code: def random_attention_mask(shape, rng=None):
      attn_mask = ids_tensor(shape, vocab_size=2, rng=rng)
      # make sure that at least one token is attended to for each batch
      attn_mask[:, -1] = 1
      return attn_mask
  
imports: import copy
  import inspect
  import json
  import random
  import tempfile
  import unittest
  from typing import List, Tuple
  import numpy
  import transformers
  from huggingface_hub import HfFolder, delete_repo, set_access_token
  from requests.exceptions import HTTPError
  from transformers import BertConfig, is_flax_available, is_torch_available
  from transformers.models.auto import get_values
  from transformers.testing_utils import TOKEN, USER, CaptureLogger, is_pt_flax_cross_test, is_staging_test, require_flax, torch_device
  from transformers.utils import logging
  from transformers.utils.generic import ModelOutput
label_desc: Use image node_id 4 for calling a global function with example usage: random_attention_mask(shape, rng) and returns: attn_mask