text: import pytest
  from fastai import *
  from fastai.vision import *
  
  #@pytest.mark.slow
  @pytest.fixture(scope="module")
  def learn():
      path = untar_data(URLs.MNIST_TINY)
      data = image_data_from_folder(path, ds_tfms=(rand_pad(2, 28), []), batch_size=16, num_workers=2)
      data.normalize()
      learn = Learner(data, simple_cnn((3,16,16,16,2), bn=True), metrics=accuracy)
      learn.fit_one_cycle(3)
      return learn
  
  def test_accuracy(learn):
      assert accuracy(*learn.get_preds()) > 0.9
  
  def test_image_data(learn):
      img,label = learn.data.train_ds[0]
      d = img.data
      assert abs(d.max()-1)<0.05
      assert abs(d.min())<0.05
      assert abs(d.mean()-0.2)<0.1
      assert abs(d.std()-0.3)<0.1
  
  def test_1cycle_lrs(learn):
      lrs = learn.recorder.lrs
      assert lrs[0]<0.001
      assert lrs[-1]<0.0001
      assert np.max(lrs)==3e-3
  
  def test_1cycle_moms(learn):
      moms = learn.recorder.moms
      assert moms[0]==0.95
      assert abs(moms[-1]-0.95)<0.01
      assert np.min(moms)==0.85
  
  