code: def __init__(
      self,
      pipeline_params,
      data_base,
      generator_params,
      input_processors=None,
      output_processors=None,
  ):
      super(CalamariPipeline, self).__init__(
          pipeline_params,
          data_base,
          generator_params,
          input_processors,
          output_processors,
      )
      if generator_params and isinstance(
          generator_params, CalamariDataGeneratorParams
      ):
          generator_params.n_folds = data_base.params.ensemble
      self._reader = None
      self._output_processors.run_parallel = False  # TODO: parallel support, but currently in voter this makes one prediction per pipeline, mega slow
  
file_path: calamari/calamari_ocr/ocr/dataset/pipeline.py
imports: from typing import Iterable
  from tfaip.data.pipeline.datapipeline import DataPipeline, DataGenerator
  from tfaip.data.pipeline.definitions import Sample, PipelineMode
  from calamari_ocr.ocr.dataset.datareader.base import CalamariDataGeneratorParams
label_desc: Use image node_id 1 to create a new CalamariPipeline object from inherited base classes: DataPipeline with example: obj = CalamariPipeline(pipeline_params, data_base, generator_params, input_processors, output_processors)