From bc5e12736c555bbdde7217d47c1f803098492109 Mon Sep 17 00:00:00 2001
From: Ryan Romanchuk <ryan@romanch.uk>
Date: Wed, 20 May 2026 21:14:17 -0500
Subject: [PATCH] Remove mlx upper version pin

The <0.31 cap was added due to yolo26x-seg training hangs on mlx 0.31.x.
Detection-only inference is unaffected; removing the cap so this package
can be used alongside projects that require mlx>=0.31.
---
 pyproject.toml | 10 +---------
 1 file changed, 1 insertion(+), 9 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index daf9c59..6f3d835 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -28,15 +28,7 @@ classifiers = [
 ]
 requires-python = ">=3.10"
 dependencies = [
-    # Upper bound on mlx: yolo26x-seg training reproducibly hangs on
-    # mlx 0.31.x (kIOGPUCommandBufferCallbackError) within 2–5 epochs
-    # despite the per-epoch ``mx.clear_cache()`` Metal-heap-fragmentation
-    # fix in ``yolo26mlx.engine.trainer``. Smaller seg models (n/s/m/l)
-    # and all detection workloads are unaffected, and the documented
-    # 81.5 s/epoch x-seg baseline was measured under mlx 0.30.x — so the
-    # supported floor is the same and the cap excludes only the broken
-    # 0.31.x line.
-    "mlx>=0.30.3,<0.31",
+    "mlx>=0.30.3",
     "numpy>=2.0.0",
     "pillow>=10.0.0",
     "pyyaml>=6.0",