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

    TF_DeleteShapeAndTypeList(output_shapes);
  }

  absl::optional<std::vector<int64_t>> make_shape(
      std::vector<int64_t>&& dims) const {
    return absl::make_optional(dims);
  }

  absl::optional<std::vector<int64_t>> unknown_shape() const {
    return absl::nullopt;
  }

  static constexpr int64_t kUnknownDim =
      shape_inference::InferenceContext::kUnknownDim;
  TF_Status* status_;

TF_CAPI_EXPORT extern void TF_SetAttrInt(TF_OperationDescription* desc,
                                         const char* attr_name, int64_t value);
TF_CAPI_EXPORT extern void TF_SetAttrIntList(TF_OperationDescription* desc,
                                             const char* attr_name,
                                             const int64_t* values,
                                             int num_values);

                   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

                                 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];

pkg sync/atomic, method (*Bool) Swap(bool) bool #50860
pkg sync/atomic, method (*Int32) Add(int32) int32 #50860
pkg sync/atomic, method (*Int32) CompareAndSwap(int32, int32) bool #50860
pkg sync/atomic, method (*Int32) Load() int32 #50860
pkg sync/atomic, method (*Int32) Store(int32) #50860
pkg sync/atomic, method (*Int32) Swap(int32) int32 #50860
pkg sync/atomic, method (*Int64) Add(int64) int64 #50860

TF_CAPI_EXPORT extern void TFE_CollectiveOpsCheckPeerHealth(
    TFE_Context* ctx, const char* task, int64_t timeout_in_ms,
    TF_Status* status);

// Information about the shape of a Tensor and its type.
struct TF_ShapeAndType {
  // Number of dimensions. -1 indicates unknown rank.
  int num_dims;
  // Array of dimensions. -1 indicates unknown dim.
  int64_t* dims;
  // The data type. May be 0 to denote unknown type.
  TF_DataType dtype;
};