code: def tuple_to_trial(data, space, status="new"):
      """Create a `orion.core.worker.trial.Trial` object from `data`.
  
      Parameters
      ----------
      data: tuple
          A tuple representing a sample point from `space`.
      space: `orion.algo.space.Space`
          Definition of problem's domain.
      status: str, optional
          Status of the trial. One of ``orion.core.worker.trial.Trial.allowed_stati``.
  
      Returns
      -------
      A trial object `orion.core.worker.trial.Trial`.
      """
      if len(data) != len(space):
          raise ValueError(
              f"Data point is not compatible with search space:\ndata: {data}\nspace: {space}"
          )
  
      params = []
      for i, dim in enumerate(space.values()):
          params.append(
              dict(name=dim.name, type=dim.type, value=data[i])
          )
  
      return Trial(params=params, status=status)
  
imports: from orion.core.utils.flatten import flatten
  from orion.core.worker.trial import Trial
label_desc: Use image node_id 3 for calling a global function with example usage: tuple_to_trial(data, space, status) and returns: Trial