Comments (6)
taishan1994
commented on June 12, 2024
在训练并将BERT+CRF模型转换为ONNX模型时，我们应该使用哪个CRF文件？根据README，我们必须使用这个文件pytext-crf，那么我们是否必须对其进行一些修改才能使其发挥作用？
convert_onnx下已经有修改好的模型了，直接设置convert_onnx.py里面的相关参数配置运行就可以了。
from pytorch_bert_bilstm_crf_ner.
colabpp
commented on June 12, 2024
谢谢你的快速回复。我们应该使用哪种CRF代码将BERT-CRF模型转换为ONNX，是pytorch-crf还是README中提到的layers/CRF.py或pytext/crf中提供的代码？
原本的pytorch-crf不能转换为onnx，这里使用了here
from pytorch_bert_bilstm_crf_ner.
taishan1994
commented on June 12, 2024
谢谢你的快速回复。我们应该使用哪种CRF代码将BERT-CRF模型转换为ONNX，是pytorch-crf还是README中提到的layers/CRF.py或pytext/crf中提供的代码？
原本的pytorch-crf不能转换为onnx，这里使用了here
convert_onnx用的其下面的convert_onnx/bert_ner_model_onnx.py里面的模型，里面使用的是from layers.CRF import CRF
from pytorch_bert_bilstm_crf_ner.
colabpp
commented on June 12, 2024
我已经开始工作了，pytorch的版本有问题。谢谢你的工作和支持。你是伟大的!
from pytorch_bert_bilstm_crf_ner.
libaiCool
commented on June 12, 2024
你好，convert_onnx.py导出的onnx模型无法支持多条数据并行推理。报错如下：
best_tags_list[:, i + 1] = history[i, :, last_idx].squeeze(1)
RuntimeError: shape mismatch: value tensor of shape [2, 2] cannot be broadcast to indexing result of shape [2]
请问该如何处理
from pytorch_bert_bilstm_crf_ner.
taishan1994
commented on June 12, 2024
因为CRF的原因，不能进行batch推理
from pytorch_bert_bilstm_crf_ner.
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- 自己数据集出现ValueError: too many values to unpack (expected 2)问题 HOT 2
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from pytorch_bert_bilstm_crf_ner.