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
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
|
============================================================
CIFAR-10 Conv-SNN Experiment
Job ID: 14363510 | Node: gpub011
Start: Mon Dec 29 10:47:15 CST 2025
============================================================
NVIDIA A40, 46068 MiB
============================================================
======================================================================
CIFAR-10 Conv-SNN Experiment
======================================================================
Model: simple
Timesteps: 25
Epochs: 50
Device: cuda
======================================================================
Loading CIFAR-10...
Train: 50000, Test: 10000
============================================================
Depth = 2 conv layers, channels = [64, 128]
============================================================
Training VANILLA...
Model: simple, params: 157,770
Epoch 1: train=0.294 test=0.387 (68.7s)
Epoch 2: train=0.363 test=0.461 (66.7s)
Epoch 3: train=0.430 test=0.510 (66.7s)
Epoch 4: train=0.508 test=0.502 (66.7s)
Epoch 5: train=0.537 test=0.575 (66.7s)
Epoch 6: train=0.560 test=0.551 (66.7s)
Epoch 7: train=0.579 test=0.577 (66.7s)
Epoch 8: train=0.592 test=0.616 (66.7s)
Epoch 9: train=0.604 test=0.620 (66.7s)
Epoch 10: train=0.615 test=0.620 (66.7s)
Epoch 11: train=0.623 test=0.637 (66.7s)
Epoch 12: train=0.633 test=0.664 (66.7s)
Epoch 13: train=0.639 test=0.660 (66.7s)
Epoch 14: train=0.647 test=0.635 (66.8s)
Epoch 15: train=0.652 test=0.679 (66.7s)
Epoch 16: train=0.657 test=0.677 (66.8s)
Epoch 17: train=0.664 test=0.678 (66.8s)
Epoch 18: train=0.669 test=0.693 (66.8s)
Epoch 19: train=0.674 test=0.697 (66.8s)
Epoch 20: train=0.677 test=0.688 (66.8s)
Epoch 21: train=0.682 test=0.705 (66.8s)
Epoch 22: train=0.681 test=0.700 (66.8s)
Epoch 23: train=0.684 test=0.708 (66.8s)
Epoch 24: train=0.691 test=0.695 (66.7s)
Epoch 25: train=0.695 test=0.708 (66.8s)
Epoch 26: train=0.696 test=0.702 (66.8s)
Epoch 27: train=0.699 test=0.713 (66.8s)
Epoch 28: train=0.703 test=0.720 (66.8s)
Epoch 29: train=0.704 test=0.718 (66.8s)
Epoch 30: train=0.706 test=0.723 (66.8s)
Epoch 31: train=0.711 test=0.736 (66.8s)
Epoch 32: train=0.711 test=0.732 (66.8s)
Epoch 33: train=0.715 test=0.733 (66.8s)
Epoch 34: train=0.717 test=0.728 (66.8s)
Epoch 35: train=0.720 test=0.730 (66.8s)
Epoch 36: train=0.723 test=0.735 (66.8s)
Epoch 37: train=0.720 test=0.727 (66.8s)
Epoch 38: train=0.726 test=0.731 (66.8s)
Epoch 39: train=0.726 test=0.739 (66.8s)
Epoch 40: train=0.728 test=0.738 (66.8s)
Epoch 41: train=0.728 test=0.738 (66.7s)
Epoch 42: train=0.730 test=0.735 (66.7s)
Epoch 43: train=0.729 test=0.737 (66.8s)
Epoch 44: train=0.731 test=0.742 (66.8s)
Epoch 45: train=0.730 test=0.750 (66.8s)
Epoch 46: train=0.733 test=0.739 (66.8s)
Epoch 47: train=0.731 test=0.748 (66.8s)
Epoch 48: train=0.731 test=0.746 (66.8s)
Epoch 49: train=0.736 test=0.747 (66.8s)
Epoch 50: train=0.735 test=0.737 (66.8s)
Best test accuracy: 0.750
Training LYAPUNOV...
Model: simple, params: 157,770
Epoch 1: train=0.290 test=0.412 λ=1.266 (177.1s)
Epoch 2: train=0.361 test=0.485 λ=1.141 (177.1s)
Epoch 3: train=0.405 test=0.508 λ=0.808 (177.0s)
Epoch 4: train=0.490 test=0.580 λ=0.641 (177.1s)
Epoch 5: train=0.532 test=0.588 λ=0.617 (177.1s)
Epoch 6: train=0.552 test=0.611 λ=0.610 (177.2s)
Epoch 7: train=0.568 test=0.632 λ=0.602 (177.1s)
Epoch 8: train=0.578 test=0.628 λ=0.600 (177.1s)
Epoch 9: train=0.590 test=0.639 λ=0.593 (177.1s)
Epoch 10: train=0.594 test=0.643 λ=0.588 (177.1s)
Epoch 11: train=0.605 test=0.662 λ=0.587 (177.1s)
Epoch 12: train=0.612 test=0.657 λ=0.585 (177.1s)
Epoch 13: train=0.615 test=0.663 λ=0.586 (177.1s)
Epoch 14: train=0.624 test=0.642 λ=0.584 (177.1s)
Epoch 15: train=0.627 test=0.673 λ=0.580 (177.1s)
Epoch 16: train=0.629 test=0.662 λ=0.582 (177.1s)
Epoch 17: train=0.636 test=0.671 λ=0.580 (177.1s)
Epoch 18: train=0.639 test=0.683 λ=0.579 (177.2s)
Epoch 19: train=0.644 test=0.673 λ=0.580 (177.2s)
Epoch 20: train=0.649 test=0.686 λ=0.581 (177.2s)
Epoch 21: train=0.650 test=0.689 λ=0.575 (177.2s)
Epoch 22: train=0.653 test=0.696 λ=0.572 (177.2s)
Epoch 23: train=0.657 test=0.695 λ=0.579 (177.2s)
Epoch 24: train=0.663 test=0.683 λ=0.574 (177.2s)
Epoch 25: train=0.662 test=0.706 λ=0.577 (177.2s)
Epoch 26: train=0.667 test=0.702 λ=0.572 (177.2s)
Epoch 27: train=0.669 test=0.701 λ=0.572 (177.2s)
Epoch 28: train=0.675 test=0.702 λ=0.572 (177.2s)
Epoch 29: train=0.675 test=0.701 λ=0.570 (177.2s)
Epoch 30: train=0.674 test=0.701 λ=0.573 (177.2s)
Epoch 31: train=0.679 test=0.718 λ=0.573 (177.2s)
Epoch 32: train=0.680 test=0.708 λ=0.569 (177.2s)
Epoch 33: train=0.684 test=0.716 λ=0.569 (177.2s)
Epoch 34: train=0.684 test=0.710 λ=0.570 (177.2s)
Epoch 35: train=0.687 test=0.719 λ=0.573 (177.2s)
Epoch 36: train=0.691 test=0.724 λ=0.573 (177.2s)
Epoch 37: train=0.692 test=0.701 λ=0.570 (177.2s)
Epoch 38: train=0.694 test=0.716 λ=0.569 (177.2s)
Epoch 39: train=0.694 test=0.726 λ=0.569 (177.2s)
Epoch 40: train=0.695 test=0.720 λ=0.569 (177.2s)
Epoch 41: train=0.697 test=0.728 λ=0.569 (177.2s)
Epoch 42: train=0.698 test=0.714 λ=0.571 (177.3s)
Epoch 43: train=0.697 test=0.719 λ=0.569 (177.2s)
Epoch 44: train=0.700 test=0.719 λ=0.571 (177.2s)
Epoch 45: train=0.699 test=0.721 λ=0.568 (177.2s)
Epoch 46: train=0.702 test=0.722 λ=0.572 (177.2s)
Epoch 47: train=0.702 test=0.727 λ=0.569 (177.2s)
Epoch 48: train=0.702 test=0.726 λ=0.571 (177.2s)
Epoch 49: train=0.701 test=0.728 λ=0.572 (177.2s)
Epoch 50: train=0.700 test=0.714 λ=0.570 (177.2s)
Best test accuracy: 0.728
============================================================
Depth = 3 conv layers, channels = [64, 128, 256]
============================================================
Training VANILLA...
Model: simple, params: 412,234
Epoch 1: train=0.293 test=0.431 (81.7s)
Epoch 2: train=0.377 test=0.464 (81.6s)
Epoch 3: train=0.449 test=0.478 (81.6s)
Epoch 4: train=0.499 test=0.577 (81.6s)
Epoch 5: train=0.563 test=0.615 (81.6s)
Epoch 6: train=0.618 test=0.665 (81.6s)
Epoch 7: train=0.642 test=0.670 (81.6s)
Epoch 8: train=0.663 test=0.693 (81.6s)
Epoch 9: train=0.679 test=0.687 (81.6s)
Epoch 10: train=0.693 test=0.715 (81.6s)
Epoch 11: train=0.704 test=0.704 (96.8s)
Epoch 12: train=0.714 test=0.701 (81.6s)
Epoch 13: train=0.718 test=0.723 (91.9s)
Epoch 14: train=0.728 test=0.734 (81.6s)
Epoch 15: train=0.734 test=0.720 (81.6s)
Epoch 16: train=0.742 test=0.730 (91.9s)
Epoch 17: train=0.748 test=0.726 (81.6s)
Epoch 18: train=0.752 test=0.754 (81.6s)
Epoch 19: train=0.758 test=0.746 (81.6s)
Epoch 20: train=0.764 test=0.760 (81.6s)
Epoch 21: train=0.770 test=0.757 (81.6s)
Epoch 22: train=0.776 test=0.756 (81.6s)
Epoch 23: train=0.781 test=0.730 (81.6s)
Epoch 24: train=0.786 test=0.752 (81.6s)
Epoch 25: train=0.790 test=0.771 (81.6s)
Epoch 26: train=0.795 test=0.772 (81.6s)
Epoch 27: train=0.796 test=0.766 (81.6s)
Epoch 28: train=0.800 test=0.760 (81.7s)
Epoch 29: train=0.804 test=0.755 (81.6s)
Epoch 30: train=0.808 test=0.754 (81.6s)
Epoch 31: train=0.810 test=0.760 (81.6s)
Epoch 32: train=0.813 test=0.771 (81.6s)
Epoch 33: train=0.817 test=0.753 (81.6s)
Epoch 34: train=0.820 test=0.784 (81.6s)
Epoch 35: train=0.819 test=0.779 (81.6s)
Epoch 36: train=0.823 test=0.773 (81.6s)
Epoch 37: train=0.823 test=0.773 (81.6s)
Epoch 38: train=0.829 test=0.778 (81.6s)
Epoch 39: train=0.831 test=0.776 (81.9s)
Epoch 40: train=0.832 test=0.785 (81.7s)
Epoch 41: train=0.831 test=0.787 (81.6s)
Epoch 42: train=0.835 test=0.780 (81.6s)
Epoch 43: train=0.836 test=0.775 (81.6s)
Epoch 44: train=0.838 test=0.779 (81.6s)
Epoch 45: train=0.837 test=0.774 (81.6s)
Epoch 46: train=0.837 test=0.777 (81.6s)
Epoch 47: train=0.839 test=0.796 (81.6s)
Epoch 48: train=0.840 test=0.775 (81.7s)
Epoch 49: train=0.839 test=0.776 (81.6s)
Epoch 50: train=0.837 test=0.777 (81.6s)
Best test accuracy: 0.796
Training LYAPUNOV...
Model: simple, params: 412,234
Epoch 1: train=0.268 test=0.346 λ=1.850 (219.1s)
Epoch 2: train=0.321 test=0.407 λ=1.465 (219.1s)
Epoch 3: train=0.381 test=0.417 λ=1.248 (219.1s)
Epoch 4: train=0.419 test=0.461 λ=1.133 (219.1s)
Epoch 5: train=0.445 test=0.511 λ=1.062 (219.1s)
Epoch 6: train=0.483 test=0.564 λ=0.977 (219.1s)
Epoch 7: train=0.517 test=0.573 λ=0.942 (219.0s)
Epoch 8: train=0.532 test=0.581 λ=0.921 (219.1s)
Epoch 9: train=0.539 test=0.596 λ=0.909 (219.1s)
Epoch 10: train=0.549 test=0.601 λ=0.907 (219.1s)
Epoch 11: train=0.557 test=0.610 λ=0.902 (219.0s)
Epoch 12: train=0.568 test=0.611 λ=0.897 (219.1s)
Epoch 13: train=0.574 test=0.612 λ=0.900 (219.1s)
Epoch 14: train=0.579 test=0.622 λ=0.894 (219.1s)
Epoch 15: train=0.580 test=0.627 λ=0.895 (219.1s)
Epoch 16: train=0.586 test=0.637 λ=0.890 (219.1s)
Epoch 17: train=0.592 test=0.645 λ=0.891 (219.1s)
Epoch 18: train=0.593 test=0.638 λ=0.889 (219.1s)
Epoch 19: train=0.599 test=0.641 λ=0.887 (219.0s)
Epoch 20: train=0.603 test=0.644 λ=0.883 (219.0s)
Epoch 21: train=0.606 test=0.645 λ=0.879 (219.1s)
Epoch 22: train=0.610 test=0.655 λ=0.882 (219.1s)
Epoch 23: train=0.612 test=0.649 λ=0.888 (219.1s)
Epoch 24: train=0.616 test=0.649 λ=0.878 (219.1s)
Epoch 25: train=0.619 test=0.661 λ=0.885 (219.1s)
Epoch 26: train=0.622 test=0.657 λ=0.882 (219.1s)
Epoch 27: train=0.626 test=0.662 λ=0.881 (219.1s)
Epoch 28: train=0.627 test=0.662 λ=0.875 (219.1s)
Epoch 29: train=0.627 test=0.660 λ=0.882 (219.1s)
Epoch 30: train=0.634 test=0.672 λ=0.879 (219.1s)
Epoch 31: train=0.633 test=0.673 λ=0.879 (219.2s)
Epoch 32: train=0.637 test=0.674 λ=0.877 (219.2s)
Epoch 33: train=0.639 test=0.664 λ=0.880 (219.2s)
Epoch 34: train=0.640 test=0.677 λ=0.883 (219.1s)
Epoch 35: train=0.639 test=0.674 λ=0.877 (219.1s)
Epoch 36: train=0.645 test=0.678 λ=0.877 (219.1s)
Epoch 37: train=0.645 test=0.665 λ=0.878 (219.1s)
Epoch 38: train=0.644 test=0.669 λ=0.875 (219.1s)
Epoch 39: train=0.649 test=0.673 λ=0.877 (219.1s)
Epoch 40: train=0.648 test=0.680 λ=0.876 (219.1s)
Epoch 41: train=0.651 test=0.674 λ=0.878 (219.1s)
Epoch 42: train=0.649 test=0.679 λ=0.881 (219.1s)
Epoch 43: train=0.651 test=0.676 λ=0.873 (219.1s)
Epoch 44: train=0.650 test=0.680 λ=0.878 (219.1s)
Epoch 45: train=0.649 test=0.684 λ=0.875 (219.1s)
Epoch 46: train=0.652 test=0.682 λ=0.882 (219.1s)
Epoch 47: train=0.653 test=0.681 λ=0.876 (219.1s)
Epoch 48: train=0.650 test=0.684 λ=0.876 (219.1s)
Epoch 49: train=0.653 test=0.679 λ=0.872 (219.1s)
Epoch 50: train=0.653 test=0.679 λ=0.877 (219.1s)
Best test accuracy: 0.684
============================================================
Depth = 4 conv layers, channels = [64, 128, 256, 512]
============================================================
Training VANILLA...
Model: simple, params: 1,572,426
Epoch 1: train=0.293 test=0.421 (91.2s)
Epoch 2: train=0.406 test=0.522 (91.1s)
Epoch 3: train=0.490 test=0.491 (91.1s)
Epoch 4: train=0.543 test=0.591 (91.2s)
Epoch 5: train=0.598 test=0.635 (91.1s)
Epoch 6: train=0.637 test=0.648 (91.2s)
Epoch 7: train=0.671 test=0.657 (91.1s)
Epoch 8: train=0.696 test=0.683 (91.2s)
Epoch 9: train=0.714 test=0.688 (91.1s)
Epoch 10: train=0.731 test=0.686 (91.1s)
Epoch 11: train=0.742 test=0.730 (91.2s)
Epoch 12: train=0.755 test=0.718 (91.1s)
Epoch 13: train=0.763 test=0.707 (91.2s)
Epoch 14: train=0.775 test=0.723 (91.1s)
Epoch 15: train=0.781 test=0.748 (91.1s)
Epoch 16: train=0.787 test=0.730 (91.2s)
Epoch 17: train=0.795 test=0.694 (91.1s)
Epoch 18: train=0.802 test=0.716 (91.1s)
Epoch 19: train=0.808 test=0.759 (91.1s)
Epoch 20: train=0.815 test=0.751 (91.2s)
Epoch 21: train=0.822 test=0.756 (91.1s)
Epoch 22: train=0.825 test=0.748 (91.1s)
Epoch 23: train=0.835 test=0.743 (91.2s)
Epoch 24: train=0.837 test=0.762 (91.1s)
Epoch 25: train=0.843 test=0.751 (91.1s)
Epoch 26: train=0.845 test=0.763 (91.1s)
Epoch 27: train=0.852 test=0.782 (91.1s)
Epoch 28: train=0.858 test=0.760 (91.1s)
Epoch 29: train=0.862 test=0.774 (91.1s)
Epoch 30: train=0.865 test=0.766 (91.1s)
Epoch 31: train=0.868 test=0.748 (91.1s)
Epoch 32: train=0.870 test=0.776 (91.1s)
Epoch 33: train=0.876 test=0.763 (91.1s)
Epoch 34: train=0.880 test=0.766 (91.1s)
Epoch 35: train=0.883 test=0.768 (91.1s)
Epoch 36: train=0.887 test=0.772 (91.1s)
Epoch 37: train=0.891 test=0.767 (91.2s)
Epoch 38: train=0.890 test=0.773 (91.1s)
Epoch 39: train=0.894 test=0.774 (91.1s)
Epoch 40: train=0.893 test=0.757 (91.1s)
Epoch 41: train=0.899 test=0.773 (91.1s)
Epoch 42: train=0.900 test=0.787 (91.1s)
Epoch 43: train=0.902 test=0.764 (91.1s)
Epoch 44: train=0.901 test=0.778 (91.1s)
Epoch 45: train=0.904 test=0.754 (91.0s)
Epoch 46: train=0.905 test=0.786 (91.1s)
Epoch 47: train=0.906 test=0.775 (91.1s)
Epoch 48: train=0.906 test=0.790 (91.1s)
Epoch 49: train=0.906 test=0.778 (91.1s)
Epoch 50: train=0.907 test=0.785 (91.0s)
Best test accuracy: 0.790
Training LYAPUNOV...
Model: simple, params: 1,572,426
Epoch 1: train=0.226 test=0.341 λ=2.642 (243.8s)
Epoch 2: train=0.238 test=0.338 λ=1.931 (243.8s)
Epoch 3: train=0.249 test=0.292 λ=1.659 (243.8s)
Epoch 4: train=0.257 test=0.327 λ=1.510 (243.8s)
Epoch 5: train=0.265 test=0.313 λ=1.386 (243.8s)
Epoch 6: train=0.282 test=0.349 λ=1.291 (243.8s)
Epoch 7: train=0.320 test=0.367 λ=1.211 (243.8s)
Epoch 8: train=0.342 test=0.389 λ=1.171 (243.9s)
Epoch 9: train=0.355 test=0.392 λ=1.157 (243.8s)
Epoch 10: train=0.361 test=0.396 λ=1.140 (243.7s)
Epoch 11: train=0.362 test=0.393 λ=1.139 (243.8s)
Epoch 12: train=0.367 test=0.398 λ=1.131 (243.8s)
Epoch 13: train=0.370 test=0.417 λ=1.123 (243.8s)
Epoch 14: train=0.373 test=0.420 λ=1.124 (243.8s)
Epoch 15: train=0.378 test=0.409 λ=1.120 (243.8s)
Epoch 16: train=0.379 test=0.408 λ=1.119 (243.8s)
Epoch 17: train=0.382 test=0.422 λ=1.117 (243.8s)
Epoch 18: train=0.382 test=0.419 λ=1.120 (243.8s)
Epoch 19: train=0.386 test=0.421 λ=1.119 (243.8s)
Epoch 20: train=0.388 test=0.421 λ=1.121 (243.8s)
Epoch 21: train=0.391 test=0.433 λ=1.127 (243.8s)
Epoch 22: train=0.395 test=0.436 λ=1.130 (243.8s)
Epoch 23: train=0.396 test=0.441 λ=1.125 (243.9s)
Epoch 24: train=0.398 test=0.437 λ=1.129 (243.8s)
Epoch 25: train=0.400 test=0.437 λ=1.136 (243.9s)
Epoch 26: train=0.399 test=0.438 λ=1.141 (243.8s)
Epoch 27: train=0.405 test=0.428 λ=1.137 (243.8s)
Epoch 28: train=0.407 test=0.441 λ=1.143 (243.8s)
Epoch 29: train=0.405 test=0.450 λ=1.139 (243.8s)
Epoch 30: train=0.410 test=0.443 λ=1.139 (243.8s)
Epoch 31: train=0.413 test=0.446 λ=1.139 (243.8s)
Epoch 32: train=0.418 test=0.453 λ=1.138 (243.8s)
Epoch 33: train=0.416 test=0.455 λ=1.138 (243.9s)
Epoch 34: train=0.419 test=0.455 λ=1.139 (243.8s)
Epoch 35: train=0.417 test=0.459 λ=1.138 (243.8s)
Epoch 36: train=0.420 test=0.459 λ=1.141 (243.8s)
Epoch 37: train=0.421 test=0.458 λ=1.139 (243.8s)
Epoch 38: train=0.425 test=0.452 λ=1.140 (243.8s)
Epoch 39: train=0.425 test=0.457 λ=1.135 (243.8s)
Epoch 40: train=0.424 test=0.458 λ=1.141 (243.9s)
Epoch 41: train=0.429 test=0.461 λ=1.138 (243.8s)
Epoch 42: train=0.428 test=0.461 λ=1.134 (243.8s)
Epoch 43: train=0.427 test=0.457 λ=1.136 (244.0s)
Epoch 44: train=0.431 test=0.461 λ=1.136 (243.8s)
Epoch 45: train=0.431 test=0.462 λ=1.138 (243.8s)
Epoch 46: train=0.432 test=0.460 λ=1.139 (243.8s)
Epoch 47: train=0.431 test=0.467 λ=1.142 (243.8s)
Epoch 48: train=0.432 test=0.470 λ=1.136 (243.8s)
Epoch 49: train=0.430 test=0.462 λ=1.136 (243.8s)
Epoch 50: train=0.430 test=0.463 λ=1.142 (243.8s)
Best test accuracy: 0.470
======================================================================
SUMMARY: CIFAR-10 Conv-SNN Results
======================================================================
Depth Vanilla Lyapunov Improvement
----------------------------------------------------------------------
2 0.737 0.714 -0.023
3 0.777 0.679 -0.098
4 0.785 0.463 -0.323
======================================================================
Results saved to runs/cifar10_conv/20251229-230105
============================================================
Finished: Mon Dec 29 23:01:08 CST 2025
============================================================
|
