使用 Tensorflow 构建 ChatBot 时输入属性错误

Question

我目前正在使用 Python 和 Tensorflow 构建一个简单的 ChatBot。但是，我不断收到属性错误：enter。有人可以看看吗？谢谢。 我正在使用最新版本的 VSC 和 macOS 10.15.7。

这是我的代码：

import nltk
from nltk.stem.lancaster import LancasterStemmer
stemmer = LancasterStemmer()
import numpy
import tflearn
import tensorflow as tf
import random
import json
import pickle


with open("/Users/Users/Untitled/intents.json") as file:
    data = json.load(file)

try:
    with open("data.pickle", "rb") as f:
        words, labels, training, output = pickle.load(f)
except:
    words = []
    labels = []
    docs_x = []
    docs_y = []

    for intent in data["intents"]:
        for pattern in intent["patterns"]:
            wrds = nltk.word_tokenize(pattern)
            words.extend(wrds)
            docs_x.append(wrds)
            docs_y.append(intent["tag"])

        if intent["tag"] not in labels:
            labels.append(intent["tag"])

    words = [stemmer.stem(w.lower()) for w in words if w != "?"]
    words = sorted(list(set(words)))

    labels = sorted(labels)

    training = []
    output = []

    out_empty = [0 for _ in range(len(labels))]

    for x, doc in enumerate(docs_x):
        bag = []

        wrds = [stemmer.stem(w.lower()) for w in doc]

        for w in words:
            if w in wrds:
                bag.append(1)
            else:
                bag.append(0)

        output_row = out_empty[:]
        output_row[labels.index(docs_y[x])] = 1

        training.append(bag)
        output.append(output_row)


    training = numpy.array(training)
    output = numpy.array(output)

    with open("data.pickle", "wb") as f:
        pickle.dump((words, labels, training, output), f)

    tf.reset_default_graph()

net = tflearn.input_data(shape=[None, len(training[0])])
net = tflearn.fully_connected(net, 8)
net = tflearn.fully_connected(net, 8)
net = tflearn.fully_connected(net, len(output[0]), activation="softmax")
net = tflearn.regression(net)

with tflearn.DNN(net) as model:
    

    try:
        model.load("model.tflearn")
    except:
        model.fit(training, output, n_epoch=1000, batch_size=8, show_metric=True)
        model.save("model.tflearn")

def bag_of_words(s, words):
        bag = [0 for _ in range(len(words))]

        s_words = nltk.word_tokenize(s)
        s_words = [stemmer.stem(word.lower()) for word in s_words]

        for se in s_words:
            for i, w in enumerate(words):
                if w == se:
                    bag[i] = 1
                
        return numpy.array(bag)


def chat():
    print("Start talking with the bot (type quit to stop)!")
    while True:
        inp = input("You: ")
        if inp.lower() == "quit":
            break

        results = model.predict([bag_of_words(inp, words)])
        results_index = numpy.argmax(results)
        tag = labels[results_index]

        for tg in data["intents"]:
            if tg['tag'] == tag:
                responses = tg['responses']

        print(random.choice(responses))

chat()

这是错误：

Traceback (most recent call last):
  File "/Users/Users/Untitled/main.py", line 76, in <module>
    with tflearn.DNN(net) as model:
AttributeError: __enter__

再一次，如果有人查看我的代码，我将不胜感激。

再次感谢。

Answer 1

在尝试阻止之前将tflearn.DNN(net) as model:替换为model=tflearn.DNN(net)。