code: def strings_split_v1(
      input=None,
      sep=None,
      maxsplit=-1,  # pylint: disable=redefined-builtin
      result_type="SparseTensor",
      source=None,
      name=None,
  ):
      """Split elements of `input` based on `sep`.
  
      Let N be the size of `input` (typically N will be the batch size). Split each
      element of `input` based on `sep` and return a `SparseTensor` or
      `RaggedTensor` containing the split tokens. Empty tokens are ignored.
  
      Examples:
  
      >>> print(tf.compat.v1.strings.split(['hello world', 'a b c']))
      SparseTensor(indices=tf.Tensor( [[0 0] [0 1] [1 0] [1 1] [1 2]], ...),
                   values=tf.Tensor([b'hello' b'world' b'a' b'b' b'c'], ...),
                   dense_shape=tf.Tensor([2 3], shape=(2,), dtype=int64))
  
      >>> print(tf.compat.v1.strings.split(['hello world', 'a b c'],
      ...     result_type="RaggedTensor"))
      <tf.RaggedTensor [[b'hello', b'world'], [b'a', b'b', b'c']]>
  
      If `sep` is given, consecutive delimiters are not grouped together and are
      deemed to delimit empty strings. For example, `input` of `"1<>2<><>3"` and
      `sep` of `"<>"` returns `["1", "2", "", "3"]`. If `sep` is None or an empty
      string, consecutive whitespace are regarded as a single separator, and the
      result will contain no empty strings at the start or end if the string has
      leading or trailing whitespace.
  
      Note that the above mentioned behavior matches python's str.split.
  
      Args:
        input: A string `Tensor` of rank `N`, the strings to split.  If
          `rank(input)` is not known statically, then it is assumed to be `1`.
        sep: `0-D` string `Tensor`, the delimiter character.
        maxsplit: An `int`. If `maxsplit > 0`, limit of the split of the result.
        result_type: The tensor type for the result: one of `"RaggedTensor"` or
          `"SparseTensor"`.
        source: alias for "input" argument.
        name: A name for the operation (optional).
  
      Raises:
        ValueError: If sep is not a string.
  
      Returns:
        A `SparseTensor` or `RaggedTensor` of rank `N+1`, the strings split
        according to the delimiter.
      """
      input = deprecation.deprecated_argument_lookup(
          "input", input, "source", source
      )
      with ops.name_scope(name, "StringSplit", [input]):
          input = ragged_tensor.convert_to_tensor_or_ragged_tensor(
              input, dtype=dtypes.string, name="input"
          )
  
          if input.shape.rank == 0:
              input = array_ops.expand_dims(input, 0)
  
          if result_type == "SparseTensor":
              if input.shape.rank == 1:
                  return string_ops.string_split_v2(
                      input, sep=sep, maxsplit=maxsplit
                  )
              else:
                  return string_split_v2(
                      input, sep=sep, maxsplit=maxsplit
                  ).to_sparse()
          elif result_type == "RaggedTensor":
              return string_split_v2(input, sep=sep, maxsplit=maxsplit)
          else:
              raise ValueError(
                  "result_type must be 'RaggedTensor' or 'SparseTensor'."
              )
  
imports: import typing
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import gen_string_ops
  from tensorflow.python.ops import map_fn
  from tensorflow.python.ops import string_ops
  from tensorflow.python.ops.ragged import ragged_array_ops
  from tensorflow.python.ops.ragged import ragged_functional_ops
  from tensorflow.python.ops.ragged import ragged_math_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.util import compat
  from tensorflow.python.util import deprecation
  from tensorflow.python.util import dispatch
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 10 for calling a global function with example usage: strings_split_v1(input, sep, maxsplit, result_type, source, name) and returns: string_ops, string_split_v2, string_split_v2