Hi @ypsoh, I also met the OOM problem with global pruning. This is strange but the GPU free memory does seem to drop after I call global pruning (not every time). How did you manage to change it to normal pruning for all the parameters?
@Michela
Here is a minimal example of iteratively calling global_pruning and training the model for a few steps after pruning: https://colab.research.google.com/drive/14t8E_17NuOY46iOwuB_TDTVUn-SVvh1a?usp=sharing 6
You can see the used GPU memory increases after each prune.
If I remove the training steps, the memory does not increase. So I guess the problem comes from training the model? But why this is a problem.