code: def test_numpy_multinomial(
      n,
      dtype,
      on_device,
      size,
      init_flags,
      method_flags,
      frontend_method_data,
      frontend,
      backend_fw,
  ):
      helpers.test_frontend_method(
          init_input_dtypes=dtype,
          init_flags=init_flags,
          backend_to_test=backend_fw,
          method_flags=method_flags,
          init_all_as_kwargs_np={
              # ToDo: to fix this temporary placeholder for BitGenerator
              "bit_generator": np.random.PCG64(),
          },
          method_input_dtypes=dtype,
          method_all_as_kwargs_np={
              "n": n,
              "pvals": np.array([1 / n] * n, dtype=dtype[0]),
              "size": size,
          },
          frontend=frontend,
          frontend_method_data=frontend_method_data,
          test_values=False,
          on_device=on_device,
      )
  
imports: from hypothesis import strategies
  import numpy
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_frontend_method
label_desc: Use image node_id 1 for calling a global function with example usage: test_numpy_multinomial(n, dtype, on_device, size, init_flags, method_flags, frontend_method_data, frontend, backend_fw) without return types