def METHOD_NAME(num_visual, training_seed):
    env = SimpleEnvironment(
        [BRAIN_NAME], num_visual=num_visual, num_vector=0, action_sizes=(1, 1)
    )
    new_hyperparams = attr.evolve(
        SAC_TORCH_CONFIG.hyperparameters,
        buffer_size=50000,
        batch_size=128,
        learning_rate=3.0e-4,
    )
    config = attr.evolve(
        SAC_TORCH_CONFIG, hyperparameters=new_hyperparams, max_steps=3000
    )
    check_environment_trains(env, {BRAIN_NAME: config}, training_seed=training_seed)