int added = 0;
    while (added < numElements) {
      // we could rely solely on #poll, but #drainTo might be more efficient when there are multiple
      // elements already available (e.g. LinkedBlockingQueue#drainTo locks only once)
      added += q.drainTo(buffer, numElements - added);
      if (added < numElements) { // not enough elements immediately available; will have to poll

}

#endif  // LIBTPU_EXCLUDE_C_API_IMPL

namespace tensorflow {

void TensorInterface::Release() {
  if (Type() == DT_STRING && NumElements() > 0) {
    TF_TString* data = static_cast<TF_TString*>(Data());
    if (CanMove() && data != nullptr) {
      for (int64_t i = 0; i < NumElements(); ++i) {
        TF_TString_Dealloc(&data[i]);
      }
    }
  }
  delete this;
}

      "x/.ATTRIBUTES/VARIABLE_VALUE", DT_FLOAT, &x_handle));
  AbstractTensorPtr x = testing::TensorHandleToTensor(x_handle.get());
  EXPECT_EQ(x->Type(), DT_FLOAT);
  EXPECT_EQ(x->NumElements(), 1);
  EXPECT_EQ(x->NumDims(), 0);
  EXPECT_FLOAT_EQ(*reinterpret_cast<float*>(x->Data()), 1.0f);

  ImmediateTensorHandlePtr y_handle;
  TF_EXPECT_OK(internal::SingleRestore(

                                             Tensor* device_tensor,
                                             StatusCallback done,
                                             bool sync_dst_compute) const {
  if (cpu_tensor->NumElements() == 0) {
    VLOG(2) << "CopyCPUTensorToDevice empty tensor";
    done(absl::OkStatus());
    return;
  }

  VLOG(2) << "CopyCPUTensorToDevice " << this << " "

  size_t offset = 0;
  for (auto const& e : v) {
    Tensor elem = e.tensor;
    if (first.tensor.dtype() == DT_STRING) {
      for (int i = 0; i < elem.NumElements(); ++i) {
        t.flat<tstring>()(offset + i) = elem.flat<tstring>()(i);
      }
      offset += elem.NumElements();
    } else {
      std::copy_n(elem.tensor_data().data(), elem.TotalBytes(),
                  const_cast<char*>(t.tensor_data().data()) + offset);

      typedef typename RealType<T>::type RealT;
      Tensor t(DataTypeToEnum<RealT>::v(), shape);
      if (t.NumElements() != static_cast<int64_t>(v.size())) {
        status = absl::InvalidArgumentError(absl::StrCat(
            "Cannot construct a tensor with ", t.NumElements(),
            " from an initializer list with ", v.size(), " elements"));
        return;
      }

  if (actual.NumElements() != expected.NumElements()) {
    if (listener->IsInterested()) {
      *listener << "\nwas looking for tensor with " << expected.NumElements()
                << " elements, found tensor with " << actual.NumElements()
                << " elements";
      return false;
    }
  }

  for (int64_t i = 0, e = actual.NumElements(); i < e; i++) {

  if (!scope.ok()) return Output();

  typedef typename Input::Initializer::RealType<T>::type DstT;

  if (val.tensor.dtype() == DataTypeToEnum<DstT>::v()) {
    return orig_const_output;
  }
  if (val.tensor.NumElements() == 0) {
    Tensor t(DataTypeToEnum<DstT>::v(), val.tensor.shape());
    return Const(scope, Input::Initializer(t));
  }

  // TODO(keveman): Refactor Cast op's kernel implementation such that the code

                                              StatusCallback done) {
  tsl::profiler::TraceMe traceme("PjRtDeviceContext::CopyDeviceTensorToCPU");
  if (device_tensor->NumElements() == 0) {
    VLOG(2) << "CopyDeviceTensorToCPU empty tensor";
    done(absl::OkStatus());
    return;
  }
  auto literal = std::make_unique<xla::MutableBorrowingLiteral>();

	metav1beta1 "k8s.io/apimachinery/pkg/apis/meta/v1beta1"

	"github.com/google/go-cmp/cmp"
	fuzz "github.com/google/gofuzz"
)

func TestAsPartialObjectMetadata(t *testing.T) {
	f := fuzz.New().NilChance(.5).NumElements(0, 1).RandSource(rand.NewSource(1))

	for i := 0; i < 100; i++ {
		m := &metav1.ObjectMeta{}
		f.Fuzz(m)
		partial := AsPartialObjectMetadata(m)
		if !reflect.DeepEqual(&partial.ObjectMeta, m) {