TF_Graph* graph, TF_Buffer* meta_graph_def, TF_Status* status) {
// TODO(sjr): Remove the IS_MOBILE_PLATFORM guard. This will require ensuring
// that the tensorflow/cc/saved_model:loader build target is mobile friendly.
#if defined(IS_MOBILE_PLATFORM) || defined(IS_SLIM_BUILD)
  status->status = tensorflow::errors::Unimplemented(
      "Loading a SavedModel is not supported on mobile. File a bug at "

1.  Address the perceived conflict directly with those involved, preferably in a
    real-time medium.
2.  If this fails, get a third party (e.g. a mutual friend, and/or someone with
    background on the issue, but not involved in the conflict) to intercede.
3.  If you are still unable to resolve the conflict, and you believe it rises to

-   If a change is needed, the contributor is requested to make the suggested
    change.
-   You make the change and submit it for the review again.
-   This cycle repeats itself until the PR gets approved.
-   Note: As a friendly reminder, we may reach out to you if the PR is awaiting
    your response for more than 2 weeks.

**4. Approved**

-   Once the PR is approved, it gets `kokoro:force-run` label applied and it
    initiates CI/CD tests.

        compatible, but if you require that default attributes to be saved with
        the model, please use `tf.compat.v1.Estimator`.
    *   Feature Columns have been upgraded to be more Eager-friendly and to work
        with Keras. As a result, `tf.feature_column.input_layer` has been
        deprecated in favor of `tf.keras.layers.DenseFeatures`. v1 feature
        columns have direct analogues in v2 except for

  }
  // For LLVM style RTTI.
  static bool classof(const AbstractOperation* ptr) {
    return ptr->getKind() == kGraph;
  }
  ~GraphOperation() override {}

 private:
  friend class GraphContext;  // For access to op_.
  TF_Graph* g_;
  std::unique_ptr<TF_OperationDescription> op_;
  // Hold `op_type` and `op_name` till both are available since we need both
  // to build a graph operation.