namespace mlir {
namespace odml {

// Creates a pass which prints out a detailed report of conversion stats with:
// success or not, % of Ops non-converted, list of non-converted Ops, etc.
std::unique_ptr<Pass> createPrintOpStatsPass(
    std::vector<std::string> accepted_dialects);

}  // namespace odml
}  // namespace mlir

  if (verbose) {
    // Print out a detailed report of non-converted stats.
    // Because this pass aborts the pass if there are unconverted ops,
    // we need to locate createPrintOpStatsPass after all optimization.
    pm.addPass(
        mlir::odml::createPrintOpStatsPass(GetAcceptedStableHLODialects()));
  }

  if (failed(pm.run(tf_module))) {
    return tensorflow::errors::Aborted("Lowering to StableHLO failed.");
  }

        delim = ", ";
      }
      *os_ << ")";
    }
    *os_ << "\n";
  }
}

}  // namespace odml
}  // namespace mlir

std::unique_ptr<mlir::Pass> mlir::odml::createPrintOpStatsPass(
    std::vector<std::string> accepted_dialects) {
  return std::make_unique<mlir::odml::PrintOpStatsPass>(&llvm::errs(),
                                                        accepted_dialects);

                                     /*smuggle_disallowed_ops=*/true);
  // Print out a detailed report of non-converted stats.
  pass_manager.addPass(mlir::odml::createPrintOpStatsPass(
      mlir::odml::GetAcceptedStableHLODialects()));
  mlir::odml::AddStablehloOptimizationPasses(pass_manager);
  if (toco_flags.has_quantization_options()) {
    stablehlo::quantization::AddQuantizationPasses(