code: def binary_ufunc_check(
      fun, lims_A=[-2, 2], lims_B=[-2, 2], test_complex=True, **kwargs
  ):
      T_A = lambda x: transform(lims_A, x)
      T_B = lambda x: transform(lims_B, x)
      scalar = 0.6
      vector = npr.rand(2)
      mat = npr.rand(3, 2)
      mat2 = npr.rand(1, 2)
      check = combo_check(fun, (0, 1), **kwargs)
      check(
          [T_A(scalar), T_A(vector), T_A(mat), T_A(mat2)],
          [T_B(scalar), T_B(vector), T_B(mat), T_B(mat2)],
      )
      if test_complex:
          comp = 0.6 + 0.3j
          matc = npr.rand(3, 2) + 0.1j * npr.rand(3, 2)
          check(
              [
                  T_A(scalar),
                  T_A(comp),
                  T_A(vector),
                  T_A(matc),
                  T_A(mat2),
              ],
              [
                  T_B(scalar),
                  T_B(comp),
                  T_B(vector),
                  T_B(matc),
                  T_B(mat2),
              ],
          )
  
file_path: autograd/tests/numpy_utils.py
imports: from __future__ import absolute_import
  from __future__ import print_function
  from builtins import range
  import itertools
  import autograd.numpy.random
  from autograd import grad
  from autograd.test_util import combo_check
  import warnings
label_desc: Use image node_id 3 for calling a global function with example usage: binary_ufunc_check(fun, lims_A, lims_B, test_complex) without return types