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import torch
from safetensors.torch import load_file
def load_model(path='model.safetensors'):
return load_file(path)
def reverse4(a3, a2, a1, a0, w):
"""Reverse bit order of 4-bit input."""
inp = torch.tensor([float(a3), float(a2), float(a1), float(a0)])
y3 = int((inp @ w['y3.weight'].T + w['y3.bias'] >= 0).item())
y2 = int((inp @ w['y2.weight'].T + w['y2.bias'] >= 0).item())
y1 = int((inp @ w['y1.weight'].T + w['y1.bias'] >= 0).item())
y0 = int((inp @ w['y0.weight'].T + w['y0.bias'] >= 0).item())
return [y3, y2, y1, y0]
if __name__ == '__main__':
w = load_model()
print('reverse4 examples:')
for val in [0b0001, 0b1000, 0b0110, 0b1010, 0b1111]:
a3, a2, a1, a0 = (val >> 3) & 1, (val >> 2) & 1, (val >> 1) & 1, val & 1
result = reverse4(a3, a2, a1, a0, w)
print(f' {a3}{a2}{a1}{a0} -> {"".join(map(str, result))}')
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