Status s = MessageToBuffer(g_def, g_buf);
  TF_ASSERT_OK(s);
  TF_FunctionLibraryDefinition* func =
      TF_NewFunctionLibraryDefinition(g_buf, status);

  TF_LookUpOpDef(func, "Add", op_buf, status);
  string actual_string(reinterpret_cast<const char*>(op_buf->data),
                       op_buf->length);
  ASSERT_EQ(TF_OK, TF_GetCode(status));

  const OpDef* expected_op_def;

                                         target_oper_names, &new_handle);
  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

// If async mode is enabled, this call blocks till all currently pending ops are
// done.
TF_CAPI_EXPORT extern void TFE_ContextExportRunMetadata(TFE_Context* ctx,
                                                        TF_Buffer* buf,
                                                        TF_Status* status);

// Some TF ops need a step container to be set to limit the lifetime of some

  const size_t size = 256;
  std::vector<char> buf;
  buf.reserve(size);
  for (int i = 0; i < size; i++) {
    buf.push_back(i);
  }
  // The fetcher just fetches slices of the buffer.
  auto fetcher = [&buf](const string& filename, size_t offset, size_t n,
                        char* buffer, TF_Status* status) -> int64_t {
    int64_t bytes_transferred;
    if (offset < buf.size()) {

  EXPECT_EQ(TF_DATA_LOSS, static_cast<TF_Code>(tensorflow::error::DATA_LOSS));
}

TEST(CAPI, GetAllOpList) {
  TF_Buffer* buf = TF_GetAllOpList();
  tensorflow::OpList op_list;
  EXPECT_TRUE(op_list.ParseFromArray(buf->data, buf->length));
  EXPECT_GT(op_list.op_size(), 0);
  TF_DeleteBuffer(buf);
}

TEST(CAPI, SetShape) {
  TF_Status* s = TF_NewStatus();
  TF_Graph* graph = TF_NewGraph();

struct TFStatusDeleter {
  void operator()(TF_Status* s) const { TF_DeleteStatus(s); }
};
using OwnedTFStatus = std::unique_ptr<TF_Status, TFStatusDeleter>;

struct TFBufferDeleter {
  void operator()(TF_Buffer* buf) const { TF_DeleteBuffer(buf); }
};
using OwnedTFBuffer = std::unique_ptr<TF_Buffer, TFBufferDeleter>;

class CGraphOptimizer : public CustomGraphOptimizer {
 public:

  auto* cell2 = TFE_MonitoringGetCellStringGauge2(gauge2, "foo", "bar");
  TFE_MonitoringStringGaugeCellSet(cell2, "str");
  auto* buf = new TF_Buffer;
  TFE_MonitoringStringGaugeCellValue(cell2, buf);
  string data(static_cast<const char*>(buf->data), buf->length);
  TF_DeleteBuffer(buf);
  EXPECT_EQ(data, "str");
  TFE_MonitoringDeleteStringGauge2(gauge2);
  TF_DeleteStatus(status);
}

  for (size_t i = 0; i < values.size(); i++) {
    memset(&option_values[i], 0, sizeof(option_values[i]));
    option_values[i].buffer_val.buf = const_cast<char*>(values[i].c_str());
    option_values[i].buffer_val.buf_length = values[i].size();
  }
  option_value.values = &option_values[0];
  option.value = &option_value;
  UniquePtrTo_TF_Status plugin_status(TF_NewStatus(), TF_DeleteStatus);

  if (use_tfrt) {
    TF_Buffer* buf = TF_NewBuffer();
    TFE_GetExecutedOpNames(ctx, buf, status);
    ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
#ifndef NDEBUG
    if (enable_grappler)
      EXPECT_NE(strstr(static_cast<const char*>(buf->data), "tf.Mul"), nullptr);
    else
      EXPECT_NE(strstr(static_cast<const char*>(buf->data), "tf.Add"), nullptr);
#endif

}

const void TFE_MonitoringStringGaugeCellValue(
    TFE_MonitoringStringGaugeCell* cell, TF_Buffer* buf) {
  tensorflow::string value = cell->cell.value();
  void* data = tensorflow::port::Malloc(value.length());
  value.copy(static_cast<char*>(data), value.length(), 0);
  buf->data = data;
  buf->length = value.length();
  buf->data_deallocator = [](void* data, size_t length) {
    tensorflow::port::Free(data);
  };
}