build:mkl --define=build_with_mkl=true --define=enable_mkl=true
build:mkl --define=tensorflow_mkldnn_contraction_kernel=0
build:mkl --define=build_with_openmp=true
build:mkl -c opt

# config to build OneDNN backend with a user specified threadpool.
build:mkl_threadpool --define=build_with_mkl=true --define=enable_mkl=true
build:mkl_threadpool --define=tensorflow_mkldnn_contraction_kernel=0

    [feature columns](https://www.tensorflow.org/get_started/feature_columns)
    and [losses](https://www.tensorflow.org/api_docs/python/tf/losses) to
    [gradient boosted trees estimators](https://github.com/tensorflow/models/tree/master/official/r1/boosted_trees).
*   The
    [python interface](https://www.tensorflow.org/versions/r1.9/api_docs/python/tf/lite)
    for the

  TF_NewWritableFile(full_path, &h, status);
  if (TF_GetCode(status) != TF_OK) {
    fprintf(stderr, "TF_NewWritableFile failed: %s\n", TF_Message(status));
    return 1;
  }
  fprintf(stderr, "wrote %s\n", full_path);
  free(full_path);
  TF_CloseWritableFile(h, status);
  if (TF_GetCode(status) != TF_OK) {
    fprintf(stderr, "TF_CloseWritableFile failed: %s\n", TF_Message(status));
  }
  TF_StringStreamDone(s);

  TF_KernelBuilder* b =