File size: 1,082 Bytes
5937f23 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 |
import torch
from safetensors.torch import load_file
def load_model(path='model.safetensors'):
return load_file(path)
def encode8to3(i7, i6, i5, i4, i3, i2, i1, i0, weights):
"""Priority encoder: returns binary index of highest-set input."""
inp = torch.tensor([float(i7), float(i6), float(i5), float(i4),
float(i3), float(i2), float(i1), float(i0)])
y2 = int((inp @ weights['y2.weight'].T + weights['y2.bias'] >= 0).item())
y1 = int((inp @ weights['y1.weight'].T + weights['y1.bias'] >= 0).item())
y0 = int((inp @ weights['y0.weight'].T + weights['y0.bias'] >= 0).item())
return y2, y1, y0
if __name__ == '__main__':
w = load_model()
print('8-to-3 Priority Encoder examples:')
for val in [0b10000000, 0b01000000, 0b00100000, 0b00010000,
0b00001000, 0b00000100, 0b00000010, 0b00000001, 0b11111111]:
bits = [(val >> (7-i)) & 1 for i in range(8)]
y2, y1, y0 = encode8to3(*bits, w)
print(f' I={"".join(map(str,bits))} -> {y2}{y1}{y0} (={4*y2+2*y1+y0})')
|