code: def floats_list(shape, scale=1.0, rng=None, name=None):
      """Creates a random float32 tensor"""
      if rng is None:
          rng = global_rng
  
      values = []
      for batch_idx in range(shape[0]):
          values.append([])
          for _ in range(shape[1]):
              values[-1].append(rng.random() * scale)
  
      return values
  
imports: import inspect
  import json
  import os
  import random
  import shutil
  import tempfile
  import unittest
  import numpy
  from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, Wav2Vec2Config, Wav2Vec2CTCTokenizer, Wav2Vec2Tokenizer
  from transformers.models.wav2vec2.tokenization_wav2vec2 import VOCAB_FILES_NAMES, Wav2Vec2CTCTokenizerOutput
  from transformers.testing_utils import require_torch, slow
  from ...test_tokenization_common import TokenizerTesterMixin
label_desc: Use image node_id 1 for calling a global function with example usage: floats_list(shape, scale, rng, name) and returns: values