code: def _feature_config(shape, dtype):
      if dtype in ("int32", "bool"):
          # int32 and bool are stored as int64 in the tf.train.Example protobuf.
          dtype = "int64"
      if shape and shape[0] is None:
          return tf.io.FixedLenSequenceFeature(
              shape[1:], dtype, allow_missing=True
          )
      return tf.io.FixedLenFeature(shape, dtype)
  
file_path: NeMo/scripts/nlp_language_modeling/t0/t0_dataset_preproc.py
imports: import json
  import os
  import re
  from argparse import ArgumentParser
  from multiprocessing import Pool
  import tensorflow
  from sacremoses import MosesDetokenizer
  from tasks_splits_and_features import _TASK_SPLITS_AND_FEATURES_DICT
label_desc: Use image node_id 1 for calling a global function with example usage: _feature_config(shape, dtype) and returns: tf, tf