From d2fee97e249af36e1de261651d82201247c15962 Mon Sep 17 00:00:00 2001
From: Disty0 <disty@disty.xyz>
Date: Fri, 31 Jan 2025 20:27:22 +0300
Subject: [PATCH] Update changelog

---
 CHANGELOG.md       | 7 ++++---
 modules/devices.py | 2 +-
 2 files changed, 5 insertions(+), 4 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 560357781..2e68b4973 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,7 +9,8 @@
 - **Docs**:
   - Updated [Debugging guide](https://github.com/vladmandic/automatic/wiki/Debug)  
 - **Torch**:
-  - for cuda environemnts set default to `torch==2.6.0+cu126`  
+  - for cuda environments set default to `torch==2.6.0+cu126`  
+    for rocm environments set default to `torch==2.6.0+rocm6.2.4`  
     *note*: to avoid disruptions sdnext does not perform torch install during in-place upgrades  
     to force torch upgrade, either start with new installation or use `--reinstall` flag  
   - add support for torch **tunable ops**, this can speed up operations by up to *10-30%* on some platforms  
@@ -25,12 +26,12 @@
   - detailer with faceid modules  
   - detailer restore pipeline before run  
   - fix `python==3.9` compatibility  
-  - handle invalid `triton` with `torch==2.6.0`  
+  - handle invalid `triton` on Linux  
   - correct library import order  
   - update requirements  
   - calculate dyn atten bmm slice rate  
   - dwpose update and patch `mmengine` installer  
-  - wrap extensions using incorrect device  
+  - ipex device wrapper with adetailer  
   - openvino error handling  
   - relax python version checks for rocm  
 
diff --git a/modules/devices.py b/modules/devices.py
index d5355abb1..70fe1271b 100644
--- a/modules/devices.py
+++ b/modules/devices.py
@@ -307,7 +307,7 @@ def set_cuda_tunable():
                 pass
             torch.cuda.tunable.set_filename(fn)
             if torch.cuda.tunable.is_enabled():
-                log.debug(f'Torche tunable: enabled={torch.cuda.tunable.is_enabled()} tuning={torch.cuda.tunable.tuning_is_enabled()} iterations={torch.cuda.tunable.get_max_tuning_iterations()} duration={torch.cuda.tunable.get_max_tuning_duration()} fn="{fn}" entries={lines}')
+                log.debug(f'Torch tunable: enabled={torch.cuda.tunable.is_enabled()} tuning={torch.cuda.tunable.tuning_is_enabled()} iterations={torch.cuda.tunable.get_max_tuning_iterations()} duration={torch.cuda.tunable.get_max_tuning_duration()} fn="{fn}" entries={lines}')
     except Exception as e:
         log.warning(f'Torch tunable: {e}')