ValueError: attempt to get argmax of an empty sequence

前提・実現したいこと

未知の行列値（8行1列）を習得して予測するニューラルネットの予測メゾッドのコードを書いていますが，なぜかargmaxの中身が空になっており，実行できない状態です．temp = [] の部分の書き方が悪いのでだと思うのですが，どのように直せばよろしいでしょうか？

発生している問題・エラーメッセージ

### 該当のソースコード

import
1import myo 
2import threading
3import time
4from time import sleep
5import numpy as np
6import tensorflow as tf
7from include.model import model
8from myo import Hub
9import os
10os.environ['TF_CPP_MIN_LOG_LEVEL']='2'
11
12
13x, y, output, global_step, y_pred_cls = model(5)
14
15saver = tf.train.Saver()
16_SAVE_PATH = "./data/tensorflow_sessions/myo_armband/"
17sess = tf.Session()
18
19status = 0
20X = []
21
22try:
23    print("Trying to restore last checkpoint ...")
24    last_chk_path = tf.train.latest_checkpoint(checkpoint_dir=_SAVE_PATH)
25    print(last_chk_path)
26    saver.restore(sess, save_path=last_chk_path)
27    print("Restored checkpoint from:", last_chk_path)
28except Exception as e:
29    print("Failed to restore checkpoint. Initializing variables instead.")
30    sess.run(tf.global_variables_initializer())
31
32class MyListener(myo.DeviceListener):
33
34    def __init__(self, queue_size=8):
35        self.lock = threading.Lock()
36        self.emg_data_queue = collections.deque(maxlen=queue_size)
37        self.ori_data_queue = collections.deque(maxlen=queue_size)
38
39    def on_connected(self, event):        
40        event.device.stream_emg(True)
41        
42    def on_emg(self, event):
43        #with self.lock:
44        if(status):
45            X.append(event.emg)
46            self.emg_data_queue.append((event.timestamp,event.emg))
47
48    def get_emg_data(self):
49        with self.lock:
50            return list(self.emg_data_queue)
51
52myo.init(bin_path=r'C:\Users\名前\Desktop\myo-sdk-win-0.9.0\bin')
53hub = myo.Hub()
54feed = myo.ApiDeviceListener()
55start = time.time()
56temp = []　　☚　ここです．
57
58status = 9999
59
60listener = MyListener()
61with hub.run_in_background(listener.on_event):
62    req_iter = 20
63    #regis_x = 999 
64    while(1):
65        if len(X) >= 64:
66            #if regis_x != X[0][0]: 
67                #print(len(X))
68            X_temp = X[0:8]
69                #print('qwe')
70                #print(X[0:2])
71                #print('qwe')
72                #print(len(X_temp))
73            X_temp = list(np.stack(X_temp).flatten())
74                #print(X_temp[0:2]) 
75                #regis_x = X[0][0]
76            pred = sess.run(y_pred_cls, feed_dict={x: np.array([X_temp])})
77            temp.append(pred[0])
78            X = []
79            
80        if time.time() - start >= 1:
81            #pred = sess.run(y_pred_cls, feed_dict={x: np.array([X_temp])})
82            #temp.append(pred[0])
83            response = np.argmax(np.bincount(temp))
84            print("Predicted gesture: {0}".format(response))
85            temp = []
86            start = time.time()
87    sleep(1)