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View Code? Open in Web Editor NEWend2end layout analysis based seq2seq
end2end layout analysis based seq2seq
python test.py
File "test.py", line 7, in
import dataset
File "/seq2seq-ocr-analysis-main/dataset.py", line 9, in
config = anyconfig.load(open("config.yaml", 'rb'))
...
raise UnknownFileTypeError("file extension={}".format(fileext))
anyconfig.globals.UnknownFileTypeError: No parser found for file 'file extension=yaml'
您好, 我这边将Seq2Seq模型转ONNX模型, 然后使用onnxruntime推理计算, 输出结果全部为0.,请问这个Seq2Seq模型转ONNX,是需要注意什么吗?
请问有没有相关的实验结果参考么?
File "", line 1, in
text_hidden = processing_text(text_list[:max_len])
File "", line 103, in processing_text
out = rnn_infer.predict(label_list)
File "C:\Users\shiqiang42\Desktop\seq2seq-layout-analysis-main\seq2seq-layout-analysis-main\rnn_infer.py", line 46, in predict
types, hidden = model(input_tensor)
File "D:\software\anaconda3\envs\ocr\lib\site-packages\torch\nn\modules\module.py", line 550, in call
result = self.forward(*input, **kwargs)
File "C:\Users\shiqiang42\Desktop\seq2seq-layout-analysis-main\seq2seq-layout-analysis-main\models\TextRNN.py", line 44, in forward
emb = self.embedding(x)
File "D:\software\anaconda3\envs\ocr\lib\site-packages\torch\nn\modules\module.py", line 550, in call
result = self.forward(*input, **kwargs)
File "D:\software\anaconda3\envs\ocr\lib\site-packages\torch\nn\modules\sparse.py", line 114, in forward
self.norm_type, self.scale_grad_by_freq, self.sparse)
File "D:\software\anaconda3\envs\ocr\lib\site-packages\torch\nn\functional.py", line 1724, in embedding
return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
RuntimeError: Expected tensor for argument #1 'indices' to have scalar type Long; but got torch.IntTensor instead (while checking arguments for embedding)
text_hidden = processing_text(int(text_list[:max_len]))
Traceback (most recent call last):
File "", line 1, in
text_hidden = processing_text(int(text_list[:max_len]))
TypeError: int() argument must be a string, a bytes-like object or a number, not 'list'
text_hidden = processing_text(text_list[:max_len])
Traceback (most recent call last):
File "", line 1, in
text_hidden = processing_text(text_list[:max_len])
File "", line 103, in processing_text
out = rnn_infer.predict(label_list)
File "C:\Users\shiqiang42\Desktop\seq2seq-layout-analysis-main\seq2seq-layout-analysis-main\rnn_infer.py", line 46, in predict
types, hidden = model(input_tensor)
File "D:\software\anaconda3\envs\ocr\lib\site-packages\torch\nn\modules\module.py", line 550, in call
result = self.forward(*input, **kwargs)
File "C:\Users\shiqiang42\Desktop\seq2seq-layout-analysis-main\seq2seq-layout-analysis-main\models\TextRNN.py", line 44, in forward
emb = self.embedding(x)
File "D:\software\anaconda3\envs\ocr\lib\site-packages\torch\nn\modules\module.py", line 550, in call
result = self.forward(*input, **kwargs)
File "D:\software\anaconda3\envs\ocr\lib\site-packages\torch\nn\modules\sparse.py", line 114, in forward
self.norm_type, self.scale_grad_by_freq, self.sparse)
File "D:\software\anaconda3\envs\ocr\lib\site-packages\torch\nn\functional.py", line 1724, in embedding
return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
RuntimeError: Expected tensor for argument #1 'indices' to have scalar type Long; but got torch.IntTensor instead (while checking arguments for embedding)
您好,请问有相应的论文吗?
你好,感谢你的分享,请问可以共享下数据及标签吗 还有模型,谢谢
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