tensorflow::condition_variable finished_execute_;
  // Notifies a StartExecute that the previous Join has finished.
  tensorflow::condition_variable finished_join_;

  // Temporary state between `StartExecute` and `Join`.
  //
  //   Inputs; pointers are to objects not owned by the DeviceThread, but which
  //   are expected to live at least until `Join` finishes:
  TFE_Context* context_ TF_GUARDED_BY(execution_mutex_);

  // A non-blocking version of `Execute`. After each call, `Join` must be called
  // before `StartExecute` is called again. Using `StartExecute` with `Join`
  // allows the caller to schedule computation on multiple ParallelDevices
  // without sequencing those operations (first call `StartExecute` on each
  // parallel device, then call `Join` on each; even if some of the `Join`s

        tests_failed = False
      else:
        tests_failed = re.search(TESTS_FAILED_RE, backtrack_line)
      if build_failed or tests_failed:
        log_fragment = '\n'.join(
            log_lines[max(k - 20, 0):min(end_line + 1, len(log_lines) - 1)])
        lines['log_fragment'] = log_fragment
        lines['status'] = (InvokeStatus.build_failed if build_failed

                               "VarHandleOp", TFE_OpGetAttrs(handle_op.get()),
                               /*expected_max_outputs=*/1,
                               cancellation_manager);
  auto outputs = parallel_device.Join(
      /*expected_output_shapes=*/{PartialTensorShape({})}, status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  const std::vector<std::unique_ptr<ParallelTensor>>& handles = *outputs;