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ltguo19 / VSUA-Captioning

Code for "Aligning Linguistic Words and Visual Semantic Units for Image Captioning", ACM MM 2019
MIT License
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When I use Reinforcement learning with CIDEr reward,there is always keyerror mistake #11

Open userpei opened 3 years ago

userpei commented 3 years ago

Traceback (most recent call last): File "train.py", line 171, in train(opt) File "train.py", line 102, in train reward = get_self_critical_reward(decoder, core_args, vrg_data, fc_feats, att_feats, weak_relas, att_masks, data, gen_result, opt) File "/peng/pyx/WeakVRD-Captioning-master/misc/rewards_graph.py", line 60, in get_self_critical_reward , cider_scores = CiderD_scorer.compute_score(gts, res) File "cider/pyciderevalcap/ciderD/ciderD.py", line 48, in compute_score (score, scores) = cider_scorer.compute_score(self._df) File "cider/pyciderevalcap/ciderD/ciderD_scorer.py", line 199, in compute_score score = self.compute_cider(df_mode) File "cider/pyciderevalcap/ciderD/ciderD_scorer.py", line 173, in compute_cider vec, norm, length = counts2vec(test) File "cider/pyciderevalcap/ciderD/ciderD_scorer.py", line 122, in counts2vec df = np.log(max(1.0, self.document_frequency[ngram])) KeyError: ('4857', '8713', '344', '993')

The numbers are different each time