how to resolve the error of out of memory for YOLOV8 model for model being trained on GPU in local machine

Question

I have this script

import ultralytics
from ultralytics import YOLO

import torch
torch.cuda.is_available()
ultralytics.checks()
 
if __name__ == "__main__":
    
    # Load a model
    model = YOLO('yolov8n.pt')  # load a pretrained model (recommended for training)

    # Train the model
    model.train(data='data.yaml', epochs=2, imgsz=832, device=0)

    # Load our custom goat model
    model = YOLO("runs/detect/train/weights/best.pt")

for this I am having the NVIDIA-SMI as

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 511.69       Driver Version: 511.69       CUDA Version: 11.6     |
|-------------------------------+----------------------+----------------------+
| GPU  Name            TCC/WDDM | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  NVIDIA GeForce ... WDDM  | 00000000:01:00.0 Off |                  N/A |
| N/A   47C    P8     3W /  N/A |      0MiB /  4096MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+

I ran the following 2 codes before running the script above

conda create -n ENV_NAME python=3.7
conda activate ENV_NAME
pip install ultralytics

conda install pytorch torchvision torchaudio pytorch-cuda=11.6 -c pytorch -c nvidia
conda install cudatoolkit

but when I am running this code I am getting the following error

Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "C:\Users\aftab\.conda\envs\pytorch_env\lib\multiprocessing\spawn.py", line 116, in spawn_main
    exitcode = _main(fd, parent_sentinel)
  File "C:\Users\aftab\.conda\envs\pytorch_env\lib\multiprocessing\spawn.py", line 126, in _main
    self = reduction.pickle.load(from_parent)
MemoryError
raise err
OSError: [WinError 1455] The paging file is too small for this operation to complete. Error loading "C:\Users\aftab\.conda\envs\pytorch_env\lib\site-packages\torch\lib\cudnn_adv_infer64_8.dll" or one of its dependencies.

I have also tried to increase the memory in Advanced settings of PC till 8092 MB. What else can I do is it possible to debug this error as I want to run the YOLOV8 model on my local machine

how to resolve the error of out of memory for YOLOV8 model for model being trained on GPU in local machine

0 Answers0