From cd99d6b874d9d09b3bb87b8485cc787885af71f1 Mon Sep 17 00:00:00 2001
From: YurenHao0426 <blackhao0426@gmail.com>
Date: Tue, 13 Jan 2026 23:49:05 -0600
Subject: init commit

---
 runs/slurm_logs/14360867_depth_exp.out | 116 +++++++++++++++++++++++++++++++++
 1 file changed, 116 insertions(+)
 create mode 100644 runs/slurm_logs/14360867_depth_exp.out

(limited to 'runs/slurm_logs/14360867_depth_exp.out')

diff --git a/runs/slurm_logs/14360867_depth_exp.out b/runs/slurm_logs/14360867_depth_exp.out
new file mode 100644
index 0000000..06d658d
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+============================================================
+Job ID: 14360867
+Node: gpub040
+Start time: Sat Dec 27 06:04:46 CST 2025
+============================================================
+Configuration:
+  EPOCHS: 30
+  DEPTHS: 2 4 6 8 10 12
+  HIDDEN_DIM: 128
+  LAMBDA_REG: 0.1
+  LR: 0.001
+  USE_SYNTHETIC: true
+============================================================
+NVIDIA A40, 46068 MiB
+============================================================
+Running: python files/experiments/depth_comparison.py --epochs 30 --depths 2 4 6 8 10 12 --hidden_dim 128 --lambda_reg 0.1 --lr 0.001 --seed 42 --out_dir runs/depth_comparison --device cuda --synthetic
+============================================================
+======================================================================
+Experiment: Vanilla vs Lyapunov-Regularized SNN
+======================================================================
+Depths: [2, 4, 6, 8, 10, 12]
+Hidden dim: 128
+Epochs: 30
+Lambda_reg: 0.1
+Device: cuda
+
+Using SYNTHETIC data for quick testing
+Data: T=50, D=100, classes=10
+
+==================================================
+Depth = 2 layers
+==================================================
+
+  Training VANILLA...
+    Final: loss=0.0000 acc=1.000 val_acc=1.000 λ=N/A ∇=0.00
+
+  Training LYAPUNOV...
+    Final: loss=0.0087 acc=1.000 val_acc=1.000 λ=0.295 ∇=0.00
+
+==================================================
+Depth = 4 layers
+==================================================
+
+  Training VANILLA...
+    Final: loss=0.0000 acc=1.000 val_acc=1.000 λ=N/A ∇=0.00
+
+  Training LYAPUNOV...
+    Final: loss=0.0429 acc=1.000 val_acc=1.000 λ=0.654 ∇=0.07
+
+==================================================
+Depth = 6 layers
+==================================================
+
+  Training VANILLA...
+    Final: loss=0.0000 acc=1.000 val_acc=1.000 λ=N/A ∇=0.00
+
+  Training LYAPUNOV...
+    Final: loss=0.0746 acc=1.000 val_acc=1.000 λ=0.859 ∇=0.20
+
+==================================================
+Depth = 8 layers
+==================================================
+
+  Training VANILLA...
+    Final: loss=0.0000 acc=1.000 val_acc=1.000 λ=N/A ∇=0.00
+
+  Training LYAPUNOV...
+    Final: loss=0.1389 acc=0.986 val_acc=0.978 λ=1.003 ∇=1.11
+
+==================================================
+Depth = 10 layers
+==================================================
+
+  Training VANILLA...
+    Final: loss=2.3013 acc=0.107 val_acc=0.084 λ=N/A ∇=0.59
+
+  Training LYAPUNOV...
+    Final: loss=0.8785 acc=0.667 val_acc=0.666 λ=1.116 ∇=7.17
+
+==================================================
+Depth = 12 layers
+==================================================
+
+  Training VANILLA...
+    Final: loss=2.3013 acc=0.107 val_acc=0.084 λ=N/A ∇=0.63
+
+  Training LYAPUNOV...
+    Final: loss=2.4441 acc=0.107 val_acc=0.084 λ=1.196 ∇=0.63
+
+======================================================================
+SUMMARY: Final Validation Accuracy by Depth
+======================================================================
+Depth    Vanilla         Lyapunov        Difference     
+----------------------------------------------------------------------
+2        1.000           1.000           0.000          
+4        1.000           1.000           0.000          
+6        1.000           1.000           0.000          
+8        1.000           0.978           -0.022         
+10       0.084           0.666           +0.582         
+12       0.084           0.084           0.000          
+======================================================================
+
+Gradient Norm Analysis (final epoch):
+----------------------------------------------------------------------
+Depth    Vanilla ∇       Lyapunov ∇     
+----------------------------------------------------------------------
+2        0.00            0.00           
+4        0.00            0.07           
+6        0.00            0.20           
+8        0.00            1.11           
+10       0.59            7.17           
+12       0.63            0.63           
+
+Results saved to runs/depth_comparison/20251227-071838
+============================================================
+Generating plots for: runs/depth_comparison/20251227-071838/
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