model.py

from tensorflow.keras.layers import Conv2D, MaxPooling2D, Dense, Flatten

model = tf.keras.Sequential([
    Conv2D(8, (3, 3), input_shape=(X_train.shape[1], X_train.shape[2], X_train.shape[3]), activation='relu', padding='same'),
    MaxPooling2D((2, 2), padding='same'),
    
    Conv2D(16, (3, 3), activation='relu', padding='same'),
    MaxPooling2D((2, 2), padding='same'),
    
    Conv2D(32, (3, 3), activation='relu', padding='same'),
    MaxPooling2D((2, 2), padding='same'),
    
    Flatten(),
    Dense(40, activation='relu'),
    Dense(10, activation='softmax')
    
])

model.summary()