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import torch
from safetensors.torch import load_file
def load_model(path='model.safetensors'):
return load_file(path)
def signbit8(a7, a6, a5, a4, a3, a2, a1, a0, weights):
"""Returns sign bit (MSB) of 8-bit number. 1 = negative in 2's complement."""
inp = torch.tensor([float(a7), float(a6), float(a5), float(a4),
float(a3), float(a2), float(a1), float(a0)])
return int((inp @ weights['neuron.weight'].T + weights['neuron.bias'] >= 0).item())
if __name__ == '__main__':
w = load_model()
print('signbit8 selected tests:')
for i in [0, 1, 127, 128, 255]:
bits = [(i >> (7-j)) & 1 for j in range(8)]
result = signbit8(*bits, w)
signed_val = i if i < 128 else i - 256
print(f' {i:3d} ({i:08b}) signed={signed_val:+4d} -> sign={result}')
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