if (op->getDialect() != tf_dialect) return WalkResult::advance();

    if (parallel_group_attr) {
      op->setAttr(TF::kParallelExecAnnotation, parallel_group_attr);
    }
    auto device_attr = op->getAttr(kDeviceAttr);
    if (!device_attr) {
      op->setAttr(kDeviceAttr, launch.getDeviceAttr());
      return WalkResult::advance();
    }

  builder.insert(metadata_op.clone());
  for (Operation& op : func.getOps()) {
    if (!IsTPUOp(&op)) continue;
    op.setAttr(TF::kReplicationInfoAttr, new_group);
  }
  TF::TPUCompilationResultOp new_result = compilation_op.clone();
  new_result->setAttr(kTpuCompilationStatus, new_group);
  builder.insert(new_result);
}

template <typename OpType>
LogicalResult FindAndExcludeOp(func::FuncOp func,

		"spec.unschedulable": fmt.Sprint(node.Spec.Unschedulable),
	}
	return generic.MergeFieldsSets(objectMetaFieldsSet, specificFieldsSet)
}

// GetAttrs returns labels and fields of a given object for filtering purposes.
func GetAttrs(obj runtime.Object) (labels.Set, fields.Set, error) {
	nodeObj, ok := obj.(*api.Node)
	if !ok {
		return nil, nil, fmt.Errorf("not a node")
	}

// WarningsOnUpdate returns warnings for the given update.
func (statusStrategy) WarningsOnUpdate(ctx context.Context, obj, old runtime.Object) []string {
	return nil
}

// GetAttrs returns labels and fields of a given object for filtering purposes.
func GetAttrs(obj runtime.Object) (labels.Set, fields.Set, error) {
	apiserver, ok := obj.(*apiextensions.CustomResourceDefinition)
	if !ok {

    if (cloned == func) continue;
    // Patch up the op attribute to point to the new function.
    for (NamedAttribute attr : op->getAttrs()) {
      auto symref = mlir::dyn_cast<FlatSymbolRefAttr>(attr.getValue());
      if (!symref) continue;
      if (symref.getValue() != func.getName()) continue;
      op->setAttr(attr.getName(),
                  FlatSymbolRefAttr::get(op->getContext(), cloned.getName()));
      break;
    }
  }

    strings::StrAppend(&setters, attr_comment);
    strings::StrAppend(&setters, "    TF_MUST_USE_RESULT Attrs ", attr_func_def,
                       " x) {\n");
    strings::StrAppend(&setters, "      Attrs ret = *this;\n");
    strings::StrAppend(&setters, "      ret.", api_def_attr.rename_to(),
                       "_ = x;\n");
    strings::StrAppend(&setters, "      return ret;\n    }\n\n");

        return func.emitError()
               << "failed to rename StableHLO function " << func.getSymName();
      }
    }
    if (is_main_func) {
      main_func_name = func.getSymNameAttr();
    }
    func->setAttr(kFromXlaCallModuleAttrName, builder.getUnitAttr());
  }
  if (!main_func_name) {
    return stablehlo_module.emitError()
           << "StableHLO module does not have an entry function";
  }
  return main_func_name;

  // Name of the main function for the eventual executable needs to be set.
  main_func->setAttr(kTfSavedModelExportedNamesAttr,
                     builder.getStrArrayAttr({func_name}));
  main_func->setAttr(
      kTfSavedModelInitializerTypeAttr,
      builder.getStringAttr(kTfSavedModelInitializerRestoreType));
  module->setAttr("tf_saved_model.semantics",
                  UnitAttr::get(builder.getContext()));

                                          dq.getArg());
      dq.getResult().replaceAllUsesWith(dcast);
      if (auto extra_attr = op->getAttr(mlir::quant::kVolatileOpAttrName)) {
        dcast->setAttr(mlir::quant::kVolatileOpAttrName, extra_attr);
      }
      dq.erase();
    } else if (auto q = llvm::dyn_cast<quantfork::QuantizeCastOp>(op)) {
      auto out_type = q.getResult().getType();

      return;
    }

    const auto [min_value, max_value] = *min_max_values;
    mlir::OpBuilder builder(aggregator_op);
    aggregator_op->setAttr("min", builder.getF32FloatAttr(min_value));
    aggregator_op->setAttr("max", builder.getF32FloatAttr(max_value));
  });
  return status;
}

bool IsCalibrationRequired(mlir::ModuleOp module_op) {
  bool calibration_required = false;