I am testing YOLOv4 on a Custom Dataset as described at https://blog.roboflow.ai/training-yolov4-on-a-custom-dataset/, using google Colab (refer to https://colab.research.google.com/drive/1mzL6WyY9BRx4xX476eQdhKDnd_eixBlG#scrollTo=GNVU7eu9CQj3). The cuda and opencv information are:
CUDA-version: 10010 (10010), cuDNN: 7.6.5, GPU count: 1
OpenCV version: 3.2.0
Prepare additional network for mAP calculation...
compute_capability = 370, cudnn_half = 0
!nvidia-smi
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.36.06 Driver Version: 418.67 CUDA Version: 10.1 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Tesla K80 Off | 00000000:00:04.0 Off | 0 |
| N/A 62C P8 30W / 149W | 0MiB / 11441MiB | 0% Default |
| | | ERR! |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
The cuda errors are:
CUDA status Error: file: ./src/blas_kernels.cu : () : line: 841 : build time: Jun 18 2020 - 13:22:47
CUDA Error: no kernel image is available for execution on the device
CUDA Error: no kernel image is available for execution on the device: File exists
darknet: ./src/utils.c:325: error: Assertion `0' failed.
