code: def test_kl_multinomial_double_backward(
      seed, ctx, base_axis, shape, func_name
  ):
      from nbla_test_utils import backward_function_tester
  
      rng = np.random.RandomState(seed)
      input0 = 1 + rng.rand(*(shape)).astype(np.float32)
      input1 = 1 + rng.rand(*(shape)).astype(np.float32)
      input0 = input0 / np.sum(input0, axis=1, keepdims=True)
      input1 = input1 / np.sum(input1, axis=1, keepdims=True)
      inputs = [input0, input1]
      backward_function_tester(
          rng,
          F.kl_multinomial,
          inputs,
          func_args=[base_axis],
          atol_f=1e-6,
          dstep=1e-3,
          ctx=ctx,
          skip_backward_check=True,
      )
  
imports: import pytest
  import numpy
  import nnabla.functions
  from nbla_test_utils import list_context
label_desc: Use image node_id 3 for calling a global function with example usage: test_kl_multinomial_double_backward(seed, ctx, base_axis, shape, func_name) without return types