class_docstr: Wrapper Class to run Inference.
  
  Args:
      opt: inference options
class_docstr_tok: ["Wrapper","Class","to","run","Inference",".","Args",":","opt",":","inference","options"]
docstr: The inference in mulitprocessing with partitioned models.
docstr_tok: ["The","inference","in","mulitprocessing","with","partitioned","models","."]
code: def infer_list_parallel(self, src):
      """The inference in mulitprocessing with partitioned models."""
      raise NotImplementedError(
          "The inference in mulitprocessing with partitioned models is not implemented."
      )
  
imports: import json
  from onmt.constants import CorpusTask, DefaultTokens, ModelTask
  from onmt.inputters.dynamic_iterator import build_dynamic_dataset_iter
  from onmt.utils.distributed import ErrorHandler, spawned_infer
  from onmt.utils.logging import init_logger
  from onmt.transforms import get_transforms_cls, make_transforms, TransformPipe
label_desc: Use image node_id 7 for calling the InferenceEngine obj's underlying member method code with example usage: obj.infer_list_parallel(src) without return types