Model model, Model grad_model, AbstractContext* ctx,
    absl::Span<AbstractTensorHandle* const> inputs, bool use_function,
    double abs_error = 1e-2);

void CheckTensorValue(AbstractTensorHandle* t, absl::Span<const float> manuals,
                      absl::Span<const int64_t> dims, double abs_error = 1e-2);

Model BuildGradModel(Model forward, GradientRegistry registry);

}  // namespace internal
}  // namespace gradients

TFE_TensorHandle* TestScalarTensorHandle(TFE_Context* ctx,
                                         const tensorflow::tstring& value);

// Return a tensor handle containing a 2x2 matrix of doubles
TFE_TensorHandle* DoubleTestMatrixTensorHandle(TFE_Context* ctx);

// Return a tensor handle containing a 2x2 matrix of floats
TFE_TensorHandle* TestMatrixTensorHandle(TFE_Context* ctx);

// APIs for sampler buckets
typedef struct TFE_MonitoringBuckets TFE_MonitoringBuckets;
TF_CAPI_EXPORT extern TFE_MonitoringBuckets*
TFE_MonitoringNewExponentialBuckets(double scale, double growth_factor,
                                    int bucket_count);
TF_CAPI_EXPORT extern void TFE_MonitoringDeleteBuckets(
    TFE_MonitoringBuckets* buckets);

// APIs for Sampler without label.

};

// Template instantiations here

inline bool IsDtypeTrainable(DataType dtype) {
  switch (dtype) {
    case DT_HALF:
    case DT_BFLOAT16:
    case DT_FLOAT:
    case DT_DOUBLE:
    case DT_COMPLEX64:
    case DT_COMPLEX128:
    case DT_RESOURCE:
    case DT_VARIANT:
      return true;
    case DT_QINT8:
    case DT_QINT16:
    case DT_QINT32:
    case DT_QUINT8:

// Create 1 dimensional tensor with values from `values`
TF_Tensor* Int32Tensor(const std::vector<int32_t>& values);

TF_Tensor* Int32Tensor(int32_t v);

TF_Tensor* DoubleTensor(double v);

TF_Tensor* FloatTensor(float v);

TF_Operation* Placeholder(TF_Graph* graph, TF_Status* s,
                          const char* name = "feed",
                          TF_DataType dtype = TF_INT32,

  Status SetOption(const std::string& name,
                   const std::vector<int64_t>& values) override;
  Status SetOption(const std::string& name,
                   const std::vector<double>& values) override;

 private:
  std::unique_ptr<TF_Filesystem> filesystem_;
  std::unique_ptr<const TF_FilesystemOps> ops_;
  std::unique_ptr<const TF_RandomAccessFileOps> random_access_file_ops_;

  virtual AbstractTensorInterface* CreateInt32Scalar(int32_t value) = 0;
  virtual AbstractTensorInterface* CreateFloatScalar(float value) = 0;
  virtual AbstractTensorInterface* CreateDoubleScalar(double value) = 0;
  virtual AbstractTensorInterface* CreateHalfScalar(Eigen::half value) = 0;
  virtual AbstractTensorInterface* CreateStringScalar(tstring value) = 0;

// The named union is needed here (as opposed to
// inside the `TF_Filesystem_Option_Value` struct)
// as MSVC does not recognize `typeof`.
typedef union TF_Filesystem_Option_Value_Union {
  int64_t int_val;
  double real_val;
  struct {
    char* buf;
    int buf_length;
  } buffer_val;
} TF_Filesystem_Option_Value_Union;

typedef struct TF_Filesystem_Option_Value {
  int type_tag;    // type of values in the values union