code: def test_backward_dot_have_scalar(seed, shape_a, shape_b):
      rng = np.random.RandomState(seed)
  
      inputs = []
      func_args = []
  
      if not shape_a:
          a = rng.randn()
          func_args += [a]
      else:
          a = rng.randn(*shape_a).astype(np.float32)
          inputs += [a]
  
      if not shape_b:
          b = rng.randn()
          func_args += [b]
      else:
          b = rng.randn(*shape_b).astype(np.float32)
          inputs += [b]
      function_network_tester(
          rng, F.dot, inputs, func_args=func_args, have_scalar=True
      )
  
file_path: nnabla/python/test/test_numpy_compat_functions.py
imports: import pytest
  import numpy
  import nnabla
  import nnabla.functions
  from nnabla.testing import assert_allclose
  from nbla_test_function_network import function_network_tester
label_desc: Use image node_id 5 for calling a global function with example usage: test_backward_dot_have_scalar(seed, shape_a, shape_b) without return types