Struggling with SVCCA in machine learning. Any tips are highly appreciated #pytorch #machinelearning https://discuss.pytorch.org/t/svcca-on-lstm-output/58096
SVCCA on LSTM output

Hi everyone, I am kind of a newbie to PyTorch and ML. I have been trying to check for nodes correlation using the svcca module from google here. The examples work well and if I try to use random tensors converted into np arrays I’m able to get the svcca values. I then tried to get the activations from a layer of an LSTM net by adding a self.activations variable to the model, which saves the activations of the LSTM layer output. def forward(self, text): embedded = self.embedding(...

@semordnilap don't have experience with SVCCA but from other Python stuff it's often matrix shapes, or other incorrect input.

(ranting a little)Imho libraries should try catch it earlier.. (also lower the LOC.. cant the documentation be separated..)

@jasper The weird thing is that matrices randomly generated with the same sizes don't return this error. It must be something in the preprocessing, probably the svd or even earlier in the preprocess.

@semordnilap hmm searching https://duckduckgo.com/?q=DLASCL+parameter&t=h_&ia=web it might be there is a NaN in your input or generated somewhere?

Also see there is a `verbose` option https://github.com/google/svcca/blob/master/cca_core.py#L217 it seems possible it'll print something.

More paranoidly... presumably it behaves the same if one of the `a`s is a copy.

DLASCL parameter at DuckDuckGo