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