Generally I suggest you to start to express what you want to achieve with something simpler like a tensor manipulation without introducing layer input etc.
In this way you can check if you could vectorize the operations that you need with tensorflow ops cause manually iterate over tensor with loops is going to be quite inefficient in general.
I suggest you to start with a small manual filled tensor that is your dummy feature map.
E.g.
import tensorflow as tf
tensor = tf.constant([[[1,2,3],[3,4,5]],[[6,7,8],[9,10,11]]])
print(tensor.shape)
print(tensor)
print(tf.reduce_max(tensor, [[2][0]]))
print(tf.reduce_min(tensor, [[2][0]]))

(2, 2, 3)

tf.Tensor(
[[[ 1  2  3]
  [ 3  4  5]]
 [[ 6  7  8]
  [ 9 10 11]]], shape=(2, 2, 3), dtype=int32)

tf.Tensor(
[[ 3  5]
 [ 8 11]], shape=(2, 2), dtype=int32)

tf.Tensor(
[[1 3]
 [6 9]], shape=(2, 2), dtype=int32)

Then I think that you can define your own “dummy” manual feature map with a small tensor:
I have this small dummy input Tensor example and I want this output  Tensor.