code: def local_to_global(self, x, model_factor, data_proc_params):
      assert (
          model_factor >= 1
      )  # Should never be < 0, this would mean, that the network increases the size
      x *= model_factor
      # reverse
      for processor in self.processors:
          x = processor.local_to_global_pos(x, data_proc_params)
      return x
  
imports: from tfaip.data.pipeline.processor.dataprocessor import SequenceProcessor
  from tfaip.data.pipeline.processor.pipeline import DataProcessorPipeline
  from calamari_ocr.ocr.dataset.imageprocessors.data_preprocessor import ImageProcessor
label_desc: Use image node_id 2 for calling the OutputToInputTransformer obj's underlying member method code with example usage: obj.local_to_global(x, model_factor, data_proc_params) and returns: x