@java.lang.Override
  public int hashCode() {
    if (memoizedHashCode != 0) {
      return memoizedHashCode;
    }
    int hash = 41;
    hash = (19 * hash) + getDescriptor().hashCode();
    hash = (37 * hash) + CPU_FIELD_NUMBER;
    hash = (53 * hash) + getCpu().hashCode();
    hash = (37 * hash) + CPU_LIMITS_FIELD_NUMBER;
    hash = (53 * hash) + getCpuLimits().hashCode();
    hash = (37 * hash) + MEMORY_FIELD_NUMBER;
    hash = (53 * hash) + getMemory().hashCode();
    hash = (37 * hash) + MEMORY_LIMITS_FIELD_NUMBER;
    hash = (53 * hash) + getMemoryLimits().hashCode();
    hash = (37 * hash) + GPUS_FIELD_NUMBER;
    hash = (53 * hash) + getGpus();
    hash = (37 * hash) + LATENCY_BUDGET_MS_FIELD_NUMBER;
    hash = (53 * hash) + getLatencyBudgetMs();
    hash = (29 * hash) + getUnknownFields().hashCode();
    memoizedHashCode = hash;
    return hash;
  }
<pre>
The maximum latency that this operator may use to process an element.

If non positive, then a system default will be used.
Operator developers should arrange for the system compute resources to be
aligned with this latency budget; e.g. if you want a ML model to produce
results within 500ms, then you should make sure you request enough
cpu/gpu/memory to achieve that.
</pre>

<code>int32 latency_budget_ms = 4;</code>

@return The latencyBudgetMs.
java-visionai/proto-google-cloud-visionai-v1/src/main/java/com/google/cloud/visionai/v1/ResourceSpecification.java