def restore_model(agents, path=None):
if path:
agents[0].restore(path)
idex = path.split("/")[-1]
else:
idex = get_max_idx("./saved_model")
path = os.path.join("./saved_model/", str(idex))
agents[0].restore(path)
logging.info("Agent model restored at {}".format(path))
return int(idex)
def restore_model(agents, path=None):
alg_tag = "current_models/CNN_DQN" if use_dqn(
) else "current_models/CNN_A2C"
try:
if path:
agents[0].restore(path)
idex = path.split("/")[-1]
else:
idex = get_max_idx(alg_tag + fmt_hyperparameters())
path = os.path.join(alg_tag + fmt_hyperparameters(), str(idex))
agents[0].restore(path)
logging.info("Agent model restored at {}".format(path))
except:
print(sys.exc_info())
logging.info("No saved Model!!")
idex = 0
return int(idex)
def main(unused_argv):
# logging.info("Train on " + fmt_output_channels())
env, info_state_size, num_actions, begin = init_env()
cnn_parameters, hidden_layers_sizes, kwargs, ret, max_len = init_hyper_paras(
)
with tf.Session() as sess:
# rival_path = "rivals/a2c_0"
# rival_path = "../saved_model/CNN_A2C_2_2_4_4_8_8_16**_32_64_32"
rival_path = "../saved_model/CNN_A2C" + fmt_hyperparameters()
rival_model = os.path.join(rival_path, str(get_max_idx(rival_path)))
agents = init_agents(sess, info_state_size, num_actions,
cnn_parameters, hidden_layers_sizes, rival_model,
**kwargs)
train(agents, env, ret, max_len, begin)
ret = evaluate(agents, env)
stat(ret, begin)