Can configure efficient-kan model for continual learning?

[lukmanulhakeem97]

Similar like what authors shown in official git repo, can use this efficient-kan model for continual learning settings. . For using efficient-kan for CL settings, I haven't found some attributes that need to be set given in official pykan;

######### cl code from pykan

setting bias_trainable=False, sp_trainable=False, sb_trainable=False is important.

otherwise KAN will have random scaling and shift for samples in previous stages

model = KAN(width=[1,1], grid=200, k=3, noise_scale=0.1, bias_trainable=False, sp_trainable=False, sb_trainable=False)

how can I set bias_trainable=False, sp_trainable=False, sb_trainable=False here, is there a way?