我正在用tflearn制作一个AI聊天机器人程序，但每次运行它时，它都会在tflearn上给我一个Traceback错误。DNN((。错误如下：
Traceback (most recent call last):
File "c:/Users/sande/Desktop/Vihaan/ThirdPartySoftware/Python/ChatBot/main.py", line 85, in <module>
model.fit(training, output, n_epoch=1000, batch_size=8, show_metric=True)
File "C:UserssandeAppDataLocalProgramsPythonPython38libsite-packagestflearnmodelsdnn.py", line 196, in fit
self.trainer.fit(feed_dicts, val_feed_dicts=val_feed_dicts,
File "C:UserssandeAppDataLocalProgramsPythonPython38libsite-packagestflearnhelperstrainer.py", line 341, in fit
snapshot = train_op._train(self.training_state.step,
File "C:UserssandeAppDataLocalProgramsPythonPython38libsite-packagestflearnhelperstrainer.py", line 826, in _train
tflearn.is_training(True, session=self.session)
File "C:UserssandeAppDataLocalProgramsPythonPython38libsite-packagestflearnconfig.py", line 95, in is_training
tf.get_collection('is_training_ops')[0].eval(session=session)
File "C:UserssandeAppDataLocalProgramsPythonPython38libsite-packagestensorflowpythonframeworkops.py", line 913, in eval
return _eval_using_default_session(self, feed_dict, self.graph, session)
File "C:UserssandeAppDataLocalProgramsPythonPython38libsite-packagestensorflowpythonframeworkops.py", line 5512, in _eval_using_default_session
return session.run(tensors, feed_dict)
File "C:UserssandeAppDataLocalProgramsPythonPython38libsite-packagestensorflowpythonclientsession.py", line 957, in run
result = self._run(None, fetches, feed_dict, options_ptr,
File "C:UserssandeAppDataLocalProgramsPythonPython38libsite-packagestensorflowpythonclientsession.py", line 1104, in _run
raise RuntimeError('Attempted to use a closed Session.')
RuntimeError: Attempted to use a closed Session.
这是代码：
import numpy
import tflearn
import tensorflow
import random
import json
import pickle
import nltk
nltk.download("punkt")
from nltk.stem.lancaster import LancasterStemmer
stemmer = LancasterStemmer()
with open("intents.json") as file:
data = json.load(file)
try:
with open("data.pickle", "rb")as f:
words, label, 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) 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)
tensorflow.compat.v1.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)
model = tflearn.DNN(net)
try:
model.load("model.tflearn")
except:
model.fit(training, output, n_epoch=1000, batch_size=8, show_metric=True)
model.save("model.tflearn")
我尝试了多种修复方法，但似乎都不起作用。我甚至尝试重新安装Tensorflow和Tflearn，因为Tensorflow也给了我一个错误。
我该如何解决这个问题？
顺便说一句，这是文件。内容：
{"intents": [
{"tag": "greeting",
"patterns": ["Hi", "How are you", "Is anyone there?", "Hello", "Good day", "Whats up"],
"responses": ["Hello!", "Good to see you again!", "Hi there, how can I help?"],
"context_set": ""
},
{"tag": "goodbye",
"patterns": ["See you later", "Goodbye", "I am Leaving", "Have a Good day"],
"responses": ["Sad to see you go :(", "Talk to you later", "Goodbye!"],
"context_set": ""
},
{"tag": "age",
"patterns": ["how old", "how old is vihaan", "what is your age", "how old are you", "age?"],
"responses": ["I am 12 years old!", "12 years young!"],
"context_set": ""
},
{"tag": "name",
"patterns": ["what is your name", "what should I call you", "whats your name?"],
"responses": ["You can call me Vihaan.", "I'm Vihaan!", "I'm Vihaan aka PyGamerViharo."],
"context_set": ""
},
{"tag": "code",
"patterns": ["Do you like python?", "like python?", "what language", "what language do you recommend?"],
"responses": ["Yes! We have made multiple projects. Check them out at www.github.com/PyGamerViharo", "I always recommend Python, even for developers!"],
"context_set": ""
}
]
}
我运行您的代码，并像这样更改代码，这对我来说很有效。我想出于某种原因，对象模型在"model.load("model.tfslearn"("中断后被处理
model = tflearn.DNN(net)
try:
model.load("model.tflearn")
except:
model = tflearn.DNN(net)
model.fit(training, output, n_epoch=1000, batch_size=8, show_metric=True)
model.save("model.tflearn")`