Harden Windows-on-Arm WSL fallback: native-CUDA probe + WSL-forwarding unsloth shim
- Future-proof: probe whether a CUDA torch wheel is installable natively for win_arm64 (uv pip install --dry-run). If it resolves (NVIDIA ships the wheel) keep the NATIVE install; otherwise fall back to WSL. WSL is used ONLY when native genuinely can't. - Create a native Windows unsloth.cmd shim (on user PATH) that forwards every "unsloth ..." into the WSL GPU env, so "unsloth studio" / "unsloth studio run" typed in PowerShell run inside WSL and stream output + the http://localhost:8888 URL back. - Run the WSL install under Continue-EAP and verify torch.cuda before reporting success so the optional (aarch64) llama.cpp prebuilt failure cannot abort or mis-report. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
Daniel Han
parent
b7e9dae027
commit
8fbd8e3fa2
1 changed files with 43 additions and 9 deletions
52
install.ps1
52
install.ps1
|
|
@ -1459,15 +1459,27 @@ shell.Run cmd, 0, False
|
|||
|
||||
# ===== Windows-on-ARM + NVIDIA GPU -> automatic WSL2 fallback (N1X "RTX Spark" / DGX Spark-class) =====
|
||||
# Native Windows-ARM64 has no CUDA PyTorch wheel and no Triton wheel for win_arm64, so the GPU
|
||||
# training/inference stack cannot run natively. When an NVIDIA GPU is present on ARM64, transparently
|
||||
# set up the supported path for an average user: enable/install WSL2 and run the Linux installer there
|
||||
# (full GPU). STRICTLY gated on ARM64 + NVIDIA -> normal x86_64 Windows (NVIDIA or AMD) and
|
||||
# ARM64-without-NVIDIA are byte-for-byte unaffected and continue the native install below.
|
||||
# stack can't run natively today. When an NVIDIA GPU is present on ARM64 AND native CUDA PyTorch is
|
||||
# NOT installable for this platform, set up the supported path: enable/install WSL2, run the Linux
|
||||
# installer there (full GPU), and create a Windows `unsloth` shim that forwards into WSL.
|
||||
# STRICTLY gated -> normal x86_64 Windows (NVIDIA or AMD) and ARM64-without-NVIDIA are byte-for-byte
|
||||
# unaffected and continue the native install below. FUTURE-PROOF: if NVIDIA ships a win_arm64 CUDA
|
||||
# torch wheel, the probe below passes and the native install is kept automatically.
|
||||
# Opt out with UNSLOTH_NO_WSL_FALLBACK=1; choose the distro with UNSLOTH_WSL_DISTRO.
|
||||
try { $_winArm64 = ([System.Runtime.InteropServices.RuntimeInformation]::OSArchitecture.ToString() -ieq 'Arm64') } catch { $_winArm64 = $false }
|
||||
if ($_winArm64 -and $HasNvidiaSmi -and (-not $SkipTorch) -and ($env:UNSLOTH_NO_WSL_FALLBACK -ne '1')) {
|
||||
step "wsl" "Windows on ARM + NVIDIA detected -- routing GPU setup through WSL2 (supported path)"
|
||||
substep "native Windows-ARM64 has no CUDA PyTorch/Triton yet; WSL2 delivers full GPU." "Yellow"
|
||||
$_nativeCudaTorchOk = $false
|
||||
if ($_winArm64 -and $HasNvidiaSmi -and (-not $SkipTorch)) {
|
||||
# Future-proof check: can a CUDA-capable torch wheel be resolved natively for this platform/index?
|
||||
$prevEapProbe = $ErrorActionPreference; $ErrorActionPreference = "Continue"
|
||||
try {
|
||||
& uv pip install --python $VenvPython --dry-run torch --index-url $TorchIndexUrl *> $null
|
||||
$_nativeCudaTorchOk = ($LASTEXITCODE -eq 0)
|
||||
} catch { $_nativeCudaTorchOk = $false } finally { $ErrorActionPreference = $prevEapProbe }
|
||||
if ($_nativeCudaTorchOk) { step "gpu" "native CUDA PyTorch now available for win_arm64 -- keeping native install" "Green" }
|
||||
}
|
||||
if ($_winArm64 -and $HasNvidiaSmi -and (-not $_nativeCudaTorchOk) -and (-not $SkipTorch) -and ($env:UNSLOTH_NO_WSL_FALLBACK -ne '1')) {
|
||||
step "wsl" "Windows on ARM + NVIDIA, native CUDA unavailable -- routing GPU setup through WSL2"
|
||||
substep "no win_arm64 CUDA PyTorch/Triton yet; WSL2 delivers full GPU (DGX Spark / RTX Spark path)." "Yellow"
|
||||
|
||||
$wslReady = $false
|
||||
if (Get-Command wsl.exe -ErrorAction SilentlyContinue) {
|
||||
|
|
@ -1523,11 +1535,33 @@ shell.Run cmd, 0, False
|
|||
} catch {} finally { $ErrorActionPreference = $prevEapChk }
|
||||
if ($torchOk) {
|
||||
step "done" "Unsloth Studio installed in WSL '$distro' -- GPU ready (torch.cuda available)." "Green"
|
||||
# Native Windows `unsloth` shim: forward every `unsloth ...` into the WSL GPU env so the user
|
||||
# never has to touch WSL. `unsloth studio` runs inside WSL and streams output + URL back here;
|
||||
# WSL2 forwards 127.0.0.1, so http://localhost:8888 works in the Windows browser.
|
||||
try {
|
||||
$shimDir = Join-Path $env:LOCALAPPDATA "Unsloth\bin"
|
||||
New-Item -ItemType Directory -Force -Path $shimDir *> $null
|
||||
$shimLines = @(
|
||||
'@echo off',
|
||||
"wsl.exe -d $distro -u root -- /root/.unsloth/studio/unsloth_studio/bin/unsloth %*"
|
||||
)
|
||||
Set-Content -LiteralPath (Join-Path $shimDir "unsloth.cmd") -Value $shimLines -Encoding ASCII
|
||||
$userPath = [Environment]::GetEnvironmentVariable("Path", "User")
|
||||
if (($userPath -split ';') -notcontains $shimDir) {
|
||||
[Environment]::SetEnvironmentVariable("Path", ($userPath.TrimEnd(';') + ";" + $shimDir), "User")
|
||||
}
|
||||
$env:Path = $env:Path.TrimEnd(';') + ";" + $shimDir
|
||||
step "shim" "created native 'unsloth' command -> forwards to WSL '$distro'" "Green"
|
||||
substep "open a NEW terminal, then (no WSL knowledge needed):" "Cyan"
|
||||
substep " unsloth studio # runs in WSL; opens http://localhost:8888" "Cyan"
|
||||
substep " unsloth studio run # also forwarded into WSL" "Cyan"
|
||||
} catch {
|
||||
substep "(shim creation failed; launch manually): wsl -d $distro -u root -- bash -lic 'unsloth studio -p 8888'" "Yellow"
|
||||
}
|
||||
} else {
|
||||
step "wsl" "WSL Studio install did not finish cleanly (torch.cuda not detected; inner exit $wslRc) -- see log above." "Yellow"
|
||||
substep "retry, or launch manually: wsl -d $distro -u root -- bash -lic 'unsloth studio -p 8888'" "Cyan"
|
||||
}
|
||||
substep "Launch it from Windows (then open http://localhost:8888):" "Cyan"
|
||||
substep " wsl -d $distro -u root -- bash -lic 'unsloth studio -p 8888'" "Cyan"
|
||||
substep "GPU training + GGUF export run inside WSL. (GGUF *inference* additionally needs a CUDA llama.cpp build.)" "Yellow"
|
||||
if ($torchOk) { $global:LASTEXITCODE = 0 }
|
||||
return
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue