troica
troica
``` mod_wsgi (pid=2401): Target WSGI script '/var/www/html/autoIPTV/autoIPTV/wsgi.py' cannot be loaded as Python module. [Thu Oct 14 20:10:15.550876 2021] [wsgi:error] [pid 2401] [remote 104.227.23.10:17571] mod_wsgi (pid=2401): Exception occurred processing WSGI script...
Actually this is the original issue. ``` mod_wsgi (pid=2806): Target WSGI script '/var/www/html/autoIPTV/autoIPTV/wsgi.py' cannot be loaded as Python module. [Thu Oct 14 20:19:08.229498 2021] [wsgi:error] [pid 2806] [remote 104.227.23.10:4031] mod_wsgi...
I think you know this issue very well. Here is my wsgi.py file ``` import os, sys sys.path.append('/var/www/html/envAutoIPTV/lib/python3.8/site-packages') sys.path.append('/var/www/html/AutoIPTV') from django.core.wsgi import get_wsgi_application os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'autoIPTV.settings') application = get_wsgi_application() ``` And...
I also found this error I am using my own YOLO v3 model on Android+Opencv4.1.1 ======================== `1 Mat blob;` `2 cv::dnn::blobFromImage(frame, blob, 0.00392, Size(416, 416), Scalar(0, 0, 0), true, false);`...
I reduce the allocated GPU memory size by Tensorflow like this. ``` gpu_options = tf.compat.v1.GPUOptions(per_process_gpu_memory_fraction=0.2) self.session = tf.compat.v1.Session(config=tf.compat.v1.ConfigProto(gpu_options=gpu_options)) ```  But I am still getting above CUDNN_STATUS_NOT_SUPPORTED error.
The same Issue on my side. ``` note: This error originates from a subprocess, and is likely not a problem with pip. ERROR: Failed building wheel for numpy Failed to...
> The same Issue on my side. > > ``` > ERROR: Failed building wheel for numpy > Failed to build numpy > ERROR: Could not build wheels for numpy,...
@artykbayevk Thanks!, You saved my day!!! Its working ... But it looks using **tf-nightly-gpu 2.5.0.dev20201207** the speed was not improved RTX-3090, CUDA11.1, CUDNN 805 Only YoloV4 Speed is over 24...
And when trace the log with _run_in_baches function i get this log result ============================================== def _run_in_batches(f, data_dict, out, batch_size): data_len = len(out) num_batches = int(data_len / batch_size) print("123") s, e...
Hello. Isn't there any news to fix this issue?