void runOnOperation() override {
    mlir::MLIRContext* ctx = &getContext();
    mlir::ModuleOp module_op = getOperation();
    mlir::PassManager pm(ctx);

    pm.addPass(CreateNoOpPass());

    EnableIrPrinting(pm, "dump2");

    if (failed(pm.run(module_op))) {
      signalPassFailure();
    }
  }
};

std::unique_ptr<mlir::OperationPass<mlir::ModuleOp>> CreateParentPass() {

  }

  // The configuration uses the default parameter values for
  // `PassManager::enableIRPrinting`, except for the `printModuleScope`
  // parameter, which is true by default. It is set to false to avoid the dump
  // file size becoming too large when the passes are running on a large model.
  pm.enableIRPrinting(std::make_unique<PrinterConfig>(
      file_name_prefix, /*print_module_scope=*/false,

                          llvm::StringRef module_name) {
  // Print the whole module after each pass, which requires disabling
  // multi-threading as well.
  pm.getContext()->disableMultithreading();
  pm.enableIRPrinting(std::make_unique<::tensorflow::DataDumperLoggerConfig>(
      [module_name, dump_group_name](const std::string& pass_tag_name,
                                     mlir::Operation* op) {

namespace tensorflow {
namespace quantization {

// Enables IR printing for `pm`. When the passes are run, each pass will dump to
// its own file with prefix `file_name_prefix`.
void EnableIrPrinting(mlir::PassManager &pm,
                      absl::string_view file_name_prefix);

// If verbosity level >= 1, this will dump intermediate IRs of passes to a file.

    sanitized.push_back(c);
  }

  return sanitized;
}

// Pass instrumentation that dumps MLIR based on the criteria specified by
// `ir_dump_*` debug options.
//
// While `mlir::PassManager::enableIRPrinting` provides a similar functionality,
// it is cumbersome to manually copy printed IRs and run them with `tf-opt`.
// Also, long MLIR dumps are often truncated during printing. Instead, this

                          llvm::StringRef module_name) {
  // Print the whole module after each pass, which requires disabling
  // multi-threading as well.
  pm.getContext()->disableMultithreading();
  pm.enableIRPrinting(std::make_unique<::tensorflow::DataDumperLoggerConfig>(
      [module_name, dump_group_name](const std::string& pass_tag_name,
                                     mlir::Operation* op) {

    // Print the whole module after each pass which requires disabling
    // multi-threading as well.
    module_op.getContext()->disableMultithreading();
    tf2xla.enableIRPrinting(
        std::make_unique<::tensorflow::DataDumperLoggerConfig>(
            [module_name](const std::string& pass_tag_name,
                          mlir::Operation* op) {