*   <li>Each other step is derived from one or more input steps. At each step, zero or more objects
 *       can be captured for later closing.
 *   <li>There is one last step (the root of the tree), from which you can extract the final result
 *       of the computation. After that result is available (or the computation fails), all objects
 *       captured by any of the steps in the pipeline are closed.
 * </ol>
 *
 * <h3>Starting a pipeline</h3>
 *

}

def ClusterConstantSinkingPass : Pass<"tf-device-constant-sinking", "mlir::func::FuncOp"> {
  let summary = "Sinks constants implicitly captured in a tf_device.cluster region.";

  let description = [{
    This pass sinks implicitly captured constants (`tf.Const` ops) used by and into
    a `tf_device.cluster` region. Performing this prior to outlining will reduce the
    number of arguments of the outlined function.

		}

		metrics = make([]MetricV2, 0, 50)
		dataUsageInfo, err := loadDataUsageFromBackend(ctx, objLayer)
		if err != nil {
			metricsLogIf(ctx, err)
			return
		}

		// data usage has not captured any data yet.
		if dataUsageInfo.LastUpdate.IsZero() {
			return
		}

		metrics = append(metrics, MetricV2{
			Description: getUsageLastScanActivityMD(),

  // state, Y is the number of tensor components that represent the input
  // elements, and Z is the number of tensor components that represent any
  // captured arguments. Y is determined by the output_shapes of an op that
  // defines the first operand of `op`.

  // TODO(jpienaar): Avoid this lookup.
  auto module = op->getParentOfType<ModuleOp>();

			expected: []string{ipv6},
			protocol: "udp",
		},
		{
			// We should only capture traffic to servers in /etc/resolv.conf nameservers
			// This checks we do not capture traffic to other servers.
			// This is important for cases like app -> istio dns server -> dnsmasq -> upstream
			// If we captured all DNS traffic, we would loop dnsmasq traffic back to our server.
			name:     "tcp localhost server",

  LogicalResult matchAndRewrite(WhileRegionOp while_op,
                                PatternRewriter &rewriter) const override {
    // Remove any extern values that are explicitly captured and returned. Also
    // replace values that simply passthrough the body with extern values. The
    // block arguments of body and while match and so the corresponding cond
    // argument can be easily found.

}

func (sp *SizeofPack) goString(indent int, field string) string {
	return fmt.Sprintf("%*s%sSizeofPack: Pack: %p", indent, "", field, sp.Pack)
}

// SizeofArgs is the size of a captured template parameter pack from
// an alias template.
type SizeofArgs struct {
	Args []AST
}

func (sa *SizeofArgs) print(ps *printState) {
	c := 0
	for _, a := range sa.Args {

				// Note that this test simulates a net-new pod being discovered during HandlePodCleanups that was not
				// delivered to the pod worker via HandlePodAdditions - there is no *known* scenario that can happen, but
				// we want to capture it in the metric. The more likely scenario is that a static pod with a predefined
				// UID is updated, which causes pod config to deliver DELETE -> ADD while the old pod is still shutting

					},
				},
			},
		),
		WithFrameworkOutOfTreeRegistry(frameworkruntime.Registry{
			"FakeNodeSelector": newFakeNodeSelector,
		}),
	)
	if err != nil {
		t.Fatal(err)
	}

	// Capture the bindings and events' controllers.
	var wg sync.WaitGroup
	wg.Add(2 * len(pods))
	bindings := make(map[string]string)

  // Lowers 2D upscaling logic to a single TFL::ResizeNearestNeighor op.
  //
  // To optimize JAX resize implementation, especially for 2D upscaling, this
  // pattern matching logic captures the following pattern to replace with the
  // single TFL::resize_nearest_neighbor op instance as a fast fused op
  // available in TFLite.
  //
  // - tfl.gather_nd -> tfl.transpose -> tfl.gather_nd -> tfl.transpose