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);

  ASSERT_TRUE(out != nullptr);
  EXPECT_EQ(TF_INT32, TF_TensorType(out));
  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(3 + 2, *output_contents);

  // Add another operation to the graph.
  TF_Operation* neg = Neg(add, graph, s);

template <typename... LabelType>
int64_t TFE_MonitoringCounterReader::Read(const LabelType&... labels) {
  return counter->Read(labels...);
}

TFE_MonitoringCounterReader* TFE_MonitoringNewCounterReader(const char* name) {
  auto* result = new TFE_MonitoringCounterReader(name);

  return result;
}

int64_t TFE_MonitoringReadCounter0(TFE_MonitoringCounterReader* cell_reader) {
  int64_t result = cell_reader->Read();

  TapeVSpace vspace(ctx);
  std::vector<int64_t> target_tensor_ids = MakeTensorIDList(targets);
  std::vector<int64_t> source_tensor_ids = MakeTensorIDList(sources);
  tensorflow::gtl::FlatSet<int64_t> sources_set(source_tensor_ids.begin(),
                                                source_tensor_ids.end());
  std::unordered_map<int64_t, TapeTensor> sources_that_are_targets;

    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_;

  return num_dims;
}

int64_t TFE_TensorHandleNumElements(TFE_TensorHandle* h, TF_Status* status) {
  if (h == nullptr) {
    status->status = tensorflow::errors::InvalidArgument("Invalid handle");
    return -1;
  }

  int64_t num_elements = -1;
  status->status = tensorflow::unwrap(h)->NumElements(&num_elements);
  return num_elements;
}

int64_t TFE_TensorHandleDim(TFE_TensorHandle* h, int dim_index,

TFE_MonitoringNewCounterReader(const char* name);

// Reads the value of a counter that was created with 0 labels.
TF_CAPI_EXPORT extern int64_t TFE_MonitoringReadCounter0(
    TFE_MonitoringCounterReader*);

// Reads the value of specific cell of a counter that was created with 1 label.
TF_CAPI_EXPORT extern int64_t TFE_MonitoringReadCounter1(
    TFE_MonitoringCounterReader*, const char* label_value);

#ifdef __cplusplus
} /* end extern "C" */

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

// Range: -128 through 127.
type int8 int8

// int16 is the set of all signed 16-bit integers.
// Range: -32768 through 32767.
type int16 int16

// int32 is the set of all signed 32-bit integers.
// Range: -2147483648 through 2147483647.
type int32 int32

// int64 is the set of all signed 64-bit integers.
// Range: -9223372036854775808 through 9223372036854775807.
type int64 int64

	"testing"
	"time"
)

func TestUnixSecondSerializer_Value(t *testing.T) {
	var (
		intValue      = math.MaxInt64
		int8Value     = int8(math.MaxInt8)
		int16Value    = int16(math.MaxInt16)
		int32Value    = int32(math.MaxInt32)
		int64Value    = int64(math.MaxInt64)
		uintValue     = uint(math.MaxInt64)
		uint8Value    = uint8(math.MaxUint8)
		uint16Value   = uint16(math.MaxUint16)
		uint32Value   = uint32(math.MaxUint32)