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];
    }

                   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));
}

                                 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];

	"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)

				schema.err = fmt.Errorf("failed to parse %s as default value for bool, got error: %v", field.DefaultValue, err)
			}
		}
	case reflect.Int, reflect.Int8, reflect.Int16, reflect.Int32, reflect.Int64:
		field.DataType = Int
		if field.HasDefaultValue && !skipParseDefaultValue {
			if field.DefaultValueInterface, err = strconv.ParseInt(field.DefaultValue, 0, 64); err != nil {

	switch fieldValue.(type) {
	case int, int8, int16, int32, int64:
		result = time.Unix(rv.Int(), 0).UTC()
	case uint, uint8, uint16, uint32, uint64:
		if uv := rv.Uint(); uv > math.MaxInt64 {
			err = fmt.Errorf("integer overflow conversion uint64(%d) -> int64", uv)
		} else {
			result = time.Unix(int64(uv), 0).UTC() //nolint:gosec
		}
	case *int, *int8, *int16, *int32, *int64:
		if rv.IsZero() {
			return nil, nil
		}

type Eq struct {
	Column interface{}
	Value  interface{}
}

func (eq Eq) Build(builder Builder) {
	builder.WriteQuoted(eq.Column)

	switch eq.Value.(type) {
	case []string, []int, []int32, []int64, []uint, []uint32, []uint64, []interface{}:
		rv := reflect.ValueOf(eq.Value)
		if rv.Len() == 0 {
			builder.WriteString(" IN (NULL)")
		} else {
			builder.WriteString(" IN (")

	case string:
		return v
	case int:
		return strconv.FormatInt(int64(v), 10)
	case int8:
		return strconv.FormatInt(int64(v), 10)
	case int16:
		return strconv.FormatInt(int64(v), 10)
	case int32:
		return strconv.FormatInt(int64(v), 10)
	case int64:
		return strconv.FormatInt(v, 10)
	case uint:
		return strconv.FormatUint(uint64(v), 10)
	case uint8:
		return strconv.FormatUint(uint64(v), 10)