From 9e3d94eca356afaa9444504bef41644f4ee1423e Mon Sep 17 00:00:00 2001
From: Przemek Pawlas <3606072+Destroy666x@users.noreply.github.com>
Date: Fri, 15 Sep 2023 20:16:52 +0200
Subject: [PATCH] fix: Windows CUDA compilation was incorrectly described

---
 .github/scripts/Build-Windows.ps1 | 4 ++--
 README.md                         | 4 ++--
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/.github/scripts/Build-Windows.ps1 b/.github/scripts/Build-Windows.ps1
index 458b60e..2d4c4ca 100644
--- a/.github/scripts/Build-Windows.ps1
+++ b/.github/scripts/Build-Windows.ps1
@@ -7,7 +7,7 @@ param(
     [switch] $SkipAll,
     [switch] $SkipBuild,
     [switch] $SkipDeps,
-    [string] $ExtraCmakeArgs
+    [string[]] $ExtraCmakeArgs
 )
 
 $ErrorActionPreference = 'Stop'
@@ -58,7 +58,7 @@ function Build {
         Ensure-Location $ProjectRoot
 
         # take cmake args from $ExtraCmakeArgs
-        $CmakeArgs = @($ExtraCmakeArgs)
+        $CmakeArgs = $ExtraCmakeArgs
         $CmakeBuildArgs = @()
         $CmakeInstallArgs = @()
 
diff --git a/README.md b/README.md
index f8a9a41..776771e 100644
--- a/README.md
+++ b/README.md
@@ -95,7 +95,7 @@ After installing the CUDA toolkit, you need to set variables to point CMake to t
 
 For example
 ```powershell
-> .github/scripts/Build-Windows.ps1 -Target x64 -ExtraCmakeFlags "-D LOCALVOCAL_WITH_CUDA=ON -D CUDA_TOOLKIT_ROOT_DIR='C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.4'"
+.github/scripts/Build-Windows.ps1 -Target x64 -ExtraCmakeArgs '-D','LOCALVOCAL_WITH_CUDA=ON','-D',"CUDA_TOOLKIT_ROOT_DIR='C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.2'"
 ```
 
 You will need to copy a few CUDA .dll files to the location of the plugin .dll for it to run. The required .dll files from CUDA (which are located in the `bin` folder of the CUDA toolkit installation directory) are:
@@ -104,4 +104,4 @@ You will need to copy a few CUDA .dll files to the location of the plugin .dll f
 - `cublas64_NN.dll`
 - `cublasLt64_NN.dll`
 
-where `NN` is the CUDA version number. For example, if you have installed CUDA 11.4 then `NN` is likely `11`.
+where `NN` is the CUDA major version number. For example, if you have installed CUDA 12.2 as in example above, then `NN` is `12`.