RewritePatternSet patterns(&getContext());
  // Add new conversion patterns here.
  PopulateLegalizeHloToTFLitePatterns(&patterns, &context);

  ConversionTarget target(context);
  target.addLegalDialect<TFL::TensorFlowLiteDialect, mhlo::MhloDialect>();
  target.addLegalOp<func::CallOp, func::ConstantOp, arith::ConstantOp>();
  target.addDynamicallyLegalOp<mhlo::CustomCallOp>(IsCustomCallLegal);

               << "': " << error.message() << "\n";
    return 1;
  }

  // Load the MLIR module.
  mlir::DialectRegistry registry;
  registry.insert<mlir::TF::TensorFlowDialect, mlir::TFL::TensorFlowLiteDialect,
                  mlir::arith::ArithDialect, mlir::func::FuncDialect>();
  mlir::MLIRContext context(registry);

  llvm::SourceMgr source_mgr;

  for (const auto& entry : denylisted_ops) {
    denylisted_mlir_op_names.insert(TfLiteToMlir(entry));
  }

  DialectRegistry registry;
  registry.insert<mlir::TFL::TensorFlowLiteDialect>();
  MLIRContext context(registry);
  StatusScopedDiagnosticHandler statusHandler(&context,
                                              /*propagate=*/true);

      registry.insert<quant::QuantizationDialect,
                      quantfork::QuantizationForkDialect>();
      mlir::RegisterAllTensorFlowDialects(registry);
      registry.insert<TFL::TensorFlowLiteDialect>();
      registry.insert<arith::ArithDialect>();
      registry.insert<func::FuncDialect>();
      registry.insert<mlir::vhlo::VhloDialect>();
      registry.insert<mlir::stablehlo::StablehloDialect>();
    });

    context_->loadDialect<arith::ArithDialect, mlir::func::FuncDialect,
                          tensor::TensorDialect, mlir::TF::TensorFlowDialect,
                          TensorFlowLiteDialect>();
    builder_ = std::make_unique<mlir::Builder>(context_.get());
    fused_lstm_func_ = createLstmCompositeFunc(builder_.get(), false, false);
    fused_lstm_func_cifg_ =

}
namespace quantfork {
class QuantizationForkDialect;
}
namespace mhlo {
class MhloDialect;
}
namespace TF {
class TensorFlowDialect;
}
namespace TFL {
class TFLDialect;
typedef TFLDialect TensorFlowLiteDialect;
}  // namespace TFL
namespace func {
class FuncOp;
}
class ModuleOp;
template <typename T>
class OperationPass;
class Type;

namespace TFL {

          registry.insert<mlir::BuiltinDialect>();
          registry.insert<mlir::arith::ArithDialect>();
          registry.insert<mlir::func::FuncDialect>();
          registry.insert<mlir::TFL::TensorFlowLiteDialect>();
          return registry;
        }()) {
    context_.loadAllAvailableDialects();

    mlir::OpBuilder builder(&context_);
    module_ = builder.create<mlir::ModuleOp>(builder.getUnknownLoc());

 public:
  MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(ReduceWhileOperandsPass)

  void getDependentDialects(DialectRegistry &registry) const override {
    registry.insert<TFL::TensorFlowLiteDialect, TF::TensorFlowDialect>();
  }
  void runOnOperation() override;
};

LogicalResult FindImplicityProducers(
    const std::vector<uint64_t> &explicitly_consumed_ids,
    std::vector<bool> &is_consumed_id,

    return "Fallback TF-Quantization-unsupported ops to TFLite Flex ops.";
  }

  void getDependentDialects(DialectRegistry &registry) const override {
    registry.insert<TFL::TensorFlowLiteDialect>();
  }

 private:
  // The mode of TF Quantization, might indicate different users/devices.
  Option<std::string> mode_{*this, "mode",

    : public impl::PrepareCompositeFunctionsPassBase<
          PrepareCompositeFunctionsPass> {
  void getDependentDialects(DialectRegistry& registry) const override {
    registry.insert<TFL::TensorFlowLiteDialect>();
  }

 public:
  MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(PrepareCompositeFunctionsPass)

  explicit PrepareCompositeFunctionsPass() {}

 private: