Update knn.py

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