code: def tokens_to_batches(
      dataset,
      sequence_length,
      batch_size,
      output_features,
      mixture_or_task=None,
  ):
      """Convert a dataset of token sequences to batches of padded/masked examples.
  
      Args:
        dataset: tf.data.Dataset containing examples with token sequences.
        sequence_length: dict of int, a dict mapping feature name to length.
        batch_size: int, the number of padded sequences in each batch.
        output_features: list of str, features to include in the dataset.
        mixture_or_task: a Task or Mixture object, used to correctly specify eos if
          provided. If none, eos is always added at the end of the sequence.
  
      Returns:
        A generator that produces batches of numpy examples.
      """
  
      if mixture_or_task:
          eos_keys = set(
              k
              for k, f in mixture_or_task.output_features.items()
              if f.add_eos
          )
      else:
          eos_keys = True
  
      dataset = transformer_dataset.pack_or_pad(
          dataset,
          sequence_length,
          pack=False,
          feature_keys=output_features,
          ensure_eos=eos_keys,
      )
  
      def _map_fn(ex):
          for key in output_features:
              tensor = ex[key]
              mask = tf.cast(tf.greater(tensor, 0), tensor.dtype)
              ex[key + "_mask"] = mask
          return ex
  
      dataset = dataset.map(
          _map_fn,
          num_parallel_calls=tf.data.experimental.AUTOTUNE,
      )
  
      dataset = dataset.batch(batch_size, drop_remainder=False)
      return tfds.as_numpy(dataset)
  
imports: import functools
  import itertools
  import os
  import re
  import time
  from absl import logging
  import mesh_tensorflow.transformer.dataset
  import seqio
  import t5.data
  from t5.models import utils
  from t5.models.t5_model import T5Model
  import tensorflow.compat.v1
  import tensorflow_datasets
  import torch
  import torch.utils.tensorboard
label_desc: Use image node_id 1 for calling a global function with example usage: tokens_to_batches(dataset, sequence_length, batch_size, output_features, mixture_or_task) and returns: tfds, ex