环境准备
宿主机环境依赖
| 组件 | 版本要求 |
|---|---|
| MUSA Linux driver | 5.1.0 / 3.3.5 |
| mtml | 2.2.0 |
| mt-container-toolkit | 2.2.0 |
-
MUSA Linux driver包含在 MUSA SDK 中,参考 下载及文档。 -
mt-container-toolkit包含在 KUAE 云原生套件中,参考 下载及文档。 -
mtml参考 安装指南。
宿主机环境检测
# 检查基础配置
dpkg -l | grep -iE 'musa|mtml|mt-container-toolkit|mthreads'
# 检查 GMI
mthreads-gmi
基础配置输出结果参考
mccxadmin@mccx-173:~$ dpkg -l | grep -iE 'musa|mtml|mt-peermem|mt-container-toolkit|mthreads'
ii mt-container-toolkit 2.2.0-1 amd64 MT Container Toolkit
ii mtml 2.2.0 amd64 mt-management
ii musa 5.1.0-server amd64 Moore Threads MUSA driver
mthreads-gmi信息参考
---------------------------------------------------------------------
mthreads-gmi:2.3.2 Driver Version:5.1.0-server
---------------------------------------------------------------------
ID Name |PCIe |%GPU Mem
0 MTT S5000 |00000000:03:00.0 |0% 1428MiB(81920MiB)
...
---------------------------------------------------------------------
启动容器环境
拉取镜像
# MUSA SDK 5.1.0(推荐)
docker pull registry.mthreads.com/presale/devtech/tensorflow_musa:5.1.0_20260623
# MUSA SDK 4.3.5
docker pull registry.mthreads.com/presale/devtech/tensorflow_musa:4.3.5_20260624
启动容器
docker run -it --rm \
--name tf_musa \
--privileged \
-v /path/to/dataset:/data \
-v /path/to/tensorflow_musa_playground:/workspace/playground \
registry.mthreads.com/presale/devtech/tensorflow_musa:5.1.0_20260623 \
/bin/bash
说明:
--privileged使容器能访问宿主机的 MUSA GPU 设备(/dev/mtgpu.*)。
验证 MUSA 环境
运行以下命令确认 MUSA 设备可见:
import tensorflow as tf
import tensorflow_musa
print("TensorFlow 版本:", tf.__version__)
devices = tf.config.list_physical_devices("MUSA")
print(f"MUSA 设备数: {len(devices)}")
for d in devices:
print(f" {d}")
预期输出(以 8 卡环境为例):
TensorFlow 版本: 2.15.1
MUSA 设备数: 8
PhysicalDevice(name='/physical_device:MUSA:0', device_type='MUSA')
PhysicalDevice(name='/physical_device:MUSA:1', device_type='MUSA')
...
PhysicalDevice(name='/physical_device:MUSA:7', device_type='MUSA')

