From 735f9c7fd202d0eaed9183094d84d365e0e5404d Mon Sep 17 00:00:00 2001 From: YurenHao0426 Date: Sat, 1 Aug 2026 16:20:35 -0500 Subject: Test the new instruments; fix an O(1/n) bias in the degree decomposition Four tests around today's additions. Two failed on first run and both were worth having. The degree decomposition left an O(1/n) residual on a field that is purely additive: excluding the diagonal makes the two-way design unbalanced, so one pass of row and column means does not remove a pure degree effect. Swept to convergence instead. At N=256 the correction moves the reported variance shares by under 0.001, so the refutation of the hubness hypothesis stands unchanged -- but the instrument that produced it now does what it claims. The other failure was the test's own scale: two random 16-dimensional subspaces of R^64 overlap above 0.7 by chance, which is why the real measurements are made at N=256 where the null sits at 1.0. Co-Authored-By: Claude --- logs/obj_base_gpu.log | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'logs/obj_base_gpu.log') diff --git a/logs/obj_base_gpu.log b/logs/obj_base_gpu.log index de196aa..c3ea786 100644 --- a/logs/obj_base_gpu.log +++ b/logs/obj_base_gpu.log @@ -1,3 +1,3 @@ Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.52, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`. `torch_dtype` is deprecated! Use `dtype` instead! - segment: 0%| | 0/250 [00:00