// Populate missing unused map keys
  DCHECK(tf_results->missing_unused_key_names.empty());
  DCHECK(tf_results->missing_unused_key_indexes.empty());
  DCHECK(tf_results->missing_unused_key_names_data.empty());

  size_t size = results.missing_unused_input_map_keys.size();
  tf_results->missing_unused_key_names.resize(size);
  tf_results->missing_unused_key_indexes.resize(size);

  for (int i = 0; i < size; ++i) {

  if (entry != GetFactories().end()) {
    default_factory = GetFactories().find(name)->second;
    return absl::OkStatus();
  }
  string msg = absl::StrCat(
      "No tracing engine factory has been registered with the key '", name,
      "' (available: ");
  // Ensure deterministic (sorted) order in the error message
  std::set<string> factories_sorted;
  for (const auto& factory : GetFactories())
    factories_sorted.insert(factory.first);

}

TF_Buffer* TF_CoordinationServiceGetKeyValue(const char* key, int64_t key_size,
                                             TF_CoordinationServiceAgent* agent,
                                             TF_Status* status) {
  auto* cc_agent = reinterpret_cast<tsl::CoordinationServiceAgent*>(agent);
  auto value = cc_agent->GetKeyValue(std::string_view(key, key_size));
  return ProcessGetKeyValueResult(value, status);
}

      "      attr {"
      "        key: 'dtype'"
      "        value {"
      "          type: DT_FLOAT"
      "        }"
      "      }"
      "    }"
      "    node_def {"
      "      name: 'read1'"
      "      op: 'ReadVariableOp'"
      "      input: 'var'"
      "      device: '/job:localhost/replica:0/task:1/device:CPU:0'"
      "      attr {"
      "        key: 'dtype'"
      "        value {"

    status->status = tensorflow::errors::FailedPrecondition(
        "Coordination service agent is not enabled.");
    return;
  }
  status->status = coord_agent->InsertKeyValue(key, value);
}

void TFE_GetConfigKeyValue(TFE_Context* ctx, const char* key,
                           int64_t timeout_in_ms, TF_Buffer* value_buf,
                           TF_Status* status) {
  tensorflow::ImmediateExecutionDistributedManager* dist_mgr =

    if (filtered_keys.count(string(v2_reader_->key())) > 0) continue;
    CHECK(entry.ParseFromArray(v2_reader_->value().data(),
                               v2_reader_->value().size()))
        << entry.InitializationErrorString();
    string key(v2_reader_->key());
    (*var_to_shape_map)[key] = TensorShape(entry.shape());
    (*var_to_data_type_map)[key] = DataType(entry.dtype());
  }

  TF_DeleteStatus(status);

  TFE_OpSetAttrType(op, "T", TFE_TensorHandleDataType(in));
  TFE_OpSetAttrInt(op, "group_size", group_size);
  TFE_OpSetAttrInt(op, "group_key", 123);
  TFE_OpSetAttrInt(op, "instance_key", 456);
  TFE_OpSetAttrString(op, "merge_op", "Add", 3);
  TFE_OpSetAttrString(op, "final_op", "Id", 2);
  std::vector<int64_t> subdiv_offsets;

  //  Worker1:
  //  cluster { job { name: "client" tasks { key: 0 value: "localhost:14525" } }
  //            job { name: "worker" tasks { key: 1 value: "localhost:14523" } }
  //          } job_name: "worker" task_index: 1 protocol: "grpc"
  //
  //  Worker0:
  //  cluster { job { name: "client" tasks { key: 0 value: "localhost:14526" } }
  //            job { name: "worker" tasks { key: 0 value: "localhost:14522" } }

    TF_SetStatus(status, TF_ALREADY_EXISTS, path);
}

// TODO(vnvo2409): `RecursivelyCreateDir` should use `CreateDir` instead of the
// default implementation. Because we could create an empty object whose
// key is equal to the `path` and Google Cloud Console will automatically
// display it as a directory tree.

void DeleteFile(const TF_Filesystem* filesystem, const char* path,
                TF_Status* status) {