code: def batch_predict(model_file: str, examples: List[Dict[str, Any]]):
      task, train_config, _training_state = load(model_file)
      return task.predict(examples)
  
imports: import gzip
  import json
  import os
  import sys
  import traceback
  from typing import Any, Dict, get_type_hints, IO, Iterator, List, Optional, Tuple, Union
  import torch
  from pytext.common.constants import Stage
  from pytext.config import ExportConfig, PyTextConfig, TestConfig
  from pytext.config.component import ComponentType, create_component, create_exporter
  from pytext.data.data import Batcher
  from pytext.data.data_handler import CommonMetadata
  from pytext.metric_reporters.channel import Channel
  from pytext.task import create_task, get_latest_checkpoint_path, load, NewTask, save, Task_Deprecated
  from pytext.task.disjoint_multitask import NewDisjointMultitask
  from pytext.trainers import TrainingState
  from pytext.utils import cuda, distributed, precision, round_seq, set_random_seeds, timing
  from pytext.utils.file_io import PathManager
label_desc: Use image node_id 17 for calling a global function with example usage: batch_predict(model_file, examples) and returns: task