def build_update(self):
"""
Select the network variables and build the operation to copy main
weights and biases to the target network.
"""
self.main_vars = get_vars('main_network', trainable=True)
self.target_vars = get_vars('target_network', trainable=False)
# Initial operation to start with target_net == main_net
self.init_target_op = copy_vars(self.main_vars, self.target_vars, 1,
'init_target')
self.target_update = copy_vars(self.main_vars, self.target_vars,
Settings.UPDATE_TARGET_RATE,
'update_target')
def build_update(self):
"""
Build the operation to copy the weights of the learner's actor network
in the agent's network.
"""
with self.sess.as_default(), self.sess.graph.as_default():
self.network_vars = get_vars('learner_actor', trainable=True)
self.update = copy_vars(self.network_vars, self.vars,
1, 'update_agent_'+str(self.n_agent))
def build_update(self):
"""
Select the network variables and build the operation to copy main
weights and biases to the target network.
"""
# Isolate vars for each network
self.actor_vars = get_vars('actor', trainable=True)
self.critic_vars = get_vars('critic', trainable=True)
self.vars = self.actor_vars + self.critic_vars
self.target_actor_vars = get_vars('target_actor', trainable=False)
self.target_critic_vars = get_vars('target_critic', trainable=False)
self.target_vars = self.target_actor_vars + self.target_critic_vars
# Initial operation to start with target_net == main_net
self.init_target_op = copy_vars(self.vars, self.target_vars, 1,
'init_target')
# Update values for target vars towards current actor and critic vars
self.target_update = copy_vars(self.vars, self.target_vars,
Settings.UPDATE_TARGET_RATE,
'target_update')
def build_update(self):
"""
Build the operation to copy the weights of the learner's actor network
in the agent's network.
"""
with self.sess.as_default(), self.sess.graph.as_default():
self.network_vars = get_vars('learner_actor', trainable=True)
# update agent with the newest actor values
# copy_vars copies the values of network_vars to self.vars with update rate '1'
self.update = copy_vars(
self.network_vars,
self.
vars, # src, dst, update copy actor with most recent weights
1,
'update_agent_' + str(self.n_agent))