_rate)
print(loss, entropy)
train.network.save_model(os.path.join(os.getcwd(), "latest"))
def network_thread(player, temp_folder):
print("Network thread started for " + temp_folder)
state_path = os.path.join(temp_folder, "State.txt")
policy_value_path = os.path.join(temp_folder, "PolicyValue.txt")
policy_value_temp = os.path.join(temp_folder, "PolicyValueTemp.txt")
while True:
sleep(0.05)
if os.access(state_path, os.F_OK) and os.access(state_path, os.R_OK):
try:
world = World(state_path, width, height)
state = world.current_state()
os.remove(state_path)
policy, value = player.policy_value(state)
#print(policy, value)
policy_str = ""
for i in range(action_count):
policy_str += str(policy[i])
if i != action_count - 1:
policy_str += "_"
value_str = str(value)
with open(policy_value_temp, 'w') as f:
f.write(policy_str + "\n")
f.write(value_str)
if os.access(policy_value_path, os.F_OK):
os.remove(policy_value_path)
shutil.move(policy_value_temp, policy_value_path)
except Exception as e:
print(str(e))
