List<Integer> result = Lists.newArrayListWithCapacity(initial.size());
    for (Iterator<Integer> iter = q.iterator(); iter.hasNext(); ) {
      Integer value = iter.next();
      result.add(value);
      if (value == 8) {
        iter.remove();
      }
    }
    assertIntact(q);
    assertThat(result).containsExactly(1, 15, 13, 8, 14);
  }

  /**

            Currency.FRANC, Country.SWITZERLAND);
    EnumBiMap<Currency, Country> bimap = EnumBiMap.create(map);

    Iterator<Currency> iter = bimap.keySet().iterator();
    assertEquals(Currency.DOLLAR, iter.next());
    assertEquals(Currency.FRANC, iter.next());
    iter.remove();

    // forward map ordered by currency
    assertThat(bimap.keySet()).containsExactly(Currency.DOLLAR, Currency.PESO).inOrder();

            Currency.FRANC, Country.SWITZERLAND);
    EnumBiMap<Currency, Country> bimap = EnumBiMap.create(map);

    Iterator<Currency> iter = bimap.keySet().iterator();
    assertEquals(Currency.DOLLAR, iter.next());
    assertEquals(Currency.FRANC, iter.next());
    iter.remove();

    // forward map ordered by currency
    assertThat(bimap.keySet()).containsExactly(Currency.DOLLAR, Currency.PESO).inOrder();

                                    " into function '", fn_name, "'");

    input_tensors->emplace_back(node, idx);

    const auto& iter = input_nodes->find(node);
    if (iter == input_nodes->end()) {
      input_nodes->insert({node, {idx}});
    } else {
      auto& indices = iter->second;
      if (std::find(indices.begin(), indices.end(), idx) != indices.end()) {
        return InvalidArgument("TF_Output ", node->name(), ":", idx,

    List<Integer> result = Lists.newArrayListWithCapacity(initial.size());
    for (Iterator<Integer> iter = q.iterator(); iter.hasNext(); ) {
      Integer value = iter.next();
      result.add(value);
      if (value == 8) {
        iter.remove();
      }
    }
    assertIntact(q);
    assertThat(result).containsExactly(1, 15, 13, 8, 14);
  }

  /**

    return;
  }
  std::vector<tensorflow::CoordinatedTask> task_vec(tasks.length);
  auto* task_iter = static_cast<const tensorflow::CoordinatedTask*>(tasks.data);
  for (size_t i = 0; i < tasks.length; ++i) {
    task_vec[i].set_job_name(task_iter->job_name());
    task_vec[i].set_task_id(task_iter->task_id());
    ++task_iter;
  }
  auto results = coord_agent->GetTaskState(task_vec);
  if (!results.ok()) {

    const ForwardOperation& op,
    std::unique_ptr<GradientFunction>* gradient_function) const {
  auto iter = registry_.find(op.op_name);
  if (iter == registry_.end()) {
    const string error_msg = "No gradient defined for op: " + op.op_name + ".";
    return errors::NotFound(error_msg);
  }
  gradient_function->reset(iter->second(op));
  return absl::OkStatus();
}

  auto iter = builder->attr_names.insert(attr_name).first;
  builder->Set(*iter, static_cast<tensorflow::DataType>(value));
}

void TF_AttrBuilderSetTypeList(TF_AttrBuilder* builder, const char* attr_name,
                               const TF_DataType* values, int num_values) {
  auto iter = builder->attr_names.insert(attr_name).first;

    if [[ ${NUM_CLUSTERS} -gt 1 ]]; then
      retry install_metallb "${KUBECONFIG_FILE}"
    fi
    KUBECONFIGS+=("${KUBECONFIG_FILE}")
  done

  ITER_END=$((NUM_CLUSTERS-1))
  for i in $(seq 0 "$ITER_END"); do
    for j in $(seq 0 "$ITER_END"); do
      if [[ "${j}" -gt "${i}" ]]; then
        NETWORK_ID_I="${CLUSTER_NETWORK_ID[i]}"
        NETWORK_ID_J="${CLUSTER_NETWORK_ID[j]}"

	histogram: prometheus.NewHistogramVec(prometheus.HistogramOpts{
		Name:    "tier_ttlb_seconds",
		Help:    "Time taken by requests served by warm tier",
		Buckets: []float64{0.01, 0.1, 1, 2, 5, 10, 60, 5 * 60, 15 * 60, 30 * 60},
	}, []string{"tier"}),
}

func (t *tierMetrics) Observe(tier string, dur time.Duration) {
	t.histogram.With(prometheus.Labels{"tier": tier}).Observe(dur.Seconds())
}