def __call__(self):
self.exit_function() # Passed in exit function
site.setquit() # Restore default builtins
exit() # Call builtin
import tflearn
import random
import pickle
import json
from root import PERSONMODEL, PERSONMODEL_TRAIN, PERSONMODEL_JSON, PERSONMODEL_LOG
# restore all of our data structures
stemmer = LancasterStemmer()
data = pickle.load(open(PERSONMODEL_TRAIN, "rb"))
words = data['words']
classes = data['classes']
train_x = data['train_x']
train_y = data['train_y']
import site
site.setquit()
# import our chat-bot intents file
with open(PERSONMODEL_JSON) as json_data:
intents = json.load(json_data)
# Build neural network
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)
# Define models and setup tensorboard
model = tflearn.DNN(net, tensorboard_dir=PERSONMODEL_LOG)
def __call__(self):
self.exit_function() # Passed in exit function
site.setquit() # Restore default builtins
exit() # Call builtin
def update_event(self, inp=-1):
self.set_output_val(0, site.setquit())