Comments (8)
Hi @qiuwei thanks for the suggestion.
Can you give a more detail description about the flush operator? As I already used several sys.stdout.flush()
to force the system print the logs.
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If I use ncrfpp with python3, the log is not written to the stdout immediately as with python 2.
That's default behavior at the moment if don't make any modifications to the code at the moment.
With the sample data, it's hard to notice though. On my own dataset, I noticed the log was flushed only after every 20ish epochs.
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Traceback (most recent call last):
File "main.py", line 438, in
train(data)
File "main.py", line 328, in train
batch_word, batch_features, batch_wordlen, batch_wordrecover, batch_char, batch_charlen, batch_charrecover, batch_label, mask = batchify_with_label(instance, data.HP_gpu)
File "main.py", line 236, in batchify_with_label
mask[idx, :seqlen] = torch.Tensor([1]*seqlen)
TypeError: mul() received an invalid combination of arguments - got (list), but expected one of:
- (Tensor other)
didn't match because some of the arguments have invalid types: (list) - (float other)
didn't match because some of the arguments have invalid types: (list)
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Epoch: 0/1
Learning rate is set as: 0.015
Traceback (most recent call last):
File "main.py", line 438, in
train(data)
File "main.py", line 328, in train
batch_word, batch_features, batch_wordlen, batch_wordrecover, batch_char, batch_charlen, batch_charrecover, batch_label, mask = batchify_with_label(instance, data.HP_gpu)
File "main.py", line 236, in batchify_with_label
mask[idx, :seqlen] = torch.Tensor([1]*seqlen)
TypeError: mul() received an invalid combination of arguments - got (list), but expected one of:
- (Tensor other)
didn't match because some of the arguments have invalid types: (list) - (Number other)
didn't match because some of the arguments have invalid types: (list)
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@nthoangcute please confirm you used the right PyTorch version. PyTorch 0.3
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@jiesutd opss! My pytorch is currently 0.5.0a0.
Traceback (most recent call last):
File "main.py", line 440, in <module>
train(data)
File "main.py", line 284, in train
model = SeqModel(data)
File "/root/vietbt/NCRFpp/model/seqmodel.py", line 31, in __init__
self.word_hidden = WordSequence(data)
File "/root/vietbt/NCRFpp/model/wordsequence.py", line 71, in __init__
self.lstm = self.lstm.cuda()
File "/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py", line 258, in cuda
return self._apply(lambda t: t.cuda(device))
File "/opt/conda/lib/python3.6/site-packages/torch/nn/modules/rnn.py", line 112, in _apply
self.flatten_parameters()
File "/opt/conda/lib/python3.6/site-packages/torch/nn/modules/rnn.py", line 105, in flatten_parameters
self.batch_first, bool(self.bidirectional))
RuntimeError: CuDNN error: CUDNN_STATUS_INTERNAL_ERROR
Maybe I have to downgrade my pytorch version to 0.3
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@UPWHY please use the PyTorch 0.3 version.
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我现在用的Python是2.7,pytorch是0.3,但是还是报错:Traceback (most recent call last):
File "main.py", line 438, in
train(data)
File "main.py", line 328, in train
batch_word, batch_features, batch_wordlen, batch_wordrecover, batch_char, batch_charlen, batch_charrecover, batch_label, mask = batchify_with_label(instance, data.HP_gpu)
File "main.py", line 236, in batchify_with_label
mask[idx, :seqlen] = torch.Tensor([1]*seqlen)
TypeError: mul() received an invalid combination of arguments - got (list), but expected one of:
- (Tensor other)
didn't match because some of the arguments have invalid types: (list) - (Number other)
didn't match because some of the arguments have invalid types: (list)
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Related Issues (20)
- Conll 使用内存大 HOT 2
- nbest score HOT 1
- Provision for Custom Features? HOT 1
- Bug in forward method when calling _viterbi_decode, mask is not provided
- about requirement HOT 1
- Can I just use the CRF layer? HOT 1
- 大神你好,请教一些关于报错的问题 HOT 1
- About "tcmalloc: large alloc" message and training aborted HOT 3
- Difference between main_parse.py and main.py HOT 1
- Different results on CPU versus GPU HOT 1
- Test Data Format for Chunking
- Experimenting with Transformer models? HOT 1
- Decode config parameter when not using CRF HOT 1
- Reading fasttext word embeddings HOT 2
- About MAX_SENTENCE_LENGTH parameter HOT 2
- Decode error with nbest=0 when not using CRF
- Resume model training from a checkpoint
- 训练一段时间后,f1为-1 HOT 2
- Unknown labels in decoding
- Support trained model serialization to ONNX format HOT 1
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