code: def _operation_to_pooling_shape(operation):
      """Takes in the operation string and returns the pooling kernel shape."""
      splitted_operation = operation.split("_")
      shape = splitted_operation[-1]
      assert "x" in shape
      filter_height, filter_width = shape.split("x")
      assert filter_height == filter_width
      return int(filter_height)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
label_desc: Use image node_id 12 for calling a global function with example usage: _operation_to_pooling_shape(operation) and returns: int