let constructor = "CreateAnalyzeVariablesPass()";
  let dependentDialects = ["TFL::TensorFlowLiteDialect"];
}

def DefaultQuantParamsPass : Pass<"tfl-default-quant", "mlir::func::FuncOp"> {
  let summary = "Apply quantization with default quantization parameter";
  let constructor = "CreateDefaultQuantParamsPass()";
  let dependentDialects = ["TFL::TensorFlowLiteDialect"];
  let options = [
    Option<"default_min_", "default-min", "double", "-1.0",

}

def LegalizeHloToTfLitePass : Pass<"tfl-legalize-hlo", "mlir::ModuleOp"> {
  let summary = "Legalize from MHLO to the TFLite dialect";
  let dependentDialects = ["TFL::TensorFlowLiteDialect"];
  let constructor = "mlir::odml::CreateLegalizeHloToTfLitePass()";
}

def LegalizeStablehloToVhloPass : Pass<"stablehlo-legalize-vhlo", "ModuleOp"> {
  let summary = "Legalize StableHLO to VHLO for ODML.";

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_traits.h"
#define GET_ATTRDEF_CLASSES
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops_attrdefs.h.inc"

namespace mlir {
namespace TFL {

typedef TFLDialect TensorFlowLiteDialect;

// The Control type is a token-like value that models control dependencies
class ControlType : public Type::TypeBase<ControlType, Type, TypeStorage> {
 public:
  using Base::Base;

  mlir::mhlo::registerAllMhloDialects(registry);
  mlir::registerAllDialects(registry);
  mlir::registerAllExtensions(registry);
  mlir::stablehlo::registerAllDialects(registry);

  registry.insert<mlir::TFL::TensorFlowLiteDialect>();
  registry.insert<mlir::kernel_gen::tf_framework::TFFrameworkDialect>();
  registry.insert<mlir::quant::QuantizationDialect>();
  registry.insert<mlir::quantfork::QuantizationForkDialect>();

void CompositeLoweringPass::runOnOperation() {
  RewritePatternSet patterns(&getContext());

  populateWithGenerated(patterns);

  ConversionTarget target(getContext());
  target.addLegalDialect<TFL::TensorFlowLiteDialect>();
  target.addLegalDialect<arith::ArithDialect>();

  if (failed(applyPartialConversion(getOperation(), target,
                                    std::move(patterns)))) {

        builder_(ctx_.get()) {
    ctx_->loadDialect<
        arith::ArithDialect, mlir::stablehlo::StablehloDialect,
        func::FuncDialect, TF::TensorFlowDialect, TFL::TensorFlowLiteDialect,
        tf_saved_model::TensorFlowSavedModelDialect,
        tf_executor::TensorFlowExecutorDialect, quant::QuantizationDialect,
        quantfork::QuantizationForkDialect>();
  }

  target.addIllegalDialect<stablehlo::StablehloDialect>();
  target.addDynamicallyLegalDialect<func::FuncDialect>(
      [&](auto) { return is_func_legal; });
  target.addLegalDialect<TFL::TensorFlowLiteDialect>();
  target.addLegalDialect<arith::ArithDialect>();
  target.addLegalDialect<vhlo::VhloDialect>();

  StablehloToOdmlTypeConverter converter;
  RewritePatternSet patterns(context);

  func.return %3 : tensor<2x1xf32>
})";
  const std::string kExpectedFB = CreateRuntimeMetadata();
  mlir::DialectRegistry registry;
  registry.insert<mlir::TFL::TensorFlowLiteDialect, mlir::arith::ArithDialect,
                  mlir::func::FuncDialect>();
  mlir::MLIRContext context(registry);
  auto module = mlir::OwningOpRef<mlir::ModuleOp>(

    return absl::InvalidArgumentError(absl::StrFormat(
        "Cannot open input file: %s. %s", input_filename, error));
  }

  if (input_mlir) {
    mlir::DialectRegistry registry;
    registry.insert<mlir::TFL::TensorFlowLiteDialect, mlir::arith::ArithDialect,
                    mlir::func::FuncDialect>();
    mlir::func::registerAllExtensions(registry);
    context->appendDialectRegistry(registry);

  void SetUp() override {
    context_ = std::make_unique<mlir::MLIRContext>();
    context_->loadDialect<mlir::arith::ArithDialect, mlir::func::FuncDialect,
                          mlir::TF::TensorFlowDialect, TensorFlowLiteDialect>();
    builder_ = std::make_unique<mlir::Builder>(context_.get());

    fused_max_unpooling_func_ =
        createMaxUnpoolingFunc(builder_.get(), {2, 4, 4, 2}, {2, 2, 2, 2});