code: def _get_batched_records(
      dataset, force_tf_compat_v1, max_num_examples=None
  ):
      """Returns a (batch_size, iterator for batched records) tuple for the dataset.
  
      Args:
        dataset: BenchmarkDataset object.
        force_tf_compat_v1: If False then Transform will use its native TF2 version,
          if True then Transform will use its TF1 version.
        max_num_examples: Maximum number of examples to read from the dataset.
  
      Returns:
        Tuple of (batch_size, iterator for batched records), where records are
        decoded tf.train.Examples.
      """
      batch_size = 1000
      common_variables = _get_common_variables(
          dataset, force_tf_compat_v1
      )
      converter = example_coder.ExamplesToRecordBatchDecoder(
          common_variables.transform_input_dataset_metadata.schema.SerializeToString()
      )
      serialized_records = benchmark_utils.batched_iterator(
          dataset.read_raw_dataset(
              deserialize=False, limit=max_num_examples
          ),
          batch_size,
      )
      records = [converter.DecodeBatch(x) for x in serialized_records]
      return batch_size, records
  
imports: import collections
  import shutil
  import tempfile
  import time
  from absl import logging
  import apache_beam
  from apache_beam.utils import shared
  import tensorflow
  import tensorflow_transform
  from tensorflow_transform import graph_tools
  from tensorflow_transform import impl_helper
  import tensorflow_transform.beam
  from tensorflow_transform.beam import impl
  from tensorflow_transform.saved import saved_transform_io
  from tensorflow_transform.saved import saved_transform_io_v2
  from tensorflow_transform.tf_metadata import dataset_metadata
  from tensorflow_transform.tf_metadata import schema_utils
  import tfx
  from tfx.benchmarks import benchmark_utils
  from tfx.benchmarks import benchmark_base
  from tfx_bsl.coders import example_coder
  from tfx_bsl.tfxio import tensor_adapter
  from tfx_bsl.tfxio import tf_example_record
label_desc: Use image node_id 3 for calling a global function with example usage: _get_batched_records(dataset, force_tf_compat_v1, max_num_examples) and returns: batch_size,  records