code: def transform_normalize_unicode(source, form, name=None):
      
  
      with ops.name_scope(name, "TransformNormalizeUnicode", [source]):
          source = convert_to_tensor_or_sparse_tensor(source, dtype=tf.string)
          if isinstance(source, tf.SparseTensor):
              result = tf.SparseTensor(
                  indices=source.indices,
                  values=ops_module.transform_normalize_unicode(source.values, form),
                  dense_shape=source.dense_shape
              )
          else:
              result = ops_module.transform_normalize_unicode(source, form)
  
          return result
docs: Normalize unicode strings tensor.
  
      Args:
          source: `Tensor` or `SparseTensor` of any shape, strings to normalize.
          form: Scalar value, name of normalization algorithm.
              One of `"NFD"`, `"NFC"`, `"NFKD"`, `"NFKC"`.
          name: A name for the operation (optional).
      Returns:
          `Tensor` or `SparseTensor` of same shape and size as input.