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792dec0 | 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 | """Standard-library inference for the exported protected ReLU head.
Run: python predict.py -0.8 -0.2 0 0.2 0.8
The reported error bound is conditional on the stored finite-data contract.
The batch-throughput study used NumPy; its timings do not describe this CLI.
"""
from pathlib import Path
import json,sys
from fractions import Fraction
def load_model(path=None):
path=Path(path) if path else Path(__file__).with_name('relu_head_example.json')
return json.loads(path.read_text())
def predict(x,model):
# Exact rational evaluation preserves the exported mathematical model.
z=Fraction(x)
head=Fraction(model['exact_head_bias'])+sum(
Fraction(w)*max(Fraction(0),z-Fraction(k))
for k,w in zip(model['exact_hinge_knots'],model['exact_hinge_weights']))
return float(abs(z)*head)
if __name__=='__main__':
model=load_model();points=[float(x) for x in sys.argv[1:]] or [-.8,-.2,0.,.2,.8]
print(json.dumps([{'x':x,'residual':predict(x,model),
'conditional_error_bound':model['conditional_uniform_error_bound'] if -1<=x<=1 else None}
for x in points],indent=2))
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