public:
  explicit FakeDevice(const DeviceAttributes& device_attributes)
      : Device(nullptr, device_attributes) {}

  Status Sync() override { return errors::Unimplemented("FakeDevice::Sync()"); }

  Allocator* GetAllocator(AllocatorAttributes attr) override { return nullptr; }

  static std::unique_ptr<Device> Make(const string& name, const string& type) {
    DeviceAttributes device_attributes;
    device_attributes.set_name(name);

#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"

    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) {}

// 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();
  }

	"k8s.io/client-go/tools/cache"
	"k8s.io/client-go/tools/record"
	"k8s.io/client-go/util/workqueue"
	"k8s.io/klog/v2"
	"k8s.io/kubernetes/pkg/registry/core/service/ipallocator"
	"k8s.io/kubernetes/pkg/util/iptree"
	netutils "k8s.io/utils/net"
)

const (
	// maxRetries is the max number of times a service object will be retried before it is dropped out of the queue.

#define TENSORFLOW_COMPILER_JIT_XLA_TENSOR_H_

#include <memory>

#include "absl/memory/memory.h"
#include "xla/client/local_client.h"
#include "xla/service/shaped_buffer.h"
#include "tensorflow/core/framework/allocator.h"
#include "tensorflow/core/framework/device_base.h"
#include "tensorflow/core/lib/core/status.h"
#include "tensorflow/core/platform/mutex.h"

namespace tensorflow {