const char* attr_name,
                                                    unsigned char* is_list,
                                                    TF_Status* status);
// Get an attribute type given an op name; a fusion of TFE_NewOp and
// TFE_OpGetAttrType for use from Python without the overhead of the individual
// calls and memory management of TFE_Op.

      : owned_executor(nullptr), unowned_executor(executor) {}

  tensorflow::EagerExecutor* executor() {
    return owned_executor == nullptr ? unowned_executor : owned_executor.get();
  }

  std::unique_ptr<tensorflow::EagerExecutor> owned_executor;
  tensorflow::EagerExecutor* unowned_executor;
};

  ///   * Might use any other error value for `status` to signal other errors.
  ///
  /// DEFAULT IMPLEMENTATION: Scans the directory tree (in parallel if possible)
  /// and fills `*entries`. Needs `get_children` and `is_directory`.
  int (*get_matching_paths)(const TF_Filesystem* filesystem, const char* glob,
                            char*** entries, TF_Status* status);

  /// Flushes any filesystem cache currently in memory
  ///

  virtual ImmediateExecutionTensorHandle* TFTensorHandleFromInterface(
      ImmediateExecutionTensorHandle* handle) = 0;

  virtual std::vector<std::string> GetLoggedOpsTestonly() { return {}; }

  // Get a list of the names of functions that have been registered.
  virtual std::vector<string> ListFunctionNames() = 0;

  struct CacheStats {
    int64_t kernel_cache_size;
    int64_t device_cache_size;

  TFE_Context* eager_ctx =
      TF_ExecutionContextGetTFEContext(wrap(ctx), status.get());
  TF_RETURN_IF_ERROR(StatusFromTF_Status(status.get()));
  TFE_TensorHandle* input_eager =
      TestTensorHandleWithDims<T, datatype>(eager_ctx, data, dims, num_dims);
  *tensor =
      unwrap(TF_CreateAbstractTensorFromEagerTensor(input_eager, status.get()));
  return absl::OkStatus();
}

// Return a scalar tensor handle with given value.