code: def test_mod2_forward(
      seed, x0_shape, x1_shape, fmod, dtype, ctx, func_name
  ):
      from nbla_test_utils import function_tester
  
      rng = np.random.RandomState(seed)
      if dtype == np.float32:
          inputs = [
              rng.randn(*x0_shape).astype(dtype),
              rng.randn(*x1_shape).astype(dtype),
          ]
      else:
          inputs = [
              rng.randint(
                  np.iinfo(dtype).min, np.iinfo(dtype).max, x0_shape
              ).astype(dtype),
              rng.randint(
                  np.iinfo(dtype).min, np.iinfo(dtype).max, x1_shape
              ).astype(dtype),
          ]
      backward = [False, False]
      func_args = [fmod]
      function_tester(
          rng,
          F.mod2,
          ref_mod2,
          inputs,
          func_name=func_name,
          func_args=func_args,
          atol_f=0,
          ctx=ctx,
          backward=backward,
      )
  
imports: import pytest
  import numpy
  import nnabla.functions
  from nbla_test_utils import list_context
label_desc: Use image node_id 2 for calling a global function with example usage: test_mod2_forward(seed, x0_shape, x1_shape, fmod, dtype, ctx, func_name) without return types