[lilac] updated to 1.8.0-5

2 files changed, 17 insertions, 9 deletions

diff --git a/.SRCINFO b/.SRCINFO
index 1f1bc1506641..d90403f8e0e0 100644
--- a/.SRCINFO
+++ b/.SRCINFO
@@ -1,7 +1,7 @@
 pkgbase = python-onnxruntime
 	pkgdesc = Cross-platform, high performance scoring engine for ML models
 	pkgver = 1.8.0
-	pkgrel = 1
+	pkgrel = 5
 	url = https://github.com/microsoft/onnxruntime
 	arch = x86_64
 	license = MIT
diff --git a/PKGBUILD b/PKGBUILD
index 78f18b09f809..f5a70effb19f 100644
--- a/PKGBUILD
+++ b/PKGBUILD
@@ -4,7 +4,7 @@ pkgbase=python-onnxruntime
 pkgname=(python-onnxruntime python-onnxruntime-cuda)
 pkgver=1.8.0
 pkgdesc='Cross-platform, high performance scoring engine for ML models'
-pkgrel=1
+pkgrel=5
 arch=(x86_64)
 url='https://github.com/microsoft/onnxruntime'
 license=(MIT)
@@ -36,6 +36,9 @@ sha512sums=('SKIP'
             '685f0235abed6e1277dd0eb9bda56c464d1987fe7fc90a3550e17ec70cc49fd15f34996a0e159f9622c4ca3e6bf29917fe51b7849342531fa2a6808d782f1e06'
             '55ba879c015df11582ff4afaa9ccca19c0e3d3a8be503629718402dbdc826e36bc3ec3ce4dd589705371d7fcf250ba2a9b30c5a3dd0cfccb8e008346f1bd6252')
 
+# Check PKGBUILDs of python-pytorch and tensorflow for CUDA architectures built by official packages
+_CUDA_ARCHITECTURES="52-real;53-real;60-real;61-real;62-real;70-real;72-real;75-real;80-real;86-real;86-virtual"
+
 prepare() {
   cd onnxruntime
 
@@ -76,14 +79,17 @@ _build() {
 build() {
   _build build
 
-  # Use clang as GCC does not work. GCC 11 uses C++ 17 by default. On the
-  # other hand, onnxruntime uses C++ 14. However, nvcc does not correctly
-  # pass -std=c++14 to the host compiler, and thus preprocessed files
-  # contains C++ 17 language features, and cicc failed to parse it. GCC 10
-  # does not work, either, as some dependent packages (ex: re2) are built
-  # with libstdc++ 11, and linking onnxruntime with libstdc++ 10 fails.
+  # 1. Use clang as GCC does not work. GCC 11 crashes with internal
+  #    compiler errors. GCC 10 does not work as some dependent packages
+  #    (ex: re2) are built with libstdc++ from GCC 11, and thus linking
+  #    onnxruntime with libstdc++ 10 fails.
+  # 2. Redefine ___is_signed to ___is_signed to workaround a regression
+  #    from CUDA 11.3 -> 11.3.1 [1].
+  # [1] https://forums.developer.nvidia.com/t/182176
   _build build-cuda \
     -DCMAKE_CUDA_HOST_COMPILER=/usr/bin/clang \
+    -DCMAKE_CUDA_FLAGS="-D__is_signed=___is_signed" \
+    -DCMAKE_CUDA_ARCHITECTURES="$_CUDA_ARCHITECTURES" \
     -Donnxruntime_USE_CUDA=ON \
     -Donnxruntime_CUDA_HOME=/opt/cuda \
     -Donnxruntime_CUDNN_HOME=/usr \
@@ -91,7 +97,9 @@ build() {
 }
 
 _check() {
-  make test
+  # Test models are no longer publicly available [1]
+  # [1] https://github.com/microsoft/onnxruntime/issues/7447
+  GTEST_FILTER='-*ModelTest*' ARGS="--rerun-failed --output-on-failure" make test
   # launch_test.py seems a script, and orttraining_* include BERT tests, which require the
   # transformers package, and failed even if the latter is installed.
   LD_LIBRARY_PATH="$PWD" pytest \