"//tensorflow/compiler/mlir/lite:tensorflow_lite",
        "//tensorflow/compiler/mlir/lite:tf_tfl_passes",
        "//tensorflow/compiler/mlir/lite/experimental/common:outline_operations",
        "//tensorflow/compiler/mlir/lite/experimental/tac/hardwares:target_hardware",
        "//tensorflow/compiler/mlir/tensorflow:cluster_util",
        "//tensorflow/compiler/mlir/tensorflow:error_util",

  size_t numRead;
  mlir::Attribute attr = mlir::parseAttribute(input, context, {}, &numRead);
  if (!attr || !mlir::isa<mlir::StringAttr>(attr)) {
    LOG(ERROR) << "Input is not parsable as a MLIR StringAttr.";
    return nullptr;
  }
  auto str_attr = mlir::cast<mlir::StringAttr>(attr);

  mlir::DialectRegistry registry;
  RegisterMlirInputDialects(registry);

#include "tensorflow/core/util/device_name_utils.h"

namespace tensorflow {
namespace tf2xla {
namespace internal {

namespace {

using mlir::Block;
using mlir::DialectRegistry;
using mlir::LogicalResult;
using mlir::ModuleOp;
using mlir::NamedAttribute;
using mlir::NamedAttrList;
using mlir::OpBuilder;
using mlir::Operation;
using mlir::OpResult;
using mlir::Region;

#include "mlir/IR/Attributes.h"  // from @llvm-project
#include "mlir/IR/Builders.h"  // from @llvm-project
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "mlir/IR/BuiltinTypes.h"  // from @llvm-project
#include "mlir/IR/Location.h"  // from @llvm-project
#include "mlir/IR/MLIRContext.h"  // from @llvm-project
#include "mlir/IR/Matchers.h"  // from @llvm-project
#include "mlir/IR/OpDefinition.h"  // from @llvm-project

TEST(TPURewriteDeviceUtilTest, TestHasModelParallelismFalse) {
  mlir::MLIRContext context;
  context.loadDialect<mlir::tf_device::TensorFlowDeviceDialect>();
  mlir::OwningOpRef<mlir::ModuleOp> module_ref =
      mlir::ModuleOp::create(mlir::UnknownLoc::get(&context));
  mlir::OpBuilder builder(module_ref->getBodyRegion());

  llvm::SmallVector<mlir::Type, 8> result_types;
  auto cluster = builder.create<mlir::tf_device::ClusterOp>(

                                            mlir::Builder builder) {
  return mlir::vhlo::ArrayV1Attr::get(builder.getContext(), value);
}

static mlir::Attribute BuildVhloDictionaryV1Attr(
    std::vector<std::pair<mlir::Attribute, mlir::Attribute>> value,
    mlir::Builder builder) {
  return mlir::vhlo::DictionaryV1Attr::get(builder.getContext(), value);
}

static mlir::Attribute BuildVhloFloatV1Attr(float value,

namespace quantization {
namespace {

using ::mlir::quant::stablehlo::ConvertMlirModuleToExportedModel;
using ::mlir::quant::stablehlo::CreateMlirContextForQuantization;
using ::mlir::quant::stablehlo::ExportOptions;
using ::mlir::quant::stablehlo::FunctionAlias;
using ::mlir::quant::stablehlo::FunctionName;
using ::mlir::quant::stablehlo::GetFunctionAliases;
using ::mlir::quant::stablehlo::kExportStepSuffix;

#include "tensorflow/compiler/mlir/tensorflow/transforms/passes.h"
#include "tensorflow/compiler/mlir/tensorflow/transforms/sparsecore/sparsecore_passes.h"
#include "tensorflow/compiler/mlir/tf2xla/internal/passes/clustering_passes.h"

namespace tensorflow {
namespace tf2xla {
namespace internal {

using mlir::OpPassManager;
using mlir::func::FuncOp;

// Adds replicated Bridge clustering pipeline passes to the given pass_manager.

        "//tensorflow/compiler/mlir/lite:tensorflow_lite",
        "//tensorflow/compiler/mlir/lite/quantization/ir:QuantOps",
        "//tensorflow/compiler/mlir/quantization/common:attrs_and_constraints",
        "//tensorflow/compiler/mlir/quantization/common:func",
        "//tensorflow/compiler/mlir/quantization/common:lift_as_function_call",
        "//tensorflow/compiler/mlir/quantization/common:uniform_quantized_types",

  for (auto fn : module->getOps<mlir::func::FuncOp>()) {
    for (auto& bb : fn) {
      for (auto& inst : bb) {
        auto attr_id = mlir::StringAttr::get(context, "value");
        if (auto attr = inst.getAttrOfType<mlir::ElementsAttr>(attr_id)) {
          mlir::Attribute rand_val;
          mlir::Type element_type = attr.getShapedType().getElementType();
          if (mlir::isa<mlir::IntegerType>(element_type)) {