//
// The last point is the real benefit of NotInHeap. The runtime uses
// it for low-level internal structures to avoid memory barriers in the
// scheduler and the memory allocator where they are illegal or simply
// inefficient. This mechanism is reasonably safe and does not compromise
// the readability of the runtime.

WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/

package ipallocator

import (
	"sync"

	"k8s.io/component-base/metrics"
	"k8s.io/component-base/metrics/legacyregistry"
)

const (
	namespace = "kube_apiserver"
	subsystem = "clusterip_allocator"
)

var (

// compile

// Copyright 2019 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

// This code failed on arm64 in the register allocator.
// See issue 33355.

package server

import (
	"bytes"
	"sync"
)

type client struct {
	junk [4]int
	mu   sync.Mutex
	srv  *Server
	gw   *gateway
	msgb [100]byte
}

    Op<TensorflowMlrtTpu_Dialect, mnemonic, !listconcat(traits, [IsolatedFromAbove])> {
}

def GetTpuHostDeviceOp : TensorflowMlrtTpu_Op<"get_tpu_host_device", [Pure]> {
  let summary = "get the tpu host allocator that implements tensorflow::Device";

  let results = (outs
    TFDeviceType:$device
  );

  let assemblyFormat = "attr-dict";
}

def CompileAndExecuteOp : TensorflowMlrtTpu_Op<"compile_and_execute"> {

#include "tensorflow/core/common_runtime/dma_helper.h"
#include "tensorflow/core/framework/tensor_reference.h"
#include "tsl/platform/statusor.h"

namespace tensorflow {

// The allocator used for Tensors assigned to the XLA device.
XlaDeviceAllocator::XlaDeviceAllocator(
    stream_executor::StreamExecutor* stream_executor)
    : stream_executor_(stream_executor) {}

WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/

package allocator

import (
	"errors"
	"fmt"
	"math/big"
	"math/rand"
	"sync"
	"time"
)

// AllocationBitmap is a contiguous block of resources that can be allocated atomically.
//

// allocator provided by pluggable vendor to do the allocate_temp of the
// tensors. The caller takes ownership of temporary variables and is responsible
// for freeing them with TF_DestroyTemporaryVariable. This function will return
// an error when the following conditions are met:
//   1. Cannot allocate a new temporary variable
//   2. Calling plugin allocator failed

	regConfirmRun.Store(int32(*(*int)(v.(*TintPointer).p)))
	return 5151, 4.0, [10]byte{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}
}

// TintPointer has a pointer member to make sure that it isn't allocated by the
// tiny allocator, so we know when its finalizer will run
type TintPointer struct {
	p *Tint
}

func (*TintPointer) m() {}

func TestFinalizerRegisterABI(t *testing.T) {
	testenv.MustHaveExec(t)

	"k8s.io/klog/v2"
	"k8s.io/kubernetes/pkg/features"
	kubecontainer "k8s.io/kubernetes/pkg/kubelet/container"
	utilstore "k8s.io/kubernetes/pkg/kubelet/util/store"
	"k8s.io/kubernetes/pkg/registry/core/service/allocator"
	utilfs "k8s.io/kubernetes/pkg/util/filesystem"
)

// length for the user namespace to create (65536).
const userNsLength = (1 << 16)

// Create a new map when we removed enough pods to avoid memory leaks

  options.graph_def_version = function_library.graph_def_version();
  options.allow_cpu_custom_calls =
      (platform_info.platform_id() == se::host::kHostPlatformId);
  options.device_allocator = GetAllocator(device, stream, platform_info);
  if (platform_info.xla_device_metadata()) {
    options.shape_determination_fns =
        platform_info.xla_device_metadata()->default_shape_determination_fns();
  }