assertThat(derReader.readOctetString()).isEqualTo("Jones".encodeUtf8())
    }

    assertThat(derReader.hasNext()).isFalse()
  }

  @Test fun `encode primitive string`() {
    val buffer = Buffer()
    val derWriter = DerWriter(buffer)

    derWriter.write("test", tagClass = DerHeader.TAG_CLASS_UNIVERSAL, tag = 26L) {
      derWriter.writeOctetString("Jones".encodeUtf8())
    }

  // More information can be found in https://kubernetes.io/docs/concepts/workloads/controllers/cron-jobs/#time-zones
  // +optional
  optional string timeZone = 8;

  // Optional deadline in seconds for starting the job if it misses scheduled
  // time for any reason.  Missed jobs executions will be counted as failed ones.
  // +optional
  optional int64 startingDeadlineSeconds = 2;

          if (op_it->second.output_tensor_info[j].GetID() == id) {
            found = true;
            Gradient* ones_like = nullptr;
            TF_RETURN_IF_ERROR(vspace.BuildOnesLike(
                op_it->second.output_tensor_info[j], &ones_like));
            (*result)[id].push_back(ones_like);
            break;
          }
        }
        if (!found) {
          return errors::Internal(

	// stop the replay go-routine.
	if h.store != nil {
		h.storeCtxCancel()
	}

	// Set logch to nil and close it.
	// This will block all Send operations,
	// and finish the existing ones.
	// All future ones will be discarded.
	h.logChMu.Lock()
	xioutil.SafeClose(h.logCh)
	h.logCh = nil
	h.logChMu.Unlock()

	if h.producer != nil {
		h.producer.Close()
		h.client.Close()
	}

    AbstractTensorHandlePtr Conj_X(temp_output);

    // Creates Ones
    name = "OnesLike_Log1p_Grad_X";
    TF_RETURN_IF_ERROR(OnesLike(ctx, Conj_X.get(), &temp_output, name.c_str()));

    AbstractTensorHandlePtr Ones_X(temp_output);

    name = "Add_Log1p_Grad_X";
    // Calculate 1 + Conj(X)
    TF_RETURN_IF_ERROR(
        AddV2(ctx, Ones_X.get(), Conj_X.get(), &temp_output, name.c_str()));

  // zero and not specified. Defaults to 1.
  // +optional
  optional int32 replicas = 1;

  // selector is the label selector for pods. Existing ReplicaSets whose pods are
  // selected by this will be the ones affected by this deployment.
  // +optional
  optional k8s.io.apimachinery.pkg.apis.meta.v1.LabelSelector selector = 2;

  // Template describes the pods that will be created.

Create a PassLib "context". This is what will be used to hash and verify passwords.

!!! tip
    The PassLib context also has functionality to use different hashing algorithms, including deprecated old ones only to allow verifying them, etc.

    For example, you could use it to read and verify passwords generated by another system (like Django) but hash any new passwords with a different algorithm like Bcrypt.

     * filter is applied (like in Maven 3).
     * <p>
     * Supported filters:
     * <ul>
     *     <li>"h" or "h(num)" - highest version or top list of highest ones filter</li>
     *     <li>"l" or "l(num)" - lowest version or bottom list of lowest ones filter</li>
     *     <li>"s" - contextual snapshot filter</li>
     *     <li>"e(G:A:V)" - predicate filter (leaves out G:A:V from range, if hit, V can be range)</li>
     * </ul>

I'll tell you a bit more about these **concepts** here, and that would hopefully give you the **intuition** you would need to decide how to deploy your API in very different environments, possibly even in **future** ones that don't exist yet.

By considering these concepts, you will be able to **evaluate and design** the best way to deploy **your own APIs**.

	h.storeCtxCancel()

	// Wait for messages to be sent...
	h.wg.Wait()

	// Set logch to nil and close it.
	// This will block all Send operations,
	// and finish the existing ones.
	// All future ones will be discarded.
	h.logChMu.Lock()
	xioutil.SafeClose(h.logCh)
	h.logCh = nil
	h.logChMu.Unlock()