code: def test_svt(
      input_size, num_samples, rotate, recognition, mock_svt_dataset
  ):
      # monkeypatch the path to temporary dataset
      datasets.SVT.URL = mock_svt_dataset
      datasets.SVT.SHA256 = None
  
      ds = datasets.SVT(
          train=True,
          download=True,
          img_transforms=Resize(input_size),
          use_polygons=rotate,
          recognition_task=recognition,
          cache_dir="/".join(mock_svt_dataset.split("/")[:-2]),
          cache_subdir=mock_svt_dataset.split("/")[-2],
      )
  
      assert len(ds) == num_samples
      assert repr(ds) == f"SVT(train={True})"
      if recognition:
          _validate_dataset_recognition_part(ds, input_size)
      else:
          _validate_dataset(ds, input_size, is_polygons=rotate)
  
imports: import os
  from shutil import move
  import numpy
  import pytest
  import tensorflow
  from doctr import datasets
  from doctr.datasets import DataLoader
  from doctr.file_utils import CLASS_NAME
  from doctr.transforms import Resize
label_desc: Use image node_id 18 for calling a global function with example usage: test_svt(input_size, num_samples, rotate, recognition, mock_svt_dataset) without return types