Loss divided by accumulate_grad_batches
number
#5680
Labels
bug
Something isn't working
help wanted
Open to be worked on
logging
Related to the `LoggerConnector` and `log()`
priority: 0
High priority task
waiting on author
Waiting on user action, correction, or update
🐛 Bug
After the 1.1.4 with the fix 5417, logging was fixed but my loss was divided by
accumulate_grad_batches
.Please reproduce using the BoringModel
Sorry, there is no BoringModel. I paste my code here
To Reproduce
I use DDP with manual backward.
If I used my environment w pl=1.1.0 or
accumulate_grad_batches
=1 (version 1.1.6), the loss is around 11 at first:If I used
accummulate_grad_batches
=3, the loss is divided by 3:Expected behavior
Loss should not be divided.
I guess 1.1.3 and before, train_loop sums all loss then average. Now it divides by
accumulate_grad_batches
then sum.Environment
conda
,pip
, source): condaThe text was updated successfully, but these errors were encountered: