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.

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