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a8fa237 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | import torch
from safetensors.torch import load_file
def load_model(path='model.safetensors'):
return load_file(path)
def thermometer_to_binary(therm, weights):
"""Convert 7-bit thermometer to 3-bit binary.
Returns (b2, b1, b0).
"""
t = torch.tensor([float(x) for x in therm])
# b2 = t3 (direct)
b2 = int((t * weights['b2.weight']).sum() + weights['b2.bias'] >= 0)
# b1 = (t1 AND NOT(t3)) OR t5
and_result = int((t * weights['b1_and.weight']).sum() + weights['b1_and.bias'] >= 0)
b1_inputs = torch.tensor([float(and_result), float(therm[5])])
b1 = int((b1_inputs * weights['b1_or.weight']).sum() + weights['b1_or.bias'] >= 0)
# b0 = (t0 AND NOT(t1)) OR (t2 AND NOT(t3)) OR (t4 AND NOT(t5)) OR t6
and0 = int((t * weights['b0_and0.weight']).sum() + weights['b0_and0.bias'] >= 0)
and2 = int((t * weights['b0_and2.weight']).sum() + weights['b0_and2.bias'] >= 0)
and4 = int((t * weights['b0_and4.weight']).sum() + weights['b0_and4.bias'] >= 0)
b0_inputs = torch.tensor([float(and0), float(and2), float(and4), float(therm[6])])
b0 = int((b0_inputs * weights['b0_or.weight']).sum() + weights['b0_or.bias'] >= 0)
return b2, b1, b0
if __name__ == '__main__':
w = load_model()
print('Thermometer to Binary Converter')
thermometers = [
[0,0,0,0,0,0,0], [1,0,0,0,0,0,0], [1,1,0,0,0,0,0], [1,1,1,0,0,0,0],
[1,1,1,1,0,0,0], [1,1,1,1,1,0,0], [1,1,1,1,1,1,0], [1,1,1,1,1,1,1],
]
for therm in thermometers:
b2, b1, b0 = thermometer_to_binary(therm, w)
print(f"{''.join(map(str,therm))} -> {b2*4 + b1*2 + b0}")
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