<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def _attempt_slice_recovery(self, shard_state, tstate):
 """Recover a slice. This is run when a slice had been previously attempted and output may have been written. If an output writer requires slice recovery, we run those logic to remove output duplicates. Otherwise we just retry the slice. If recovery is needed, then the entire slice will be dedicated to recovery logic. No data processing will take place. Thus we call the slice "recovery slice". This is needed for correctness: An output writer instance can be out of sync from its physical medium only when the slice dies after acquring the shard lock but before committing shard state to db. The worst failure case is when shard state failed to commit after the NAMED task for the next slice was added. Thus, recovery slice has a special logic to increment current slice_id n to n+2. If the task for n+1 had been added, it will be dropped because it is behind shard state. Args: shard_state: an instance of Model.ShardState. tstate: an instance of Model.TransientShardState. Returns: _TASK_DIRECTIVE.PROCEED_TASK to continue with this retry. _TASK_DIRECTIVE.RECOVER_SLICE to recover this slice. The next slice will start at the same input as this slice but output to a new instance of output writer. Combining outputs from all writer instances is up to implementation. """

    mapper_spec = tstate.mapreduce_spec.mapper
    if not (tstate.output_writer and
            tstate.output_writer._supports_slice_recovery(mapper_spec)):
      return self._TASK_DIRECTIVE.PROCEED_TASK

    tstate.output_writer = tstate.output_writer._recover(
        tstate.mapreduce_spec, shard_state.shard_number,
        shard_state.retries + 1)
    return self._TASK_DIRECTIVE.RECOVER_SLICE