def random_sample_fullyfree(s, *_):
lin = [n for n in s.nodes() if n != 0]
random.shuffle(lin)
return mindep.deplen(s, linearization=[0] + lin)
def deplen(s, *_):
lin = mindep.randlin_projective(s, head_final_bias=0)[1]
return mindep.deplen(s, linearization=lin, filters=filters)
def weighted_deplen(s, lang, *_):
weights = WEIGHTS[lang]
lin = opt_mindep.get_linearization(s, weights, thing_fn=CONDITIONING)
score = mindep.deplen(s, lin)
return score
def deplen(s, *_):
_, min_deplin = mindep.mindep_projective_alternating(s)
return mindep.deplen(s, linearization=min_deplin, filters=filters)
def deplen(s, *_):
return mindep.deplen(s, filters=filters)
def real_deplen(s, *_): # keep
return mindep.deplen(s)