#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/partial_tensor_shape.h"
#include "tensorflow/core/framework/shape_inference.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/tensor.pb.h"  // NOLINT
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/tensor_shape.pb.h"
#include "tensorflow/core/framework/types.h"

    num_elements *= shape[i];
  }
  std::vector<float> data(num_elements);
  for (size_t j = 0; j < num_elements; ++j) {
    data[j] = j;
  }
  DLManagedTensor dlm_in = {};
  DLTensor* dltensor_in = &dlm_in.dl_tensor;
  dltensor_in->data = data.data();
  dltensor_in->device = {kDLCPU, 0};
  dltensor_in->ndim = static_cast<int32_t>(shape.size());
  dltensor_in->dtype = {kDLFloat, 32, 1};
  dltensor_in->shape = shape.data();

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

#include "absl/types/span.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/immediate_execution_context.h"
#include "tensorflow/c/eager/immediate_execution_tensor_handle.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"

}
TF_AbstractTensor* TF_OutputListGet(TF_OutputList* o, int i) {
  return wrap(unwrap(o)->outputs[i]);
}
void TF_OutputListPushBack(TF_OutputList* o, TF_AbstractTensor* tensor,
                           TF_Status* s) {
  unwrap(o)->outputs.push_back(unwrap(tensor));
}

void TF_AbstractOpSetOpType(TF_AbstractOp* op, const char* const op_type,
                            TF_Status* s) {
  tsl::Set_TF_Status_from_Status(

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

#include "tensorflow/c/eager/abstract_tensor_handle.h"

namespace tensorflow {

std::string AbstractTensorHandle::DebugString() const {
  PartialTensorShape shape;
  Status s = Shape(&shape);
  std::string shape_string;
  if (!s.ok()) {

  tensorflow::AsyncValueTensor* av_tensor =
      tensorflow::AsyncValueTensor::FromTensor(&tensor);
  av_tensor->SetBuffer(std::move(buffer));

  TF_ASSERT_OK_AND_ASSIGN(auto c_buffer, GetPjRtCBufferFromTensor(&tensor));

  EXPECT_THAT(c_buffer, NotNull());
}

TEST(TensorPjRtBufferUtilTest, SetPjRtCBufferToTensorNotAsyncValueTensor) {
  tensorflow::Tensor tensor(DT_FLOAT, {1});

  // Convert from AbstractTensor to TF_Tensor.
  TF_Tensor* theta_tensor;
  TF_RETURN_IF_ERROR(GetValue(theta, &theta_tensor));

  // Get number of elements and fill data.
  int num_elems = TF_TensorElementCount(theta_tensor);
  vector<float> theta_data(num_elems);
  memcpy(theta_data.data(), TF_TensorData(theta_tensor),
         TF_TensorByteSize(theta_tensor));

  // Initialize space for the numerical gradient.

};

struct LoggedTensor {
  TFE_TensorHandle* tensor;
  LoggedTensor() = delete;
  explicit LoggedTensor(TFE_TensorHandle* tensor) : tensor(tensor) {}
  ~LoggedTensor() { TFE_DeleteTensorHandle(tensor); }
};

int64_t LoggedTensorDim(void* data, int dim_index, TF_Status* status) {
  return TFE_TensorHandleDim(reinterpret_cast<LoggedTensor*>(data)->tensor,
                             dim_index, status);
}

    status->status = cc_status;
    return nullptr;
  }

  tensorflow::Tensor* tensor = var_info->var_info.var()->tensor();
  TF_Tensor* result_tensor =
      tensorflow::TF_TensorFromTensor(*tensor, &cc_status);
  status->status = cc_status;
  return result_tensor;
}

void TF_DeleteVariableInfo(TF_VariableInfo* var_info) {
  if (var_info != nullptr) {
    delete var_info;

  ParallelTensor* parallel_tensor = reinterpret_cast<ParallelTensor*>(
      TFE_TensorHandleDevicePointer(tensor, status));
  if (TF_GetCode(status) != TF_OK) return nullptr;
  if (parallel_tensor->num_tensors() == 1) {
    // Copy-off for single-device tensors is allowed to make debugging dynamic
    // control flow easier.
    return TFE_TensorHandleCopySharingTensor(parallel_tensor->tensor(0),