Comments (17)
Hi @tjb-tech! First of all, is your GPU readily set up with CUDA? You can verify that by running nvidia-smi
and checking the reported CUDA version.
If you enable the --use_gpu
option on the train_classifier.py
script, it will automatically use the GPU at index 0 for training and nvidia-smi
should list a new python process.
from sense.
Hi @tjb-tech! First of all, is your GPU readily set up with CUDA? You can verify that by running
nvidia-smi
and checking the reported CUDA version.If you enable the
--use_gpu
option on thetrain_classifier.py
script, it will automatically use the GPU at index 0 for training andnvidia-smi
should list a new python process.
First of all, thank you very much for your timely reply to us. Through your method, we have checked that nvidia-smi does have a new line of Python process. However, I found that the CPU utilization rate was close to 100%, while the GPU utilization rate was close to 1%. Could you tell me why? I hope to get your professional reply. Thank you very much
from sense.
The problem with video datasets is that loading and decoding of the videos can get expensive. So it can happen that the update step of the model on the GPU is done faster than the preparation of the next batch, which leads to the CPU being utilized more than the GPU.
However, a utilization of 1% is really low. Could you verify with the following command during training if the utilization is constantly that low or if there are at least some periodic spikes?
watch -n 1 nvidia-smi
And could you send over your CPU and GPU specs?
from sense.
The problem with video datasets is that loading and decoding of the videos can get expensive. So it can happen that the update step of the model on the GPU is done faster than the preparation of the next batch, which leads to the CPU being utilized more than the GPU.
However, a utilization of 1% is really low. Could you verify with the following command during training if the utilization is constantly that low or if there are at least some periodic spikes?watch -n 1 nvidia-smiAnd could you send over your CPU and GPU specs?
First of all, thank you very much for taking time out of your busy schedule to answer my questions. My CPU is I5-9300H, and my GPU is GTX1650. The screenshots of SMI before and after operation are as follows. The running status of my CPU and GPU is as follows. Thank you again for your prompt and enthusiastic reply. Looking forward to hearing from you soon
from sense.
Thanks for the info! It looks like the Python process is allocating some memory on the GPU, which is a good sign. Do you see any other output on the console of the epochs being finished? And do you get a resulting checkpoint?
Generally, does training in PyTorch work for you in other projects?
One more thing you could check is the following:
import torch
torch.cuda.is_available()
I must admit that we haven't tested our code on Windows in a while, so there might also be a platform-related issue.
from sense.
Hey @tjb-tech, have you been able to resolve your issue?
from sense.
Hey @tjb-tech, have you been able to resolve your issue?
Thank you very much for your concern and I'm sorry for not replying to you in time. We tried using torch.cuda.is_available(), and the return value is true, but the GPU and CPU usage are still the same as before, so I think it may be a system compatibility issue, which you can do some further research on. By the way, my system is Windows 10.
from sense.
Thanks for the update. Do you still get a checkpoint after training and how long does it take? Because if that generally works, I would go ahead and close this issue for now.
from sense.
Thanks for your reply. That's all about the GPU problem for the time being. I'm still trying to run your sense_studio code but we encountered the first error:
* Serving Flask app "sense_studio" (lazy loading)
* Environment: production
WARNING: This is a development server. Do not use it in a production deployment.
Use a production WSGI server instead.
* Debug mode: on
* Restarting with stat
* Debugger is active!
* Debugger PIN: 105-309-328
* Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)
I tried the following scenario
from gevent import pywsgi
if __name__ == '__main__':
Server = pywsgi.WSGIServer(('0.0.0.0', 5000), app)
server.serve_forever()
Here we go
But again, I encountered the following problems
[2021-04-06 13:19:30,225] ERROR in app: Exception on / [GET]
Traceback (most recent call last):
File "D:\Anaconda\envs\sense\lib\site-packages\flask\app.py", line 2447, in wsgi_app
response = self.full_dispatch_request()
File "D:\Anaconda\envs\sense\lib\site-packages\flask\app.py", line 1952, in full_dispatch_request
rv = self.handle_user_exception(e)
File "D:\Anaconda\envs\sense\lib\site-packages\flask\app.py", line 1821, in handle_user_exception
reraise(exc_type, exc_value, tb)
File "D:\Anaconda\envs\sense\lib\site-packages\flask\_compat.py", line 39, in reraise
raise value
File "D:\Anaconda\envs\sense\lib\site-packages\flask\app.py", line 1950, in full_dispatch_request
rv = self.dispatch_request()
File "D:\Anaconda\envs\sense\lib\site-packages\flask\app.py", line 1936, in dispatch_request
return self.view_functions[rule.endpoint](**req.view_args)
File "D:/MyDocuments/Service Outsourcing/sense/tools/sense_studio/sense_studio.py", line 46, in projects_overview
project['exists'] = os.path.exists(project['path'])
TypeError: 'bool' object is not subscriptable
127.0.0.1 - - [2021-04-06 13:19:30] "GET / HTTP/1.1" 500 490 0.004986
127.0.0.1 - - [2021-04-06 13:19:30] "GET /favicon.ico HTTP/1.1" 404 420 0.000999
from sense.
* Serving Flask app "sense_studio" (lazy loading)
* Environment: production
WARNING: This is a development server. Do not use it in a production deployment.
Use a production WSGI server instead.
* Debug mode: on
* Restarting with stat
* Debugger is active!
* Debugger PIN: 105-309-328
* Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)
This is a regular output and not relevant when running this application locally. You don't need to worry about setting up a WSGI server.
If the second error persists, I will have to take a look at that though 😕 Can you already send me the contents of your sense/tools/sense_studio/projects_config.json
?
from sense.
* Serving Flask app "sense_studio" (lazy loading) * Environment: production WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. * Debug mode: on * Restarting with stat * Debugger is active! * Debugger PIN: 105-309-328 * Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)
This is a regular output and not relevant when running this application locally. You don't need to worry about setting up a WSGI server.
If the second error persists, I will have to take a look at that though 😕 Can you already send me the contents of your
sense/tools/sense_studio/projects_config.json
?
Of course, my file looks like this
from sense.
Very interesting. This is either a very outdated format or an error occurred. Anyway, I would recommend deleting this file and trying again. Also you might want to pull our latest master
branch, as we've recently added a few improvements.
from sense.
Very interesting. This is either a very outdated format or an error occurred. Anyway, I would recommend deleting this file and trying again. Also you might want to pull our latest
master
branch, as we've recently added a few improvements.
Thank you so much for your timely help. We have opened Sense Studio and created our own project. We have also uploaded our own data, but we can't click the Training button, the browser shows JavaScript :void(0); , as shown in the figure below
I would appreciate it very much if you could answer my questions
from sense.
Yes, the training module has only been added a few days ago, so after pulling our latest updates this feature should be enabled for you.
from sense.
I am very sorry that I have not been able to continue to discuss this project with you recently due to my busy business. Your suggestion last time was very effective and I admire it very much. These two days, I reviewed your project again, and carefully read the blog on the 20BN official website. I noticed the following test screen in your demo video, which was very impressive.
I want to achieve this effect on my computer. Could you please tell me how the content of this test page is completed? Could you share this part? My heartfelt thanks in advance! Once again, I would like to express my admiration for your open source spirit.
from sense.
Hey @tjb-tech, thank you for the kind words!
That specific demo which you found on our website is kind of old and wasn't obtained using sense
. We haven't released this exact model with this exact set of classes. However, we've recently been working on providing a gesture control demo within sense
which might do what you need. It's still work in progress (model weights haven't been released yet) but you can already have a look here: #149.
from sense.
It looks like the original issue has been solved, so I'm going to close this thread now.
We're happy to keep supporting you, if more questions come up!
from sense.
Related Issues (20)
- train my-datasets HOT 9
- model fps HOT 6
- Training 20bn data HOT 3
- Need Help, very bad performance with my own dataset HOT 8
- how to use annotation on sense studio? HOT 4
- Need Help!! When I run normally, I am always prompted 'no module named' futures' HOT 7
- why are my fps rates so low HOT 4
- About the pretrain model HOT 22
- Is the dataset for Action Recognition open source? HOT 3
- Can you provide the format of the “project_config.json”
- 20bn website 503 Service Temporarily Unavailable HOT 19
- Need help!!!very bad performance with hmdb51 dataset!!! HOT 4
- How can I get the fitness activity datasets
- What method is used from 2D convolution expansion to 3D convolution?
- Unable to download Jester
- About pre-trained model HOT 1
- Weights files missing. HOT 7
- I can't visit '20bn.com' website HOT 1
- Has this great project stopped updating?
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from sense.