Comments (1)
This is caused by the update of PyTorch.
You can set it to cpu tensor for length
https://github.com/allanj/ner_incomplete_annotation/blob/master/model/bilstm_encoder.py#L69
For this one, replace char_seq_lens
with char_seq_lens.cpu()
https://github.com/allanj/ner_incomplete_annotation/blob/master/model/bilstm_encoder.py#L79
For this one, replace sorted_seq_len
with sorted_seq_len.cpu()
from ner_incomplete_annotation.
Related Issues (12)
- I am interested in implementing the PyTorch version of this project. HOT 5
- About the training of contextual embedding HOT 1
- [Question] NNCRF not using margions in forward HOT 2
- Using the same dataset to train and evaluate the model can't reach to 100% F1 score HOT 3
- Thanks for the'hard method', when will you relase the soft version ? HOT 7
- how to obtain the dataset Youku and Taobao HOT 1
- I tried to replace the bilstm encoder to bert-based encoder on your source code, by utilising huggingface transformers, which might be interest to you and others ?
- batch_size HOT 3
- question on the dynet soft implementation HOT 1
- What if the dev data is not completely labeled? HOT 4
- Results reproduction HOT 9
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