code: def __init__(
      self,
      predictor: Predictor,
      input_file: str,
      output_file: Optional[str],
      batch_size: int,
      print_to_console: bool,
      has_dataset_reader: bool,
      multitask_head: Optional[str] = None,
  ) -> None:
      self._predictor = predictor
      self._input_file = input_file
      self._output_file = (
          None if output_file is None else open(output_file, "w")
      )
      self._batch_size = batch_size
      self._print_to_console = print_to_console
      self._dataset_reader = (
          None if not has_dataset_reader else predictor._dataset_reader
      )
      self._multitask_head = multitask_head
      if self._multitask_head is not None:
          if self._dataset_reader is None:
              raise ConfigurationError(
                  "You must use a dataset reader when using --multitask-head."
              )
          if not isinstance(
              self._dataset_reader, MultiTaskDatasetReader
          ):
              raise ConfigurationError(
                  "--multitask-head only works with a multitask dataset reader."
              )
      if (
          isinstance(self._dataset_reader, MultiTaskDatasetReader)
          and self._multitask_head is None
      ):
          raise ConfigurationError(
              "You must specify --multitask-head when using a multitask dataset reader."
          )
  
imports: from typing import List, Iterator, Optional
  import argparse
  import sys
  import json
  from allennlp.commands.subcommand import Subcommand
  from allennlp.common import logging
  from allennlp.common.checks import check_for_gpu, ConfigurationError
  from allennlp.common.file_utils import cached_path, open_compressed
  from allennlp.common.util import lazy_groups_of
  from allennlp.data.dataset_readers import MultiTaskDatasetReader
  from allennlp.models.archival import load_archive
  from allennlp.predictors.predictor import Predictor, JsonDict
  from allennlp.data import Instance
label_desc: Use image node_id 1 to create a new _PredictManager object  with example: obj = _PredictManager(predictor, input_file, output_file, batch_size, print_to_console, has_dataset_reader, multitask_head)