How are weights organized in Conv2D layers?
If you print those shapes using below for loop

weights_m=model.get_weights()
for i in range(8):
  print(weights_m[i].shape)


you will get output as 

(3, 3, 1, 32)
(32,)
(3, 3, 32, 64)
(64,)
(9216, 128)
(128,)
(128, 10)
(10,)  

so we will get one layer weight and bias. we have a total of 4 layers(2 conv + 2 dense) so 8 weight vectors.