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fca4fc0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | #!/usr/bin/env python
import numpy as np
#from moverscore_v2 import get_idf_dict, word_mover_score
from moverscore import get_idf_dict, word_mover_score
from collections import defaultdict
class MoverScore:
def __init__(self, lang="en", model_type=None):
self.lang = lang
self.model_type=model_type
#self.model = load_model(model_type=model_type, lang=lang)
self.idf_dict_ref = None
self.idf_dict_hyp = None
def compute_score(self, gts, res):
assert gts.keys()==res.keys()
assert self.idf_dict_hyp is not None and self.idf_dict_hyp is not None
# convert dict to list of str
cands = list(map(lambda x:x[0], res.values()))
refs = list(map(lambda x:x[0], gts.values()))
scores = word_mover_score(refs, cands, self.idf_dict_ref, self.idf_dict_hyp, \
stop_words=[], n_gram=1, remove_subwords=True)
#print(np.mean(scores), max(scores))
return np.mean(scores), scores
def make_dict(self, all_gts, all_res, vids):
gold = []
pred = []
for vid in vids:
gold.extend(all_gts[vid]["sentences"])
pred.extend([pred["sentence"] for pred in all_res[vid]])
self.idf_dict_ref = get_idf_dict(gold)
self.idf_dict_hyp = get_idf_dict(pred)
#print(self.idf_dict_hyp)
def method(self):
return "MoverScore"
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