code: def test_unique_forward(
      seed,
      x_shape,
      flatten,
      axis,
      sorted,
      with_index,
      with_inverse,
      with_counts,
      ctx,
      func_name,
  ):
      rng = np.random.RandomState(seed)
      input = rng.randint(-10, 10, x_shape).astype(np.float32)
      vinput = nn.Variable.from_numpy_array(input)
      func_args = [
          flatten,
          axis,
          sorted,
          with_index,
          with_inverse,
          with_counts,
      ]
      with nn.context_scope(ctx), nn.auto_forward():
          o = F.unique(vinput, *func_args)
          o = force_tuple(o)
      r = ref_unique(input, *func_args)
      assert len(o) == len(r)
      for act, ref in zip(o, r):
          assert_allclose(act.d, ref)
          assert func_name == act.parent.name
  
file_path: nnabla/python/test/function/test_unique.py
imports: import pytest
  import numpy
  import nnabla
  import nnabla.functions
  from nbla_test_utils import list_context
  from nnabla.testing import assert_allclose
label_desc: Use image node_id 3 for calling a global function with example usage: test_unique_forward(seed, x_shape, flatten, axis, sorted, with_index, with_inverse, with_counts, ctx, func_name) without return types