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"""
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Threshold Network for All-out-of-8 Gate (8-input AND)
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A formally verified single-neuron threshold network.
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Outputs 1 only when all 8 inputs are true.
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Equivalent to an 8-input AND gate.
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"""
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import torch
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from safetensors.torch import load_file
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class ThresholdAllOutOf8:
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"""
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All-out-of-8 threshold gate (8-input AND).
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Circuit: output = (sum of inputs - 8 >= 0)
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Fires only when hamming weight = 8.
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"""
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def __init__(self, weights_dict):
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self.weight = weights_dict['weight']
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self.bias = weights_dict['bias']
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def __call__(self, bits):
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inputs = torch.tensor([float(b) for b in bits])
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weighted_sum = (inputs * self.weight).sum() + self.bias
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return (weighted_sum >= 0).float()
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@classmethod
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def from_safetensors(cls, path="model.safetensors"):
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return cls(load_file(path))
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if __name__ == "__main__":
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weights = load_file("model.safetensors")
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model = ThresholdAllOutOf8(weights)
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print("All-out-of-8 Gate Tests:")
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print("-" * 35)
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for hw in range(9):
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bits = [1]*hw + [0]*(8-hw)
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out = int(model(bits).item())
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expected = 1 if hw >= 8 else 0
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status = "OK" if out == expected else "FAIL"
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print(f"HW={hw}: {out} [{status}]")
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