return true;
  }
  std::string shard_string;
  if (op->hasAttr(kXLAShardingAttr)) {
    shard_string =
        op->getAttrOfType<StringAttr>(kXLAShardingAttr).strref().str();
  } else {
    shard_string = op->getAttrOfType<StringAttr>(kShardingAttr).strref().str();
  }
  xla::OpSharding sharding;
  if (!shard_string.empty() && sharding.ParseFromString(shard_string)) {
    // Only checking op with TUPLE sharding

    : public impl::StripSavedModuleMetadataPassBase<
          StripSavedModuleMetadataPass> {
  void runOnOperation() override;
};

bool ShouldStripAttr(NamedAttribute &namedAttr) {
  auto name = namedAttr.getName().strref();
  return name.starts_with("tf_saved_model.");
}

void StripModule(Operation *module) {
  auto stripAttrs = llvm::to_vector<4>(llvm::make_filter_range(
      module->getAttrs(),

struct StripTfAttributesPass
    : public impl::StripTfAttributesPassBase<StripTfAttributesPass> {
  void runOnOperation() override;
};

bool ShouldStripAttr(NamedAttribute &namedAttr) {
  StringRef name = namedAttr.getName().strref();
  if (name.starts_with("tf.") || name.starts_with("tf_")) return true;
  StringRef value = namedAttr.getValue().getDialect().getNamespace();
  return value == "tf" || value.starts_with("tf_");
}

    if (auto name = loc.dyn_cast<NameLoc>()) {
      return name.getName().strref();
    } else if (auto fused_name = loc.dyn_cast<FusedLoc>()) {
      for (auto sub_loc : fused_name.getLocations()) {
        if (auto named_sub_loc = sub_loc.dyn_cast<NameLoc>()) {
          return named_sub_loc.getName().strref();
        }
      }
    }
    return llvm::StringRef("");
  };

  auto entry_function_attr =
      func_op->getAttrOfType<DictionaryAttr>("tf.entry_function");

  SmallVector<StringRef> inputs;
  mlir::dyn_cast_or_null<StringAttr>(entry_function_attr.get("inputs"))
      .strref()
      .split(inputs, /*Separator=*/",");

  return inputs;
}

void ConvertMainArgAttrs(func::FuncOp main_func_op, const int arg_idx,
                         const StringRef index_path) {

    if (!DeviceNameUtils::ParseFullName(name.str(), &device))
      return op->emitOpError(
          llvm::formatv("bad '{0}' attribute, '{1}', not a valid device",
                        kDevicesAttr, name.strref()));

    if (auto gpu_metadata = mlir::dyn_cast<mlir::TF::GpuDeviceMetadata>(attr)) {
      devices->AddGpuDevice(device, gpu_metadata);
    } else {
      devices->AddDevice(device);
    }
  }

  padding_nums.reserve(padding_nums_size);
  if (conv_padding.strref() == "EXPLICIT") {
    for (auto padding_elem :
         op.getExplicitPaddingAttr().template getAsRange<IntegerAttr>()) {
      padding_nums.push_back(padding_elem.getInt());
    }
  } else if (conv_padding.strref() == "VALID") {
    padding_nums.resize(padding_nums_size, 0);
  } else {

  // derived attribute defined in ODS.
  if (derived_attrs) {
    for (auto derived_attr : derived_attrs) {
      attrs_to_ignore.insert(
          mlir::StringRefToView(derived_attr.getName().strref()));
    }
  }

  if (ignore_unregistered_attrs) {
    TF_RETURN_IF_ERROR(
        GetUnregisteredAttrs(inst, op_reg_data, &attrs_to_ignore));
  }

    // non-derived ones.
    llvm::StringSet<> getDefinedAttributeNames() {
      llvm::StringSet<> all_attrs;
      for (auto& attr : (*this)->getAttrs()) {
        all_attrs.insert(attr.getName().strref());
      }
      for (const auto& operand : llvm::enumerate(getArgumentTypes())) {
        if (auto attr_name = getArgAttrOfType<StringAttr>(
            operand.index(), kAttrArgumentNameAttr)) {

    mlir::MLIRContext *context, llvm::ArrayRef<mlir::NamedAttribute> attrs,
    llvm::SmallVectorImpl<mlir::NamedAttribute> &output) {
  for (mlir::NamedAttribute attr : attrs) {
    if (attr.getName().strref().contains(
            mlir::tfg::TFGraphDialect::getDeviceAttrKey())) {
      tensorflow::DeviceNameUtils::ParsedName parsed_name;
      if (!tensorflow::DeviceNameUtils::ParseFullName(