old_contents: import os
  
  from numpy.testing import assert_raises
  
  from fuel import config
  from fuel.datasets import BinarizedMNIST
  from tests import skip_if_not_available
  
  
  def test_binarized_mnist_train():
      skip_if_not_available(datasets=['binarized_mnist.hdf5'])
  
      dataset = BinarizedMNIST('train', load_in_memory=False)
      handle = dataset.open()
      data, = dataset.get_data(handle, slice(0, 10))
      assert data.dtype == 'uint8'
      assert data.shape == (10, 1, 28, 28)
      assert dataset.num_examples == 50000
      dataset.close(handle)
  
  
  def test_binarized_mnist_valid():
      skip_if_not_available(datasets=['binarized_mnist.hdf5'])
  
      dataset = BinarizedMNIST('valid', load_in_memory=False)
      handle = dataset.open()
      data, = dataset.get_data(handle, slice(0, 10))
      assert data.dtype == 'uint8'
      assert data.shape == (10, 1, 28, 28)
      assert dataset.num_examples == 10000
      dataset.close(handle)
  
  
  def test_binarized_mnist_test():
      skip_if_not_available(datasets=['binarized_mnist.hdf5'])
  
      dataset = BinarizedMNIST('test', load_in_memory=False)
      handle = dataset.open()
      data, = dataset.get_data(handle, slice(0, 10))
      assert data.dtype == 'uint8'
      assert data.shape == (10, 1, 28, 28)
      assert dataset.num_examples == 10000
      dataset.close(handle)
  
  
  def test_binarized_mnist_invalid_split():
      assert_raises(ValueError, BinarizedMNIST, 'dummy')
  
  
  def test_binarized_mnist_data_path():
      assert BinarizedMNIST('train').data_path == os.path.join(
          config.data_path, 'binarized_mnist.hdf5')
  
new_contents: import hashlib
  import os
  
  from numpy.testing import assert_raises
  
  from fuel import config
  from fuel.datasets import BinarizedMNIST
  from tests import skip_if_not_available
  
  
  def test_binarized_mnist_train():
      skip_if_not_available(datasets=['binarized_mnist.hdf5'])
  
      dataset = BinarizedMNIST('train', load_in_memory=False)
      handle = dataset.open()
      data, = dataset.get_data(handle, slice(0, 10))
      assert data.dtype == 'uint8'
      assert data.shape == (10, 1, 28, 28)
      assert hashlib.md5(data).hexdigest() == '0922fefc9a9d097e3b086b89107fafce'
      assert dataset.num_examples == 50000
      dataset.close(handle)
  
  
  def test_binarized_mnist_valid():
      skip_if_not_available(datasets=['binarized_mnist.hdf5'])
  
      dataset = BinarizedMNIST('valid', load_in_memory=False)
      handle = dataset.open()
      data, = dataset.get_data(handle, slice(0, 10))
      assert data.dtype == 'uint8'
      assert data.shape == (10, 1, 28, 28)
      assert hashlib.md5(data).hexdigest() == '65e8099613162b3110a7618037011617'
      assert dataset.num_examples == 10000
      dataset.close(handle)
  
  
  def test_binarized_mnist_test():
      skip_if_not_available(datasets=['binarized_mnist.hdf5'])
  
      dataset = BinarizedMNIST('test', load_in_memory=False)
      handle = dataset.open()
      data, = dataset.get_data(handle, slice(0, 10))
      assert data.dtype == 'uint8'
      assert data.shape == (10, 1, 28, 28)
      assert hashlib.md5(data).hexdigest() == '0fa539ed8cb008880a61be77f744f06a'
      assert dataset.num_examples == 10000
      dataset.close(handle)
  
  
  def test_binarized_mnist_invalid_split():
      assert_raises(ValueError, BinarizedMNIST, 'dummy')
  
  
  def test_binarized_mnist_data_path():
      assert BinarizedMNIST('train').data_path == os.path.join(
          config.data_path, 'binarized_mnist.hdf5')
  
subject: Add sumcheck verification for train, valid and test subsets