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"""
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Threshold Network for 4-input NOR 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 ThresholdNOR4:
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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, x1, x2, x3, x4):
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inputs = torch.tensor([float(x1), float(x2), float(x3), float(x4)])
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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 = ThresholdNOR4(weights)
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print("4-input NOR Gate Truth Table:")
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print("-" * 35)
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correct = 0
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for x1 in [0, 1]:
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for x2 in [0, 1]:
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for x3 in [0, 1]:
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for x4 in [0, 1]:
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out = int(model(x1, x2, x3, x4).item())
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expected = 1 - (x1 | x2 | x3 | x4)
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status = "OK" if out == expected else "FAIL"
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if out == expected:
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correct += 1
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print(f"NOR4({x1}, {x2}, {x3}, {x4}) = {out} [{status}]")
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print(f"\nTotal: {correct}/16 correct")
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