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63 lines
1.8 KiB
Python
63 lines
1.8 KiB
Python
import argparse
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from ai import AI
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import numpy as np
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from tqdm import tqdm
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global solution
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def result_callback(word):
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global solution
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result = ['0', '0', '0', '0', '0']
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for i, letter in enumerate(word):
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if solution[i] == word[i]:
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result[i] = '2'
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elif letter in solution:
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result[i] = '1'
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else:
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pass
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return result
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def main(args):
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global solution
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if args.n is None:
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raise Exception('Need to specify n (i.e. n = 1 for wordle, n = 4 for quordle, n = 16 for sedecordle).')
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ai = AI(args.vocab_file, args.model_file, use_q_model=args.q_model, device=args.device)
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total_guesses = 0
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wins = 0
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num_eval = args.num_eval
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np.random.seed(0)
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for i in tqdm(range(num_eval)):
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idx = np.random.choice(range(len(ai.vocab)))
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solution = ai.vocab[idx]
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ai.reset(solution)
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guesses, word = ai.solve_eval(results_callback=result_callback)
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if word != solution:
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total_guesses += 5
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else:
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total_guesses += guesses
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wins += 1
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print(f"q_model?: {args.q_model} \t average guesses per game: {total_guesses / num_eval} \t win rate: {wins / num_eval}")
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if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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parser.add_argument('--n', dest='n', type=int, default=None)
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parser.add_argument('--vocab_file', dest='vocab_file', type=str, default='wordle_words.txt')
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parser.add_argument('--num_eval', dest="num_eval", type=int, default=1000)
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parser.add_argument('--model_file', dest="model_file", type=str, default='wordle_ppo_model')
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parser.add_argument('--q_model', dest="q_model", type=bool, default=False)
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parser.add_argument('--device', dest="device", type=str, default="cuda")
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args = parser.parse_args()
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main(args) |