evaluate.py

def evaluate_mask(model, env, totalGames):
    scores = 0
    numOfGames = 0
    numOfWins = 0
    observation, info = env.reset()
    while(numOfGames < totalGames):      
        invalidActions = env.action_masks()
        action, states = model.predict(observation,action_masks=invalidActions,deterministic=False)
        observation, reward, terminated,truncated, info = env.step(action)
        env.render()
        if terminated:
            scores += env.score
            numOfGames += 1
            if env.score == env.WINNING_SCORE:
                numOfWins += 1
            observation, info = env.reset()
            print(info)
    return [scores / numOfGames, 100 * numOfWins / numOfGames]

def evaluate(model, env, totalGames):
    scores = 0
    numOfGames = 0
    numOfWins = 0
    timesteps = 0
    observation, info = env.reset()
    while(numOfGames < totalGames and timesteps < 10000):
        action, states = model.predict(observation,deterministic=False)
        observation, reward, terminated,truncated, info = env.step(action)
        timesteps += 1
        env.render()
        if terminated:
            scores += env.score
            numOfGames += 1
            if env.score == env.WINNING_SCORE:
                numOfWins += 1
            observation, info = env.reset()
            print(info)
    if numOfGames==0:#was unable to play one game(picked too many uncovered tiles)
        return [0,0]    
    return [scores / numOfGames, 100 * numOfWins / numOfGames]

def evaluate_random(model, env, totalGames):
    scores = 0
    numOfGames = 0
    numOfWins = 0
    timesteps = 0
    observation, info = env.reset()
    while(numOfGames < totalGames and timesteps < 10000):
        action = env.action_space.sample()
        observation, reward, terminated,truncated, info = env.step(action)
        timesteps += 1
        env.render()
        if terminated:
            scores += env.score
            numOfGames += 1
            if env.score == env.WINNING_SCORE:
                numOfWins += 1
            observation, info = env.reset()
            print(info)
    if numOfGames==0:#was unable to play one game(picked too many uncovered tiles)
        return [0,0]    
    return [scores / numOfGames, 100 * numOfWins / numOfGames]