add_new_spec(QuantizationComponentSpec::COMPONENT_BIAS,
                   QuantizationComponentSpec::TENSORTYPE_INT_32);
    }

    if (quant_options_.unit_wise_quantization_specs().empty()) {
      // Opt-out a node named `test_opt_out`.
      UnitWiseQuantizationSpec* new_spec =
          quant_options_.add_unit_wise_quantization_specs();

  }
}

// CHECK-LABEL: func @conv2d_unmatching_unit
// CHECK: "tf.PartitionedCall"
// CHECK-SAME: f = @composite_conv2d_fn_1
// Check that the `_tfl_quant_trait` attribute exists since the unit is not in `unit_wise_quantization_specs`.
// CHECK-SAME: _tfl_quant_trait = "fully_quantizable"
// CHECK-SAME: loc(callsite("Model/conv2d@conv2d_unmatching_unit"("Conv2D") at "QuantizationUnit({{.*}})"))

// -----

  // `quantization_method` for matching nodes and ops. If there are conflicts
  // or ambiguity in this unit-wise precision, our quantizer will raise an
  // error.
  repeated UnitWiseQuantizationSpec unit_wise_quantization_specs = 17;

  // (TF1 SavedModel only) Collection of tags identifying the MetaGraphDef
  // within the SavedModel to analyze. If not specified, ["serve"] is used.
  repeated string tags = 5;

  if not quantization_options.unit_wise_quantization_specs:
    return

  sorted_top_level_component_specs = sorted(
      quantization_options.quantization_method.quantization_component_specs,
      key=lambda x: x.quantization_component,
  )

  for unitwise_spec in quantization_options.unit_wise_quantization_specs:
    if not unitwise_spec.unit:
      raise ValueError(

            preset_method=_PresetMethod.METHOD_STATIC_RANGE_INT8
        ),
        tags=tags,
        signature_keys=[signature_key],
        op_set=quant_opts_pb2.XLA,
        unit_wise_quantization_specs=[
            quant_opts_pb2.UnitWiseQuantizationSpec(
                unit=[],
                quantization_method=quant_opts_pb2.QuantizationMethod(