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Results 1 - 10 of 12 for minimizeC (0.23 sec)
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pkg/kubelet/util/manager/cache_based_manager.go
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 {
Registered: Sat Jun 15 01:39:40 UTC 2024 - Last Modified: Tue Jun 04 06:25:43 UTC 2024 - 8.3K bytes - Viewed (0) -
android/guava/src/com/google/common/collect/ImmutableSet.java
// 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
Registered: Wed Jun 12 16:38:11 UTC 2024 - Last Modified: Sun Jun 02 13:36:19 UTC 2024 - 22.5K bytes - Viewed (0) -
android/guava/src/com/google/common/collect/ImmutableSortedSet.java
* 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
Registered: Wed Jun 12 16:38:11 UTC 2024 - Last Modified: Sun Jun 02 13:36:19 UTC 2024 - 36.8K bytes - Viewed (0) -
pilot/pkg/bootstrap/server.go
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 }
Registered: Fri Jun 14 15:00:06 UTC 2024 - Last Modified: Thu Jun 13 17:48:28 UTC 2024 - 46.3K bytes - Viewed (0) -
.bazelrc
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.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 17:12:54 UTC 2024 - 52.9K bytes - Viewed (0) -
src/net/http/h2_bundle.go
// 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:
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Tue Jun 04 16:19:04 UTC 2024 - 364.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.td
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.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 21:18:05 UTC 2024 - 99.6K bytes - Viewed (0) -
src/cmd/compile/internal/ssagen/ssa.go
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)
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Mon Jun 10 19:44:43 UTC 2024 - 284.9K bytes - Viewed (0) -
RELEASE.md
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.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 730.3K bytes - Viewed (0) -
docs/en/docs/release-notes.md
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Fri Jun 14 15:07:37 UTC 2024 - 395.4K bytes - Viewed (0)