code: def test_with_tf_tensors(synthetic_dataset):
      fields_to_read = ["id.*", "image_png"]
      readers = [
          make_reader(
              synthetic_dataset.url,
              schema_fields=fields_to_read,
              workers_count=1,
          ),
          make_reader(
              synthetic_dataset.url,
              schema_fields=fields_to_read,
              workers_count=1,
          ),
      ]
  
      with WeightedSamplingReader(readers, [0.5, 0.5]) as mixer:
          mixed_tensors = tf_tensors(mixer)
  
          with tf.Session() as sess:
              sess.run(mixed_tensors)
  
imports: from __future__ import division
  import numpy
  import pytest
  import six
  import tensorflow.compat.v1
  from petastorm import make_reader
  from petastorm.ngram import NGram
  from petastorm.predicates import in_lambda
  from petastorm.pytorch import DataLoader
  from petastorm.test_util.reader_mock import ReaderMock
  from petastorm.tf_utils import tf_tensors, make_petastorm_dataset
  from petastorm.unischema import Unischema, UnischemaField
  from petastorm.weighted_sampling_reader import WeightedSamplingReader
  from petastorm.tests.test_tf_utils import create_tf_graph
label_desc: Use image node_id 7 for calling a global function with example usage: test_with_tf_tensors(synthetic_dataset) without return types