respBytes []byte, apiErr APIError, errMsg string,
) {
	if h.forceStarted {
		_, apiErr = ahs.stopHealSequence(pathJoin(h.bucket, h.object))
		if apiErr.Code != "" {
			return respBytes, apiErr, ""
		}
	} else {
		oh, exists := ahs.getHealSequence(pathJoin(h.bucket, h.object))
		if exists && !oh.hasEnded() {
			errMsg = "Heal is already running on the given path " +

  TF_Buffer* ret = TF_NewBuffer();
  TF_CHECK_OK(MessageToBuffer(server_def, ret));
  return ret;
}

void TF_MakeInternalErrorStatus(TF_Status* status, const char* errMsg) {
  status->status = tensorflow::errors::Internal(errMsg);
}

struct TF_CheckpointReader : public tensorflow::checkpoint::CheckpointReader {
  using tensorflow::checkpoint::CheckpointReader::CheckpointReader;

		t.Fatalf("%s: Expected to fail since the NewMultipartUpload is initialized on a non-existent bucket.", instanceType)
	}
	if errMsg != err.Error() {
		t.Errorf("%s, Expected to fail with Error \"%s\", but instead found \"%s\".", instanceType, errMsg, err.Error())
	}

	// Create bucket before initiating NewMultipartUpload.
	err = obj.MakeBucket(context.Background(), bucket, MakeBucketOptions{})
	if err != nil {

		nh := newHealSequence(GlobalContext, hip.bucket, hip.objPrefix, handlers.GetSourceIP(r), hip.hs, hip.forceStart)
		go func() {
			respBytes, apiErr, errMsg := globalAllHealState.LaunchNewHealSequence(nh, objectAPI)
			hr := healResp{respBytes, apiErr, errMsg}
			respCh <- hr
		}()
	}

	// Due to the force-starting functionality, the Launch
	// call above can take a long time - to keep the