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Set short TORCHINDUCTOR_CACHE_DIR to fix Windows MAX_PATH crash

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This commit is contained in:
Roland Tannous 2026-02-27 21:50:54 +00:00
commit bd7c17708b
1 changed files with 9 additions and 0 deletions
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9
setup.ps1
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@ -493,6 +493,15 @@ pip install --upgrade pip 2>&1 | Out-Null
# PyTorch bundles its own CUDA runtime, so this works regardless
# of whether the CUDA Toolkit is installed yet.
# The CUDA tag is chosen based on the driver's max supported CUDA version.
# Windows MAX_PATH (260 chars) causes Triton kernel compilation to fail because
# the auto-generated filenames are extremely long. Use a short cache directory.
$TorchCacheDir = "C:\tc"
if (-not (Test-Path $TorchCacheDir)) { New-Item -ItemType Directory -Path $TorchCacheDir -Force | Out-Null }
$env:TORCHINDUCTOR_CACHE_DIR = $TorchCacheDir
[Environment]::SetEnvironmentVariable('TORCHINDUCTOR_CACHE_DIR', $TorchCacheDir, 'User')
Write-Host "[OK] TORCHINDUCTOR_CACHE_DIR set to $TorchCacheDir (avoids MAX_PATH issues)" -ForegroundColor Green
$CuTag = Get-PytorchCudaTag
Write-Host " Installing PyTorch with CUDA support ($CuTag)..." -ForegroundColor Cyan
pip install torch torchvision torchaudio --index-url "https://download.pytorch.org/whl/$CuTag" 2>&1 | Out-Null