code: def test_mocking_imagenet_decoders():
      """Test with SkipDecoding."""
      ds, ds_info = tfds.load(
          "imagenet2012",
          split="train",
          decoders={"image": tfds.decode.SkipDecoding()},
          with_info=True,
      )
      assert ds.element_spec == {
          "file_name": tf.TensorSpec(shape=(), dtype=tf.string),
          "image": tf.TensorSpec(
              shape=(), dtype=tf.string
          ),  # Encoded images
          "label": tf.TensorSpec(shape=(), dtype=tf.int64),
      }
      for ex in ds.take(10):
          # Image decoding should works
          image = ds_info.features["image"].decode_example(ex["image"])
          image.shape.assert_is_compatible_with((None, None, 3))
          assert image.dtype == tf.uint8
  
imports: import functools
  import pickle
  import numpy
  import pytest
  import tensorflow
  import tensorflow_datasets
label_desc: Use image node_id 6 for calling a global function with example usage: test_mocking_imagenet_decoders() without return types