code: def concat(values, axis, name: str = "concat"):
      """tf.concat for structured tensors.
  
      Does not support (yet) checks on illegal axis values, et cetera.
  
      Args:
        values: a sequence of StructuredTensors.
        axis: an axis to concatenate upon.
        name: the name of the op(s).
  
      Returns:
        the params reorganized according to indices.
      """
      if name is None:
          name = "concat"
      _assert_concat_compatible_structured_tensors(values)
  
      def leaf_op(values):
          return array_ops.concat(values, axis)
  
      # TODO(martinz): handle axis when it is a tensor.
      axis = array_ops.get_positive_axis(axis, values[0].rank)
      with ops.name_scope(name, "StructuredConcat", values):
          return _extend_op(values, leaf_op)
  
imports: from typing import Sequence
  from tensorflow.core.config import flags
  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.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops.ragged import dynamic_ragged_shape
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.ops.ragged.row_partition import RowPartition
  from tensorflow.python.ops.structured.structured_tensor import StructuredTensor
  from tensorflow.python.util import deprecation
  from tensorflow.python.util import dispatch
label_desc: Use image node_id 6 for calling a global function with example usage: concat(values, axis, name) and returns: array_ops, _extend_op