c.lock.Lock()
	defer c.lock.Unlock()
	var prev *v1.Pod
	key := objectKey{namespace: pod.Namespace, name: pod.Name, uid: pod.UID}
	prev = c.registeredPods[key]
	c.registeredPods[key] = pod
	// To minimize unnecessary API requests to the API server for the configmap/secret get API
	// only invoke AddReference the first time RegisterPod is called for a pod.
	if prev == nil {
		for name := range names {

  // The suppression also covers the cast to E[], discussed below.
  // In the backport, we don't have those cases and thus don't need this suppression.
  // We keep it to minimize diffs.
  @SuppressWarnings("unchecked")
  public static <E> ImmutableSet<E> copyOf(Collection<? extends E> elements) {
    /*
     * TODO(lowasser): consider checking for ImmutableAsList here

     * ImmutableSortedSet#orderedBy}.
     */
    /*
     * TODO(cpovirk): use Object[] instead of E[] in the mainline? (The backport is different and
     * doesn't need this suppression, but we keep it to minimize diffs.) Generally be more clear
     * about when we have an Object[] vs. a Comparable[] or other array type in internalArray? If we
     * used Object[], we might be able to optimize toArray() to use clone() sometimes. (See

	caserver "istio.io/istio/security/pkg/server/ca"
	"istio.io/istio/security/pkg/server/ca/authenticate"
	"istio.io/istio/security/pkg/server/ca/authenticate/kubeauth"
)

const (
	// debounce file watcher events to minimize noise in logs
	watchDebounceDelay = 100 * time.Millisecond
)

func init() {
	// Disable gRPC tracing. It has performance impacts (See https://github.com/grpc/grpc-go/issues/695)
	grpc.EnableTracing = false
}

build:rbe_base --jobs=800
build:rbe_base --remote_executor=grpcs://remotebuildexecution.googleapis.com
build:rbe_base --remote_timeout=3600
build:rbe_base --spawn_strategy=remote,worker,standalone,local
# Attempt to minimize the amount of data transfer between bazel and the remote
# workers:
build:rbe_base --remote_download_toplevel
test:rbe_base --test_env=USER=anon

# TODO(kanglan): Check if we want to merge rbe_linux into rbe_linux_cpu.

// The maximum wasted space per dataBuffer is 2x the largest size class,
// which happens when the dataBuffer has multiple chunks and there is
// one unread byte in both the first and last chunks. We use a few size
// classes to minimize overheads for servers that typically receive very
// small request bodies.
//
// TODO: Benchmark to determine if the pools are necessary. The GC may have
// improved enough that we can instead allocate chunks like this:

  let description = [{
    It is beneficial for performance to assign a `Split` op to the same device
    as its predecessor. This is because the weight of cut edges is always
    minimized when the `Split` is with its predecessor. This colocation
    constraint will be used by the placer graph optimization to assign a device
    to the op.

			mulop := ssa.OpMul64F
			addop := ssa.OpAdd64F
			subop := ssa.OpSub64F
			pt := types.FloatForComplex(n.Type()) // Could be Float32 or Float64
			wt := types.Types[types.TFLOAT64]     // Compute in Float64 to minimize cancellation error

			areal := s.newValue1(ssa.OpComplexReal, pt, a)
			breal := s.newValue1(ssa.OpComplexReal, pt, b)
			aimag := s.newValue1(ssa.OpComplexImag, pt, a)

        an issue in the Keras GitHub repo.
    *   **Error such as `Cannot recognize variable...`.** The new optimizer
        requires all optimizer variables to be created at the first
        `apply_gradients()` or `minimize()` call. If your workflow calls
        optimizer to update different parts of model in multiple stages,
        please call `optimizer.build(model.trainable_variables)` before the
        training loop.

### Internal

* ♻ Refactor dict value extraction to minimize key lookups `fastapi/utils.py`. PR [#3139](https://github.com/tiangolo/fastapi/pull/3139) by [@ShahriyarR](https://github.com/ShahriyarR).