code: def test_interpolate_nearest_forward_backward(
      seed,
      inshape,
      outsize,
      scale,
      sdim_only,
      align_corners,
      half_pixel,
      half_pixel_for_nn,
      channel_last,
      ctx,
      func_name,
  ):
      if channel_last and func_name == "Interpolate":
          pytest.skip(
              "Interpolate with channel_last is only supported in CUDA."
          )
      if sdim_only and channel_last:
          pytest.skip(
              "Interpolate for spatial dimension only data is only supported for channel_first option."
          )
  
      from nbla_test_utils import function_tester
  
      rng = np.random.RandomState(seed)
      inputs = [rng.randn(*inshape).astype(np.float32)]
      func_args = [
          scale,
          outsize,
          "nearest",
          align_corners,
          half_pixel,
          half_pixel_for_nn,
          channel_last,
      ]
      function_tester(
          rng,
          F.interpolate,
          ref_interpolate,
          inputs,
          func_name=func_name,
          func_args=func_args,
          atol_f=1e-6,
          atol_b=1e-2,
          dstep=2e-3,
          ctx=ctx,
      )
  
imports: from __future__ import division
  import pytest
  import numpy
  import nnabla.functions
  import refs
  from nbla_test_utils import list_context
label_desc: Use image node_id 13 for calling a global function with example usage: test_interpolate_nearest_forward_backward(seed, inshape, outsize, scale, sdim_only, align_corners, half_pixel, half_pixel_for_nn, channel_last, ctx, func_name) without return types