code: def _tf_tensors_ngram(
      reader, shuffling_queue_capacity, min_after_dequeue
  ):
      """A tensorflow data adapter for ngrams. Return value is a named tuple with tensorflow tensors supplying
      the data directly into a Tensoflow graph. See `tf_tensor` documentation for input/output arguments meaning.
      """
  
      fields_as_list = tf.py_func(
          lambda _: _sanitize_and_flatten(next(reader)),
          [tf.constant(1)],
          _schema_to_tf_dtypes_ngram(reader.schema, reader.ngram),
      )
  
      if shuffling_queue_capacity > 0:
          # Pass py_func output via shuffling queue if requested.
          fields_as_list = _shuffling_queue(
              shuffling_queue_capacity,
              min_after_dequeue,
              _schema_to_tf_dtypes_ngram(reader.schema, reader.ngram),
              fields_as_list,
          )
  
      return _unflatten_and_set_shape(
          reader.schema, reader.ngram, fields_as_list
      )
  
imports: import datetime
  import sys
  import warnings
  from calendar import timegm
  from collections import OrderedDict, namedtuple
  from decimal import Decimal
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 11 for calling a global function with example usage: _tf_tensors_ngram(reader, shuffling_queue_capacity, min_after_dequeue) and returns: _unflatten_and_set_shape