Hi ptrblck,
Thank you for your kind reply.


Thanks, I will look at it.


Yes, it is ComplexBatchNorm2d 9 (and ComplexBatchNorm1D) that has this memory leak. It looks like the memory is not freed correctly, but since Python usually takes care of this for me, I do not know how to deal with such issue.


Sorry I was not very clear. No, complex NNs give me better results! Especially since I use those networks to learn from physical systems where there are internal complex variables. What does not show (obvious) significant improvements is the ComplexBatchNorm() (the batch norm that takes into account the covariance matrix between the real and imaginary part) compared to NaiveComplexBatchNorm() (which basically perform batch norm independently on the real and imaginary part). But it is likely problem dependent, I need to perform further tests once my memory issue corrected.