On WSL2 an AMD GPU is exposed through DirectX para-virtualisation (/dev/dxg), not the native amdgpu KFD driver — so /dev/kfd doesn't exist and import amdsmi fails, which breaks ROCm platform detection in tools like vLLM. amd-smi-wsl restores the amdsmi import surface using data sources that do work under WSL2 (the HIP runtime + Windows interop), so those tools start cleanly — no patching required.

This is a property of the WSL2 GPU stack, not of any single card, so it applies broadly across RDNA generations (RDNA3 / RDNA3.5 / RDNA4 desktop Radeon & Radeon PRO, and Ryzen AI APUs).

import amdsmi            # this package, not the native one
amdsmi.amdsmi_init()
h = amdsmi.amdsmi_get_processor_handles()[0]
print(amdsmi.amdsmi_get_gpu_asic_info(h)["market_name"])
# -> AMD Radeon(TM) 8060S Graphics

✨ Highlights

• 🔌 100% import-compatible — every public symbol of the upstream binding: all 190 amdsmi_* functions, all enums, and the full exception hierarchy.
• 🧠 Real data, not fakes — device name, gfx arch, VRAM, compute units, UUID and live memory from torch.cuda (HIP); PCI id, subsystem id, revision and driver info from Windows interop.
• ♻️ torch re-entrancy safe — a thread-local guard breaks the amdsmi_init → torch.cuda → amdsmi_init recursion that PyTorch's ROCm build would otherwise trigger.
• 🎯 vLLM canonical names — returns device_id as a hex string ("0x1586") so vLLM resolves the canonical name (e.g. AMD_Radeon_8060S).
• 🧪 Honest NOT_SUPPORTED stubs for features the platform genuinely lacks (RAS/ECC, partitioning, set_*, events…), exactly like the native library.
• 📦 Zero hard deps — pure-Python, no compiled extensions; torch is never pinned so it won't fight your ROCm install.

🚀 Proven in production

Used as the platform shim to serve a 35B vision-MoE in 4-bit AWQ (Qwen3.6-35B-A3B) on a single AMD Radeon 8060S (Strix Halo, gfx1151) under WSL2 with source-built vLLM — amd-smi-wsl supplies the amdsmi surface vLLM's ROCm platform detection needs, end-to-end OpenAI-compatible serving included.

Why

On WSL2 any AMD GPU is exposed through DirectX para-virtualisation (/dev/dxg + dxgkrnl), not the native amdgpu KFD driver. The Linux /dev/kfd device and its sysfs topology simply do not exist, so — regardless of which Radeon / Ryzen GPU you have:

• import amdsmi (native) fails / amdsmi_init() raises, and
• downstream code such as vLLM then fails ROCm platform detection and device-name / topology queries at startup,

even though the HIP runtime itself works perfectly via /dev/dxg.

This package restores the amdsmi import surface and re-implements the queryable subset on top of data sources that do work in WSL2:

Note on torch re-entrancy. PyTorch's ROCm build resolves its device count through amdsmi itself. Since this package replaces amdsmi, a naive probe would recurse (amdsmi_init -> torch.cuda -> amdsmi_init ...). A thread-local re-entrancy guard breaks that cycle so torch falls back to its native HIP device count. See the v0.2.0 entry in the changelog.

API coverage

The package exposes every public symbol of the upstream binding — all 190 amdsmi_* functions, all AmdSmi* enums, and the full exception hierarchy — so import amdsmi is binary-compatible at the Python level.

• Implemented for real (read-only queries that map cleanly to HIP / Windows data): init / shutdown, processor & socket handle enumeration, asic_info, board_info, vram_info, vram_usage, memory_total, memory_usage, device_uuid, device_bdf, driver_info, gpu_id, subsystem_id/name, revision, vendor_name, topo_get_link_type, topo_get_numa_node_number, lib_version, rocm_version, status_code_to_string, and best-effort activity / clock_info / temp_metric / power_info (when the running torch build exposes them).
• Faithful NOT_SUPPORTED stubs for everything the platform genuinely lacks under WSL2: the entire CPU/HSMP/EPYC surface, performance counters, RAS/ECC, compute/memory partitioning, every set_* mutator, GPU reset, KFD info, XGMI status, and event notification. These raise AmdSmiLibraryException(AMDSMI_STATUS_NOT_SUPPORTED) — exactly what the native library does for unsupported features.

Install

pip install amd-smi-wsl

torch (ROCm build) is expected to already be present in your environment and is therefore not declared as a hard dependency.

Only install this where the real amdsmi cannot be used. In a normal native-Linux ROCm install you should keep the official amdsmi.

Environment variables

• HSA_ENABLE_DXG_DETECTION — auto-set to 1 for you. On WSL2 the HIP/HSA runtime only enumerates the DirectX-paravirtualized GPU when this is exported before the first torch.cuda call. Importing this package sets it (via os.environ.setdefault, so an explicit value you set is always respected) when it detects WSL — so import amdsmi is self-contained and you no longer have to export it by hand. Only applied inside WSL, and skipped when AMDSMI_WSL_DISABLE is set.
• AMDSMI_WSL_DISABLE=1 — make amdsmi_init() raise NOT_SUPPORTED (and skip the HSA_ENABLE_DXG_DETECTION auto-set), useful to test a caller's fallback path.

Relationship to vLLM

This package makes the native-amdsmi code paths in vLLM's vllm/platforms/rocm.py and vllm/platforms/__init__.py work unchanged on WSL2, as an alternative to patching vLLM with torch.cuda fallbacks (cf. vLLM PR #37189).

With this package installed, vLLM resolves the canonical device name from its hex-keyed _ROCM_DEVICE_ID_NAME_MAP (because asic_info["device_id"] is returned as a lowercase hex string such as "0x1586"), e.g.:

from vllm.platforms import rocm_platform_plugin
import vllm.platforms.rocm as rocm
rocm_platform_plugin()              # -> 'vllm.platforms.rocm.RocmPlatform'
rocm.RocmPlatform.get_device_name(0)  # -> 'AMD_Radeon_8060S'
rocm._GCN_ARCH                      # -> 'gfx1151'

Verified environment

The mechanism is GPU-agnostic (it only relies on the HIP runtime + Windows interop, which behave the same for any Radeon / Ryzen GPU under WSL2). The numbers below are from one fully validated end-to-end setup — WSL2 + AMD Radeon 8060S (Strix Halo, gfx1151) + ROCm 7.2.4 + PyTorch 2.9.1 — and the device-specific values (name, device_id, gfx arch) will naturally differ on other cards:

Telemetry that the platform does not expose (clock_info, temp_metric, power_info, gpu_activity) raises AMDSMI_STATUS_NOT_SUPPORTED, as expected.

License

MIT. Status constants, enum values and exception classes are derived from the MIT-licensed ROCm/amdsmi project.