class_docstr: Transformation which skip the decoding entirelly.
  
  Example of usage:
  
  ```python
  ds = tfds.load(
      'imagenet2012',
      split='train',
      decoders={
          'image': tfds.decode.SkipDecoding(),
      }
  )
  
  for ex in ds.take(1):
    assert ex['image'].dtype == tf.string
  ```
code: def dtype(self):
      tensor_info = self.feature.get_serialized_info()
      return tree_utils.map_structure(lambda t: t.dtype, tensor_info)
  
imports: import abc
  import functools
  from tensorflow_datasets.core.utils import tree_utils
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
label_desc: Use image node_id 1 for calling the SkipDecoding obj's underlying member method code with example usage: obj.dtype() and returns: tree_utils