code: def load_watch():
      """
      Loads some of the 6-axis inertial sensor data from my smartwatch project. The sensor data was
      recorded as study subjects performed sets of 20 shoulder exercise repetitions while wearing a
      smartwatch. It is a multivariate time series.
  
      The study can be found here: https://arxiv.org/abs/1802.01489
  
      Returns
      -------
      data : dict
          data['X'] : list, length 140
              | inertial sensor data, each element with shape [n_samples, 6]
              | sampled at 50 Hz
          data['y'] : array, length 140
              target vector (exercise type)
          data['side'] : array, length 140
              the extremity side, 1 = right, 0 = left
          data['subject'] : array, length 140
              the subject (participant) number
          data['X_labels'] : str list, length 6
              ordered labels for the sensor data variables
          data['y_labels'] :str list, length 7
              ordered labels for the target (exercise type)
  
      Examples
      --------
      >>> from seglearn.datasets import load_watch
      >>> data = load_watch()
      >>> print(data.keys())
      """
      module_path = dirname(__file__)
      data = np.load(
          module_path + "/data/watch_dataset.npy", allow_pickle=True
      ).item()
      return data
  
label_desc: Use image node_id 1 for calling a global function with example usage: load_watch() and returns: data