ResNet encoder difference

[Malitha123]

Hi,

Just out of curiosity, what is the fundamental difference between the ResEnc M, ResEnc L and ResEnc XL in architecture wise? Does it change the depth of the network?

[GregorKoehler]

Hi,

unfortunately, I can't give a concise answer to this, but in this file you can follow the algorithm for how the plans are set for a given configuration:
https://github.com/MIC-DKFZ/nnUNet/blob/master/nnunetv2/experiment_planning/experiment_planners/residual_unets/residual_encoder_unet_planners.py

Look at the get_plans_for_configuration method and what changes for the M / L / XL configurations (hint: UNet_reference_val_2d / UNet_reference_val_3d).

If that doesn't help, I'd propose creating plans for the individual configurations (M / L / XL) in your case (dataset) and looking at the plans differences.

A rough overview would be:
For determining the network topology, this function is used:
https://github.com/MIC-DKFZ/nnUNet/blob/master/nnunetv2/experiment_planning/experiment_planners/network_topology.py#L30

The above-mentioned get_plans_for_configuration progressively reduces the patch size to match the target GPU memory estimate and adapts the topology following get_pool_and_conv_props.

I hope this helps!

[Malitha123]

Thank you for your response. I will take a look

[GregorKoehler]

In order to not have this issue stale for a while, I'll close it for now. Feel free to re-open if questions arise which can't be answered from the documentation.