code: def test_dataloader_from_lhotse_shar_cuts_combine_datasets_unweighted(
      cutset_shar_path: Path, cutset_shar_path_other: Path
  ):
      """
      Note: if we iterated more mini-batches in this test, in the expectation there
      will be 50-50 % mini-batch occupancy of examples from both datasets.
      """
      config = OmegaConf.create(
          {
              "shar_path": [cutset_shar_path, cutset_shar_path_other],
              "sample_rate": 16000,
              "shuffle": True,
              "use_lhotse": True,
              "num_workers": 0,
              # lhotse specific
              "use_bucketing": True,
              "num_buckets": 2,
              "drop_last": False,
              "batch_duration": 4.0,  # seconds
              "quadratic_duration": 15.0,  # seconds
              "shuffle_buffer_size": 10,
              "bucket_buffer_size": 100,
              "seed": 0,
              "shar_seed": 0,
          }
      )
  
      dl = get_lhotse_dataloader_from_config(
          config=config,
          global_rank=0,
          world_size=1,
          dataset=UnsupervisedAudioDataset(),
      )
  
      # Note: we use islice here because with Lhotse Shar the dataloader will always be infinite.
      batches = [batch for batch in islice(dl, 4)]
      assert len(batches) == 4
  
      b = batches[0]
      assert (
          len([cid for cid in b["ids"] if cid.startswith("dummy")]) == 3
      )  # dataset 1
      assert (
          len([cid for cid in b["ids"] if cid.startswith("other")]) == 0
      )  # dataset 2
  
      b = batches[1]
      assert (
          len([cid for cid in b["ids"] if cid.startswith("dummy")]) == 0
      )  # dataset 1
      assert (
          len([cid for cid in b["ids"] if cid.startswith("other")]) == 3
      )  # dataset 2
  
      b = batches[2]
      assert (
          len([cid for cid in b["ids"] if cid.startswith("dummy")]) == 1
      )  # dataset 1
      assert (
          len([cid for cid in b["ids"] if cid.startswith("other")]) == 2
      )  # dataset 2
  
      b = batches[3]
      assert (
          len([cid for cid in b["ids"] if cid.startswith("dummy")]) == 2
      )  # dataset 1
      assert (
          len([cid for cid in b["ids"] if cid.startswith("other")]) == 1
      )
  
imports: from io import BytesIO
  from itertools import islice
  from pathlib import Path
  from typing import Dict, List, Tuple
  import pytest
  import torch
  from omegaconf import OmegaConf
  from nemo.collections.common.data.lhotse import get_lhotse_dataloader_from_config
label_desc: Use image node_id 16 for calling a global function with example usage: test_dataloader_from_lhotse_shar_cuts_combine_datasets_unweighted(cutset_shar_path, cutset_shar_path_other) without return types