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Having problems at step 2 #3
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Hi, @6wom9 ! I followed the README instructions and ended up with the same error as yours... |
Hmm... that's strange. Did you guys download the Bert model file and decompress it? |
At first please double-check the model path (model_dir). |
Hi, @saminfatehir! Thanks, @saminfatehir ! :) @6wom9 I could run the code using Python 3.7. To fix the problem, try these steps: 1- Uninstall your previous tensorflow version (try in the terminal: pip uninstall tensorflow and see if it works) Did it work? |
Thanks for your description @di-press; |
Hi @di-press, thanks for your great contributions. After implying your advices, step 2 and step 3 worked well. I run the IDE (Pycharm) run as administrator, but It's not worked. |
Hi @6wom9! I coulnd't run the code completely yet. I'm having an error at step 2, and couldn't complete all the steps suggested in the README. It seems I'm having a problem with bert-as-service. When I type in the terminal, as suggested in this README in step 2, this command: bert-serving-start -model_dir uncased_L-12_H-768_A-12/ -num_worker=4 -max_seq_len=NONE -show_tokens_to_client -pooling_layer -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 my computer crashes instantly, and I need to reboot it manually. It crashes when WORKER-1 tries to load a graph (do you remember in step 2, where the workers appears, in terminal, trying to load graphs? It is in this step that I have an issue). Maybe I don't have enough memory or other hardrware requirement to run the code... Please, can you tell: 1- how much memory you have? Really thanks! |
Hi @saminfatehir, Hi again @di-press I also couldn't run the code with my personal computer, It crashed at step 2. For this reason I am using computer laboratory in my university. |
Hi @6wom9 Hmmm... That's strange. |
Good morning @saminfatehir, Apologies for any ignorance, as I'm relatively new to Python. I completed step 1. Upon step two, my terminal in both PyCharm and Command Prompt seems to stagnate indefinitely at the point in the screenshot above. As per the above comments, I have ensured that the BERT model is decompressed directly into the personality_detection folder, using the same BERT file used in the example, such that copying and pasting the exact example line for step 2 seems to access it fine. I also depreciated TensorFlow to 1.13.0rc0, 1.13.0rc1, and 1.13.0rc2, all to the same effect. I am currently using 1.13.0rc1 as I attempt other solutions. Please don't let me know if there's any additional information you would need for this. Computer specifications:
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Hi @LifeofLucidity, Hmm... That's strange. does your computer crash on step 2? |
Hi @saminfatehir, Thanks for the quick response. My computer does not crash on step 2, instead, it simply sits there indefinitely. For about 5 to 7 minutes the CPU and memory usage spikes before going back down with no changes in the terminal. I tried letting it run as long as possible to be certain processes weren't simply taking a long time. Your suggestion of reducing the number of workers to 1 helped a certain amount. It seems to have progressed an additional few steps into the process before stagnating again without progress. This can be seen in my attached screenshot. |
Hi @LifeofLucidity, It seems step 2 to have passed successfully and the bert server is ready to serve the requests. Now you can try step 3 in the other terminal. |
Hi @saminfatehir, I wasn't aware that I had to open a second terminal to complete step 3. I was under the impression I would wait for a process to finish so I could begin step 3 in the exact same terminal. However, you are completely correct. After opening a second terminal and starting step 3, it ran to completion with no issues. I ran into a hiccup when attempting to run predictor.py, which I have posted in the issue pertaining to that subject. Many thanks for your engagement. |
I cloned this code from Github according to requirements.txt. And then, I've run "shrink_data.py". But I am having problems at step 2. What should I do in this condition? Although I've checked this issue, I can not understand anything.
tensorflow == 1.15.0
I'm very very new with python.
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