code: def binop_lt():
      iris = h2o.import_file(
          path=pyunit_utils.locate("smalldata/iris/iris_wheader.csv")
      )
      rows, cols = iris.dim
      iris.show()
  
      # frame/scaler
      res = iris < 5
      res_rows, res_cols = res.dim
      assert res_rows == rows and res_cols == cols, "dimension mismatch"
      new_rows = iris[res[0]].nrow
      assert new_rows == 22, "wrong number of rows returned"
  
      res = 5 > iris
      res_rows, res_cols = res.dim
      assert res_rows == rows and res_cols == cols, "dimension mismatch"
      new_rows = iris[res[0]].nrow
      assert new_rows == 22, "wrong number of rows returned"
  
      # frame/vec
      # try:
      #    res = iris < iris[0]
      #    res.show()
      #    assert False, "expected error. objects of different dimensions not supported."
      # except EnvironmentError:
      #    pass
  
      # try:
      #    res = iris[2] > iris
      #    res.show()
      #    assert False, "expected error. objects of different dimensions not supported."
      # except EnvironmentError:
      #    pass
  
      # vec/vec
      res = iris[0] < iris[1]
      res_rows = res.nrow
      assert res_rows == rows, "dimension mismatch"
      new_rows = iris[res].nrow
      assert new_rows == 0, "wrong number of rows returned"
  
      # frame/frame
      res = iris < iris
      res_rows, res_cols = res.dim
      assert res_rows == rows and res_cols == cols, "dimension mismatch"
  
      res = iris[0:2] < iris[1:3]
      res_rows, res_cols = res.dim
      assert res_rows == rows and res_cols == 2, "dimension mismatch"
  
label_desc: Use image node_id 1 for calling a global function with example usage: binop_lt() without return types