#include "tensorflow/core/framework/cpp_shape_inference.pb.h"
#include "tensorflow/core/framework/full_type.pb.h"
#include "tensorflow/core/framework/kernel_def.pb.h"
#include "tensorflow/core/framework/log_memory.h"
#include "tensorflow/core/framework/node_def_util.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/partial_tensor_shape.h"
#include "tensorflow/core/framework/shape_inference.h"

  {
    tensorflow::mutex_lock c(session->graph->mu);
    if (VLOG_IS_ON(1)) {
      VLOG(1) << "Enqueuing named tensor with id " << tensor_id
              << ", with input graph: "
              << session->graph->graph.ToGraphDefDebug().DebugString();
      tensorflow::Tensor internal_tensor;
      if (tensorflow::TF_TensorToTensor(tensor, &internal_tensor).ok()) {
        VLOG(1) << "Enqueu'ing tensor content: "

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

#include "absl/log/log.h"
#include "tensorflow/c/experimental/filesystem/filesystem_interface.h"
#include "tensorflow/c/experimental/filesystem/modular_filesystem_registration.h"

      attr_name, static_cast<const char*>(value), length);
  if (!s.ok()) {
    LOG(WARNING) << "Unable to set attribute: " << attr_name;
  }
}

void TFE_OpSetAttrInt(TFE_Op* op, const char* attr_name, int64_t value) {
  auto s = tensorflow::unwrap(op)->SetAttrInt(attr_name, value);
  if (!s.ok()) {
    LOG(WARNING) << "Unable to set attribute: " << attr_name;
  }
}

    const string dev_name(TF_DeviceListName(devices, i, status.get()));
    CHECK_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());
    if (dev_type == device_type) {
      *device_name = dev_name;
      LOG(INFO) << "Found " << device_type << " device " << *device_name;
      TF_DeleteDeviceList(devices);
      return true;
    }
  }
  TF_DeleteDeviceList(devices);
  return false;
}

                 absl::Span<AbstractTensorHandle*> grad_inputs) override {
    // TODO(vnvo2409): Add control dependency
    /* Given upstream grad U and a Log1p op: Y = log(1 + X), the gradients are:
     *
     *    dX = U / (1 + X)
     *
     */

    AbstractTensorHandle* upstream_grad = grad_outputs[0];
    AbstractTensorHandle* X = forward_inputs_[0];

  LOG(INFO) << "There are " << num_devices << " devices.";
  for (int i = 0; i < num_devices; ++i) {
    const char* device_name = TF_DeviceListName(device_list, i, s);
    CHECK_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
    const char* device_type = TF_DeviceListType(device_list, i, s);
    CHECK_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);