// TFE_NewTensorHandleFromDeviceMemory.
void DeallocatorWrapperFunc(void* data, size_t len, void* dlmt_vptr) {
  TFE_CallDLManagedTensorDeleter(dlmt_vptr);
}

// Checks whether the stride array matches the layout of compact, row-majored
// data.
bool IsValidStrideCompactRowMajorData(int64_t* shape_arr, int64_t* stride_arr,
                                      int ndim) {
  bool valid = true;

  delete shape_list;
}

void TF_DeleteShapeAndTypeListArray(TF_ShapeAndTypeList** shape_list_array,
                                    int num_items) {
  if (shape_list_array == nullptr) return;
  for (int i = 0; i < num_items; ++i) {
    TF_DeleteShapeAndTypeList(shape_list_array[i]);
  }
  delete[] shape_list_array;
}

namespace tensorflow {
Status TF_TensorToTensor(const TF_Tensor* src, Tensor* dst);

    // Try to extract the wrong number of components from a parallel tensor
    std::array<TFE_TensorHandle*, 1> correct_components{value_one.get()};
    TensorHandlePtr combined_value = CreatePerDeviceValues(
        context.get(), correct_components, device_name, status.get());
    ASSERT_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());

    std::array<TensorHandlePtr, 2> incorrect_components;

limitations under the License.
==============================================================================*/

#include "tensorflow/c/eager/parallel_device/parallel_device_testlib.h"

#include <array>

#include "tensorflow/c/c_api.h"
#include "tensorflow/c/c_api_experimental.h"
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/core/platform/test.h"

#include "tensorflow/c/experimental/gradients/math_grad.h"

#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/gradients.h"
#include "tensorflow/c/experimental/ops/array_ops.h"
#include "tensorflow/c/experimental/ops/math_ops.h"
#include "tensorflow/c/experimental/ops/nn_ops.h"

using std::vector;
using tensorflow::ops::AddV2;
using tensorflow::ops::Div;

  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  TF_Tensor* result_tensor = TFE_TensorHandleResolve(result_t, status.get());

  // Copy Tensor data into an array.
  float result_data[4] = {0};
  memcpy(&result_data[0], TF_TensorData(result_tensor),
         TF_TensorByteSize(result_tensor));

  int data_len = 4;  // length of result_data
  for (int i = 0; i < data_len; i++) {