diff --git a/knn.py b/knn.py
index 55b1f1543b0066a1446d269249879ed9c1591d17..b99e3c2902529633a8e0893175bb66580a79ba75 100644
--- a/knn.py
+++ b/knn.py
@@ -1,6 +1,10 @@
 #Libraries
 import numpy as np
 import matplotlib.pyplot as plt
+import math
+import random
+from read_cifar import *
+
 #Functions
 def distance_matrix(Y , X):
     #This function takes as parameters two matrices X and Y
@@ -26,7 +30,7 @@ def knn_predict(dists, labels_train, k):
 
 def evaluate_knn(data_train, labels_train, data_test, labels_test, k):
     #This function evaluates the knn classifier rate
-    labels_test__pred=knn_predict(distance_matrix(data_train, data_test), labels_train, k)
+    labels_test_pred=knn_predict(distance_matrix(data_train, data_test), labels_train, k)
     num_samples= data_test.shape[0]
     num_correct= (labels_test == labels_test_pred).sum().item()
     accuracy= 100 * (num_correct / num_samples)  #The accuracy is the percentage of the correctly predicted classes