Inconsistencies in ADE20K model inference output for the same input image.
MartaFdez97 opened this issue · 3 comments
MartaFdez97 commented
Hello,
I am doing inference with the ade20k model and I am seeing that for the same input, I get a different output. I have saved the data and model variables to be always the same and yet I still have variability. Why does this happen? Also, I have removed the rescale.
My code:
import pickle
with open('data.pkl', 'rb') as f:
data = pickle.load(f)
with open('model.pkl', 'rb') as f:
model = pickle.load(f)
# forward the model
with torch.no_grad():
result = model(return_loss=False, rescale=False, **data)
return result
uyzhang commented
There is a random reasoning part in ham_head, which may fluctuate slightly, but it exists.
MartaFdez97 commented
It fluctuates even if the weights are the fixed? I do not get how can It be possible