for (int i = 0; i < low_pads.size(); ++i) {
    new_low_pads[i] = low_pads[i].getInt() + parent_low_pads[i].getInt();
    new_high_pads[i] = high_pads[i].getInt() + parent_high_pads[i].getInt();
    new_interior_pads[i] =
        interior_pads[i].getInt() + parent_interior_pads[i].getInt();
  }

  // Replace pad_op with a new pad having new attributes, taking the

  if (!producer) return mlir::failure();
  versions->set_producer(producer.getInt());

  auto min_consumer = mlir::dyn_cast_or_null<mlir::IntegerAttr>(
      version_attr.get("min_consumer"));
  if (min_consumer) versions->set_min_consumer(min_consumer.getInt());

  auto bad_consumers = mlir::dyn_cast_or_null<mlir::ArrayAttr>(
      version_attr.get("bad_consumers"));

    << op->getAttrOfType<mlir::IntegerAttr>("op_key").getInt() << ") device("
    << op->getAttr("device") << ") " << op->getAttr("op_name") << "()";

  fallback_common::PrintExecuteOpCommon(p, op);
  fallback_common::PrintExecuteOpFuncAttribute(p, op);

  p << " num_args(" << op->getAttrOfType<mlir::IntegerAttr>("num_args").getInt()
    << ')';
}

void ExecuteOp::print(OpAsmPrinter &p) {

    for (auto op : require_device_ordinal_ops) {
      if (op->getAttrOfType<IntegerAttr>(kDeviceOrdinalAttr).getInt() == -1) {
        OpBuilder builder(op);
        int device_ordinal =
            op->getAttrOfType<IntegerAttr>(kReplicaIdAttr).getInt() %
            device_num;
        op->setAttr(kDeviceOrdinalAttr,
                    builder.getI64IntegerAttr(device_ordinal));
      }
    }
  }
}

    const std::unordered_set<std::string>& aggregator_ops_to_ignore,
    SmallVector<Value>& statistics_outputs, SmallVector<StringRef>& ids,
    SmallVector<int32_t>& calibration_methods) {
  for (auto op : region.getOps<TF::CustomAggregatorOp>()) {
    if (aggregator_ops_to_ignore.count(op.getId().str())) continue;

    ids.push_back(op.getId());
    calibration_methods.push_back(op.getCalibrationMethod());

  for (int i : llvm::seq<int>(1, num_dims - 1)) {
    Value input_size_i = GetDimValue(builder, loc, input_shape_value, i);
    const int stride_i = mlir::cast<IntegerAttr>(strides[i]).getInt();
    const int dilation_i = mlir::cast<IntegerAttr>(dilations[i]).getInt();
    const int filter_i = filter_shape.getDimSize(i - 1);
    Value pad_i_low, pad_i_high;
    GetSamePaddingValues(builder, loc, input_size_i, filter_i, dilation_i,

      component.Run(*module_op, quantization_config);

  EXPECT_THAT(pre_calibration_result, IsOk());

  SmallVector<func::FuncOp> func_ops;
  for (auto func_op : pre_calibration_result->getOps<func::FuncOp>()) {
    func_ops.push_back(func_op);
  }
  ASSERT_THAT(func_ops, SizeIs(2));
  EXPECT_THAT(func_ops, Contains(HasSymName("main")));

	err := f.GenerateStruct(&opts)
	if err != nil {
		return 0
	}
	opts.MeshHolder = meshHolder
	c := aggregate.NewController(opts)

	iterations, err := f.GetInt()
	if err != nil {
		return 0
	}
	for i := 0; i < iterations%30; i++ {
		opType, err := f.GetInt()
		if err != nil {
			return 0
		}
		switch ops[opType%maxOps] {
		case "AddRegistry":
			err = runAddRegistry(f, c)
		case "DeleteRegistry":

        source.getAST().getStatementBlock().visit(transformer);
        for (Object method : source.getAST().getMethods()) {
            MethodNode methodNode = (MethodNode) method;
            methodNode.getCode().visit(transformer);
        }
    }

    public static ClassNode getScriptClass(SourceUnit source) {

    protected Jdt create() {
        return new Jdt(getTransformer());
    }

    @Override
    @SuppressWarnings("unchecked")
    protected void configure(Jdt jdtContent) {
        EclipseJdt jdtModel = getJdt();
        jdtModel.getFile().getBeforeMerged().execute(jdtContent);
        jdtContent.setSourceCompatibility(jdtModel.getSourceCompatibility());
        jdtContent.setTargetCompatibility(jdtModel.getTargetCompatibility());