*   Updates `sqlite3` to `3.44.0` to keep in sync with master branch.

# Release 2.4.0

\## Major Features and Improvements

*   `tf.distribute` introduces experimental support for asynchronous training of
    models via the
    [`tf.distribute.experimental.ParameterServerStrategy`](https://www.tensorflow.org/api_docs/python/tf/distribute/experimental/ParameterServerStrategy)
    API. Please see the

  // re-use a thread.
  std::vector<std::unique_ptr<DeviceThread>> device_threads_;
  // A cancellation manager to use if the caller does not provide one. When ops
  // are executed asynchronously this must outlive the queued op, so it can't be
  // function-local to Execute.
  mutable std::unique_ptr<CancellationManager> default_cancellation_manager_;
};

  ExpectScalarEq<float>(result_components[1].get(), 3.);
}

TEST(PARALLEL_DEVICE, TestCollectiveSync) { TestCollective(/*async=*/false); }

// Note that ops on the parallel device currently don't execute
// asynchronously. The test is just that we don't get deadlocks.
TEST(PARALLEL_DEVICE, TestCollectiveAsync) { TestCollective(/*async=*/true); }

void RegisterCollectiveMulFunction(TFE_Context* context,