code: def run(self):
      has_reader = self._dataset_reader is not None
      if has_reader:
          for batch in lazy_groups_of(
              self._get_instance_data(), self._batch_size
          ):
              for result in self._predict_instances(batch):
                  self._maybe_print_to_console_and_file(result)
      else:
          for batch_json in lazy_groups_of(
              self._get_json_data(), self._batch_size
          ):
              for model_input, result in izip(
                  batch_json, self._predict_json(batch_json)
              ):
                  self._maybe_print_to_console_and_file(
                      result, json.dumps(model_input)
                  )
  
      if self._output_file is not None:
          self._output_file.close()
  
imports: from __future__ import absolute_import
  from __future__ import print_function
  import argparse
  import sys
  import json
  from allennlp.commands.subcommand import Subcommand
  from allennlp.common.checks import check_for_gpu, ConfigurationError
  from allennlp.common.util import lazy_groups_of
  from allennlp.models.archival import load_archive
  from allennlp.predictors.predictor import Predictor, JsonDict
  from allennlp.data import Instance
  from io import open
label_desc: Use image node_id 7 for calling the _PredictManager obj's underlying member method code with example usage: obj.run() without return types