def METHOD_NAME():
    env = MemoryEnvironment([BRAIN_NAME], action_sizes=(1, 1), step_size=0.5)
    new_networksettings = attr.evolve(
        SAC_TORCH_CONFIG.network_settings,
        memory=NetworkSettings.MemorySettings(memory_size=16, sequence_length=16),
    )
    new_hyperparams = attr.evolve(
        SAC_TORCH_CONFIG.hyperparameters,
        batch_size=256,
        learning_rate=3e-4,
        buffer_init_steps=1000,
        steps_per_update=2,
    )
    config = attr.evolve(
        SAC_TORCH_CONFIG,
        hyperparameters=new_hyperparams,
        network_settings=new_networksettings,
        max_steps=4000,
    )
    check_environment_trains(env, {BRAIN_NAME: config}, training_seed=1212)