What does `tf.strided_slice()` do?

Question

I am wondering what tf.strided_slice() operator actually does.
The doc says,

To a first order, this operation extracts a slice of siz

Answer 1

I find this technique useful to debug the solution. rule: always omit recurring patterns and try to keep step at (end-1).

t = tf.constant([[[1, 1, 1], [2, 2, 2]],
             [[3, 3, 3], [4, 4, 4]],
             [[5, 5, 5], [6, 6, 6]]])  

# ex 1:
tf.strided_slice(t, [1, 0, 0], [2, 1, 3], [1, 1, 1])

# 3rd position:
1,0,0 > 3     
1,0,1 > 3
1,0,2 > 3
# 2nd and 1st position:satisfies the rule listed above, skipping these.

# ex 2:
tf.strided_slice(t, [1, 0, 0], [2, 2, 3], [1, 1, 1])

# 3rd position:
1,0,0 > 3     
1,0,1 > 3
1,0,2 > 3
# 2nd positon:
1,1,0 > 4
1,1,1 > 4
1,1,2 > 4
# 1st position: satisfies the rule listed above, skipping.

# Ex 3:
tf.strided_slice(t, [1, -1, 0], [2, -3, 3], [1, -1, 1])

# 3rd position:
1,-1,0 > 4
1,-1,1 > 4
1,-1,2 > 4
# 2nd position:
1,-2,0 > 3
1,-2,1 > 3
1,-2,2 > 3
# 1st position:satisfies the rule listed above, skipping.