}

// NormalizeScore invoked after scoring all nodes.
func (pl *TaintToleration) NormalizeScore(ctx context.Context, _ *framework.CycleState, pod *v1.Pod, scores framework.NodeScoreList) *framework.Status {
	return helper.DefaultNormalizeScore(framework.MaxNodeScore, true, scores)
}

// ScoreExtensions of the Score plugin.
func (pl *TaintToleration) ScoreExtensions() framework.ScoreExtensions {
	return pl
}

{{ end }}
{{ with .PortMatch }}
    match:
    - port: {{.}}
{{ end }}
`, args)
	default:
		panic(variant + " unknown")
	}
}

type scArgs struct {
	Namespace string
	Egress    []string
}

func (args scArgs) Config(t *testing.T, variant string) string {
	return tmpl.MustEvaluate(`apiVersion: networking.istio.io/v1alpha3
kind: Sidecar
metadata:
  name: "{{.Namespace}}"

    Res<TensorOf<[TF_Float16, TF_Float32]>, [{A 1-D float tensor of shape `[M]` representing the corresponding
scores for each selected box, where `M <= max_output_size`.  Scores only differ
from corresponding input scores when using Soft NMS (i.e. when
`soft_nms_sigma>0`)}]>:$selected_scores,
    Res<TF_Int32Tensor, [{A 0-D integer tensor representing the number of valid elements in

*   In `Attention` and `AdditiveAttention` layers, the `call()` method now
    accepts a `return_attention_scores` argument. When set to True, the layer
    returns the attention scores as an additional output argument.
*   Adds `tf.metrics.log_cosh` and `tf.metrics.logcosh` API entrypoints with the
    same implementation as their `tf.losses` equivalent.