class_docstr: Envelope Variance Channel Selection method with
  (optionally) learnable per mel-band weights.
code: def _get_chunks_indx(
      self, in_len, chunk_size, chunk_stride, discard_last=False
  ):
      i = -1
      for i in range(
          self._count_chunks(in_len, chunk_size, chunk_stride)
      ):
          yield i * chunk_stride, i * chunk_stride + chunk_size
      if not discard_last and i * chunk_stride + chunk_size < in_len:
          if in_len - (i + 1) * chunk_stride > 0:
              yield (i + 1) * chunk_stride, in_len
  
imports: import argparse
  import os
  from copy import deepcopy
  from pathlib import Path
  import lhotse
  import soundfile
  import torch
  import torchaudio
  import tqdm
  from torch.utils.data import DataLoader, Dataset
label_desc: Use image node_id 4 for calling the EnvelopeVariance obj's underlying member method code with example usage: obj._get_chunks_indx(in_len, chunk_size, chunk_stride, discard_last) without return types