Merge branch 'jz/native-runner-tt' into jz/tt-llama-kv-cache

Author: jackzhxng

.ci/docker/build.sh

@@ -37,6 +37,10 @@ case "${IMAGE_NAME}" in
     ARM_SDK=yes
     CLANG_VERSION=12
     ;;
+  executorch-ubuntu-22.04-qnn-sdk)
+    QNN_SDK=yes
+    CLANG_VERSION=12
+    ;;
   executorch-ubuntu-22.04-clang12-android)
     LINTRUNNER=""
     CLANG_VERSION=12
@@ -72,6 +76,7 @@ docker build \
   --build-arg "LINTRUNNER=${LINTRUNNER:-}" \
   --build-arg "BUILD_DOCS=${BUILD_DOCS}" \
   --build-arg "ARM_SDK=${ARM_SDK:-}" \
+  --build-arg "QNN_SDK=${QNN_SDK:-}" \
   --build-arg "ANDROID_NDK_VERSION=${ANDROID_NDK_VERSION:-}" \
   -f "${OS}"/Dockerfile \
   "$@" \

.ci/docker/ci_commit_pins/pytorch.txt

@@ -1 +1 @@
-export-D64151426
+c8a648d4dffb9f0133ff4a2ea0e660b42105d3ad

.ci/docker/ci_commit_pins/torchao.txt

@@ -13,7 +13,7 @@ install_ubuntu() {
   apt-get install -y --no-install-recommends clang-"$CLANG_VERSION"
   apt-get install -y --no-install-recommends llvm-"$CLANG_VERSION"
   # Also require LLD linker from llvm and libomp to build PyTorch from source
-  apt-get install -y lld "libomp-${CLANG_VERSION}-dev"
+  apt-get install -y lld "libomp-${CLANG_VERSION}-dev" "libc++-${CLANG_VERSION}-dev"
 
   # Use update-alternatives to make this version the default
   update-alternatives --install /usr/bin/clang clang /usr/bin/clang-"$CLANG_VERSION" 50

.ci/docker/common/install_clang.sh

@@ -1,5 +1,5 @@
 mpmath==1.3.0
-numpy==1.22.0; python_version == '3.10'
+numpy==1.21.3; python_version == '3.10'
 numpy==1.23.2; python_version == '3.11'
 numpy; python_version >= '3.12'
 PyYAML==6.0.1

.ci/docker/requirements-ci.txt

@@ -82,5 +82,7 @@ COPY --chown=ci-user:ci-user ./arm /opt/arm
 # Set up ARM SDK if needed
 RUN if [ -n "${ARM_SDK}" ]; then git config --global user.email "[email protected]"; git config --global user.name "OSS CI"; bash /opt/arm/setup.sh --i-agree-to-the-contained-eula /opt/arm-sdk; chown -R ci-user:ci-user /opt/arm-sdk; fi
 
+ARG QNN_SDK
+
 USER ci-user
 CMD ["bash"]

.ci/docker/ubuntu/Dockerfile

@@ -88,8 +88,8 @@ def model_should_run_on_event(model: str, event: str) -> bool:
     if event == "pull_request":
         return model in ["mv3", "vit"]
     elif event == "push":
-        # 'emformer_predict' is running super slow. Only run it periodically
-        return model not in ["emformer_predict"]
+        # These are super slow. Only run it periodically
+        return model not in ["dl3", "edsr", "emformer_predict"]
     else:
         return True
 

.ci/scripts/gather_test_models.py

@@ -19,6 +19,8 @@ else
 fi
 
 # As Linux job is running inside a Docker container, all of its dependencies
-# have already been installed
-install_executorch
+# have already been installed, so we use PyTorch build from source here instead
+# of nightly. This allows CI to test against latest commits from PyTorch
+install_executorch "use-pt-pinned-commit"
 build_executorch_runner "${BUILD_TOOL}"
+do_not_use_nightly_on_ci

.ci/scripts/setup-linux.sh

@@ -31,8 +31,9 @@ install_qnn() {
 }
 
 setup_libc++() {
+  clang_version=$1
   sudo apt-get update
-  pkgs_to_check=('libc++-dev')
+  pkgs_to_check=("libc++-${clang_version}-dev")
   j=0
   while [ $j -lt ${#pkgs_to_check[*]} ]; do
     install_status=$(verify_pkg_installed ${pkgs_to_check[$j]})
@@ -47,5 +48,6 @@ setup_libc++() {
   done
 }
 
-setup_libc++
+# This needs to match with the clang version from the Docker image
+setup_libc++ 12
 install_qnn

.ci/scripts/setup-qnn-deps.sh

@@ -35,7 +35,6 @@ run_and_verify() {
         exit 1
     fi
     $PYTHON_EXECUTABLE -m examples.models.llama.eval_llama \
-	--model llama2 \
 	-c stories110M.pt \
 	-p params.json \
 	-t tokenizer.model \