Comments (4)
barryflower
commented on September 2, 2024
12
Further to this problem there is an easy fix. Just add/change the following 3 lines in modules.py. Starting from the bottom so that the line numbers I show don't change.
Change line 59 to:
return input_weighted, input_encoded.to(device) # Fixed CUDA bug #
Change line 11 to:
return Variable(torch.zeros(1, x.size(0), hidden_size).to(device)) # Fixed CUDA bug #
Add after line 4:
from constants import device # Fixed CUDA bug BF 20190710 #
Thats it!
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ywatanabe1989
commented on September 2, 2024
Me too.
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shwangdev
commented on September 2, 2024
Me tooo
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barryflower
commented on September 2, 2024
Yes, the same problem. Has this been tested with cuda?
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Related Issues (20)
- why not use tanh in encoder while use it in decoder ? HOT 2
- FileNotFoundError: [Errno 2] No such file or directory: '/da-rnn/plots/pred_0.png' HOT 1
- I got an error when run main_predict.py after running main.py successful HOT 3
- one of the variables needed for gradient computation has been modified by an inplace operation
- How many epoch should I choose? HOT 1
- why use companies' stock price to predict NASDAQ-100 Index?
- Is there any room for gpu memory improvements? HOT 2
- The result value is different from raw data because of StandardScaler(). How can I get the plots and calculate MSE use raw data?
- It's weird that this code can only performance well on predicting 'NDX' HOT 1
- Dose this model genelarize well on your (other) dataset? HOT 1
- Evaluation mode missing on validation and predict
- tensor problem
- Multi-Step Prediction
- Can't find tanh function in eqn. 8 HOT 1
- Current values of external factor are used for prediction in your code? HOT 11
- Regarding scaling of data HOT 2
- Reg predicting the output HOT 1
- NaN issues when changing dat-aset. HOT 2
- Data overlapping in train/test split HOT 1
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