1 创建基础容器

拉取镜像

docker pull ubuntu

通过网盘分享的文件：ubuntu_24.04.tar
链接: https://pan.baidu.com/s/123tm6MhQqRWanv_R5iCRcA?pwd=9xs3 提取码: 9xs3

创建容器

docker run -itd -u root \
--ipc=host \
--network=host \
--privileged \
--device=/dev/davinci_manager \
--device=/dev/devmm_svm \
--device=/dev/hisi_hdc \
-v /var/log/npu/:/usr/slog \
-v /usr/local/bin/npu-smi:/usr/local/bin/npu-smi \
-v /usr/local/Ascend/driver:/usr/local/Ascend/driver \
-v /usr/local/Ascend/firmware:/usr/local/Ascend/firmware \
-v /usr/local/sbin:/usr/local/sbin \
-v /etc/hccn.conf:/etc/hccn.conf \
--name comfyui \
ubuntu:latest \
/bin/bash

进入容器

docker exec -it comfyui bash 

查看系统版本

cat /etc/os-release

PRETTY_NAME="Ubuntu 24.04.2 LTS"
NAME="Ubuntu"
VERSION_ID="24.04"
VERSION="24.04.2 LTS (Noble Numbat)"
VERSION_CODENAME=noble
ID=ubuntu
ID_LIKE=debian
HOME_URL="https://www.ubuntu.com/"
SUPPORT_URL="https://help.ubuntu.com/"
BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/"
PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy"
UBUNTU_CODENAME=noble
LOGO=ubuntu-logo

2 安装环境

2.1 安装依赖

apt-get update
apt-get install -y gcc g++ make cmake zlib1g zlib1g-dev openssl libsqlite3-dev libssl-dev libffi-dev libbz2-dev libxslt1-dev unzip pciutils net-tools libblas-dev gfortran libblas3 vim zip wget git

# 安装过程中时区选择'Asia/Shanghai' 5，69

2.2 安装conda

mkdir /root/downloads
cd /root/downloads
wget https://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/Miniconda3-py311_25.1.1-2-Linux-aarch64.sh
bash Miniconda3-py311_25.1.1-2-Linux-aarch64.sh
# 安装过程中全选yes
source ~/.bashrc

2.3 安装cann

社区版资源下载-资源下载中心-昇腾社区

在资源中心下载并上传配套的软件包到服务器

# 添加环境变量
export LD_LIBRARY_PATH=/usr/local/Ascend/driver/lib64/common:/usr/local/Ascend/driver/lib64/driver:${LD_LIBRARY_PATH}
echo "export LD_LIBRARY_PATH=/usr/local/Ascend/driver/lib64/common:/usr/local/Ascend/driver/lib64/driver:${LD_LIBRARY_PATH}" >> ~/.bashrc

# 添加权限
chmod +x Ascend-cann-*
# 安装
./Ascend-cann-toolkit_8.3.RC1.alpha002_linux-aarch64.run --install 
echo "source /usr/local/Ascend/ascend-toolkit/set_env.sh" >> ~/.bashrc
source ~/.bashrc
./Ascend-cann-kernels-910b_8.3.RC1.alpha002_linux-aarch64.run --install

3 python环境

3.1 python环境创建

conda create -n comfyui python=3.11
conda activate comfyui
echo "conda activate comfyui" >> ~/.bashrc

3.2 安装依赖

pip3 install attrs numpy==1.26.4 decorator sympy cffi pyyaml pathlib2 psutil protobuf scipy requests absl-py -i https://pypi.tuna.tsinghua.edu.cn/simple

安装torchvision包

pip3 install torchvision==0.20.1 -i https://pypi.tuna.tsinghua.edu.cn/simple

安装torch

pip3 install torch==2.5.1 -i https://pypi.tuna.tsinghua.edu.cn/simple

安装torch_npu

# 安装
pip install torch_npu==2.5.1 -i https://pypi.tuna.tsinghua.edu.cn/simple

验证

python3 -c "import torch;import torch_npu; a = torch.randn(3, 4).npu(); print(a + a);"

4 ComfyUI

4.1安装

cd /root/
git clone https://github.com/comfyanonymous/ComfyUI.git
cd ComfyUI/
pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple

安装插件（可选）

cd custom_nodes/
git clone https://github.com/ltdrdata/ComfyUI-Manager.git
cd ComfyUI-Manager/
pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple     

4.2 代码修改

cd /root/ComfyUI/
vim main.py 
# 添加以下内容
import torch 
import torch_npu
torch.npu.config.allow_internal_format = False
torch.npu.set_compile_mode(jit_compile=False)

4.3 启动UI

cd /root/ComfyUI/
python main.py

4.4 下载模型

根据工作流按需下载模型权重（以Wan2.2文生视频为例）

魔搭有专门的Comfy Org组织

注意：不要使用fp8格式的权重

下载权重到指定文件夹，然后在UI界面上刷新并加载一下

diffusion_models

cd /root/ComfyUI/models/diffusion_models
# Wan_2.2
modelscope download --model Comfy-Org/Wan_2.2_ComfyUI_Repackaged split_files/diffusion_models/wan2.2_t2v_low_noise_14B_fp16.safetensors --local_dir ./
modelscope download --model Comfy-Org/Wan_2.2_ComfyUI_Repackaged split_files/diffusion_models/wan2.2_t2v_high_noise_14B_fp16.safetensors --local_dir ./

loras

cd /root/ComfyUI/models/loras
# Wan_2.2
modelscope download --model Comfy-Org/Wan_2.2_ComfyUI_Repackaged split_files/loras/wan2.2_t2v_lightx2v_4steps_lora_v1.1_low_noise.safetensors --local_dir ./
modelscope download --model Comfy-Org/Wan_2.2_ComfyUI_Repackaged split_files/loras/wan2.2_t2v_lightx2v_4steps_lora_v1.1_high_noise.safetensors --local_dir ./

vae

cd /root/ComfyUI/models/vae
# Wan_2.1
modelscope download --model Comfy-Org/Wan_2.1_ComfyUI_repackaged split_files/vae/wan_2.1_vae.safetensors --local_dir ./

text_encoders

cd /root/ComfyUI/models/text_encoders
modelscope download --model Comfy-Org/Wan_2.2_ComfyUI_Repackaged split_files/text_encoders/umt5_xxl_fp16.safetensors --local_dir ./

4.5 执行工作流

选择权重并点击运行

效果

4.6 多卡运行

ComfyUI Manager搜索并安装ComfyUI-MultiGPU插件，安装完成后需重启ComfyUI。在工作流中用该插件的节点替换原本的模型加载节点，将模型加载到指定的卡上。