typedef enum TF_DataType {
  TF_FLOAT = 1,
  TF_DOUBLE = 2,
  TF_INT32 = 3,  // Int32 tensors are always in 'host' memory.
  TF_UINT8 = 4,
  TF_INT16 = 5,
  TF_INT8 = 6,
  TF_STRING = 7,
  TF_COMPLEX64 = 8,  // Single-precision complex
  TF_COMPLEX = 8,    // Old identifier kept for API backwards compatibility
  TF_INT64 = 9,
  TF_BOOL = 10,
  TF_QINT8 = 11,     // Quantized int8

// TF_Tensor holds a multi-dimensional array of elements of a single data type.
// For all types other than TF_STRING, the data buffer stores elements
// in row major order.  E.g. if data is treated as a vector of TF_DataType:
//
//   element 0:   index (0, ..., 0)
//   element 1:   index (0, ..., 1)
//   ...
//
// The format for TF_STRING tensors is:
//   start_offset: array[uint64]
//   data:         byte[...]
//

                        void* deallocator_arg) {
  TF_ManagedBuffer* buf = nullptr;
  if (dtype != TF_STRING && dtype != TF_RESOURCE &&
      tensorflow::DataTypeCanUseMemcpy(
          static_cast<tensorflow::DataType>(dtype)) &&
      reinterpret_cast<intptr_t>(data) % std::max(1, EIGEN_MAX_ALIGN_BYTES) !=
          0) {
    // TF_STRING and TF_RESOURCE tensors have a different representation in

  EXPECT_EQ(TF_UINT8, static_cast<TF_DataType>(tensorflow::DT_UINT8));
  EXPECT_EQ(TF_INT16, static_cast<TF_DataType>(tensorflow::DT_INT16));
  EXPECT_EQ(TF_INT8, static_cast<TF_DataType>(tensorflow::DT_INT8));
  EXPECT_EQ(TF_STRING, static_cast<TF_DataType>(tensorflow::DT_STRING));
  EXPECT_EQ(TF_COMPLEX64, static_cast<TF_DataType>(tensorflow::DT_COMPLEX64));
  EXPECT_EQ(TF_COMPLEX, TF_COMPLEX64);

}

TFE_TensorHandle* TestScalarTensorHandle(TFE_Context* ctx,
                                         const tensorflow::tstring& value) {
  TF_Status* status = TF_NewStatus();
  TF_Tensor* t = TFE_AllocateHostTensor(ctx, TF_STRING, nullptr, 0, status);
  tstring* data = static_cast<tstring*>(TF_TensorData(t));
  *data = value;
  TFE_TensorHandle* th = TFE_NewTensorHandleFromTensor(ctx, t, status);