CUDA out of memory.

[FiorenzoParascandolo1]

Hi,
I'm using KANLinear in my own project. I have a problem of CUDA out of memory.
Specifically:

• the model A uses a unique MLP layer (1 and only 1 MLP layer in the whole network) to map a (160, 8, 197, 197) vector in a (160, 8, 197, 197) vector.
• the model B uses a unique KANLinear layer (1 and only 1 KANLinear layer in the whole network) to map a (160, 8, 197, 197) vector in a (160, 8, 197, 197) vector.

The "whole network" is a transformer based on MLP both for model A and model B.
The model A uses the 60% of the VRAM of a GPU with 24GB of VRAM, while the second model shows CUDA out of memory problem. Since the difference in the number of parameters for the two models is negligible:
the difference is equal to the difference between a single nn.Linear(197, 197) and a single KanLinear(197, 197), how is it possible to have a CUDA out of memory problem?