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Problem arises when I train updown_nocaps setting #9
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Hi @chenxy99 — glad you liked our work! It looks like your predictions are not being uploaded to EvalAI for validation. Can you double-check if you compute machine has internet access? Also, please try to save one prediction file as JSON (and remove |
Thanks for your help. It works well. |
That's great, glad it worked! |
Hello, I find that your code works well in a single gpu scenario. But in multi-gpus setting, it seems to have some problem. I use the script below
It seems there are some problems form the output of CBS.
I would like to know how I can fix this problem. Thanks for your help a lot again. |
Hello @kdexd , this morning, I find that every time I submit my evaluation json file to EVAL AI, the status is always 'submitted'. I wait for about 4 hours, but I still cannot get the 'finished' status (It usually costs 1 minute to change to 'finished' status). I would like to know whether there is something wrong with the eval ai for nocaps from this morning and hopefully, you can help me solve this issue. Thanks a lot. |
Hi, thanks a lot for this great dataset.
First, I follow the instruction on 'How to setup this codebase?' to set up my anaconda env (updown) as well as set the token through EvalAI CLI.
Next, based on the instruction on 'How to train your captioner?', I use the script
I find that the script can run through into the validation part in /scripts/train.py and print first 25 captions with their Image ID in train.py Line 261-263
Then, however, the script seems to stop running like the figure shown below.
And I wait for a long time (at least half an hour) I got an error message
I doubt that there exist to be some problem with evalai. But in the conda list, I found the evalai has been installed. Hence, I doubt one possibility is that when I run
pip install -r requirements.txt
, I find a message that some modules are incompatible. I try a lot, but I cannot find a good balance so that all of the modules are compatible.So I hope that you can provide the environment.yaml
conda env export > environment.yaml
for me and I can try it by using the same versions of all the modules.If it is not the case, could you help me to solve this problem.
Thanks a lot again.
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