func TestExpirePod(t *testing.T) {
	nodeName := "node"
	testPods := []*v1.Pod{
		makeBasePod(t, nodeName, "test-1", "100m", "500", "", []v1.ContainerPort{{HostIP: "127.0.0.1", HostPort: 80, Protocol: "TCP"}}),
		makeBasePod(t, nodeName, "test-2", "200m", "1Ki", "", []v1.ContainerPort{{HostIP: "127.0.0.1", HostPort: 8080, Protocol: "TCP"}}),

              fieldPath: metadata.name
        - name: POD_NAMESPACE
          valueFrom:
            fieldRef:
              fieldPath: metadata.namespace
        - name: NODE_NAME
          valueFrom:
            fieldRef:
              fieldPath: spec.nodeName
        - name: INSTANCE_IP
          valueFrom:
            fieldRef:
              fieldPath: status.podIP
        - name: SERVICE_ACCOUNT
          valueFrom:

	state, err := getStateData(cs)
	if err != nil {
		return framework.AsStatus(err)
	}
	// we don't need to hold the lock as only one node will be reserved for the given pod
	podVolumes, ok := state.podVolumesByNode[nodeName]
	if ok {
		allBound, err := pl.Binder.AssumePodVolumes(klog.FromContext(ctx), pod, nodeName, podVolumes)
		if err != nil {

                  fieldPath: spec.nodeName
            - name: REPAIR_RUN_AS_DAEMON
              value: "true"
            - name: REPAIR_SIDECAR_ANNOTATION
              value: "sidecar.istio.io/status"
            - name: NODE_NAME
              valueFrom:
                fieldRef:
                  apiVersion: v1
                  fieldPath: spec.nodeName
            - name: GOMEMLIMIT

# Text form of tensorflow.tf2xla.Config proto.
feed {
  id { node_name: "x_const" }
  shape {
    dim { size: 1 }
  }
}
feed {
  id { node_name: "y_const" }
  shape {
    dim { size: 1 }
  }
}
feed {
  id { node_name: "z_identity"}
  shape {
    dim { size: 1 }
  }
}
fetch {
  id { node_name: "x_y_sum" }
}
fetch {
  id { node_name: "x_z_sum" }

			want:     &PreFilterResult{NodeNames: sets.New[string]()},
		},
		"nil receiver populated input": {
			in:   &PreFilterResult{NodeNames: sets.New("node1")},
			want: &PreFilterResult{NodeNames: sets.New("node1")},
		},
		"empty receiver populated input": {
			receiver: &PreFilterResult{NodeNames: sets.New[string]()},
			in:       &PreFilterResult{NodeNames: sets.New("node1")},
			want:     &PreFilterResult{NodeNames: sets.New[string]()},

# Text form of tensorflow.tf2xla.Config proto.
feed {
  id { node_name: "x_hold" }
  shape {
    dim { size: 2 }
    dim { size: 2 }
  }
  name: "x"
}
feed {
  id { node_name: "y_hold" }
  shape {
    dim { size: 2 }
    dim { size: 2 }
  }
  name: "y"
}
fetch {
  id { node_name: "x_y_prod" }
  name: "x_y_prod"
}
fetch {
  id { node_name: "x_y_sum" }
  name: "x_y_sum"

  while (!nodes_to_visit.empty()) {
    const string node_name = nodes_to_visit.front();
    nodes_to_visit.pop();
    if (reachable_node_names->find(node_name) != reachable_node_names->end()) {
      continue;
    }
    reachable_node_names->insert(node_name);
    NodeDef* node = name_to_node_map.at(node_name);
    if (kVariableTypes->find(node->op()) != kVariableTypes->end()) {

feed {
  id { node_name: "x_const" }
  shape {
    dim { size: 1 }
  }
}
feed {
  id { node_name: "y_const" }
  shape {
    dim { size: 1 }
  }
}
feed {
  id { node_name: "z" output_index: 1}
  shape {
    dim { size: 1 }
  }
  type: DT_INT32
}
fetch {
  id { node_name: "x_y_sum" }
}
fetch {
  id { node_name: "x_z_sum" }

# Text form of tensorflow.tf2xla.Config proto.
feed {
  id { node_name: "p_hold" }
  shape {}
}
feed {
  id { node_name: "x_hold" }
  shape {
    dim { size: 1 }
  }
}
feed {
  id { node_name: "y_hold" }
  shape {
    dim { size: 1 }
  }
}
fetch {
  id { node_name: "result" }