RuntimeError: masked_select: expected BoolTensor or ByteTensor for mask

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Traceback (most recent call last): File "C:/Users/Administrator/Desktop/bert_crf/train.py", line 191, in model.fit(train_dataloader, epochs=20, steps_per_epoch=None, callbacks=[evaluator]) File "D:\python36\lib\site-packages\bert4torch\models.py", line 213, in fit output, loss, loss_detail = self.train_step(train_X, train_y, grad_accumulation_steps) File "D:\python36\lib\site-packages\bert4torch\models.py", line 131, in train_step loss_detail = self.criterion(output, train_y) File "D:\python36\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl return forward_call(*input, **kwargs) File "C:/Users/Administrator/Desktop/bert_crf/train.py", line 122, in forward return model.crf.neg_log_likelihood_loss(*outputs, labels) File "D:\python36\lib\site-packages\bert4torch\layers.py", line 913, in neg_log_likelihood_loss forward_score, scores = self._forward_alg(feats, mask) File "D:\python36\lib\site-packages\bert4torch\layers.py", line 862, in _forward_alg masked_cur_partition = cur_partition.masked_select(mask_idx) # [x * tag_size]

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测试运行的脚本是ner任务： /Tongjilibo/bert4torch/blob/master/examples/sequence_labeling/task_sequence_labeling_ner_crf.py 运行环境 windows10 pycharm 最新版本0.1.6的bert4torch torch==1.10

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已经自我修复了 ，不知道是不是只有我自己的问题 还是说所有的都是这样的

[Tongjilibo]

已经自我修复了 ，不知道是不是只有我自己的问题 还是说所有的都是这样的

你是用的pip版本吗？pip上的0.1.6版本当时配合的task_sequence_labeling_ner_crf.py也是attention_mask转为bool类型的，后续我在CRF内部自己转bool()类型了，你可以用git上的最新代码试下，应该就没刚刚的问题了

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是的用 pip install bert4torch 进行安装

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直接git 是可以的 没有问题的

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[Tongjilibo]

刚看到，你这边这个问题还有吗？