ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  EXPECT_TF_META("v", 0, TF_ATTR_INT, -1);
}

TEST_F(CApiAttributesTest, Names) {
  auto desc = init("string");
  TF_SetAttrString(desc, "v", "bunny", 5);

  auto oper = TF_FinishOperation(desc, s_);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  EXPECT_TF_META("v", -1, TF_ATTR_STRING, 5);

  ASSERT_EQ(1, TF_OperationGetNumAttrs(oper));

For details on best practices with 2.0, see
[the Effective 2.0 guide](https://www.tensorflow.org/beta/guide/effective_tf2)

For information on upgrading your existing TensorFlow 1.x models, please refer
to our
[Upgrade](https://medium.com/tensorflow/upgrading-your-code-to-tensorflow-2-0-f72c3a4d83b5)
and [Migration](https://www.tensorflow.org/beta/guide/migration_guide) guides.
We have also released a collection of

  TF_ImportGraphDefResults results;
  GraphImportGraphDefLocked(graph, bundle.meta_graph_def.graph_def(),
                            import_opts, &results, status);
  TF_DeleteImportGraphDefOptions(import_opts);
  if (!status->status.ok()) return nullptr;

  if (meta_graph_def != nullptr) {
    status->status = MessageToBuffer(bundle.meta_graph_def, meta_graph_def);
    if (!status->status.ok()) return nullptr;
  }

  # Now grab the NDK API level to use. Note that this is different from the
  # SDK API level, as the NDK API level is effectively the *min* target SDK
  # version.
  meta = open(os.path.join(android_ndk_home_path, 'meta/platforms.json'))
  platforms = json.load(meta)
  meta.close()
  aliases = platforms['aliases']
  api_levels = sorted(list(set([aliases[i] for i in aliases])))

  android_ndk_api_level = prompt_loop_or_load_from_env(