code: def _get_batch_logits_and_labels(
      num_sequences, max_tokens_in_sequence, vocab_size
  ):
      num_tokens_in_sequence = (
          np.random.choice(max_tokens_in_sequence, num_sequences) + 1
      )
      batch_logits, batch_labels = [], []
      for num_tokens in num_tokens_in_sequence:
          logits, labels = _get_sequence_logits_and_labels(
              num_tokens, vocab_size
          )
          batch_logits.append(logits)
          batch_labels.append(labels)
      return np.array(batch_logits, dtype=object), np.array(
          batch_labels, dtype=object
      )
  
file_path: privacy/tensorflow_privacy/privacy/privacy_tests/membership_inference_attack/seq2seq_mia_test.py
imports: from absl.testing import absltest
  import numpy
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack.data_structures import AttackType
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack.seq2seq_mia import run_seq2seq_attack
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack.seq2seq_mia import Seq2SeqAttackInputData
label_desc: Use image node_id 1 for calling a global function with example usage: _get_batch_logits_and_labels(num_sequences, max_tokens_in_sequence, vocab_size) and returns: np,  np