def test(env, actor_model, is_discrete):
    '\n\t\tTests the model.\n\t\tParameters:\n\t\t\tenv - the environment to test the policy on\n\t\t\tactor_model - the actor model to load in\n\t\tReturn:\n\t\t\tNone\n\t'
    print(f'Testing {actor_model}', flush=True)
    if (actor_model == ''):
        print(f"Didn't specify model file. Exiting.", flush=True)
        sys.exit(0)
    obs_dim = env.observation_space.shape[0]
    if is_discrete:
        act_dim = env.action_space.n
    else:
        act_dim = env.action_space.shape[0]
    policy = FeedForwardActorNN(obs_dim, act_dim, is_discrete)
    policy.load_state_dict(torch.load(actor_model))
    eval_policy(policy=policy, env=env, render=True, is_discrete=is_discrete)
Tests the model.
Parameters:
        env - the environment to test the policy on
        actor_model - the actor model to load in
Return:
        None
def test(env, actor_model, is_discrete):
    '\n\t\tTests the model.\n\t\tParameters:\n\t\t\tenv - the environment to test the policy on\n\t\t\tactor_model - the actor model to load in\n\t\tReturn:\n\t\t\tNone\n\t'
    print(f'Testing {actor_model}', flush=True)
    if (actor_model == ):
        print(f"Didn't specify model file. Exiting.", flush=True)
        sys.exit(0)
    obs_dim = env.observation_space.shape[0]
    if is_discrete:
        act_dim = env.action_space.n
    else:
        act_dim = env.action_space.shape[0]
    policy = FeedForwardActorNN(obs_dim, act_dim, is_discrete)
    policy.load_state_dict(torch.load(actor_model))
    eval_policy(policy=policy, env=env, render=True, is_discrete=is_discrete)