By model architecture, I'm interested in knowing the following:
- Number of nodes in input layer
- Number of nodes in subsequent layers
- Number of layers in the architecture
- Number of filters and kernels in each layer
For more context, I'm creating a ConvWTA that previously took in 32x32 images but now I'm modifying the model to take in 16x16 images and I'm not exactly sure about how I should go about modifying the architecture/whether this needs to be done in the first place other than the input layer. I also want to include a bottleneck in the model so I'm planning out the architecture but would appreciate some guidance or resources.