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Address reviewer feedback: cmake PATH persistence, stale cache, torch error check

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1. Persist cmake PATH to user registry so Refresh-Environment cannot
   drop it later in the same setup run. Previously the process-only
   PATH addition at phase 1 could vanish when Refresh-Environment
   rebuilt PATH from registry during phase 2/3 installs.

2. Clean stale CMake cache before configure. If a previous run built
   with CUDA and the user reruns without a GPU (or vice versa), the
   cached GGML_CUDA value would persist. Now the build dir is removed
   before configure.

3. Explicitly set -DGGML_CUDA=OFF for CPU-only builds instead of just
   omitting CUDA flags. This prevents cmake from auto-detecting a
   partial CUDA installation.

4. Fix CUDA cmake flag indentation -- was misaligned from the original
   PR, now consistently indented inside the if/else block.

5. Fail hard if pip install torch returns a non-zero exit code instead
   of silently continuing with a broken environment.
This commit is contained in:
Daniel Han 2026-03-18 06:12:27 +00:00
commit 4f1e9df5ff
1 changed files with 47 additions and 25 deletions
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72
studio/setup.ps1
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@ -351,6 +351,11 @@ if (-not $HasCmake) {
foreach ($d in $cmakeDefaults) {
if (Test-Path (Join-Path $d "cmake.exe")) {
$env:Path = "$d;$env:Path"
# Persist to user PATH so Refresh-Environment does not drop it later
$userPath = [Environment]::GetEnvironmentVariable('Path', 'User')
if (-not $userPath -or $userPath -notlike "*$d*") {
[Environment]::SetEnvironmentVariable('Path', "$d;$userPath", 'User')
}
$HasCmake = $null -ne (Get-Command cmake -ErrorAction SilentlyContinue)
if ($HasCmake) {
Write-Host " Found cmake at $d (added to PATH)" -ForegroundColor Gray
@ -920,6 +925,10 @@ if ($HasNvidiaSmi) {
Write-Host " Installing PyTorch with CUDA support ($CuTag)..." -ForegroundColor Cyan
Write-Host " (This download is ~2.8 GB -- may take a few minutes)" -ForegroundColor Gray
pip install torch torchvision torchaudio --index-url "https://download.pytorch.org/whl/$CuTag"
if ($LASTEXITCODE -ne 0) {
Write-Host "[FAILED] PyTorch CUDA install failed (exit code $LASTEXITCODE)" -ForegroundColor Red
exit 1
}
# Install Triton for Windows (enables torch.compile -- without it training can hang)
Write-Host " Installing Triton for Windows..." -ForegroundColor Cyan
@ -928,6 +937,10 @@ if ($HasNvidiaSmi) {
} else {
Write-Host " Installing PyTorch (CPU-only)..." -ForegroundColor Cyan
pip install torch torchvision torchaudio
if ($LASTEXITCODE -ne 0) {
Write-Host "[FAILED] PyTorch install failed (exit code $LASTEXITCODE)" -ForegroundColor Red
exit 1
}
}
# Ordered heavy dependency installation — shared cross-platform script
@ -1091,7 +1104,14 @@ if (Test-Path $LlamaServerBin) {
}
}
# -- Step B: cmake configure (CUDA + Unsloth flags) --
# -- Step B: cmake configure --
# Clean stale CMake cache to prevent previous CUDA settings from leaking
# into a CPU-only rebuild (or vice versa).
$CmakeCacheFile = Join-Path $BuildDir "CMakeCache.txt"
if (Test-Path $CmakeCacheFile) {
Remove-Item -Recurse -Force $BuildDir
}
if ($BuildOk) {
Write-Host ""
Write-Host "--- cmake configure ---" -ForegroundColor Cyan
@ -1120,33 +1140,35 @@ if (Test-Path $LlamaServerBin) {
$CmakeArgs += '-DLLAMA_CURL=OFF'
}
$CmakeArgs += '-DCMAKE_EXE_LINKER_FLAGS=/NODEFAULTLIB:LIBCMT'
# CUDA flags (Unsloth-aligned) -- only if GPU available
# CUDA flags -- only if GPU available, otherwise explicitly disable
if ($HasNvidiaSmi -and $NvccPath) {
$CmakeArgs += '-DGGML_CUDA=ON'
$CmakeArgs += "-DCUDAToolkit_ROOT=$CudaToolkitRoot"
$CmakeArgs += "-DCUDA_TOOLKIT_ROOT_DIR=$CudaToolkitRoot"
$CmakeArgs += "-DCMAKE_CUDA_COMPILER=$NvccPath"
$CmakeArgs += '-DGGML_CUDA_FA_ALL_QUANTS=ON'
$CmakeArgs += '-DGGML_CUDA_F16=OFF'
$CmakeArgs += '-DGGML_CUDA_GRAPHS=OFF'
$CmakeArgs += '-DGGML_CUDA_FORCE_CUBLAS=OFF'
$CmakeArgs += '-DGGML_CUDA_PEER_MAX_BATCH_SIZE=8192'
if ($CudaArch) {
# Validate nvcc actually supports this architecture
if (Test-NvccArchSupport -NvccExe $NvccPath -Arch $CudaArch) {
$CmakeArgs += "-DCMAKE_CUDA_ARCHITECTURES=$CudaArch"
} else {
# GPU arch too new for this toolkit — fall back to highest supported.
# PTX forward-compatibility will JIT-compile for the actual GPU at runtime.
$maxArch = Get-NvccMaxArch -NvccExe $NvccPath
if ($maxArch) {
$CmakeArgs += "-DCMAKE_CUDA_ARCHITECTURES=$maxArch"
Write-Host " [WARN] GPU is sm_$CudaArch but nvcc only supports up to sm_$maxArch" -ForegroundColor Yellow
Write-Host " Building with sm_$maxArch (PTX will JIT for your GPU at runtime)" -ForegroundColor Yellow
$CmakeArgs += '-DGGML_CUDA=ON'
$CmakeArgs += "-DCUDAToolkit_ROOT=$CudaToolkitRoot"
$CmakeArgs += "-DCUDA_TOOLKIT_ROOT_DIR=$CudaToolkitRoot"
$CmakeArgs += "-DCMAKE_CUDA_COMPILER=$NvccPath"
$CmakeArgs += '-DGGML_CUDA_FA_ALL_QUANTS=ON'
$CmakeArgs += '-DGGML_CUDA_F16=OFF'
$CmakeArgs += '-DGGML_CUDA_GRAPHS=OFF'
$CmakeArgs += '-DGGML_CUDA_FORCE_CUBLAS=OFF'
$CmakeArgs += '-DGGML_CUDA_PEER_MAX_BATCH_SIZE=8192'
if ($CudaArch) {
# Validate nvcc actually supports this architecture
if (Test-NvccArchSupport -NvccExe $NvccPath -Arch $CudaArch) {
$CmakeArgs += "-DCMAKE_CUDA_ARCHITECTURES=$CudaArch"
} else {
# GPU arch too new for this toolkit -- fall back to highest supported.
# PTX forward-compatibility will JIT-compile for the actual GPU at runtime.
$maxArch = Get-NvccMaxArch -NvccExe $NvccPath
if ($maxArch) {
$CmakeArgs += "-DCMAKE_CUDA_ARCHITECTURES=$maxArch"
Write-Host " [WARN] GPU is sm_$CudaArch but nvcc only supports up to sm_$maxArch" -ForegroundColor Yellow
Write-Host " Building with sm_$maxArch (PTX will JIT for your GPU at runtime)" -ForegroundColor Yellow
}
# else: omit flag entirely, let cmake pick defaults
}
# else: omit flag entirely, let cmake pick defaults
}
}
} else {
$CmakeArgs += '-DGGML_CUDA=OFF'
}
$cmakeOutput = cmake @CmakeArgs 2>&1 | Out-String