from kan import KAN import torch # Create a KAN with 2 inputs, 5 hidden neurons, and 1 output model = KAN(width=[2, 5, 1], grid=5, k=3) # Training follows a standard loop structure # model.train(dataset, opt="LBFGS", steps=20) Use code with caution. Copied to clipboard
A basic setup for a KAN involves importing the library and defining the layer structure: kan.py
While more parameter-efficient for some tasks, the current implementation is often slower than optimized MLPs. from kan import KAN import torch # Create