import torch
from safetensors.torch import load_file

def load_model(path='model.safetensors'):
    return load_file(path)

def buffer4(x3, x2, x1, x0, weights):
    """4-bit buffer (identity function)."""
    inp = torch.tensor([float(x3), float(x2), float(x1), float(x0)])

    y0 = int((inp @ weights['y0.weight'].T + weights['y0.bias'] >= 0).item())
    y1 = int((inp @ weights['y1.weight'].T + weights['y1.bias'] >= 0).item())
    y2 = int((inp @ weights['y2.weight'].T + weights['y2.bias'] >= 0).item())
    y3 = int((inp @ weights['y3.weight'].T + weights['y3.bias'] >= 0).item())

    return y3, y2, y1, y0

if __name__ == '__main__':
    w = load_model()
    print('4-bit Buffer:')
    for i in [0, 5, 10, 15]:
        x3, x2, x1, x0 = (i >> 3) & 1, (i >> 2) & 1, (i >> 1) & 1, i & 1
        y3, y2, y1, y0 = buffer4(x3, x2, x1, x0, w)
        print(f'  {x3}{x2}{x1}{x0} -> {y3}{y2}{y1}{y0}')