// is just for efficiency, not correctness.
	args := make([]string, 64)

	// Compute total number of endpoint chains across all services
	// to get a sense of how big the cluster is.
	totalEndpoints := 0
	for svcName := range proxier.svcPortMap {
		totalEndpoints += len(proxier.endpointsMap[svcName])
	}
	proxier.largeClusterMode = (totalEndpoints > largeClusterEndpointsThreshold)

	{"ideal exp float", "{{typeOf 1e1}}", "float64", 0, true},
	{"ideal complex", "{{typeOf 1i}}", "complex128", 0, true},
	{"ideal int", "{{typeOf " + bigInt + "}}", "int", 0, true},
	{"ideal too big", "{{typeOf " + bigUint + "}}", "", 0, false},
	{"ideal nil without type", "{{nil}}", "", 0, false},

	// Fields of structs.
	{".X", "-{{.X}}-", "-x-", tVal, true},
	{".U.V", "-{{.U.V}}-", "-v-", tVal, true},

	//
	// For short inputs, the averages may not run in our favor, but then we
	// can often fall back to using the length-512 tmp available in the
	// top-most call. (Also a short allocation would not be a big deal.)
	//
	// For pathological inputs, we fall back to allocating a new tmp of length
	// max(maxID, numLMS/2). This level of the recursion needs maxID,

// or that is min pages or greater in size but not aligned to min. min must be
// a non-zero power of 2 <= maxPagesPerPhysPage.
//
// max is a hint for how big of a region is desired. If max >= pallocChunkPages, then
// findScavengeCandidate effectively returns entire free and unscavenged regions.
// If max < pallocChunkPages, it may truncate the returned region such that size is

  for (Node* node : graph_->nodes()) {
    if (!IsCompilationCandidate(node)) {
      cluster_for_node_[node->id()].Get() = nullptr;
      continue;
    }

    // We want clusters to be big enough that the benefit from XLA's
    // optimizations offsets XLA related overhead (for instance we add some
    // Switch/Merge nodes into the graph to implement lazy compilation).  To

	{"ideal exp float", "{{typeOf 1e1}}", "float64", 0, true},
	{"ideal complex", "{{typeOf 1i}}", "complex128", 0, true},
	{"ideal int", "{{typeOf " + bigInt + "}}", "int", 0, true},
	{"ideal too big", "{{typeOf " + bigUint + "}}", "", 0, false},
	{"ideal nil without type", "{{nil}}", "", 0, false},

	// Fields of structs.
	{".X", "-{{.X}}-", "-x-", tVal, true},
	{".U.V", "-{{.U.V}}-", "-v-", tVal, true},

// ordering needs to match the same byte ordering the compiler would emit. The compiler always
// emits the bitmap data in little endian byte ordering, so on big endian platforms these
// uintptrs will have their byte orders swapped from what they normally would be.
//
// heapBitsInSpan(span.elemsize) or span.isUserArenaChunk must be true.
//
//go:nosplit

		//
		// This happens repeatedly for all objects that are created concurrently() avoiding this
		// as a List() call is an important performance improvement.
		//
		// Spark based s3a committers are a  big enough use-case to have this optimization.
		//
		// A sample code to see the improvements is as follows, this sample code is
		// simply a read on JSON from MinIO and write it back as "parquet".
		//

			// We stop counting pods and removing finalizers here to:
			// 1. Ensure that the UIDs representation are under 20 KB.
			// 2. Cap the number of finalizer removals so that syncing of big Jobs
			//    doesn't starve smaller ones.
			//
			// The job will be synced again because the Job status and Pod updates
			// will put the Job back to the work queue.
			reachedMaxUncountedPods = true

	// encoding/binary helpers to write the bytes without worrying
	// about the ordering.
	binary.BigEndian.PutUint32(sa.raw[2:6], px_proto_oe)
	// This field is deliberately big-endian, unlike the previous
	// one. The kernel expects SID to be in network byte order.
	binary.BigEndian.PutUint16(sa.raw[6:8], sa.SID)
	copy(sa.raw[8:14], sa.Remote)
	for i := 14; i < 14+IFNAMSIZ; i++ {
		sa.raw[i] = 0