Added AoT for Qwen, Phi, Gemma & Whisper

.ci/docker/ci_commit_pins/optimum-executorch.txt

@@ -1 +1 @@
-36e3dd54effb3f6d13d792029609292fdd5502bb
+40b02a2dc61bbf901a2df91719f47c98d65368ec

.ci/docker/ci_commit_pins/pytorch.txt

@@ -1 +1 @@
-6fc0ad22f0a07b6f38d138861c56a765d5a9bb02
+4d4abec80f03cd8fdefe1d9cb3a60d3690cd777e

.ci/scripts/build-qnn-sdk.sh

@@ -11,8 +11,10 @@ set -o xtrace
 
 build_qnn_backend() {
   echo "Start building qnn backend."
-  export ANDROID_NDK_ROOT=${ANDROID_NDK_ROOT:-/opt/ndk}
-  export QNN_SDK_ROOT=${QNN_SDK_ROOT:-/tmp/qnn/2.28.0.241029}
+  # Source QNN configuration
+  source "$(dirname "${BASH_SOURCE[0]}")/../../backends/qualcomm/scripts/install_qnn_sdk.sh"
+  setup_android_ndk
+  install_qnn
   export EXECUTORCH_ROOT="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")/../.." && pwd)"
 
   parallelism=$(( $(nproc) - 1 ))

.ci/scripts/setup-conda.sh

@@ -9,7 +9,7 @@ set -ex
 
 install_conda() {
   pushd .ci/docker || return
-  ${CONDA_INSTALL} -y --file conda-env-ci.txt
+  ${CONDA_INSTALL} -c conda-forge -y --file conda-env-ci.txt
   popd || return
 }
 

.ci/scripts/setup-linux.sh

@@ -11,6 +11,7 @@ set -exu
 source "$(dirname "${BASH_SOURCE[0]}")/utils.sh"
 
 read -r BUILD_TOOL BUILD_MODE EDITABLE < <(parse_args "$@")
+echo "Build tool: $BUILD_TOOL, Mode: $BUILD_MODE"
 
 # As Linux job is running inside a Docker container, all of its dependencies
 # have already been installed, so we use PyTorch build from source here instead

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

@@ -10,4 +10,5 @@ set -ex
 source "$(dirname "${BASH_SOURCE[0]}")/../../backends/qualcomm/scripts/install_qnn_sdk.sh"
 
 setup_libcpp 12
-install_qnn
+setup_android_ndk
+install_qnn

.ci/scripts/setup-samsung-linux-deps.sh

@@ -0,0 +1,68 @@
+#!/bin/bash
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# Copyright (c) Samsung Electronics Co. LTD
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+set -ex
+
+
+download_ai_lite_core() {
+  API_BASE="https://soc-developer.semiconductor.samsung.com/api/v1/resource/ai-litecore/download"
+  API_KEY="kn10SoSY3hkC-9Qny5TqD2mnqVrlupv3krnjLeBt5cY"
+
+  VERSION="0.5"
+  OS_NAME="Ubuntu 22.04"
+  OUT_FILE="/tmp/exynos-ai-litecore-v${VERSION}.tar.gz"
+  TARGET_PATH="/tmp/exynos_ai_lite_core"
+
+  mkdir -p ${TARGET_PATH}
+  # Presigned issue URL
+  JSON_RESP=$(curl -sS -G \
+    --location --fail --retry 3 \
+    -H "apikey: ${API_KEY}" \
+    --data-urlencode "version=${VERSION}" \
+    --data-urlencode "os=${OS_NAME}" \
+    "${API_BASE}")
+
+  DOWNLOAD_URL=$(echo "$JSON_RESP" | sed -n 's/.*"data":[[:space:]]*"\([^"]*\)".*/\1/p')
+
+  if [[ -z "$DOWNLOAD_URL" ]]; then
+    echo "Failed to extract download URL"
+    echo "$JSON_RESP"
+    exit 1
+  fi
+
+  # Download LiteCore
+  curl -sS -L --fail --retry 3 \
+    --output "$OUT_FILE" \
+    "$DOWNLOAD_URL"
+
+  echo "Download done: $OUT_FILE"
+
+
+  tar -C "${TARGET_PATH}" --strip-components=1 -xzvf "${OUT_FILE}"
+
+  export EXYNOS_AI_LITECORE_ROOT=${TARGET_PATH}
+  export LD_LIBRARY_PATH=${LD_LIBRARY_PATH:-}:${EXYNOS_AI_LITECORE_ROOT}/lib/x86_64-linux
+}
+
+install_enn_backend() {
+  NDK_INSTALLATION_DIR=/opt/ndk
+  rm -rf "${NDK_INSTALLATION_DIR}" && sudo mkdir -p "${NDK_INSTALLATION_DIR}"
+  ANDROID_NDK_VERSION=r27b
+
+  # build Exynos backend
+  export ANDROID_NDK_ROOT=${ANDROID_NDK_ROOT:-/opt/ndk}
+  bash backends/samsung/build.sh --build all
+  # set env variable
+  export EXECUTORCH_ROOT="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")/../.." && pwd)"
+  export PYTHONPATH=${PYTHONPATH:-}:${EXECUTORCH_ROOT}/..
+}
+
+AI_LITE_CORE_VERSION=0.5.0
+
+download_ai_lite_core ${AI_LITE_CORE_VERSION}
+install_enn_backend

.ci/scripts/setup-vulkan-linux-deps.sh

@@ -23,6 +23,7 @@ install_swiftshader() {
 
   export VK_ICD_FILENAMES="${_swiftshader_dir}/swiftshader/build/Linux/vk_swiftshader_icd.json"
   export LD_LIBRARY_PATH="${_swiftshader_dir}/swiftshader/build/Linux/"
+  export ETVK_USING_SWIFTSHADER=1
 }
 
 install_vulkan_sdk() {
@@ -42,7 +43,7 @@ install_vulkan_sdk() {
   export PATH="${PATH}:${_vulkan_sdk_dir}/${VULKAN_SDK_VERSION}/x86_64/bin/"
 }
 
-VULKAN_SDK_VERSION="1.3.296.0"
+VULKAN_SDK_VERSION="1.4.321.1"
 
 install_swiftshader
 install_vulkan_sdk "${VULKAN_SDK_VERSION}"

.ci/scripts/setup-windows.ps1

@@ -0,0 +1,24 @@
+param (
+    [string]$editable = "false"
+)
+
+conda create --yes --quiet -n et python=3.12
+conda activate et
+
+# Activate the VS environment - this is required for Dynamo to work, as it uses MSVC.
+# There are a bunch of environment variables that it requires.
+# See https://learn.microsoft.com/en-us/cpp/build/building-on-the-command-line.
+& "C:\Program Files (x86)\Microsoft Visual Studio\2022\BuildTools\Common7\Tools\Launch-VsDevShell.ps1" -Arch amd64
+
+# Install test dependencies
+pip install -r .ci/docker/requirements-ci.txt
+
+if ($editable -eq 'true') {
+    install_executorch.bat --editable
+} else {
+    install_executorch.bat
+}
+if ($LASTEXITCODE -ne 0) {
+    Write-Host "Installation was unsuccessful. Exit code: $LASTEXITCODE."
+    exit $LASTEXITCODE
+}

.ci/scripts/test_backend_linux.sh

@@ -0,0 +1,55 @@
+#!/usr/bin/env bash
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+set -eux
+
+SUITE=$1
+FLOW=$2
+ARTIFACT_DIR=$3
+
+REPORT_FILE="$ARTIFACT_DIR/test-report-$FLOW-$SUITE.csv"
+
+echo "Running backend test job for suite $SUITE, flow $FLOW."
+echo "Saving job artifacts to $ARTIFACT_DIR."
+
+# The generic Linux job chooses to use base env, not the one setup by the image
+eval "$(conda shell.bash hook)"
+CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]")
+conda activate "${CONDA_ENV}"
+
+export PYTHON_EXECUTABLE=python
+
+# CMake options to use, in addition to the defaults.
+EXTRA_BUILD_ARGS=""
+
+if [[ "$FLOW" == *qnn* ]]; then
+    # Setup QNN sdk and deps - note that this is a bit hacky due to the nature of the
+    # Qualcomm build. TODO (gjcomer) Clean this up once the QNN pybinding integration is
+    # cleaned up.
+    PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh --build-tool cmake
+    PYTHON_EXECUTABLE=python source .ci/scripts/build-qnn-sdk.sh
+    QNN_X86_LIB_DIR=`realpath build-x86/lib/`
+    export LD_LIBRARY_PATH"=$QNN_X86_LIB_DIR:$QNN_SDK_ROOT/lib/x86_64-linux-clang/:${LD_LIBRARY_PATH:-}"
+
+    # TODO Get SDK root from install scripts
+    EXTRA_BUILD_ARGS+=" -DEXECUTORCH_BUILD_QNN=ON -DQNN_SDK_ROOT=$QNN_SDK_ROOT"
+fi
+
+if [[ "$FLOW" == *vulkan* ]]; then
+    # Setup swiftshader and Vulkan SDK which are required to build the Vulkan delegate
+    source .ci/scripts/setup-vulkan-linux-deps.sh
+
+    EXTRA_BUILD_ARGS+=" -DEXECUTORCH_BUILD_VULKAN=ON"
+fi
+
+# We need the runner to test the built library.
+PYTHON_EXECUTABLE=python CMAKE_ARGS="$EXTRA_BUILD_ARGS" .ci/scripts/setup-linux.sh --build-tool cmake --build-mode Release --editable true
+
+EXIT_CODE=0
+python -m executorch.backends.test.suite.runner $SUITE --flow $FLOW --report "$REPORT_FILE" || EXIT_CODE=$?
+
+# Generate markdown summary.
+python -m executorch.backends.test.suite.generate_markdown_summary "$REPORT_FILE" > ${GITHUB_STEP_SUMMARY:-"step_summary.md"} --exit-code $EXIT_CODE

.ci/scripts/test_backend_macos.sh

@@ -0,0 +1,30 @@
+#!/usr/bin/env bash
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+set -eux
+
+SUITE=$1
+FLOW=$2
+ARTIFACT_DIR=$3
+
+REPORT_FILE="$ARTIFACT_DIR/test-report-$FLOW-$SUITE.csv"
+
+echo "Running backend test job for suite $SUITE, flow $FLOW."
+echo "Saving job artifacts to $ARTIFACT_DIR."
+
+${CONDA_RUN} --no-capture-output pip install awscli==1.37.21
+
+bash .ci/scripts/setup-conda.sh
+eval "$(conda shell.bash hook)"
+
+PYTHON_EXECUTABLE=python
+${CONDA_RUN} --no-capture-output .ci/scripts/setup-macos.sh --build-tool cmake --build-mode Release
+
+EXIT_CODE=0
+${CONDA_RUN} --no-capture-output python -m executorch.backends.test.suite.runner $SUITE --flow $FLOW --report "$REPORT_FILE" || EXIT_CODE=$?
+
+# Generate markdown summary.
+${CONDA_RUN} --no-capture-output python -m executorch.backends.test.suite.generate_markdown_summary "$REPORT_FILE" > ${GITHUB_STEP_SUMMARY:-"step_summary.md"} --exit-code $EXIT_CODE