code: def create_tensor_concat_graph(
      sess: Session,
      input_values: List[Any],
      input_dtype: Any,
      num_concats: List[int],
      paddings: Optional[List[int]] = None,
      output_shape: Optional[List[int]] = None,
  ) -> Tensor:
      del sess
      del output_shape
  
      const_input_ops = [
          constant_op.constant(i, dtype=input_dtype)
          for i in input_values
      ]
      return gen_tpu_ops.xla_concat_nd(
          const_input_ops, num_concats, paddings
      )
  
imports: from typing import Any, List, Optional
  from absl.testing import parameterized
  import numpy
  from tensorflow.compiler.tests import xla_test
  from tensorflow.python.client.session import Session
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework.ops import control_dependencies
  from tensorflow.python.framework.ops import Tensor
  from tensorflow.python.ops import gen_tpu_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
label_desc: Use image node_id 3 for calling a global function with example usage: create_tensor_concat_graph(sess, input_values, input_dtype, num_concats, paddings, output_shape) and returns: gen_tpu_ops