def find_most_violated_constraint_margin(x, y, model, sparm):
"""Return ybar associated with x's most violated constraint.
The find most violated constraint function for margin rescaling.
The default behavior is that this returns the value from the
general find_most_violated_constraint function."""
w = list(model.w)
print '\nFinding most violated constraint'
print ' w: ',w
print ' y: ',y
A = path.compute_loss_augmented_terms(x, w, y, path.L2)
ybar = viterbi.solve(A)
D = path.compute_data_terms(x, w)
print ' ybar: ',ybar
print ' loss: ',path.compute_loss(y, ybar, path.L2)
#print 'Data terms:\n', np.round(D, 2)
#print 'Loss augmented terms:\n', np.round(A, 2)
return ybar
def classify_example(x, model, sparm):
"""Given a pattern x, return the predicted label."""
w = list(model.w)
return viterbi.solve(path.compute_data_terms(x, w))
