I have trained a vision model on custom data on GPU(NVIDIA GeForce RTX 3060-12gig) using Fastai - 2.5.3. when I deployed that model in production on GPU(tesla 32 gig/ Cuda-10.2) for continuous predictions I noticed that that model is loaded on GPU but using my CPU as well on the server. so I tested that locally and the result was the same it was using both GPU and CPU on prediction.
so my question is. did I miss something or is there any problem with drivers?
model = load_learner(f’ai/fastai_recog.pkl’, cpu=False)
image_path = ‘path/to/image.jpg’
if ‘http’ in image_path:
with model.no_bar(): preds = model.predict(requests.get(image_path, stream=True).content)
with model.no_bar(): preds = model.predict(open(image_path, ‘rb’).read())