def __init__(self):
self.config = tf.ConfigProto(
gpu_options=tf.GPUOptions(per_process_gpu_memory_fraction=0.23),
# device_count = {'gpu': 2}
)
self.session = tf.Session(config=self.config)
self.model_test = create_model
self.dataset = list(
data_utils.prepare_multi_task_data(FLAGS.data_dir,
FLAGS.in_vocab_size,
FLAGS.out_vocab_size))
self.pred = run_valid_test(self.session,
self.model_test,
mode='Test',
data_set=self.dataset)
def query():
message = str(request.args.get('message'))
for way in WAY_LS:
if way in message:
message = message.replace("-", " ")
user_in = PrepUtility.create_test_seq_in(message)
PrepUtility.prepareNLUMessage(user_in, test_seq_in_path)
date_set = prepare_multi_task_data(data_path, 10000, 10000)
date_set = list(date_set)
in_seq_test, out_seq_test, label_test = date_set[2]
test_set = read_data_test(in_seq_test, out_seq_test, label_test)
start = time.time()
predictions = model.predict(test_set)
#print(time.time()-start)
response = get_response(message)
return jsonify(response)
if ckpt:
print("Reading model parameters from %s" % ckpt.model_checkpoint_path)
model_test.saver.restore(session, ckpt.model_checkpoint_path)
# model_train.saver.restore(session, ckpt.model_checkpoint_path)
else:
print("Created model with fresh parameters.")
session.run(tf.global_variables_initializer())
return model_test #model_train,
vocab_path = ''
tag_vocab_path = ''
label_vocab_path = ''
date_set = data_utils.prepare_multi_task_data(FLAGS.data_dir,
FLAGS.in_vocab_size,
FLAGS.out_vocab_size)
date_set = list(date_set)
in_seq_train, out_seq_train, label_train = date_set[0]
in_seq_dev, out_seq_dev, label_dev = date_set[1]
in_seq_test, out_seq_test, label_test = date_set[2]
vocab_path, tag_vocab_path, label_vocab_path = date_set[3]
result_dir = FLAGS.model_dir + '/test_results'
if not os.path.isdir(result_dir):
os.makedirs(result_dir)
current_taging_valid_out_file = result_dir + '/tagging.valid.hyp.txt'
current_taging_test_out_file = result_dir + '/tagging.test.hyp.txt'
date_set = list(date_set)
in_seq_test, out_seq_test, label_test = date_set[2]
test_set = read_data_test(in_seq_test, out_seq_test, label_test)
start = time.time()
predictions = model.predict(test_set)
#print(time.time()-start)
response = get_response(message)
return jsonify(response)
@app.route("/api/countries")
def countries():
response = dict(countries=COUNTRIES, classes=CLASSES)
return jsonify(response)
# Load chatting page
@app.route('/')
def index():
return render_template('chat.html')
if __name__ == "__main__":
date_set = prepare_multi_task_data(data_path, 10000, 10000)
date_set = list(date_set)
in_seq_test, out_seq_test, label_test = date_set[2]
test_set = read_data_test(in_seq_test, out_seq_test, label_test)
model.predict(test_set)
write_json(dict(), "ticket.json")
app.run(debug=False, port=1234)