code: def test_image_augmentation_forward(seed, shape, ctx, func_name):
      rng = np.random.RandomState(seed)
      inputs = [rng.randn(16, 3, 8, 8).astype(np.float32)]
      i = nn.Variable(inputs[0].shape)
      # NNabla forward
      with nn.context_scope(ctx), nn.auto_forward():
          o = F.image_augmentation(i)
      assert o.d.shape == inputs[0].shape
  
      func_kargs = {
          "shape": shape,
          "pad": (2, 2),
          "min_scale": 0.8,
          "max_scale": 1.2,
          "angle": 0.2,
          "aspect_ratio": 1.1,
          "distortion": 0.1,
          "flip_lr": True,
          "flip_ud": False,
          "brightness": 0.1,
          "brightness_each": True,
          "contrast": 1.1,
          "contrast_center": 0.5,
          "contrast_each": True,
          "noise": 0.1,
          "seed": 0,
      }
  
      with nn.context_scope(ctx), nn.auto_forward():
          o = F.image_augmentation(i, **func_kargs)
      assert o.d.shape == (inputs[0].shape[0],) + shape
  
      # Checking recomputation
      from nbla_test_utils import recomputation_test
  
      recomputation_test(
          rng=rng,
          func=F.image_augmentation,
          vinputs=[i],
          func_args=[],
          func_kwargs=func_kargs,
          ctx=ctx,
      )
  
      func_kargs["seed"] = -1
      recomputation_test(
          rng=rng,
          func=F.image_augmentation,
          vinputs=[i],
          func_args=[],
          func_kwargs=func_kargs,
          ctx=ctx,
      )
  
imports: import pytest
  import numpy
  import nnabla
  import nnabla.functions
  from test_flip import ref_flip
  from nbla_test_utils import list_context
label_desc: Use image node_id 1 for calling a global function with example usage: test_image_augmentation_forward(seed, shape, ctx, func_name) without return types