Error in class Voc of chatbot_tutorial.py

In the class Voc (line 283), the trim function(line 306) does not correctly reinitialize the word2count dictionary:

def trim(self, min_count):
        if self.trimmed:
            return
        self.trimmed = True

        keep_words = []

        for k, v in self.word2count.items():
            if v >= min_count:
                keep_words.append(k)

        print('keep_words {} / {} = {:.4f}'.format(
            len(keep_words), len(self.word2index), len(keep_words) / len(self.word2index)
        ))

        # Reinitialize dictionaries
        self.word2index = {}
        self.word2count = {}
        self.index2word = {PAD_token: "PAD", SOS_token: "SOS", EOS_token: "EOS"}
        self.num_words = 3 # Count default tokens

        for word in keep_words:
            self.addWord(word)

As the word2count dictionary is reinitialized, self.addWord(word) will only make all the word counts equal to 1, since keep_words will contain the unique words from word2count. The counts from the original conversations are lost. Could you please verify this?

Start in chatbot_tutorial.py around class Voc at line 283 and trim at line 306. Reproduce the behavior by comparing word counts before and after trimming, then verify that retained words preserve their original counts while excluded words are removed. Done when the tutorial's vocabulary trimming behavior matches the issue's expected count preservation.