if (!input_type.hasStaticShape() || !weights_type.hasStaticShape() ||
      (has_bias && !bias_type.hasStaticShape())) {
    return failure();
  }

  // Folding only implemented for 1D input, 2D weights and 1D bias
  if (input_type.getShape().size() != 1 ||
      weights_type.getShape().size() != 2 ||
      (has_bias && bias_type.getShape().size() != 1)) {
    return failure();
  }

  // Get the sizes

  - [beta] `Federated Replica Sets` create and maintain matching
    `Replica Set`s in some or all clusters in a federation, with the
    desired replica count distributed equally or according to
    specified per-cluster weights.
	([docs](http://kubernetes.io/docs/user-guide/federation/federated-replicasets.md))
	([kubernetes/features#46](https://github.com/kubernetes/enhancements/issues/46))

			Weight:      5,
		}, {
			Destination: &networking.Destination{Host: "foo.baz.east"},
			Weight:      -1,
		}}, valid: false},
		{name: "total weight > 100", routes: []*networking.RouteDestination{{
			Destination: &networking.Destination{Host: "foo.baz.south"},
			Weight:      550,
		}, {
			Destination: &networking.Destination{Host: "foo.baz.east"},
			Weight:      500,
		}}, valid: true},

.h3,.h4,.h5,.h6,h1,h2,h3,h4,h5,h6{margin-bottom:.5rem;font-weight:500;line-height:1.2}.h1,h1{font-size:2.5rem}.h2,h2{font-size:2rem}.h3,h3{font-size:1.75rem}.h4,h4{font-size:1.5rem}.h5,h5{font-size:1.25rem}.h6,h6{font-size:1rem}.lead{font-size:1.25rem;font-weight:300}.display-1{font-size:6rem;font-weight:300;line-height:1.2}.display-2{font-size:5.5rem;font-weight:300;line-height:1.2}.display-3{font-size:4.5rem;font-weight:300;line-height:1.2}.display-4{font-size:3.5rem;font-weight:300;line-heigh...

.h3,.h4,.h5,.h6,h1,h2,h3,h4,h5,h6{margin-bottom:.5rem;font-weight:500;line-height:1.2}.h1,h1{font-size:2.5rem}.h2,h2{font-size:2rem}.h3,h3{font-size:1.75rem}.h4,h4{font-size:1.5rem}.h5,h5{font-size:1.25rem}.h6,h6{font-size:1rem}.lead{font-size:1.25rem;font-weight:300}.display-1{font-size:6rem;font-weight:300;line-height:1.2}.display-2{font-size:5.5rem;font-weight:300;line-height:1.2}.display-3{font-size:4.5rem;font-weight:300;line-height:1.2}.display-4{font-size:3.5rem;font-weight:300;line-heigh...

	}

	rss, err = fp.ipvs.GetRealServers(vs)
	if err != nil {
		t.Errorf("failed to get real server, err: %v", err)
	}
	for _, rs := range rss {
		if rs.Weight != 1 {
			t.Logf("unexpected realserver weight: %d, expected weight: 1", rs.Weight)
			t.Errorf("unexpected realserver state")
		}
	}
}

func TestIPv4Proxier(t *testing.T) {
	tests := []struct {
		name         string

,h5,h6{margin-bottom:.5rem;font-family:inherit;font-weight:500;line-height:1.2;color:inherit}.h1,h1{font-size:2.5rem}.h2,h2{font-size:2rem}.h3,h3{font-size:1.75rem}.h4,h4{font-size:1.5rem}.h5,h5{font-size:1.25rem}.h6,h6{font-size:1rem}.lead{font-size:1.25rem;font-weight:300}.display-1{font-size:6rem;font-weight:300;line-height:1.2}.display-2{font-size:5.5rem;font-weight:300;line-height:1.2}.display-3{font-size:4.5rem;font-weight:300;line-height:1.2}.display-4{font-size:3.5rem;font-weight:300;lin...

  return %1 : tensor<1x2x3x5xf32>
}

// CHECK: %[[WEIGHT:.+]] = "tfl.pseudo_qconst"() <{qtype = tensor<1x2x4x5x!quant.uniform<i8:f32, 1.000000e+00>>, value = dense<1> : tensor<1x2x4x5xi8>}>
// CHECK: %[[DQ:.+]] = "tfl.dequantize"(%[[WEIGHT]]) : (tensor<1x2x4x5x!quant.uniform<i8:f32, 1.000000e+00>>) -> tensor<1x2x4x5xf32>

      ('to_xla_per_tensor', quant_opts_pb2.XLA, False),
      ('stablehlo_per_channel', quant_opts_pb2.STABLEHLO, True),
      # TODO: b/289761265 - [Converter Component][TF-Quantizer] Improve Weight-
      # only Quantization
      # Enable this back once new weight-only quantizer is supported for per-
      # channel quantization.
      # ('to_xla_per_channel', quant_opts_pb2.XLA, True),
  )
  @test_util.run_in_graph_and_eager_modes

				{
					ExtenderName: "FakeExtender1",
					Weight:       1,
					Prioritizers: []tf.PriorityConfig{
						{
							Weight:   3,
							Function: tf.Node1PrioritizerExtender,
						},
					},
				},
				{
					ExtenderName: "FakeExtender2",
					Weight:       1,
					Prioritizers: []tf.PriorityConfig{
						{
							Weight:   2,
							Function: tf.Node2PrioritizerExtender,