0.安装Ubutu22.04
WSL方案目前不可行，需要安装实体机Ubuntu22.04
[!hint] 注意: 以下章节弃用, WSL方案目前不可行
shell
wsl --install -d Ubuntu-24.04 wsl --export Ubuntu-24.04 D:\WSL\Ubuntu-24.04\Ubuntu-24.04.tar wsl --unregister Ubuntu-24.04 wsl --import Ubuntu-24.04 D:\WSL\Ubuntu-24.04 D:\WSL\Ubuntu-24.04\Ubuntu-24.04.tar --version 2 wsl -d Ubuntu-24.04 #配置默认用户 ubuntu2404 config --default-user cerry
确保DNS服务器固定，网络正常访问
echo 'nameserver 8.8.8.8' | sudo tee /etc/resolv.conf > /dev/null echo '[network]' | sudo tee /etc/wsl.conf > /dev/null echo 'generateResolvConf = false' | sudo tee -a /etc/wsl.conf > /dev/null
换源
sudo mv /etc/apt/sources.list.d/ubuntu.sources /etc/apt/backup-sources.list.d-ubuntu.sources sudo vim /etc/apt/sources.list.d/tuna.sources
input Types: deb URIs: https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ #如果使用其他镜像站，上面这行可以改成其他镜像站的网址 Suites: noble noble-updates noble-backports Components: main universe restricted multiverse Signed-By: /usr/share/keyrings/ubuntu-archive-keyring.gpg
Types: deb URIs: http://security.ubuntu.com/ubuntu #如果安全更新需要使用镜像站，上面这行也改成 URIs: https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ Suites: noble-security Components: main universe restricted multiverse Signed-By: /usr/share/keyrings/ubuntu-archive-keyring.gpg
1. 安装Miniconda3
shell
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
chmod a+x Miniconda3-latest-Linux-x86_64.sh
./Miniconda3-latest-Linux-x86_64.sh2.安装 驱动包
form WSL How to guide - Use ROCm on Radeon GPUs
shell
# 1. 安装AMD 统一内核模式 GPU 驱动程序、ROCm 和图形
sudo apt update
wget https://repo.radeon.com/amdgpu-install/6.4.2.1/ubuntu/noble/amdgpu-install_6.4.60402-1_all.deb
sudo apt install ./amdgpu-install_6.4.60402-1_all.deb
# 2. 安装WSL 用例
amdgpu-install -y --usecase=wsl,rocm --no-dkms
<output
[sudo] password for cerry:
Hit:1 https://mirrors.tuna.tsinghua.edu.cn/ubuntu noble InRelease
Hit:2 https://mirrors.tuna.tsinghua.edu.cn/ubuntu noble-updates InRelease
Hit:3 https://mirrors.tuna.tsinghua.edu.cn/ubuntu noble-backports InRelease
Hit:4 http://security.ubuntu.com/ubuntu noble-security InRelease
Hit:5 https://repo.radeon.com/amdgpu/6.4.2.1/ubuntu noble InRelease
Hit:6 https://repo.radeon.com/rocm/apt/6.4.2 noble InRelease
Reading package lists... Done
Reading package lists... Done
Building dependency tree... Done
Reading state information... Done
hsa-runtime-rocr4wsl-amdgpu is already the newest version (25.10-2188619.24.04).
rocm is already the newest version (6.4.2.60402-120~24.04).
0 upgraded, 0 newly installed, 0 to remove and 2 not upgraded.验证：
shell
(base) cerry@cerry-ROG-Flow-X13-GV301RA-GV301RA:~$ rocminfo
ROCk module version 6.12.12 is loaded
=====================
HSA System Attributes
=====================
Runtime Version: 1.15
Runtime Ext Version: 1.7
System Timestamp Freq.: 1000.000000MHz
Sig. Max Wait Duration: 18446744073709551615 (0xFFFFFFFFFFFFFFFF) (timestamp count)
Machine Model: LARGE
System Endianness: LITTLE
Mwaitx: DISABLED
XNACK enabled: NO
DMAbuf Support: YES
VMM Support: YES
==========
HSA Agents
==========
*******
Agent 1
*******
Name: AMD Ryzen 7 6800HS with Radeon Graphics
Uuid: CPU-XX
Marketing Name: AMD Ryzen 7 6800HS with Radeon Graphics
Vendor Name: CPU
Feature: None specified
Profile: FULL_PROFILE
Float Round Mode: NEAR
Max Queue Number: 0(0x0)
Queue Min Size: 0(0x0)
Queue Max Size: 0(0x0)
Queue Type: MULTI
Node: 0
Device Type: CPU
Cache Info:
L1: 32768(0x8000) KB
Chip ID: 0(0x0)
ASIC Revision: 0(0x0)
Cacheline Size: 64(0x40)
Max Clock Freq. (MHz): 4785
BDFID: 0
Internal Node ID: 0
Compute Unit: 16
SIMDs per CU: 0
Shader Engines: 0
Shader Arrs. per Eng.: 0
WatchPts on Addr. Ranges:1
Memory Properties:
Features: None
Pool Info:
Pool 1
Segment: GLOBAL; FLAGS: FINE GRAINED
Size: 15591488(0xede840) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Recommended Granule:4KB
Alloc Alignment: 4KB
Accessible by all: TRUE
Pool 2
Segment: GLOBAL; FLAGS: EXTENDED FINE GRAINED
Size: 15591488(0xede840) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Recommended Granule:4KB
Alloc Alignment: 4KB
Accessible by all: TRUE
Pool 3
Segment: GLOBAL; FLAGS: KERNARG, FINE GRAINED
Size: 15591488(0xede840) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Recommended Granule:4KB
Alloc Alignment: 4KB
Accessible by all: TRUE
Pool 4
Segment: GLOBAL; FLAGS: COARSE GRAINED
Size: 15591488(0xede840) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Recommended Granule:4KB
Alloc Alignment: 4KB
Accessible by all: TRUE
ISA Info:
*******
Agent 2
*******
Name: gfx1035
Uuid: GPU-XX
Marketing Name: AMD Radeon Graphics
Vendor Name: AMD
Feature: KERNEL_DISPATCH
Profile: BASE_PROFILE
Float Round Mode: NEAR
Max Queue Number: 128(0x80)
Queue Min Size: 64(0x40)
Queue Max Size: 131072(0x20000)
Queue Type: MULTI
Node: 1
Device Type: GPU
Cache Info:
L1: 16(0x10) KB
L2: 2048(0x800) KB
Chip ID: 5761(0x1681)
ASIC Revision: 2(0x2)
Cacheline Size: 128(0x80)
Max Clock Freq. (MHz): 2200
BDFID: 2048
Internal Node ID: 1
Compute Unit: 12
SIMDs per CU: 2
Shader Engines: 1
Shader Arrs. per Eng.: 2
WatchPts on Addr. Ranges:4
Coherent Host Access: FALSE
Memory Properties: APU
Features: KERNEL_DISPATCH
Fast F16 Operation: TRUE
Wavefront Size: 32(0x20)
Workgroup Max Size: 1024(0x400)
Workgroup Max Size per Dimension:
x 1024(0x400)
y 1024(0x400)
z 1024(0x400)
Max Waves Per CU: 32(0x20)
Max Work-item Per CU: 1024(0x400)
Grid Max Size: 4294967295(0xffffffff)
Grid Max Size per Dimension:
x 4294967295(0xffffffff)
y 4294967295(0xffffffff)
z 4294967295(0xffffffff)
Max fbarriers/Workgrp: 32
Packet Processor uCode:: 122
SDMA engine uCode:: 47
IOMMU Support:: None
Pool Info:
Pool 1
Segment: GLOBAL; FLAGS: COARSE GRAINED
Size: 7795744(0x76f420) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Recommended Granule:2048KB
Alloc Alignment: 4KB
Accessible by all: FALSE
Pool 2
Segment: GLOBAL; FLAGS: EXTENDED FINE GRAINED
Size: 7795744(0x76f420) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Recommended Granule:2048KB
Alloc Alignment: 4KB
Accessible by all: FALSE
Pool 3
Segment: GROUP
Size: 64(0x40) KB
Allocatable: FALSE
Alloc Granule: 0KB
Alloc Recommended Granule:0KB
Alloc Alignment: 0KB
Accessible by all: FALSE
ISA Info:
ISA 1
Name: amdgcn-amd-amdhsa--gfx1035
Machine Models: HSA_MACHINE_MODEL_LARGE
Profiles: HSA_PROFILE_BASE
Default Rounding Mode: NEAR
Default Rounding Mode: NEAR
Fast f16: TRUE
Workgroup Max Size: 1024(0x400)
Workgroup Max Size per Dimension:
x 1024(0x400)
y 1024(0x400)
z 1024(0x400)
Grid Max Size: 4294967295(0xffffffff)
Grid Max Size per Dimension:
x 4294967295(0xffffffff)
y 4294967295(0xffffffff)
z 4294967295(0xffffffff)
FBarrier Max Size: 32
ISA 2
Name: amdgcn-amd-amdhsa--gfx10-3-generic
Machine Models: HSA_MACHINE_MODEL_LARGE
Profiles: HSA_PROFILE_BASE
Default Rounding Mode: NEAR
Default Rounding Mode: NEAR
Fast f16: TRUE
Workgroup Max Size: 1024(0x400)
Workgroup Max Size per Dimension:
x 1024(0x400)
y 1024(0x400)
z 1024(0x400)
Grid Max Size: 4294967295(0xffffffff)
Grid Max Size per Dimension:
x 4294967295(0xffffffff)
y 4294967295(0xffffffff)
z 4294967295(0xffffffff)
FBarrier Max Size: 32
*** Done ***3. # Install PyTorch for ROCm
form: Install PyTorch for Radeon GPUs on WSL
shell
conda create -n ROCm python=3.12
conda activite ROCm
sudo apt install python3-pip -y
pip3 install --upgrade pip wheel
wget https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.2/torch-2.6.0%2Brocm6.4.2.git76481f7c-cp312-cp312-linux_x86_64.whl
wget https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.2/torchvision-0.21.0%2Brocm6.4.2.git4040d51f-cp312-cp312-linux_x86_64.whl
wget https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.2/pytorch_triton_rocm-3.2.0%2Brocm6.4.2.git7e948ebf-cp312-cp312-linux_x86_64.whl
wget https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.2/torchaudio-2.6.0%2Brocm6.4.2.gitd8831425-cp312-cp312-linux_x86_64.whl
pip3 uninstall torch torchvision pytorch-triton-rocm
pip3 install torch-2.6.0+rocm6.4.2.git76481f7c-cp312-cp312-linux_x86_64.whl torchvision-0.21.0+rocm6.4.2.git4040d51f-cp312-cp312-linux_x86_64.whl torchaudio-2.6.0+rocm6.4.2.gitd8831425-cp312-cp312-linux_x86_64.whl pytorch_triton_rocm-3.2.0+rocm6.4.2.git7e948ebf-cp312-cp312-linux_x86_64.whl
# 检查安装是否成功
python3 -c 'import torch' 2> /dev/null && echo 'Success' || echo 'Failure'
(ROCm) cerry@cerry-ROG-Flow-X13-GV301RA-GV301RA:~$ python3 -c 'import torch' 2> /dev/null && echo 'Success' || echo 'Failure'
Success
(ROCm) cerry@cerry-ROG-Flow-X13-GV301RA-GV301RA:~$ python3 -c 'import torch; print(torch.cuda.is_available())'
True
(ROCm) cerry@cerry-ROG-Flow-X13-GV301RA-GV301RA:~$ python3 -c "import torch; print(f'device name [0]:', torch.cuda.get_device_name(0))"
device name [0]: AMD Radeon Graphics
(ROCm) cerry@cerry-ROG-Flow-X13-GV301RA-GV301RA:~$ python3 -m torch.utils.collect_env