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import torch
from safetensors.torch import load_file
def load_model(path='model.safetensors'):
return load_file(path)
def reverse8(a7, a6, a5, a4, a3, a2, a1, a0, weights):
"""8-bit bit reversal."""
inp = torch.tensor([float(a7), float(a6), float(a5), float(a4),
float(a3), float(a2), float(a1), float(a0)])
outputs = []
for i in range(8):
y = int((inp @ weights[f'y{i}.weight'].T + weights[f'y{i}.bias'] >= 0).item())
outputs.append(y)
return outputs
if __name__ == '__main__':
w = load_model()
print('reverse8 examples:')
test_cases = [
(1, 0, 0, 0, 0, 0, 0, 0),
(0, 0, 0, 0, 0, 0, 0, 1),
(1, 0, 1, 0, 0, 1, 0, 1),
]
for bits in test_cases:
result = reverse8(*bits, w)
print(f' {list(bits)} -> {result}')
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