class RaiseToTFOpsPass
    : public PassWrapper<RaiseToTFOpsPass, OperationPass<func::FuncOp>> {
 public:
  MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(RaiseToTFOpsPass)

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

    : public impl::TPUClusterFormationPassBase<TPUClusterFormationPass> {
 public:
  explicit TPUClusterFormationPass(bool strict_clusters)
      : strict_clusters_(strict_clusters) {}

  void getDependentDialects(DialectRegistry& registry) const override {
    registry.insert<mlir::tf_device::TensorFlowDeviceDialect>();
  }

  void runOnOperation() override;

 private:
  bool strict_clusters_;
};

    "_tpu_compilation_status";

namespace mlir {
namespace TFDevice {
namespace {

struct EmbeddingSequencingPass
    : public ::impl::EmbeddingSequencingPassBase<EmbeddingSequencingPass> {
  void getDependentDialects(mlir::DialectRegistry& registry) const override {
    registry.insert<TF::TensorFlowDialect>();
  }

  void runOnOperation() override;
};

template <typename InputContainer>

  }

  StringRef getDescription() const final {
    // This is a brief description of the pass.
    return "Quantize composite functions with QDQ input/outputs.";
  }

  void getDependentDialects(DialectRegistry& registry) const override {
    registry.insert<TF::TensorFlowDialect, quant::QuantizationDialect,
                    quantfork::QuantizationForkDialect>();
  }

 private:

      return true;
    }
  }
  return false;
}

struct EmbeddingPipeliningPass
    : public ::impl::EmbeddingPipeliningPassBase<EmbeddingPipeliningPass> {
  void getDependentDialects(mlir::DialectRegistry& registry) const override {
    registry.insert<TF::TensorFlowDialect>();
  }

  void runOnOperation() override;
};

bool UseEmbeddingPipelining(ModuleOp& module) {