@java.lang.Override
  public void writeTo(com.google.protobuf.CodedOutputStream output) throws java.io.IOException {
    if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(cpu_)) {
      com.google.protobuf.GeneratedMessageV3.writeString(output, 1, cpu_);
    }
    if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(memory_)) {
      com.google.protobuf.GeneratedMessageV3.writeString(output, 2, memory_);
    }
    if (gpus_ != 0) {
      output.writeInt32(3, gpus_);
    }
    if (latencyBudgetMs_ != 0) {
      output.writeInt32(4, latencyBudgetMs_);
    }
    if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(cpuLimits_)) {
      com.google.protobuf.GeneratedMessageV3.writeString(output, 5, cpuLimits_);
    }
    if (!com.google.protobuf.GeneratedMessageV3.isStringEmpty(memoryLimits_)) {
      com.google.protobuf.GeneratedMessageV3.writeString(output, 6, memoryLimits_);
    }
    getUnknownFields().writeTo(output);
  }
<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