code: def _test_continuous_ngram_tf(
      ngram_fields, dataset_num_files_1, reader_factory
  ):
      """Tests continuous ngram in tf of a certain length. Continuous here refers to
      that this reader will always return consecutive ngrams due to shuffle being false
      and partition being 1.
      """
  
      ngram = NGram(
          fields=ngram_fields,
          delta_threshold=10,
          timestamp_field=TestSchema.id,
      )
      with reader_factory(
          dataset_num_files_1.url,
          schema_fields=ngram,
          shuffle_row_groups=False,
      ) as reader:
          readout_examples = tf_tensors(reader)
  
          # Make sure we have static shape info for all fields
          for timestep in readout_examples:
              for field in readout_examples[timestep]:
                  assert field.get_shape().dims is not None
  
          # Read a bunch of entries from the dataset and compare the data to reference
          expected_id = 0
          with tf.Session() as sess:
              for _ in range(5):
                  actual = sess.run(readout_examples)
                  expected_ngram = _get_named_tuple_from_ngram(
                      ngram, dataset_num_files_1.data, expected_id
                  )
                  _assert_equal_ngram(actual, expected_ngram)
                  expected_id = expected_id + 1
  
imports: from decimal import Decimal
  import numpy
  import pytest
  import tensorflow.compat.v1
  from unittest import mock
  from petastorm import make_reader
  from petastorm.ngram import NGram
  from petastorm.tests.conftest import SyntheticDataset, maybe_cached_dataset
  from petastorm.tests.test_common import create_test_dataset, TestSchema
  from petastorm.tests.test_tf_utils import create_tf_graph
  from petastorm.tf_utils import tf_tensors
label_desc: Use image node_id 6 for calling a global function with example usage: _test_continuous_ngram_tf(ngram_fields, dataset_num_files_1, reader_factory) without return types