Time to calculate criterion / MSE

[dzimm]

I’ve analysed the run times during in training script, and it turns out (if I’ve done everything right), that calculating the criterion (torch.nn.MSELoss()) takes most of the time (factor 10 compared to forward() ).

Is there anything I can do to improve the runtime ?

[dzimm]

OK found the issue.
Apparently the gpu still works in the background and measuring your runtime only works correctly if you use torch.cuda.synchronize() :

Strange speed of tensor.sum()

Hello, all. I meet a problem that speed of function tensor.sum() is strange when calculate the same kind of Tensor. I want to calculate the confusion matrix of a foreground/background segmentation model, and below is my testing code: import time import torch def func(pr, gt): dump = 0.0 for gt_i in range(2): for pr_i in range(2): num = (gt == gt_i) * (pr == pr_i) start = time.time() dump += num.sum() print("Finding Time: {} {}…