def build_actor_critic(sess, env):
w_init = tflearn.initializations.xavier_initializer()
with tf.variable_scope("model", reuse=None, initializer=w_init):
with tf.name_scope("actor"):
actor = ActorNetwork(sess, env, config, is_training=True)
with tf.name_scope("critic"):
critic = CriticNetwork(sess, env, config, is_training=True)
sess.run(tf.global_variables_initializer())
# Initialize target network weights
actor.update_target_network()
critic.update_target_network()
return actor, critic
def build_actor_critic(sess, env, env_eval):
w_init = tflearn.initializations.xavier_initializer()
with tf.variable_scope("model", reuse=None, initializer=w_init):
with tf.name_scope("actor"):
actor = ActorNetwork(sess, env, config, is_training=True)
with tf.name_scope("critic"):
critic = CriticNetwork(sess, env, config, is_training=True)
# if config.noise_std:
# actor_noise = OrnsteinUhlenbeckActionNoise(mu=np.zeros(env.input_cardin * env.state_cardin),
# sigma=config.noise_std,
# sigma_dec=config.noise_dec)
# else:
# actor_noise = None
with tf.variable_scope("model", reuse=True):
with tf.name_scope("actor"):
actor_eval = ActorNetwork(sess,
env_eval,
config,
is_training=False)
with tf.name_scope("critic"):
critic_eval = CriticNetwork(sess,
env_eval,
config,
is_training=False)
sess.run(tf.global_variables_initializer())
# Initialize target network weights
actor.update_target_network()
critic.update_target_network()
return actor, critic, actor_eval, critic_eval #, actor_noise