Closed 2nayk closed 3 years ago
Hi @2nayk! Thanks so much for checking out lucent
! The activations
attribute seen in the Activation Atlas notebook is actually obtained by iterating over ImageNet samples (see the docstring in https://github.com/tensorflow/lucid/blob/master/lucid/modelzoo/aligned_activations.py). Unfortunately as of now, lucent
has no support for this and I am busy at the moment so I probably won't have time to build this feature. But I'll be happy to merge any PRs that would help lucent
support this!
Hello @greentfrapp. Thank you so much for looking into this and sending me the relevant link. For the time being, I will follow the lucid code for my dataset :)
Hi, thanks for this great library! I'm trying to reproduce the Activation Atlas notebook using lucent, creating grid cells in the end.
In the notebook, "raw activation" is available in a numpy.ndarray format by "model.layers[7].activations" to utilise in the next Dimensionality reduction section. How can I get this raw activation using lucent?
I did create visualised images using lucent render_vis first, and then flattened them to use UMAP fit method, but I'm not sure this is correct. Any suggestion would be appreciated.