def __init__(self):
print("Init")
if self.instance is not None:
raise ValueError("Bot fonksiyonunu çağır mayı unuttn? ")
self.stemmer = LancasterStemmer()
data = pickle.load(open(path.getPath('trained_data'), "rb"))
self.words = data['words']
self.classes = data['classes']
train_x = data['train_x']
train_y = data['train_y']
with open(path.getJsonPath()) as json_data:
self.intents = json.load(json_data)
net = tflearn.input_data(shape=[None, len(train_x[0])])
net = tflearn.fully_connected(net, 8)
net = tflearn.fully_connected(net, 8)
net = tflearn.fully_connected(net, len(train_y[0]), activation='softmax')
net = tflearn.regression(net)
self.model = tflearn.DNN(net, tensorboard_dir=path.getPath('train_logs'))
self.model.load(path.getPath('model.tflearn'))
train_x = list(
training[:,
0]) #eğitilmiş datayı sıfır bir diye iki ayrı listeye dönüştürdük
train_y = list(
training[:, 1]) #kelimeleri ve verileri modelimize girmeye hazır kıldık
tf.reset_default_graph()
net = tflearn.input_data(shape=[None, len(train_x[0])]) #
net = tflearn.fully_connected(net, 8)
net = tflearn.fully_connected(net, 8)
net = tflearn.fully_connected(net, len(train_y[0]),
activation='softmax') #olanözcükler
net = tflearn.regression(net)
model = tflearn.DNN(net, tensorboard_dir=path.getPath('train_logs'))
model.fit(train_x, train_y, n_epoch=20000, batch_size=500, show_metric=True)
model.save(path.getPath('model.tflearn'))
def clean_up_sentence(sentence): #cümleleri temizleyeceğiz
sentence_words = nltk.word_tokenize(sentence)
sentence_words = [stemmer.stem(word.lower()) for word in sentence_words
] #büyük küçük harf farkını ortdan kaldırdık
return sentence_words #cümlelerdeki kelimeleri döndürdük
def bow(sentence, words, show_details=False):
sentence_words = clean_up_sentence(sentence)
bag = [0] * len(words)
for s in sentence_words: