From b537efebed3c2bcaa1a8f114281fda25f61f7a3c Mon Sep 17 00:00:00 2001 From: jinghanhu Date: Mon, 4 Aug 2025 17:00:14 +0800 Subject: [PATCH] Merge release 1.28 (#1401) --- docker/build_image.py | 2 +- modelscope/pipelines/multi_modal/diffusers_wrapped/vaehook.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/docker/build_image.py b/docker/build_image.py index 844eff9d..bfef7be5 100644 --- a/docker/build_image.py +++ b/docker/build_image.py @@ -277,7 +277,7 @@ class LLMImageBuilder(Builder): if not args.vllm_version: args.vllm_version = '0.8.5.post1' if not args.lmdeploy_version: - args.lmdeploy_version = '0.7.2.post1' + args.lmdeploy_version = '0.9.1' if not args.autogptq_version: args.autogptq_version = '0.7.1' if not args.flashattn_version: diff --git a/modelscope/pipelines/multi_modal/diffusers_wrapped/vaehook.py b/modelscope/pipelines/multi_modal/diffusers_wrapped/vaehook.py index 711a287e..5455bd18 100644 --- a/modelscope/pipelines/multi_modal/diffusers_wrapped/vaehook.py +++ b/modelscope/pipelines/multi_modal/diffusers_wrapped/vaehook.py @@ -277,7 +277,7 @@ def custom_group_norm(input, """ b, c, h, w = input.shape channel_in_group = c // num_groups - input_reshaped = input.reshape(1, b * num_groups, channel_in_group, h, w) + input_reshaped = input.reshape(b * num_groups, channel_in_group, h, w) out = F.batch_norm( input_reshaped,