How does tf.keras.layers.Conv2D with padding='same' and strides > 1 behave?

Question

I read What is the difference between 'SAME' and 'VALID' padding in tf.nn.max_pool of tensorflow? but this is not true to my experiment.

import t         


        

Answer 1

In tensorflow, for stride s and input size n, padding with same gives:

⌈n/s⌉

or the ceiling of input size divided by stride.