code: def get_question_samp(bsz, seq_len, vocab_size, seed):
      np.random.seed(seed)
      in_ids = np.random.randint(vocab_size, size=(bsz, seq_len))
      mask = np.random.choice([True, False], size=(bsz, seq_len))
      seg_ids = np.random.randint(1, size=(bsz, seq_len))
      return in_ids, mask, seg_ids
  
file_path: tinygrad/test/models/test_bert.py
imports: import unittest
  import numpy
  from tinygrad.tensor import Tensor
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: get_question_samp(bsz, seq_len, vocab_size, seed) and returns: in_ids,  mask,  seg_ids