old_contents: 
  from numpy.testing import assert_array_equal
  
  from pystruct.models import GridCRF
  
  from pystruct.datasets import generate_blocks_multinomial
  
  from pystruct.learners import FrankWolfeSSVM
  
  
  def test_multinomial_blocks_frankwolfe():
      X, Y = generate_blocks_multinomial(n_samples=50, noise=0.4,
                                         seed=0)
      crf = GridCRF(inference_method='qpbo')
      clf = FrankWolfeSSVM(model=crf, C=1, line_search=True,
                           batch_mode=False, dual_check_every=500)
      clf.fit(X, Y)
      Y_pred = clf.predict(X)
      assert_array_equal(Y, Y_pred)
  
new_contents: 
  from numpy.testing import assert_array_equal
  
  from pystruct.models import GridCRF
  
  from pystruct.datasets import generate_blocks_multinomial
  
  from pystruct.learners import FrankWolfeSSVM
  
  
  def test_multinomial_blocks_frankwolfe():
      X, Y = generate_blocks_multinomial(n_samples=50, noise=0.5,
                                         seed=0)
      crf = GridCRF(inference_method='qpbo')
      clf = FrankWolfeSSVM(model=crf, C=1, line_search=True,
                           batch_mode=False, dual_check_every=500)
      clf.fit(X, Y)
      Y_pred = clf.predict(X)
      assert_array_equal(Y, Y_pred)
  
subject: TEST use same amount of noise for frank wolfe test as for other test. Works now that C is scaled correctly :)