Comments (5)
I haven't met this problem before.
It seems like it is about switches between native and cudnn in earlier discussion about pytorch discussion
The recent version of pytorch adopt two different ways for different backends:
For native:
checkAllSameGPU(c, {log_probs_arg, targets_arg});
For cudnn:
checkBackend(c, {*log_probs}, Backend::CUDA); checkBackend(c, {*targets}, Backend::CPU);
You can debug based on your pytorch version and the backend used (torch.backends.cudnn.enabled).
from vac_cslr.
what is your pytorch version?Thanks
from vac_cslr.
1.10.0 and 1.10.1 works for me.
from vac_cslr.
My pytorch is also 1.10.0,What is your ctcdecode version?
When I run main.py, the following error occurs:
(your) (base) quchunguang@ubuntu:~/sunday/CSLR$ python main.py
Loading model
Traceback (most recent call last):
File "main.py", line 207, in
processor = Processor(args)
File "main.py", line 33, in init
self.model, self.optimizer = self.loading()
File "main.py", line 96, in loading
loss_weights=self.arg.loss_weights,
File "/home/quchunguang/sunday/CSLR/slr_network.py", line 38, in init
self.decoder = utils.Decode(gloss_dict, num_classes, 'beam')
File "/home/quchunguang/sunday/CSLR/utils/decode.py", line 19, in init
self.ctc_decoder = ctcdecode.CTCBeamDecoder(vocab, beam_width=10, blank_id=blank_id,
AttributeError: module 'ctcdecode' has no attribute 'CTCBeamDecoder'
from vac_cslr.
The version has been presented in Readme, it seems like you did not install ctcdecoder successfully.
from vac_cslr.
Related Issues (20)
- Torch not compiled with CUDA enabled HOT 2
- Error when i run the training part main.py HOT 1
- unable to run successfully when I run main.py HOT 1
- unable to successfully install CTC HOT 5
- Detailed code running steps HOT 19
- Visualizing the predicted alignments HOT 1
- unable to run these repository on google colab HOT 1
- Data augmention error HOT 4
- about the feature extractor architecture HOT 6
- Successfully inference, but unable to train HOT 3
- Visualize Epoch vs Loss HOT 1
- Hardware and Software Specifications for this research. HOT 3
- Gloss Segment Boundary Assignment Algorithm (GSBA) HOT 1
- Does your PHOENIX-2014-T dataset have /1/ folder? HOT 1
- model or model.parameters()? HOT 2
- Does your model produce different results each time it is run? HOT 4
- Training the baseline (without VAC, SMKD) HOT 2
- How can I use a trained model to test a video?
- unable to reconize any word but the loss is decreasing??? HOT 1
- Does preprocess.sh have an effect if using datasets other than phoneix?
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