--project "$NETWORK_PROJECT" \
      --router-region "$REGION" \
      --router "$NETWORK-nat-router" \
      --nat-primary-subnet-ip-ranges \
      --auto-allocate-nat-external-ips \
      ${GCE_PRIVATE_CLUSTER_PORTS_PER_VM:+--min-ports-per-vm ${GCE_PRIVATE_CLUSTER_PORTS_PER_VM}}
  fi
}

function delete-all-firewall-rules() {
  local -a fws

	attrs := &lifecycle.PodAdmitAttributes{Pod: pod, OtherPods: pods}
	if utilfeature.DefaultFeatureGate.Enabled(features.InPlacePodVerticalScaling) {
		// Use allocated resources values from checkpoint store (source of truth) to determine fit
		otherPods := make([]*v1.Pod, 0, len(pods))
		for _, p := range pods {
			op := p.DeepCopy()
			kl.updateContainerResourceAllocation(op)

    }

    @Override
    public void forEach(Consumer<? super K> action) {
      checkNotNull(action);
      // avoids entry allocation for those maps that allocate entries on iteration
      map.forEach((k, v) -> action.accept(k));
    }

    @Override
    public int size() {
      return map().size();
    }

    @Override

  for (int i = 0; i < len; ++i) {
    values[i] = TF_NewBuffer();
    status->status = MessageToBuffer(attr->list().shape(i), values[i]);
    if (!status->status.ok()) {
      // Delete everything allocated to far, the operation has failed.
      for (int j = 0; j <= i; ++j) {
        TF_DeleteBuffer(values[j]);
      }
      return;
    }
  }
}

    a single value from first replica.

    The benefit of this optimization is reduced memory requirement on host. For
    multiple writes (one from each replica) to such variables, the host would
    allocate buffer space to receive the device output from all replicas, which is
    not required. We can use the output of first replica in such cases.
  }];

	}

	resyncStatus := ResyncFailed
	defer func() {
		s.markStatus(resyncStatus, opts, objectAPI)
		globalSiteResyncMetrics.incBucket(opts, resyncStatus)
		s.workerCh <- struct{}{}
	}()
	// Allocate new results channel to receive ObjectInfo.
	objInfoCh := make(chan itemOrErr[ObjectInfo])
	cfg, err := getReplicationConfig(ctx, opts.bucket)
	if err != nil {

  // Hold current ND index in input tensor when computing
  // permutation.
  llvm::OwningArrayRef<uint64_t> current_input_index(
      input_tensor.getType().getRank());

  // Allocate raw data and retrieve address of the first char in its raw
  // buffer.
  llvm::OwningArrayRef<char> raw_output_arr(input_tensor.getRawData());
  char* raw_output = (char*)raw_output_arr.data();

// The returned connRequestDelHandle can be used to remove the item from
// the set.
func (s *connRequestSet) Add(v chan connRequest) connRequestDelHandle {
	idx := len(s.s)
	// TODO(bradfitz): for simplicity, this always allocates a new int-sized
	// allocation to store the index. But generally the set will be small and
	// under a scannable-threshold. As an optimization, we could permit the *int

	n := int(testing.AllocsPerRun(1000, func() {
		_, release, err := c.grabConn(ctx)
		if err != nil {
			t.Fatal(err)
		}
		release(nil)
	}))
	if n > 0 {
		t.Fatalf("Conn.grabConn allocated %v objects; want 0", n)
	}
}

func BenchmarkGrabConn(b *testing.B) {
	b.ReportAllocs()
	c := new(Conn)
	ctx := context.Background()
	for i := 0; i < b.N; i++ {

				t.Fatalf("expected to have at least one TableRow, but got: %d", len(rows))
			}

			func() {
				defer func() {
					if err := recover(); err != nil {
						// Same as stdlib http server code. Manually allocate stack
						// trace buffer size to prevent excessively large logs
						const size = 64 << 10
						buf := make([]byte, size)
						buf = buf[:runtime.Stack(buf, false)]