class TFTensorType : public Type::TypeBase<TFTensorType, Type, TypeStorage> {
 public:
  using Base::Base;
  static constexpr StringLiteral name = "tfrt.tf_tensor";
};

// The MLIR type represents a tensorflow::Allocator.
class TFAllocatorType
    : public Type::TypeBase<TFAllocatorType, Type, TypeStorage> {
 public:
  using Base::Base;
  static constexpr StringLiteral name = "tfrt.tf_allocator";
};

}  // namespace fallback

)

type netTokenChecker struct {
	released bool
	// We want to use a finalizer to check that all acquired tokens are returned,
	// so we arbitrarily pad the tokens with a string to defeat the runtime's
	// “tiny allocator”.
	unusedAvoidTinyAllocator string
}

func (c *netTokenChecker) panicUnreleased() {
	panic("internal error: net token acquired but not released")

#include <vector>

#include <gtest/gtest.h>
#include "tensorflow/compiler/jit/test_util.h"
#include "xla/pjrt/pjrt_client.h"
#include "xla/shape.h"
#include "xla/shape_util.h"
#include "tensorflow/core/framework/allocator.h"
#include "tensorflow/core/framework/device.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/types.h"

//
// 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"> {

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)