int64_t num_values = 1;
  for (int i = 0; i < num_dims; ++i) {
    num_values *= dims[i];
  }
  TF_Tensor* t =
      TF_AllocateTensor(TF_INT32, dims, num_dims, sizeof(int32_t) * num_values);
  memcpy(TF_TensorData(t), values, sizeof(int32_t) * num_values);
  return t;
}

TF_Tensor* Int32Tensor(const std::vector<int32_t>& values) {
  int64_t dims = values.size();
  return Int32Tensor(&dims, 1, values.data());
}

      EXPECT_EQ(0, TF_NumDims(out));  // scalar
      ASSERT_EQ(sizeof(int32_t), TF_TensorByteSize(out));
      int32_t* output_contents = static_cast<int32_t*>(TF_TensorData(out));
      EXPECT_EQ(expected_results[i], *output_contents);
    }
  }

  void CompareInt32Tensor(const std::vector<int32_t>& expected, TF_Tensor* t) {
    int32_t* data = static_cast<int32_t*>(TF_TensorData(t));
    size_t size = TF_TensorByteSize(t);

  }
}

void TestEncodeDecode(int line, const std::vector<string>& data) {
  const int64_t n = data.size();
  absl::Status status;
  for (const std::vector<int64_t>& dims :
       std::vector<std::vector<int64_t>>{{n}, {1, n}, {n, 1}, {n / 2, 2}}) {
    // Create C++ Tensor
    Tensor src(tensorflow::DT_STRING, TensorShape(dims));
    for (int64_t i = 0; i < src.NumElements(); ++i) {
      src.flat<tstring>()(i) = data[i];
    }

pkg math/rand/v2, func Float32() float32 #61716
pkg math/rand/v2, func Float64() float64 #61716
pkg math/rand/v2, func Int() int #61716
pkg math/rand/v2, func Int32() int32 #61716
pkg math/rand/v2, func Int32N(int32) int32 #61716
pkg math/rand/v2, func Int64() int64 #61716
pkg math/rand/v2, func Int64N(int64) int64 #61716
pkg math/rand/v2, func IntN(int) int #61716
pkg math/rand/v2, func N[$0 intType]($0) $0 #61716

                   int64_t value) {
  desc->node_builder.Attr(attr_name, static_cast<int64_t>(value));
}

void TF_SetAttrIntList(TF_OperationDescription* desc, const char* attr_name,
                       const int64_t* values, int num_values) {
  desc->node_builder.Attr(
      attr_name, ArraySlice<const int64_t>(
                     reinterpret_cast<const int64_t*>(values), num_values));
}

pkg syscall (openbsd-386), type Kevent_t struct, Data int32
pkg syscall (openbsd-386), type Mclpool struct, Grown uint32
pkg syscall (openbsd-386), type RtMetrics struct, Expire uint32
pkg syscall (openbsd-386), type Stat_t struct, Ino uint32
pkg syscall (openbsd-386), type Stat_t struct, Lspare0 int32
pkg syscall (openbsd-386), type Stat_t struct, Lspare1 int32

pkg sync, method (*Map) Clear() #61696
pkg sync/atomic, func AndInt32(*int32, int32) int32 #61395
pkg sync/atomic, func AndInt64(*int64, int64) int64 #61395
pkg sync/atomic, func AndUint32(*uint32, uint32) uint32 #61395
pkg sync/atomic, func AndUint64(*uint64, uint64) uint64 #61395
pkg sync/atomic, func AndUintptr(*uintptr, uintptr) uintptr #61395
pkg sync/atomic, func OrInt32(*int32, int32) int32 #61395
pkg sync/atomic, func OrInt64(*int64, int64) int64 #61395

                                 const int64_t* dims, int num_dims) {
  DCHECK(index >= 0 && index < shape_list->num_items);
  TF_ShapeAndType& shape = shape_list->items[index];
  DCHECK(shape.dims == nullptr) << "Shape at " << index << " is already set!";
  DCHECK(num_dims >= 0) << "Number of dimensions cannot be negative!";
  shape.num_dims = num_dims;
  shape.dims = new int64_t[num_dims];

	if len(ps.subs) != 2 {
		t.Fatalf("expected 2 subscribers")
	}
	if want, got := int32(2), ps.NumSubscribers(Mask(1)); got != want {
		t.Fatalf("want %d subscribers, got %d", want, got)
	}
	if want, got := int32(2), ps.NumSubscribers(Mask(2)); got != want {
		t.Fatalf("want %d subscribers, got %d", want, got)
	}
	if want, got := int32(2), ps.NumSubscribers(Mask(1|2)); got != want {
		t.Fatalf("want %d subscribers, got %d", want, got)

	types  Mask
	filter func(entry T) bool
}

// PubSub holds publishers and subscribers
type PubSub[T Maskable, M Maskable] struct {
	// atomics, keep at top:
	types          uint64
	numSubscribers int32
	maxSubscribers int32

	// not atomics:
	subs []*Sub[T]
	sync.RWMutex
}

// Publish message to the subscribers.
// Note that publish is always non-blocking send so that we don't block on slow receivers.