Convolution output matrix for stride 1

CNNOM.py

import numpy as np
input_matrix=np.array([[3,0,1,2,7,4],
                       [1,5,8,9,3,1],
                       [2,7,2,5,1,3],
                       [0,1,3,1,7,8],
                       [4,2,1,6,2,8],
                       [2,4,5,2,3,9] 
                      ])
                      

filter_matrix = np.array([[1,0,-1],
                         [1,0,-1],
                         [1,0,-1]
                         ])                      
       
       
input_size = len(input_matrix)
filter_size = len(filter_matrix)
stride=1
padding =0

output_size = int((input_size+(2*padding)-filter_size)/stride)+1
print(output_size)       


Output_matrix = np.zeros((output_size,output_size))
Output_matrix

for i in range(len(input_matrix)-2):
    
    for j in range(len(input_matrix)-2):
                
        x = input_matrix[i:filter_size+i , j:filter_size+j]
        
        y=x.ravel()*filter_matrix.ravel()
        Output_matrix[i][j]=y.sum()