def test_discrete_bcq_impl(
observation_shape,
action_size,
learning_rate,
optim_factory,
encoder_factory,
q_func_factory,
gamma,
n_critics,
target_reduction_type,
action_flexibility,
beta,
scaler,
):
impl = DiscreteBCQImpl(
observation_shape=observation_shape,
action_size=action_size,
learning_rate=learning_rate,
optim_factory=optim_factory,
encoder_factory=encoder_factory,
q_func_factory=create_q_func_factory(q_func_factory),
gamma=gamma,
n_critics=n_critics,
target_reduction_type=target_reduction_type,
action_flexibility=action_flexibility,
beta=beta,
use_gpu=None,
scaler=scaler,
)
torch_impl_tester(impl,
discrete=True,
deterministic_best_action=q_func_factory != "iqn")
def test_discrete_bcq_impl(
observation_shape,
action_size,
learning_rate,
optim_factory,
encoder_factory,
q_func_factory,
gamma,
n_critics,
bootstrap,
share_encoder,
target_reduction_type,
action_flexibility,
beta,
scaler,
augmentation,
):
impl = DiscreteBCQImpl(
observation_shape,
action_size,
learning_rate,
optim_factory,
encoder_factory,
create_q_func_factory(q_func_factory),
gamma,
n_critics,
bootstrap,
share_encoder,
target_reduction_type,
action_flexibility,
beta,
use_gpu=False,
scaler=scaler,
augmentation=augmentation,
)
torch_impl_tester(impl,
discrete=True,
deterministic_best_action=q_func_factory != "iqn")
def test_discrete_bcq_impl(observation_shape, action_size, learning_rate,
optim_factory, encoder_factory, gamma, n_critics,
bootstrap, share_encoder, action_flexibility, beta,
q_func_type, scaler, augmentation, n_augmentations):
impl = DiscreteBCQImpl(observation_shape,
action_size,
learning_rate,
optim_factory,
encoder_factory,
gamma,
n_critics,
bootstrap,
share_encoder,
action_flexibility,
beta,
q_func_type,
use_gpu=False,
scaler=scaler,
augmentation=augmentation,
n_augmentations=n_augmentations)
torch_impl_tester(impl,
discrete=True,
deterministic_best_action=q_func_type != 'iqn')