parameters: (self)
return_statement: return outputs
docstring: Checks iterator stop condition, gets DALI outputs and perform reset in case of StopIteration
docstring_summary: Checks iterator stop condition, gets DALI outputs and perform reset in case of StopIteration
docstring_tokens: Checks iterator stop condition gets DALI outputs and perform reset in case of StopIteration
function: def _get_outputs(self):
          """
          Checks iterator stop condition, gets DALI outputs and perform reset in case of StopIteration
          """
          # if pipeline was not scheduled ever do it here
          if not self._ever_scheduled:
              self._schedule_runs(False)
          if self._size > 0 and self._counter >= self._size:
              self._end_iteration()
  
          outputs = []
          try:
              for p in self._pipes:
                  with p._check_api_type_scope(types.PipelineAPIType.ITERATOR):
                      outputs.append(p.share_outputs())
          except StopIteration as e:
              # in case ExternalSource returns StopIteration
              if self._size < 0 and self._auto_reset:
                  self.reset()
              raise e
          self._check_batch_size(outputs)
          return outputs
function_tokens: def _get_outputs ( self ) : # if pipeline was not scheduled ever do it here if not self . _ever_scheduled : self . _schedule_runs ( False ) if self . _size > 0 and self . _counter >= self . _size : self . _end_iteration ( ) outputs = [ ] try : for p in self . _pipes : with p . _check_api_type_scope ( types . PipelineAPIType . ITERATOR ) : outputs . append ( p . share_outputs ( ) ) except StopIteration as e : # in case ExternalSource returns StopIteration if self . _size < 0 and self . _auto_reset : self . reset ( ) raise e self . _check_batch_size ( outputs ) return outputs