old_contents: #import convolutional_mlp, dbn, logistic_cg, logistic_sgd, mlp, rbm, SdA_loops, SdA
  import convolutional_mlp, logistic_cg, logistic_sgd, mlp, SdA_loops, SdA
  from nose.plugins.skip import SkipTest
  #TODO: dbn, rbm, SdA, SdA_loops, convolutional_mlp
  def test_logistic_sgd():
      logistic_sgd.sgd_optimization_mnist(n_iter=10)
  def test_logistic_cg():
      logistic_cg.cg_optimization_mnist(n_iter=10)
  def test_mlp():
      mlp.sgd_optimization_mnist(n_iter=5)
  def test_convolutional_mlp():
      raise SkipTest('Implementation not finished')
      convolutional_mlp.evaluate_lenet5(n_iter=5)
  def test_dbn():
      raise SkipTest('Implementation not finished')
  def test_rbm():
      raise SkipTest('Implementation not finished')
  def test_SdA_loops():
      raise SkipTest('Implementation not finished')
      SdA_loops.sgd_optimization_mnist()
  def test_SdA():
      raise SkipTest('Implementation not finished')
      SdA.sgd_optimization_mnist()
  
new_contents: #import convolutional_mlp, dbn, logistic_cg, logistic_sgd, mlp, rbm, SdA_loops, SdA
  import convolutional_mlp, logistic_cg, logistic_sgd, mlp
  from nose.plugins.skip import SkipTest
  #TODO: dbn, rbm, SdA, SdA_loops, convolutional_mlp
  def test_logistic_sgd():
      logistic_sgd.sgd_optimization_mnist(n_iter=10)
  def test_logistic_cg():
      logistic_cg.cg_optimization_mnist(n_iter=10)
  def test_mlp():
      mlp.sgd_optimization_mnist(n_iter=5)
  def test_convolutional_mlp():
      convolutional_mlp.evaluate_lenet5(n_iter=5,nkerns=[5,5])
  def test_dbn():
      raise SkipTest('Implementation not finished')
  def test_rbm():
      raise SkipTest('Implementation not finished')
  def test_SdA_loops():
      raise SkipTest('Implementation not finished')
      SdA_loops.sgd_optimization_mnist()
  def test_SdA():
      raise SkipTest('Implementation not finished')
      SdA.sgd_optimization_mnist()
  
subject: enable the convolutional_mlp.py for the buildbot by lowering the number of nkern to have it run in a decent time.