Comments (6)
Hi. As you say, the memory allocation failure is associated with your GPU, not related to your system main memory.
from char-rnn.
Sad, but good to know, thank you.
from char-rnn.
By the way, do you mind posting the parameters you are hoping to use for training, so I can use them in my testing. It wont solve your memory issue, but just out of my own personal curiosity really. Edit, oh I see you've included them, in your command output ;-)
from char-rnn.
Do you mind giving me some details about your dataset, ie how large it is, the various dimensions and any other characteristics and so on please?
from char-rnn.
I was going to target something along the lines of:
-eval_val_every 500 -num_layers 6 -rnn_size 600 -dropout 0.5 -seq_length 100
I don't know how to evaluate the dataset, so I just zipped it up (1 meg zipped): https://www.dropbox.com/s/77uiqp1zbhfgut4/mtg.zip?dl=0
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Thanks!
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Related Issues (20)
- This usually indicates a bug.
- output not being stored as .txt HOT 1
- Sampling Text HOT 3
- Length of primetext causes it to fail
- Question:
- Torch readline.o error
- Th: command not found, Torch installed fine HOT 3
- Question: Is there a way to "pause" temporarily without making it restart? HOT 3
- Random alias of folder created in same location as real
- AMD? HOT 2
- Links in readme.md not working in certain editors
- cutorch installation make error HOT 1
- Package 'python-software-properties' has no installation candidate
- Installation problem: readline.h HOT 2
- Failed to clone the RNN
- How can I change the model form LSTM to GRU?
- Training stuck on "cloning criterion"
- Duo GPU Capabilities? HOT 4
- how do i implement this code in python? HOT 3
- Code
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