def test_cql_impl(observation_shape, action_size, actor_learning_rate,
critic_learning_rate, temp_learning_rate,
alpha_learning_rate, gamma, tau, n_critics, bootstrap,
share_encoder, initial_temperature, initial_alpha,
alpha_threshold, n_action_samples, eps, use_batch_norm,
q_func_type, scaler, augmentation, n_augmentations,
encoder_params):
impl = CQLImpl(observation_shape,
action_size,
actor_learning_rate,
critic_learning_rate,
temp_learning_rate,
alpha_learning_rate,
gamma,
tau,
n_critics,
bootstrap,
share_encoder,
initial_temperature,
initial_alpha,
alpha_threshold,
n_action_samples,
eps,
use_batch_norm,
q_func_type,
use_gpu=False,
scaler=scaler,
augmentation=augmentation,
n_augmentations=n_augmentations,
encoder_params=encoder_params)
torch_impl_tester(impl,
discrete=False,
deterministic_best_action=q_func_type != 'iqn')
def test_cql_impl(
observation_shape,
action_size,
actor_learning_rate,
critic_learning_rate,
temp_learning_rate,
alpha_learning_rate,
actor_optim_factory,
critic_optim_factory,
temp_optim_factory,
alpha_optim_factory,
encoder_factory,
q_func_factory,
gamma,
tau,
n_critics,
bootstrap,
share_encoder,
initial_temperature,
initial_alpha,
alpha_threshold,
n_action_samples,
soft_q_backup,
scaler,
action_scaler,
augmentation,
):
impl = CQLImpl(
observation_shape,
action_size,
actor_learning_rate,
critic_learning_rate,
temp_learning_rate,
alpha_learning_rate,
actor_optim_factory,
critic_optim_factory,
temp_optim_factory,
alpha_optim_factory,
encoder_factory,
encoder_factory,
create_q_func_factory(q_func_factory),
gamma,
tau,
n_critics,
bootstrap,
share_encoder,
initial_temperature,
initial_alpha,
alpha_threshold,
n_action_samples,
soft_q_backup,
use_gpu=False,
scaler=scaler,
action_scaler=action_scaler,
augmentation=augmentation,
)
torch_impl_tester(impl,
discrete=False,
deterministic_best_action=q_func_factory != "iqn")
def test_cql_impl(
observation_shape,
action_size,
actor_learning_rate,
critic_learning_rate,
temp_learning_rate,
alpha_learning_rate,
actor_optim_factory,
critic_optim_factory,
temp_optim_factory,
alpha_optim_factory,
encoder_factory,
q_func_factory,
gamma,
tau,
n_critics,
target_reduction_type,
initial_temperature,
initial_alpha,
alpha_threshold,
conservative_weight,
n_action_samples,
soft_q_backup,
scaler,
action_scaler,
reward_scaler,
):
impl = CQLImpl(
observation_shape=observation_shape,
action_size=action_size,
actor_learning_rate=actor_learning_rate,
critic_learning_rate=critic_learning_rate,
temp_learning_rate=temp_learning_rate,
alpha_learning_rate=alpha_learning_rate,
actor_optim_factory=actor_optim_factory,
critic_optim_factory=critic_optim_factory,
temp_optim_factory=temp_optim_factory,
alpha_optim_factory=alpha_optim_factory,
actor_encoder_factory=encoder_factory,
critic_encoder_factory=encoder_factory,
q_func_factory=create_q_func_factory(q_func_factory),
gamma=gamma,
tau=tau,
n_critics=n_critics,
target_reduction_type=target_reduction_type,
initial_temperature=initial_temperature,
initial_alpha=initial_alpha,
alpha_threshold=alpha_threshold,
conservative_weight=conservative_weight,
n_action_samples=n_action_samples,
soft_q_backup=soft_q_backup,
use_gpu=None,
scaler=scaler,
action_scaler=action_scaler,
reward_scaler=reward_scaler,
)
torch_impl_tester(
impl, discrete=False, deterministic_best_action=q_func_factory != "iqn"
)