code: def _get_sequence_logits_and_labels(num_tokens, vocab_size):
      sequence_logits = []
      for _ in range(num_tokens):
          token_logits = np.random.random(vocab_size)
          token_logits /= token_logits.sum()
          sequence_logits.append(token_logits)
      sequence_labels = np.random.choice(vocab_size, num_tokens)
      return np.array(sequence_logits, dtype=np.float32), np.array(
          sequence_labels, dtype=np.float32
      )
  
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 2 for calling a global function with example usage: _get_sequence_logits_and_labels(num_tokens, vocab_size) and returns: np,  np