diff --git a/knn.py b/knn.py
index f3006bde1c5699e67ce407b33bb71d85af6da9df..511353b0799291f023c4ee61120081f17b68c166 100644
--- a/knn.py
+++ b/knn.py
@@ -15,12 +15,9 @@ from tqdm import tqdm
 def distance_matrix(A,B) : 
     sum_of_squaresA= np.sum(A**2, axis = 1, keepdims = True)
     sum_of_squaresB = np.sum(B**2, axis = 1)
-    # sum_of_squaresA = np.tile(sum_of_squaresAVect, (np.shape(B)[0], 1))
-    # sum_of_squaresB = np.tile(sum_of_squaresBVect, (np.shape(A)[0], 1))
 
     # Calculate the dot product between the two matrices
     dot_product = np.dot(A, B.T)
-    # dot_product = np.einsum('ij,jk', A, B.T)
     # Calculate the Euclidean distance matrix using the hint provided
     dists = np.sqrt(sum_of_squaresA + sum_of_squaresB - 2 * dot_product)
     return dists