if (status->status.ok()) {
    char* buf = new char[new_handle.size() + 1];
    memcpy(buf, new_handle.c_str(), new_handle.size() + 1);
    *handle = buf;
  }
}

void TF_PRun(TF_DeprecatedSession* s, const char* handle,
             // Input tensors
             const char** c_input_names, TF_Tensor** c_inputs, int ninputs,
             // Output tensors

  for (const auto& factory : GetFactories())
    factories_sorted.insert(factory.first);
  const char* comma = "";
  for (const string& factory : factories_sorted) {
    msg += comma + factory;
    comma = ", ";
  }
  msg += ")";

  return errors::InvalidArgument(msg.c_str());
}

static TracingContext* CreateTracingExecutionContext(const char* fn_name,
                                                     TF_Status* s) {

}

// Exercises tensorflow's C API.
int main(int argc, char** argv) {
  TF_InitMain(argv[0], &argc, &argv);

  struct TF_StringStream* s = TF_GetLocalTempDirectories();
  const char* path;

  if (!TF_StringStreamNext(s, &path)) {
    fprintf(stderr, "TF_GetLocalTempDirectories returned no results\n");
    return 1;
  }

  char file_name[100];
  time_t t = time(NULL);

}

// --------------------------  Resource  ---------------------------------------
void TF_CreatePluginResource(TF_OpKernelContext* ctx,
                             const char* container_name,
                             const char* plugin_resource_name,
                             void* plugin_resource, void (*delete_func)(void*),
                             TF_Status* status) {

TF_Function* TF_GraphToFunctionWithControlOutputs(
    const TF_Graph* fn_body, const char* fn_name,
    unsigned char append_hash_to_fn_name, int num_opers,
    const TF_Operation* const* opers, int ninputs, const TF_Output* inputs,
    int noutputs, const TF_Output* outputs, const char* const* output_names,
    int ncontrol_outputs, const TF_Operation* const* control_outputs,
    const char* const* control_output_names, const TF_FunctionOptions* opts,

  // the operation, its `StartCancel` method will be called if op execution
  // fails on any device in order to cancel the others.
  void StartExecute(TFE_Context* context, const char* operation_name,
                    std::vector<TFE_TensorHandle*> inputs,
                    const TFE_OpAttrs* attributes, int expected_max_outputs,
                    CancellationManager& cancellation_manager,

  TFE_ContextSetServerDef(ctx, 0, serialized.data(), serialized.size(), status);
  EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);

  const char task0_name[] = "/job:localhost/replica:0/task:0/device:CPU:0";
  const char task1_name[] = "/job:localhost/replica:0/task:1/device:CPU:0";
  const char task2_name[] = "/job:localhost/replica:0/task:2/device:CPU:0";

  // Create one variable per task.

namespace gradients {
namespace internal {
namespace {
using std::vector;
using tensorflow::TF_StatusPtr;
using tracing::TracingOperation;

class CppGradients
    : public ::testing::TestWithParam<std::tuple<const char*, bool, bool>> {
 protected:
  void SetUp() override {
    TF_StatusPtr status(TF_NewStatus());
    TF_SetTracingImplementation(std::get<0>(GetParam()), status.get());
    Status s = StatusFromTF_Status(status.get());

                                  const char* label1, const char* label2);

// APIs for String Gauge with 3 labels.
typedef struct TFE_MonitoringStringGauge3 TFE_MonitoringStringGauge3;
TF_CAPI_EXPORT extern TFE_MonitoringStringGauge3* TFE_MonitoringNewStringGauge3(
    const char* name, TF_Status* out_status, const char* description,
    const char* label1, const char* label2, const char* label3);

}

Status SetAttrString(AbstractOperation* op_, const char* attr_name,
                     const char* data, size_t length,
                     ForwardOperation* forward_op_) {
  forward_op_->attrs.Set(attr_name, StringPiece(data, length));
  return op_->SetAttrString(attr_name, data, length);
}
Status SetAttrInt(AbstractOperation* op_, const char* attr_name, int64_t value,
                  ForwardOperation* forward_op_) {