code: def custom_call_v2(
      call_target_name,
      operands,
      result_specs,
      backend_config=None,
      has_side_effect=None,
      name=None,
  ):
      """Emits an HLO `CustomCall` operation with multiple outputs.
  
      See `CustomCall` specification at
        https://tensorflow.org/xla/operation_semantics#customcall,
      and `mhlo.custom_call` specification at
        https://tensorflow.org/mlir/hlo_ops#mhlocustom_call_mlirmhlocustomcallop.
  
      Args:
        call_target_name: Name of the user function. The function signature must
          conform to version 3 of the API, see
          `API_VERSION_STATUS_RETURNING_UNIFIED`. All operands and results assumed
          to be in the default layout.
        operands: A sequence of tensors with possibly different types.
        result_specs: A sequence of tensor specs for all results.
        backend_config: A string that encodes a metadata for the backend. Empty
          string by default.
        has_side_effect: Indicates whether the custom call has side effects. `False`
          by default.
        name: Optional name of the operation.
  
      Returns:
        A tuple of output tensors.
      """
      return gen_xla_ops.xla_custom_call_v2(
          operands=operands,
          call_target_name=call_target_name,
          backend_config=""
          if backend_config is None
          else backend_config,
          has_side_effect=False
          if has_side_effect is None
          else has_side_effect,
          result_dtypes=tuple(spec.dtype for spec in result_specs),
          result_shapes=tuple(spec.shape for spec in result_specs),
          name=name,
      )
  
imports: from tensorflow.compiler.tf2xla.ops import gen_xla_ops
  from local_xla.xla import xla_data_pb2
  from tensorflow.core.framework import attr_value_pb2
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import bitwise_ops
  from tensorflow.python.ops import gen_math_ops
  from tensorflow.python.ops import gen_random_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import random_ops_util
  from tensorflow.python.ops import special_math_ops
  from tensorflow.python.ops.numpy_ops import np_utils
label_desc: Use image node_id 23 for calling a global function with example usage: custom_call_v2(call_target_name, operands, result_specs, backend_config, has_side_effect, name) and returns: gen_xla_ops