Thanks for your readiness to help!
For me, the use case is to have a functionality to visualize (or at least print) the layers of an architecture.
Say I'd like to use some fancy architecture for the neural network powering my policy, built out of CNNs and MLPs. Usually, I can summarize the architecture (and the amount of parameters of each layer) for usual torch models using a simple print(model) statement, and that's also what is promised by the documentation (down at examples). However, there are also other packages such as torchinfo which can do this. For more advanced visualization, you can use the onnx export and load it into other tools to get some graphical representation.

I understand that the onnx export might be the most difficult (although also the most beautiful one), but perhaps some kind of print summary would be helpful, to see of which layers (with how many parameters) a model (module) consists of?
Actually what the examples states would already be sufficient (at least for me :D ):

>>> print(cnn)
MultiAgentConvNet(
 (agent_networks): ModuleList(
 (0): ConvNet(
 (0): Conv2d(4, 32, kernel_size=(5, 5), stride=(2, 2))
 (1): ELU(alpha=1.0)
 (2): Conv2d(32, 32, kernel_size=(5, 5), stride=(2, 2))
 (3): ELU(alpha=1.0)
 (4): Conv2d(32, 32, kernel_size=(5, 5), stride=(2, 2))
 (5): ELU(alpha=1.0)
 (6): SquashDims()
 )
 )
)