code: def test_children_node_finders():
      # Train a linear model decision tree
      X = np.linspace(-4, 4).reshape((-1, 1))
      Y = np.sin(X)
      regr = linear_model_tree(X=X, y=Y)
  
      # Create a LinearTreeDefinition Object
      inBounds = {0: (-4, 4)}
      model_def = LinearTreeDefinition(
          regr, unscaled_input_bounds=inBounds
      )
  
      # Extract leaf and split information
      spts = model_def.splits
      lvs = model_def.leaves
  
      # Ensure that at the root node, the number of left leaves and the number of
      # right leaves sum to the total number of leaves in the tree
      num_left_leaves_at_root = len(spts[0][0]["left_leaves"])
      num_right_leaves_at_root = len(spts[0][0]["right_leaves"])
      total_leaves = len(lvs[0])
  
      assert (
          num_left_leaves_at_root + num_right_leaves_at_root
          == total_leaves
      )
  
imports: import numpy
  import pyomo.environ
  import pytest
  from omlt.dependencies import lineartree_available
  from pytest import approx
  from omlt import OmltBlock
  import omlt
label_desc: Use image node_id 15 for calling a global function with example usage: test_children_node_finders() without return types