How to process the first conv layer in network?

LAYERS is set to "features" in the default rundissect_pytorch.sh, and after run rundissect_pytorch.sh, I will see the visualized results about the all 256 units from probes/pytorch_alexnet_imagenet/features.html.
My question is if I want to see the scores of the first conv layer in network(such as alexnet) with 64 units, what should I do.
If I need to make some changes to LAYERS in rundissect_pytorch.sh or do something else?
I would be appreciate if the author could clear my confusion.
THANKS!

Start with rundissect_pytorch.sh and inspect how the LAYERS setting maps to the generated probes/pytorch_alexnet_imagenet/features.html output. Check the repository's PyTorch layer-dissection entry points and existing documentation for selecting individual layers. Done means documenting the steps needed to view scores for the first convolutional layer and its 64 units.

索引モデルが issue の本文から書いたものです。