"""
Threshold Network for All-out-of-8 Gate (8-input AND)

A formally verified single-neuron threshold network.
Outputs 1 only when all 8 inputs are true.
Equivalent to an 8-input AND gate.
"""

import torch
from safetensors.torch import load_file


class ThresholdAllOutOf8:
    """
    All-out-of-8 threshold gate (8-input AND).

    Circuit: output = (sum of inputs - 8 >= 0)
    Fires only when hamming weight = 8.
    """

    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 >= 0).float()

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


if __name__ == "__main__":
    weights = load_file("model.safetensors")
    model = ThresholdAllOutOf8(weights)

    print("All-out-of-8 Gate Tests:")
    print("-" * 35)
    for hw in range(9):
        bits = [1]*hw + [0]*(8-hw)
        out = int(model(bits).item())
        expected = 1 if hw >= 8 else 0
        status = "OK" if out == expected else "FAIL"
        print(f"HW={hw}: {out}  [{status}]")