{Name: "Name", DBName: "name", BindNames: []string{"Name"}, DataType: schema.String},
		{Name: "Age", DBName: "age", BindNames: []string{"Age"}, DataType: schema.Uint, Size: 64},
		{Name: "Birthday", DBName: "birthday", BindNames: []string{"Birthday"}, DataType: schema.Time},
		{Name: "CompanyID", DBName: "company_id", BindNames: []string{"CompanyID"}, DataType: schema.Int, Size: 64},

			field.DataType = Bytes
		}
	}

	if dataTyper, ok := fieldValue.Interface().(GormDataTypeInterface); ok {
		field.DataType = DataType(dataTyper.GormDataType())
	}

	if v, ok := field.TagSettings["AUTOCREATETIME"]; (ok && utils.CheckTruth(v)) || (!ok && field.Name == "CreatedAt" && (field.DataType == Time || field.DataType == Int || field.DataType == Uint)) {
		if field.DataType == Time {
			field.AutoCreateTime = UnixTime

func (c *StandardClaims) UnmarshalJSON(b []byte) (err error) {
	return jsonparser.ObjectEach(b, func(key []byte, value []byte, dataType jsonparser.ValueType, _ int) error {
		if len(key) == 0 {
			return nil
		}
		switch key[0] {
		case 'a':
			if string(key) == "accessKey" {
				if dataType != jsonparser.String {
					return errors.New("accessKey: Expected string")
				}

                                                       TF_Status* status) const;

  // Construct a parallel tensor consisting of the scalar values from `values`.
  template <typename DataType>
  std::unique_ptr<ParallelTensor> ScalarsFromSequence(
      absl::Span<const DataType> values, TFE_Context* context,
      TF_Status* status) const;

  // A parallel tensor with scalar integers numbering component devices.

				relation.FieldSchema, schema, field.Name)
			return
		}

		// use same data type for foreign keys
		if copyableDataType(primaryKeyField.DataType) {
			relation.Polymorphic.PolymorphicID.DataType = primaryKeyField.DataType
		}
		relation.Polymorphic.PolymorphicID.GORMDataType = primaryKeyField.GORMDataType
		if relation.Polymorphic.PolymorphicID.Size == 0 {

  handle_ = other.handle_;
  handle_->Ref();
}
TapeTensor::~TapeTensor() { handle_->Unref(); }

int64_t TapeTensor::GetID() const { return ToId(handle_); }

tensorflow::DataType TapeTensor::GetDType() const {
  return handle_->DataType();
}
AbstractTensorHandle* TapeTensor::GetHandle() const { return handle_; }

AbstractTensorHandle* TapeTensor::ZerosLike() const { return nullptr; }

class TapeVSpace

 public:
  explicit GraphTensor(TF_Output output, TF_Graph* graph)
      : TracingTensorHandle(kGraph), output_(output), graph_(graph) {}

  tensorflow::DataType DataType() const override {
    return static_cast<tensorflow::DataType>(TF_OperationOutputType(output_));
  }

  absl::Status Shape(tensorflow::PartialTensorShape* shape) const override {
    DCHECK(shape != nullptr);
    TF_Status status;

  virtual bool GetBool(absl::string_view attr_name, bool* result) const = 0;
  virtual bool GetType(absl::string_view attr_name, DataType* result) const = 0;
  virtual absl::Status GetTypeList(
      absl::string_view attr_name,
      absl::InlinedVector<DataType, 4>* type_list) const = 0;

 private:
  const AbstractOpAttrsKind kind_;
};

}  // namespace tensorflow

  explicit AbstractTensorHandle(AbstractTensorHandleKind kind) : kind_(kind) {}
  ~AbstractTensorHandle() override {}

 public:
  // Returns tensor dtype.
  virtual tensorflow::DataType DataType() const = 0;

  // Returns the status of the tensor handle. If it is a tfrt::TensorHandle,
  // the tensor handle can be an error and return non-OK status.
  virtual absl::Status TensorHandleStatus() const;

absl::Status SetAttrBool(AbstractOperation*, const char* attr_name, bool value,
                         ForwardOperation*);
absl::Status SetAttrType(AbstractOperation*, const char* attr_name,
                         DataType value, ForwardOperation*);
absl::Status SetAttrShape(AbstractOperation*, const char* attr_name,
                          const int64_t* dims, const int num_dims,
                          ForwardOperation*);