TF_ASSERT_OK_AND_ASSIGN(RepeatedPtrField<FieldIndex> field_tags,
                          ExtractFieldTags(R"pb(
                            field_tag { field: 2 }
                            field_tag { index: 1505 }
                            field_tag { field: 5 }
                            field_tag { map_key { ui32: 123 } }
                          )pb"));
  RepeatedPtrField<FieldIndex> field_tags_sub;

using ::tensorflow::protobuf::Message;
using ::tensorflow::protobuf::RepeatedPtrField;

// Number of sequential FieldIndex matches of `a` in `b`. (Length of initial
// subsequence.)
// Example: `a = {4, 2}`, `b = {4, 2, 1, 3}`, `fieldTagMatches(a, b) == 2`
absl::StatusOr<int> fieldTagMatches(
    const RepeatedPtrField<::tensorflow::proto_splitter::FieldIndex>& a,
    const RepeatedPtrField<::tensorflow::proto_splitter::FieldIndex>& b);

using ::tensorflow::protobuf::Message;
using ::tensorflow::protobuf::RepeatedPtrField;
// NOLINTNEXTLINE: clang-tidy missing-includes false positive
using ::tensorflow::protobuf::io::CodedOutputStream;
// NOLINTNEXTLINE: clang-tidy missing-includes false positive
using ::tensorflow::protobuf::io::StringOutputStream;

absl::StatusOr<int> fieldTagMatches(const RepeatedPtrField<FieldIndex>& a,

using tensorflow::SavedObjectGraph;
using tensorflow::Status;
using tensorflow::StructuredValue;
using tensorflow::TensorSpecProto;
using tensorflow::libexport::TFPackage;
using tensorflow::protobuf::RepeatedPtrField;
using tensorflow::tracing::graph::GraphFunction;

TaggedValue MakeCallable(const std::string& fn_name, Function fn,
                         AbstractContext* ctx) {
  auto CallFn = [fn_name, fn, ctx](TaggedValue args_,

#include "tensorflow/core/platform/path.h"
#include "tensorflow/core/protobuf/meta_graph.pb.h"
#include "tensorflow/core/util/tensor_bundle/tensor_bundle.h"

namespace tensorflow {
namespace libexport {

using protobuf::RepeatedPtrField;

tensorflow::StatusOr<TFPackage> TFPackage::Load(const std::string& path) {
  // Load the proto
  TFPackage tf_package;
  const string saved_model_pb_path = io::JoinPath(path, kSavedModelFilenamePb);

  // in constant time.
  tensorflow::StatusOr<const tensorflow::NodeDef*> GetGraphDefNode(
      std::string name);

  // Returns a list of function defs in the SavedModel.
  const protobuf::RepeatedPtrField<FunctionDef>& GetFunctionDefs();

  // Returns a BundleReader for reading variable values.
  //
  // This TFPackage retains ownership of the underlying reader.
  tensorflow::BundleReader* GetVariableReader() {

    // Referenced from tensorflow::ImporterBase::CreateOperation

    const auto set_segment_sizes_attr =
        [&](const tensorflow::NameRangeMap& arg_ranges,
            const tensorflow::protobuf::RepeatedPtrField<
                tensorflow::OpDef::ArgDef>& args,
            llvm::StringRef attr_name) {
          std::vector<int32_t> values;
          values.reserve(args.size());
          for (const auto& arg : args) {

  int size;

  // Maps op names to the number of times they appear in the cluster.
  absl::flat_hash_map<absl::string_view, int> op_histogram;
};

void HistogramMapToRepeatedOpAndCount(
    protobuf::RepeatedPtrField<XlaAutoClusteringSummary::OpAndCount>* result,
    const absl::flat_hash_map<absl::string_view, int>& histogram) {
  for (const auto& pair : histogram) {
    XlaAutoClusteringSummary::OpAndCount* new_entry = result->Add();

}

// Converts an MLIR dense string elements attribute to a TensorFlow tensor
// proto.
void ConvertStringElementsAttr(
    const DenseStringElementsAttr attr,
    protobuf::RepeatedPtrField<std::string>* output) {
  for (const auto& val : attr.getRawStringData())
    output->Add({val.data(), val.size()});
}

template <typename T>
void ConvertComplexElementsAttr(const mlir::DenseElementsAttr attr,

    tensorflow::OpList op_list;
    op_list.ParseFromArray(op_list_buffer->data, op_list_buffer->length);
    ASSERT_GE(op_list.op_size(), 1);
    typedef tensorflow::protobuf::RepeatedPtrField<tensorflow::OpDef> OpDefs;
    const OpDefs& ops = op_list.op();
    bool found = std::find_if(ops.begin(), ops.end(),
                              [](const tensorflow::OpDef& op_def) {