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

    size = 0;
    if (methodCase_ == 1) {
      size +=
          com.google.protobuf.CodedOutputStream.computeMessageSize(
              1, (com.google.cloud.vertexai.api.SampledShapleyAttribution) method_);
    }
    if (methodCase_ == 2) {
      size +=
          com.google.protobuf.CodedOutputStream.computeMessageSize(
              2, (com.google.cloud.vertexai.api.IntegratedGradientsAttribution) method_);
    }
    if (methodCase_ == 3) {
      size +=
          com.google.protobuf.CodedOutputStream.computeMessageSize(
              3, (com.google.cloud.vertexai.api.XraiAttribution) method_);
    }
    if (topK_ != 0) {
      size += com.google.protobuf.CodedOutputStream.computeInt32Size(4, topK_);
    }
    if (((bitField0_ & 0x00000001) != 0)) {
      size += com.google.protobuf.CodedOutputStream.computeMessageSize(5, getOutputIndices());
    }
    if (methodCase_ == 7) {
      size +=
          com.google.protobuf.CodedOutputStream.computeMessageSize(
              7, (com.google.cloud.vertexai.api.Examples) method_);
    }
    size += getUnknownFields().getSerializedSize();
    memoizedSize = size;
    return size;
  }
<pre>
If populated, only returns attributions that have
[output_index][google.cloud.aiplatform.v1.Attribution.output_index]
contained in output_indices. It must be an ndarray of integers, with the
same shape of the output it's explaining.

If not populated, returns attributions for
[top_k][google.cloud.aiplatform.v1.ExplanationParameters.top_k] indices of
outputs. If neither top_k nor output_indices is populated, returns the
argmax index of the outputs.

Only applicable to Models that predict multiple outputs (e,g, multi-class
Models that predict multiple classes).
</pre>

<code>.google.protobuf.ListValue output_indices = 5;</code>
java-vertexai/proto-google-cloud-vertexai-v1/src/main/java/com/google/cloud/vertexai/api/ExplanationParameters.java