code: def deserialize_sparse_tensors(tensors, types, shapes, classes):
      """Deserializes sparse tensors.
  
      Args:
        tensors: a structure of tensors to deserialize.
        types: a structure that holds information about types of `tensors`
        shapes: a structure that holds information about shapes of `tensors`
        classes: a structure of objects that identify the dataset item classes
  
      Returns:
        `tensors` with any serialized sparse tensors replaced by their deserialized
        version.
      """
      ret = nest.pack_sequence_as(
          types,
          [
              sparse_ops.deserialize_sparse(
                  tensor, dtype=ty, rank=shape.ndims
              )
              if c is sparse_tensor.SparseTensor
              else tensor
              for (tensor, ty, shape, c) in zip(
                  nest.flatten(tensors),
                  nest.flatten(types),
                  nest.flatten(shapes),
                  nest.flatten(classes),
              )
          ],
      )
      return ret
  
file_path: tensorflow-upstream/tensorflow/python/data/util/sparse.py
imports: from tensorflow.python.data.util import nest
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.ops import sparse_ops
label_desc: Use image node_id 4 for calling a global function with example usage: deserialize_sparse_tensors(tensors, types, shapes, classes) and returns: ret