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https://github.com/guillaumemeyer/watermarks-remover.git
synced 2026-08-22 13:11:57 +02:00
fix: Windows setup_ctrlregen.ps1 torch install (probe published indices, keep CUDA torch) (#124)
Three independent failure modes from #117: - $ErrorActionPreference 'Stop' + 2>$null on a native command aborts the script on torch's harmless stderr warnings (e.g. "Failed to initialize NumPy" when torch is installed before numpy). Run the probes through a new Invoke-NativeQuiet helper that lowers EAP to 'Continue' for the block and restores it afterwards. - The wheel index tag was derived from the driver's CUDA version, e.g. cu131 for a 13.1 driver, which does not exist (HTTP 403) and silently fell back to the default index, i.e. the CPU build on Windows. Probe the published indices and pick the highest one <= driver that answers HTTP 200; cu126 is still forced below compute capability 7.5. - Installing torch alone let requirements-ctrlregen.txt resolve torchvision from PyPI, and torchvision pins an exact torch, so pip replaced the +cu build with a +cpu one while the script still exited 0. Install torch AND torchvision together from the chosen index, and verify after the requirements install that torch.cuda.is_available() is true - if a GPU was detected but torch ends up CPU-only, warn loudly and exit non-zero. Also add a CI step (windows-latest, pwsh) that parses the setup .ps1 scripts and asserts the post-install CUDA verification survives. Fixes #117
This commit is contained in:
Guillaume Meyer (The Opinionated Man)
parent
b3de4c0085
commit
d4dd4735e9
@@ -1,28 +1,35 @@
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<#
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.SYNOPSIS
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Port a Windows de setup_ctrlregen.sh.
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Windows port of setup_ctrlregen.sh.
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.DESCRIPTION
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Bootstrap del checkout externo noai-watermark para el backend opcional de
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eliminacion en dominio de pixel (CtrlRegen).
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Bootstraps an external noai-watermark checkout for the optional CtrlRegen
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pixel-domain removal backend.
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El proyecto upstream (https://github.com/mertizci/noai-watermark) no incluye
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fichero LICENSE, asi que su codigo se trata como all-rights-reserved y NO se
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empaqueta en este repositorio. Este script lo clona en local e instala solo
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las dependencias que necesita clean_ctrlregen.py.
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The upstream project (https://github.com/mertizci/noai-watermark) does not
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ship a LICENSE file, so its code is treated as all-rights-reserved and is NOT
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bundled in this repository. This script clones it locally and installs only
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the dependencies that clean_ctrlregen.py needs.
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Diferencia con la version .sh: el venv de Windows vive en .venv\Scripts\
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en vez de .venv/bin/, y si el indice de torch para tu version de CUDA no
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existe se cae al torch por defecto en vez de abortar.
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Differences from the .sh version: the Windows venv lives in .venv\Scripts\
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instead of .venv/bin/.
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The torch index is not derived from the driver's CUDA version: the published
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indices are probed (the highest one <= the driver's CUDA that answers HTTP
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200), and torch AND torchvision are installed together from that index so
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installing requirements-ctrlregen.txt cannot replace them with CPU builds
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from PyPI. If a GPU is detected but the final torch has no CUDA support, the
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script warns loudly and exits with a non-zero exit code (never "Done" with a
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silent CPU-only environment).
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.PARAMETER Dir
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Directorio del checkout (por defecto: $env:NOAI_WATERMARK_DIR o ~\noai-watermark)
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Checkout directory (default: $env:NOAI_WATERMARK_DIR or ~\noai-watermark)
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.PARAMETER Ref
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Commit a usar (por defecto: el SHA fijado; no apuntes a una rama movil)
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Commit to use (default: the pinned SHA; do not point at a moving branch)
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.PARAMETER Python
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Interprete usado para crear el venv (por defecto: python)
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Interpreter used to create the venv (default: python)
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#>
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[CmdletBinding()]
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param(
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@@ -37,7 +44,24 @@ $ScriptDir = Split-Path -Parent $MyInvocation.MyCommand.Path
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function Invoke-Checked {
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param([string]$What, [scriptblock]$Block)
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& $Block
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if ($LASTEXITCODE -ne 0) { throw "$What fallo (codigo $LASTEXITCODE)" }
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if ($LASTEXITCODE -ne 0) { throw "$What failed (exit code $LASTEXITCODE)" }
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}
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# Runs a native command discarding its stderr safely.
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# In Windows PowerShell, redirecting a native executable's stderr (2>$null,
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# 2>&1, 2>file) wraps each line in an ErrorRecord; with
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# $ErrorActionPreference = 'Stop' the first one aborts the script. Lower EAP to
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# 'Continue' for just this block (e.g. torch warnings on stderr) and restore it
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# afterwards.
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function Invoke-NativeQuiet {
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param([scriptblock]$Block)
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$prev = $ErrorActionPreference
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try {
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$ErrorActionPreference = 'Continue'
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& $Block 2>$null
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} finally {
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$ErrorActionPreference = $prev
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}
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}
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if (-not $Dir) {
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@@ -50,89 +74,148 @@ if (-not (Test-Path $Dir)) { New-Item -ItemType Directory -Force -Path $Dir | Ou
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$Dir = (Resolve-Path $Dir).Path
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if (-not (Test-Path (Join-Path $Dir '.git'))) {
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Write-Host "Clonando noai-watermark en $Dir (ref fijado: $Ref)"
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Write-Host "Cloning noai-watermark into $Dir (pinned ref: $Ref)"
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Invoke-Checked 'git clone' { git clone --depth 1 --filter=blob:none --sparse https://github.com/mertizci/noai-watermark.git $Dir }
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Invoke-Checked 'git fetch' { git -C $Dir fetch --depth 1 origin $Ref }
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Invoke-Checked 'git checkout' { git -C $Dir checkout --detach $Ref }
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Invoke-Checked 'sparse-checkout' { git -C $Dir sparse-checkout set --no-cone '/src/' }
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$head = (git -C $Dir rev-parse HEAD).Trim()
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if ($head -ne $Ref) { throw "error: se esperaba el ref fijado $Ref, se obtuvo $head" }
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if ($head -ne $Ref) { throw "error: expected pinned ref $Ref, got $head" }
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} else {
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Write-Host "Usando checkout existente: $Dir"
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Write-Host "Using existing checkout: $Dir"
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}
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$venvPython = Join-Path $Dir '.venv\Scripts\python.exe'
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if (-not (Test-Path $venvPython)) {
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Write-Host "Creando venv en $Dir\.venv"
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Invoke-Checked 'crear venv' { & $Python -m venv (Join-Path $Dir '.venv') }
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Write-Host "Creating venv at $Dir\.venv"
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Invoke-Checked 'create venv' { & $Python -m venv (Join-Path $Dir '.venv') }
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}
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Write-Host 'Instalando dependencias de Python'
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# pip fijado (un --upgrade pip sin pin es un punto de deriva de cadena de suministro).
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Write-Host 'Installing Python dependencies'
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# Pinned pip (an unpinned --upgrade pip was a supply-chain drift point).
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Invoke-Checked 'pip install pip' { & $venvPython -m pip install --upgrade 'pip==26.2.1' }
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# torch con el indice de plataforma correcto antes que el resto de pines.
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# Install torch from the correct platform index before the remaining pins.
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#
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# OJO: nvidia-smi reporta la CUDA MAXIMA QUE SOPORTA EL DRIVER, no la que hay
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# que instalar; el driver es retrocompatible, asi que un wheel cu126 corre sin
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# problema sobre un driver 13.0. Derivar el tag del wheel de esa cifra -como
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# hace la version .sh- es incorrecto en general, y rompe de verdad en GPUs
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# antiguas: los wheels cu128+ y CUDA 13 eliminaron Maxwell/Pascal/Volta, asi
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# que en una Pascal (sm_61) instalarian un torch sin kernels para la tarjeta y
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# fallaria en ejecucion con "no kernel image is available for execution".
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# Por eso mandamos la compute capability, no la version del driver.
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# NOTE: nvidia-smi reports the MAXIMUM CUDA the driver supports, not the CUDA
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# to install; the driver is backward compatible, so a cu126 wheel runs fine on
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# a 13.0 driver. Deriving the wheel tag from that number - as the .sh version
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# does - is wrong in general: there is no index per driver version (e.g. a 13.1
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# driver would yield cu131, which does not exist, HTTP 403, and the script
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# would fall back to the default torch, which is the CPU build on Windows).
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# Instead the published indices are probed and the highest one <= the driver's
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# CUDA is chosen. Also, cu128+ / CUDA 13 wheels dropped Maxwell/Pascal/Volta
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# kernels, so on a Pascal (sm_61) they would install a torch without kernels
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# for the card, failing at runtime with "no kernel image is available for
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# execution". That is why the compute capability is used, not the driver
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# version.
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$knownTags = @(
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@{ tag = 'cu130'; version = [version]'13.0' },
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@{ tag = 'cu129'; version = [version]'12.9' },
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@{ tag = 'cu128'; version = [version]'12.8' },
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@{ tag = 'cu126'; version = [version]'12.6' },
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@{ tag = 'cu124'; version = [version]'12.4' },
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@{ tag = 'cu121'; version = [version]'12.1' },
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@{ tag = 'cu118'; version = [version]'11.8' }
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)
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# Picks the wheel index: the highest one <= the driver's CUDA answering 2xx.
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# cc < 7.5 forces cu126 (last index with Maxwell/Pascal/Volta kernels).
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function Select-TorchTag([double]$cc, [string]$driverCuda) {
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if ($cc -and $cc -lt 7.5) { return 'cu126' }
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if ($driverCuda -notmatch '^([0-9]+)\.([0-9]+)$') { return $null }
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$driverVersion = [version]"$($Matches[1]).$($Matches[2])"
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foreach ($c in $knownTags) {
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if ($c.version -gt $driverVersion) { continue }
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try {
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$resp = Invoke-WebRequest -UseBasicParsing -Method Head -Uri "https://download.pytorch.org/whl/$($c.tag)" -TimeoutSec 15 -ErrorAction Stop
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if ($resp.StatusCode -ge 200 -and $resp.StatusCode -lt 300) { return $c.tag }
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} catch { } # index not published / network error: try the next one
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}
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return $null
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}
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$cuda = $null
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$cc = $null
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if (Get-Command nvidia-smi -ErrorAction SilentlyContinue) {
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$smi = (& nvidia-smi | Out-String)
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if ($smi -match 'CUDA Version:\s*([0-9]+\.[0-9]+)') { $cuda = $Matches[1] }
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$capRaw = (& nvidia-smi --query-gpu=compute_cap --format=csv,noheader 2>$null | Select-Object -First 1)
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$capRaw = (Invoke-NativeQuiet { & nvidia-smi --query-gpu=compute_cap --format=csv,noheader } | Select-Object -First 1)
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if ($capRaw -and ($capRaw.Trim() -match '^[0-9]+\.[0-9]+$')) { $cc = [double]$capRaw.Trim() }
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}
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# Install torch AND torchvision together from the same index. If only torch
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# were installed, the requirements install would resolve torchvision from PyPI,
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# and torchvision pins an exact torch version, so pip would uninstall the +cu
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# build and replace it with the +cpu one, silently and with exit 0. Installing
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# them together closes that hole; the final verification below checks it too.
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$torchOk = $false
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if ($cuda) {
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if ($cc -and $cc -lt 7.5) {
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# Ultimo indice cuyos wheels aun traen kernels de Maxwell/Pascal/Volta.
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$tag = 'cu126'
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Write-Host "GPU NVIDIA compute capability $cc (anterior a Turing): forzando $tag,"
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Write-Host "porque los wheels cu128+ / CUDA 13 ya no incluyen kernels para esta tarjeta."
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Write-Host "NVIDIA GPU with compute capability $cc (pre-Turing): forcing $tag,"
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Write-Host "because cu128+ / CUDA 13 wheels no longer ship kernels for this card."
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} else {
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$tag = 'cu' + ($cuda -replace '\.', '')
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Write-Host "GPU NVIDIA detectada (driver soporta CUDA $cuda); usando $tag"
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$tag = Select-TorchTag $cc $cuda
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if ($tag) {
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Write-Host "NVIDIA GPU detected (driver supports CUDA $cuda); using published index $tag"
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} else {
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Write-Warning "no published torch index <= CUDA $cuda; falling back to the default torch (likely CPU)"
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}
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}
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if ($tag) {
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$index = "https://download.pytorch.org/whl/$tag"
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& $venvPython -m pip install torch torchvision --index-url $index
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if ($LASTEXITCODE -eq 0) { $torchOk = $true }
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else { Write-Warning "the index $index failed; falling back to the default torch" }
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}
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$index = "https://download.pytorch.org/whl/$tag"
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& $venvPython -m pip install torch --index-url $index
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if ($LASTEXITCODE -eq 0) { $torchOk = $true }
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else { Write-Warning "el indice $index fallo; se cae al torch por defecto" }
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} else {
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Write-Host 'Sin GPU NVIDIA detectada; instalando torch por defecto (CPU)'
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Write-Host 'No NVIDIA GPU detected; installing the default torch (CPU)'
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}
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if (-not $torchOk) {
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Invoke-Checked 'pip install torch' { & $venvPython -m pip install torch }
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}
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# Comprobacion decisiva: que el torch instalado traiga kernels para ESTA GPU.
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if ($cc) {
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$smTarget = 'sm_' + ($cc -replace '\.', '')
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$archs = (& $venvPython -c "import torch; print(' '.join(torch.cuda.get_arch_list()))" 2>$null)
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if ($LASTEXITCODE -eq 0 -and $archs) {
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if ($archs -match [regex]::Escape($smTarget)) {
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Write-Host "OK: torch incluye $smTarget (archs: $archs)"
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} else {
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Write-Warning "el torch instalado NO incluye $smTarget - CtrlRegen fallara en GPU."
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Write-Warning "archs disponibles: $archs"
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Write-Warning "reinstala con un indice mas antiguo, p.ej.:"
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Write-Warning " & '$venvPython' -m pip install --force-reinstall torch --index-url https://download.pytorch.org/whl/cu126"
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}
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}
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Invoke-Checked 'pip install torch torchvision' { & $venvPython -m pip install torch torchvision }
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}
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Invoke-Checked 'pip install requirements' { & $venvPython -m pip install -r (Join-Path $ScriptDir 'requirements-ctrlregen.txt') }
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# Final verification (AFTER requirements, the step that could have replaced the
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# +cu torch with a +cpu one): if a GPU is present but the final torch has no
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# CUDA support, warn loudly and exit non-zero instead of pretending success
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# with a silent CPU-only environment.
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if ($cc -or $cuda) {
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$probe = Invoke-NativeQuiet {
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& $venvPython -c "import torch; print(torch.cuda.is_available()); print(' '.join(torch.cuda.get_arch_list()))"
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}
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if ($LASTEXITCODE -eq 0 -and $probe) {
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$lines = @($probe)
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$cudaOk = ($lines[0].Trim() -eq 'True')
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$archs = $lines[1]
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if (-not $cudaOk) {
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Write-Warning 'NVIDIA GPU detected but torch.cuda.is_available() = False.'
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Write-Warning 'CtrlRegen would run on CPU (very slow) or fail on GPU.'
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Write-Warning 'Reinstall torch and torchvision together from a published index, e.g.:'
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Write-Warning " & '$venvPython' -m pip install --force-reinstall torch torchvision --index-url https://download.pytorch.org/whl/cu130"
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exit 1
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}
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if ($cc) {
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$smTarget = 'sm_' + ($cc -replace '\.', '')
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if ($archs -and ($archs -notmatch [regex]::Escape($smTarget))) {
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Write-Warning "the installed torch does NOT include $smTarget - CtrlRegen will fail on GPU."
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Write-Warning "available archs: $archs"
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Write-Warning "reinstall from an older index, e.g.:"
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Write-Warning " & '$venvPython' -m pip install --force-reinstall torch torchvision --index-url https://download.pytorch.org/whl/cu126"
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} elseif ($archs) {
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Write-Host "OK: torch includes $smTarget (archs: $archs)"
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}
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}
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} else {
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Write-Warning 'could not verify torch after installing requirements'
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}
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}
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Write-Host ''
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Write-Host 'Listo. Para quitar una marca:'
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Write-Host 'Done. Remove a watermark with:'
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Write-Host ''
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Write-Host " `$env:NOAI_WATERMARK_DIR = '$Dir'"
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Write-Host " & '$venvPython' '$ScriptDir\clean_ctrlregen.py' IMAGEN -o SALIDA"
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Write-Host " \`$env:NOAI_WATERMARK_DIR = '$Dir'"
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Write-Host " & '$venvPython' '$ScriptDir\clean_ctrlregen.py' IMAGE -o OUTPUT"
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