code: def generate_random_dataset(
      T_range_min, T_range_max, B=1, D=80, dataset_size=100
  ):
      """Generate random dataset with T values within a given range, B, D"""
      T_values = [
          random.randint(T_range_min, T_range_max)
          for i in range(dataset_size)
      ]
      dataset = []
      for t in T_values:
          dataset.append(generate_random_data_sample(t, B, D))
      return dataset, sum(T_values) / dataset_size
  
imports: from fairseq import tasks
  import numpy
  import logging
  import random
  from fairseq import options
  import torch
  import os
  import soundfile
  from fairseq.data.audio.audio_utils import get_waveform, parse_path
label_desc: Use image node_id 2 for calling a global function with example usage: generate_random_dataset(T_range_min, T_range_max, B, D, dataset_size) and returns: dataset,  unknown