def _build_actor(self):
self.policy = create_normal_policy(self.observation_shape,
self.action_size,
self.actor_encoder_factory,
min_logstd=-6.0,
max_logstd=0.0,
use_std_parameter=True)
def _build_actor(self):
self.policy = create_normal_policy(self.observation_shape,
self.action_size,
self.use_batch_norm,
min_logstd=-6.0,
max_logstd=0.0,
use_std_parameter=True,
encoder_params=self.encoder_params)
def test_create_normal_policy(observation_shape, action_size, batch_size,
use_batch_norm):
policy = create_normal_policy(observation_shape, action_size,
use_batch_norm)
assert isinstance(policy, NormalPolicy)
x = torch.rand((batch_size, ) + observation_shape)
y = policy(x)
assert y.shape == (batch_size, action_size)
def _build_actor(self):
self.policy = create_normal_policy(self.observation_shape,
self.action_size,
self.use_batch_norm,
encoder_params=self.encoder_params)
def _build_actor(self):
self.policy = create_normal_policy(self.observation_shape,
self.action_size,
self.actor_encoder_factory)
