"""
Threshold Network for MOD-8 Circuit

A formally verified threshold network computing Hamming weight mod 8.
Uses the algebraic weight pattern [1, 1, 1, 1, 1, 1, 1, -7].
"""

import torch
from safetensors.torch import load_file


class ThresholdMod8:
    def __init__(self, weights_dict):
        self.weight = weights_dict['weight']
        self.bias = weights_dict['bias']

    def __call__(self, bits):
        inputs = torch.tensor([float(b) for b in bits])
        weighted_sum = (inputs * self.weight).sum() + self.bias
        return weighted_sum

    @classmethod
    def from_safetensors(cls, path="model.safetensors"):
        return cls(load_file(path))


if __name__ == "__main__":
    weights = load_file("model.safetensors")
    model = ThresholdMod8(weights)

    print("MOD-8 Circuit Tests:")
    for hw in range(9):
        bits = [1]*hw + [0]*(8-hw)
        out = model(bits).item()
        print(f"HW={hw}: weighted_sum={out:.0f}, HW mod 8 = {hw % 8}")