return nullptr;
  }
  return tensor;
}

// Deleter for DLManagedTensor
void DLManagedTensorDeleter(DLManagedTensor* arg) {
  TfDlManagedTensorCtx* owner =
      static_cast<TfDlManagedTensorCtx*>(arg->manager_ctx);
  owner->reference.Unref();
  delete owner;
}

// Converts TF_DATAType to DLPack data type.
DLDataType GetDlDataType(TF_DataType data_type, TF_Status* status) {
  DLDataType dtype;
  dtype.lanes = 1;

    operation_name_ = operation_name;
    step_id_ = step_id;
    op_inputs_ = inputs;
    attributes_ = attributes;
    expected_max_outputs_ = expected_max_outputs;
    cancellation_manager_ = &cancellation_manager;
    execution_state_ = ExecutionState::kReadyToExecute;
  }
  start_execute_.notify_one();
}

std::vector<TensorHandlePtr> DeviceThread::Join(TF_Status* status) {

    TFE_CancellationManager* cancellation_manager) {
  tensorflow::unwrap(cancellation_manager)->StartCancel();
}

bool TFE_CancellationManagerIsCancelled(
    TFE_CancellationManager* cancellation_manager) {
  return tensorflow::unwrap(cancellation_manager)->IsCancelled();
}

bool TFE_CancellationManagerIsCancelling(
    TFE_CancellationManager* cancellation_manager) {

  CancellationManager cancellation_manager;
  parallel_device.StartExecute(context.get(), std::vector<ParallelTensor*>(),
                               "VarHandleOp", TFE_OpGetAttrs(handle_op.get()),
                               /*expected_max_outputs=*/1,
                               cancellation_manager);
  auto outputs = parallel_device.Join(

  tensorflow::PluginResource* cc_resource_ptr = new tensorflow::PluginResource(
      plugin_resource, plugin_resource_name, delete_func);
  auto cc_status =
      cc_ctx->resource_manager()->Create<tensorflow::PluginResource>(
          container_name, plugin_resource_name, cc_resource_ptr);
  status->status = cc_status;
}

void TF_LookupOrCreatePluginResource(

               const GradientRegistry& registry) {
  TF_RETURN_IF_ERROR(op_->Execute(retvals, num_retvals));
  for (int i = 0; i < *num_retvals; i++) {
    // TODO(srbs): Manage refcount of ForwardOperation's inputs/outputs.
    forward_op_->outputs.push_back(retvals[i]);
  }
  // TODO(b/166669239): This is needed to support AttrBuilder::Get for string

#include "tensorflow/core/protobuf/error_codes.pb.h"
#include "tensorflow/core/public/version.h"

#if !defined(IS_MOBILE_PLATFORM)
#include "tensorflow/core/common_runtime/eager/context_distributed_manager.h"
#endif  // !IS_MOBILE_PLATFORM

using tensorflow::string;

namespace {

string DeviceName(const tensorflow::Device* d) {
  return (d == nullptr) ? "cpu:0" : d->name();
}

  // to build a graph operation.
  string op_type_;
  const char* op_name_ = nullptr;
  // TODO(srbs): Use this.
  string device_name_;
};

// GraphContext wraps a TF_Graph modeling a single function and manages the
// "execution" of operation, i.e. adding them to the function.
class GraphContext : public TracingContext {
 public:
  explicit GraphContext(const char* name)
      : TracingContext(kGraph),

                              int* num_retvals) {
  TF_RETURN_IF_ERROR(parent_op_->Execute(retvals, num_retvals));
  for (int i = 0; i < *num_retvals; i++) {
    // TODO(srbs): Manage refcount of ForwardOperation's inputs/outputs.
    forward_op_.outputs.push_back(retvals[i]);
  }
  // TODO(b/166669239): This is needed to support AttrBuilder::Get for string