def _make_agent_modules(self):
self.policy = StochasticPolicy(self._dummy_env,
256,
a_range=5,
action_size=self._dummy_env.goal_size)
self.v_module = Value(self._dummy_env, 256, use_antigoal=False)
self.policy_lo = StochasticPolicy(self._dummy_env, 256)
self.v_module_lo = Value(self._dummy_env, 256, use_antigoal=False)
def _make_agent_modules(self):
self.vae = VQVAEDiscriminator(state_size=self._dummy_env.state_size, **self.vae_args)
self.vae.load_checkpoint(self.vae_checkpoint_path)
kwargs = dict(env=self._dummy_env, hidden_size=self.hidden_size, num_layers=self.num_layers,
goal_size=self.vae.code_size, normalize_inputs=self.normalize_inputs)
self.policy = StochasticPolicy(**kwargs)
self.v_module = Value(use_antigoal=self.use_antigoal, **kwargs)
def _make_agent_modules(self):
self._make_skill_embedding()
kwargs = dict(env=self._dummy_env,
hidden_size=self.hidden_size,
num_layers=self.num_layers,
goal_size=self.skill_n,
normalize_inputs=self.normalize_inputs)
self.policy = StochasticPolicy(**kwargs)
self.v_module = Value(use_antigoal=False, **kwargs)
def _make_agent_modules(self):
self.policy = Policy(self._dummy_env, 128, a_range=5, action_size=2)
self.p_target = Policy(self._dummy_env, 128, a_range=5, action_size=2)
self.p_target.load_state_dict(self.policy.state_dict())
self.q_module = Critic(self._dummy_env, 128, a_range=5, action_size=2)
self.q_target = Critic(self._dummy_env, 128, a_range=5, action_size=2)
self.q_target.load_state_dict(self.q_module.state_dict())
self.policy_lo = StochasticPolicy(self._dummy_env, 256, goal_size=2)
self.v_module_lo = Value(self._dummy_env,
256,
goal_size=2,
use_antigoal=False)
def _make_agent_modules(self):
self.policy = StochasticPolicy(self._dummy_env, 128)
self.v_module = Value(self._dummy_env, 128, use_antigoal=False)
def _make_agent_modules(self):
self.policy = StochasticPolicy(self._dummy_env, 256)
self.v_module = Value(self._dummy_env,
256,
use_antigoal=self.use_antigoal)