* Bundle zlibwapi.dll required by cuDNN in redist artifacts of pre…

…sets for CUDA (issue bytedeco/javacv#1767)

.github/actions/deploy-windows/action.yml

@@ -74,11 +74,14 @@ runs:
           echo Installing CUDA, cuDNN, etc
           curl -LO https://developer.download.nvidia.com/compute/cuda/11.6.0/local_installers/cuda_11.6.0_511.23_windows.exe
           curl -LO https://developer.download.nvidia.com/compute/redist/cudnn/v8.3.2/local_installers/11.5/cudnn-windows-x86_64-8.3.2.44_cuda11.5-archive.zip
+          curl -LO http://www.winimage.com/zLibDll/zlib123dllx64.zip
           cuda_11.6.0_511.23_windows.exe -s
           unzip cudnn-windows-x86_64-8.3.2.44_cuda11.5-archive.zip
+          unzip zlib123dllx64.zip
           move cudnn-windows-x86_64-8.3.2.44_cuda11.5-archive\bin\*.dll "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v11.6\bin"
           move cudnn-windows-x86_64-8.3.2.44_cuda11.5-archive\include\*.h "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v11.6\include"
           move cudnn-windows-x86_64-8.3.2.44_cuda11.5-archive\lib\*.lib "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v11.6\lib\x64"
+          move dll_x64/zlibwapi.dll "%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v11.6\bin"
 
           echo Applying hotfix to Visual Studio 2019 for CUDA
           curl -LO https://github.com/raw/microsoft/STL/main/stl/inc/cmath

CHANGELOG.md

@@ -1,4 +1,5 @@
 
+ * Bundle `zlibwapi.dll` required by cuDNN in redist artifacts of presets for CUDA ([issue bytedeco/javacv#1767](https://github.com/bytedeco/javacv/issues/1767))
  * Harmonize string and buffer pointer types of function parameters from DepthAI ([issue #1155](https://github.com/bytedeco/javacpp-presets/issues/1155))
  * Bundle correctly OpenMP library for PyTorch builds on Mac as well
  * Remove dependency on CUDA from presets for Triton Inference Server ([pull #1151](https://github.com/bytedeco/javacpp-presets/pull/1151))

cuda/src/main/java/org/bytedeco/cuda/presets/cudnn.java

@@ -36,7 +36,7 @@
 @Properties(inherit = cublas.class, value = {
     @Platform(include = {"<cudnn.h>", "<cudnn_version.h>", "<cudnn_ops_infer.h>", "<cudnn_ops_train.h>", "<cudnn_adv_infer.h>", "<cudnn_adv_train.h>", "<cudnn_cnn_infer.h>", "<cudnn_cnn_train.h>"},
         link = {"cudnn@.8", "cudnn_ops_infer@.8", "cudnn_ops_train@.8", "cudnn_adv_infer@.8", "cudnn_adv_train@.8", "cudnn_cnn_infer@.8", "cudnn_cnn_train@.8"}),
-    @Platform(value = "windows-x86_64", preload = {"cudnn64_8", "cudnn_ops_infer64_8", "cudnn_ops_train64_8", "cudnn_adv_infer64_8", "cudnn_adv_train64_8", "cudnn_cnn_infer64_8", "cudnn_cnn_train64_8"})},
+    @Platform(value = "windows-x86_64", preload = {"zlibwapi", "cudnn64_8", "cudnn_ops_infer64_8", "cudnn_ops_train64_8", "cudnn_adv_infer64_8", "cudnn_adv_train64_8", "cudnn_cnn_infer64_8", "cudnn_cnn_train64_8"})},
         target = "org.bytedeco.cuda.cudnn", global = "org.bytedeco.cuda.global.cudnn")
 @NoException
 public class cudnn implements InfoMapper {