import torch
from safetensors.torch import load_file

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

def reverse4(a3, a2, a1, a0, w):
    """Reverse bit order of 4-bit input."""
    inp = torch.tensor([float(a3), float(a2), float(a1), float(a0)])
    y3 = int((inp @ w['y3.weight'].T + w['y3.bias'] >= 0).item())
    y2 = int((inp @ w['y2.weight'].T + w['y2.bias'] >= 0).item())
    y1 = int((inp @ w['y1.weight'].T + w['y1.bias'] >= 0).item())
    y0 = int((inp @ w['y0.weight'].T + w['y0.bias'] >= 0).item())
    return [y3, y2, y1, y0]

if __name__ == '__main__':
    w = load_model()
    print('reverse4 examples:')
    for val in [0b0001, 0b1000, 0b0110, 0b1010, 0b1111]:
        a3, a2, a1, a0 = (val >> 3) & 1, (val >> 2) & 1, (val >> 1) & 1, val & 1
        result = reverse4(a3, a2, a1, a0, w)
        print(f'  {a3}{a2}{a1}{a0} -> {"".join(map(str, result))}')