code: def test_khatri_rao_tensorly_1(columns, rows):
      columns = columns
      rows = rows
      matrices = [
          ivy.arange(k * columns).reshape((k, columns)) for k in rows
      ]
      res = ivy.khatri_rao(matrices)
      # resulting matrix must be of shape (prod(n_rows), n_columns)
      n_rows = 3 * 4 * 2
      n_columns = 4
      assert res.shape[0] == n_rows
      assert res.shape[1] == n_columns
  
imports: import math
  from hypothesis import strategies
  from hypothesis import assume
  import numpy
  import pytest
  import itertools
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_test, BackendHandler
  import ivy
label_desc: Use image node_id 35 for calling a global function with example usage: test_khatri_rao_tensorly_1(columns, rows) without return types