@java.lang.Override
  public int getSerializedSize() {
    int size = memoizedSize;
    if (size != -1) return size;

    size = 0;
    if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(cpu_)) {
      size += com.google.protobuf.GeneratedMessageV3.computeStringSize(1, cpu_);
    }
    if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(memory_)) {
      size += com.google.protobuf.GeneratedMessageV3.computeStringSize(2, memory_);
    }
    if (gpus_ != 0) {
      size += com.google.protobuf.CodedOutputStream.computeInt32Size(3, gpus_);
    }
    if (latencyBudgetMs_ != 0) {
      size += com.google.protobuf.CodedOutputStream.computeInt32Size(4, latencyBudgetMs_);
    }
    if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(cpuLimits_)) {
      size += com.google.protobuf.GeneratedMessageV3.computeStringSize(5, cpuLimits_);
    }
    if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(memoryLimits_)) {
      size += com.google.protobuf.GeneratedMessageV3.computeStringSize(6, memoryLimits_);
    }
    size += getUnknownFields().getSerializedSize();
    memoizedSize = size;
    return size;
  }
<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