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path: root/experiments/measure_direction_quality_existing_ckpt.py
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2026-04-07Add fast direction-quality measurement on existing DFA checkpointsYurenHao0426
3-seed result on the existing dfa_s{42,123,456}.pt checkpoints from results/confirmatory/checkpoints_A2/, computing per-layer cosine of DFA's local credit signal e_T@B_l^T vs the true BP gradient at h_l. Key findings: per-layer cos (3-seed mean): l0: +0.42 (high — embedding alignment) l1: +0.006 (essentially zero) l2: -0.015 (essentially zero) l3: -0.004 (essentially zero) l4: -0.004 (essentially zero) layer-mean across all 5: +0.07-0.10 The deep blocks (l1-l4) have essentially zero alignment with BP grad in the vanilla scale-failure regime. Layer 0 dominates the headline. The script reconstructs the training-time random Bs by replaying the RNG sequence (torch.manual_seed + ResidualMLP construction + randn draws), since the existing checkpoints don't save Bs. For the still-running direction-quality experiment which DOES save Bs, the script auto-detects the dict format and uses the saved Bs directly.