}
    return success();
  }
};

class LiftTfliteFlexOpsPass
    : public impl::LiftTfliteFlexOpsPassBase<LiftTfliteFlexOpsPass> {
  void getDependentDialects(DialectRegistry& registry) const override {
    registry.insert<TF::TensorFlowDialect>();
  }

 public:
  MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(LiftTfliteFlexOpsPass)

 public:
  StringRef getArgument() const final { return "unfuse-mhlo-batch-norm-pass"; }
  StringRef getDescription() const final {
    return "Unfuses MHLO batch norm inference op into arithmetic ops";
  }
  void getDependentDialects(::mlir::DialectRegistry &registry) const override {
    // TODO(b/299514833): Remove TensorFlowDialect usage.
    registry.insert<shape::ShapeDialect, mlir::TF::TensorFlowDialect>();
  }

  }

  StringRef getDescription() const final {
    // This is a brief description of the pass.
    return "Insert custom aggregation ops for the calibration procedure";
  }

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

  void runOnOperation() override;

 private:
  enum TestCase {
    TEST_CASE_MIN_MAX,

// passes. Currently, per-channel quantization only supports 1D results.
class PreprocessOpPass
    : public PassWrapper<PreprocessOpPass, OperationPass<ModuleOp>> {
  void getDependentDialects(DialectRegistry& registry) const override {
    registry.insert<TF::TensorFlowDialect, QuantizationDialect,
                    quantfork::QuantizationForkDialect>();
  }

 public:

  StringRef getDescription() const final {
    // This is a brief description of the pass.
    return "Apply graph optimizations such as fusing and constant folding to "
           "prepare lifting.";
  }

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

  void runOnOperation() override;

 private:
  Option<OpSet> op_set_{

#include "tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.h.inc"

struct DecomposeReduceDatasetPass
    : public impl::DecomposeReduceDatasetPassBase<DecomposeReduceDatasetPass> {
  void getDependentDialects(DialectRegistry& registry) const override {
    registry.insert<tf_device::TensorFlowDeviceDialect>();
  }

  void runOnOperation() override;
};

struct ReduceWhileOperandsPass
    : public impl::ReduceWhileOperandsPassBase<ReduceWhileOperandsPass> {
 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(

  }

  StringRef getDescription() const final {
    // This is a brief description of the pass.
    return "Apply converting Tensorflow Xla ops to non-xla ops.";
  }

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

  void runOnOperation() override;
};

           "output will be merged into the main function's `FetchOp`. The "
           "initializer functions will be removed after this pass.";
  }

  void runOnOperation() override;

 private:
  void getDependentDialects(DialectRegistry& registry) const override {
    registry
        .insert<TF::TensorFlowDialect, tf_executor::TensorFlowExecutorDialect,
                tf_saved_model::TensorFlowSavedModelDialect>();
  }
};

  StringRef getArgument() const final { return "quant-raise-flex-fallback"; }

  StringRef getDescription() const final {
    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.