code: def test_from_folders_only_train(tmpdir):
      seed_everything(42)
  
      train_dir = Path(tmpdir / "train")
      train_dir.mkdir()
  
      (train_dir / "a").mkdir()
      _rand_image().save(train_dir / "a" / "1.png")
      _rand_image().save(train_dir / "a" / "2.png")
  
      (train_dir / "b").mkdir()
      _rand_image().save(train_dir / "b" / "1.png")
      _rand_image().save(train_dir / "b" / "2.png")
  
      spectrograms_data = AudioClassificationData.from_folders(
          train_dir, batch_size=1
      )
  
      data = next(iter(spectrograms_data.train_dataloader()))
      imgs, labels = data["input"], data["target"]
      assert imgs.shape == (1, 3, 128, 128)
      assert labels.shape == (1,)
  
imports: from pathlib import Path
  from typing import Tuple
  import flash
  import numpy
  import pytest
  import torch
  from flash.audio import AudioClassificationData
  from flash.core.utilities.imports import _MATPLOTLIB_AVAILABLE, _PIL_AVAILABLE, _TOPIC_AUDIO_AVAILABLE
  from pytorch_lightning import seed_everything
label_desc: Use image node_id 10 for calling a global function with example usage: test_from_folders_only_train(tmpdir) without return types