Update on "Use at::Vectorized in optimized log_softmax"

This should allow us to enable this op in OSS, because Vectorized handles any Sleef issues for us as needed. (I considered going straight to sharing the PyTorch core implementation, but we need parallel_for enabled for that and this improvement is easy enough to make.)

Differential Revision: [D69473208](https://our.internmc.facebook.com/intern/diff/D69473208/)

[ghstack-poisoned]

Author: Github Executorch

.ci/scripts/build_llama_android.sh

@@ -10,6 +10,12 @@ set -exu
 # shellcheck source=/dev/null
 source "$(dirname "${BASH_SOURCE[0]}")/utils.sh"
 
+if [[ -z "${PYTHON_EXECUTABLE:-}" ]]; then
+  PYTHON_EXECUTABLE=python3
+fi
+which "${PYTHON_EXECUTABLE}"
+CMAKE_PREFIX_PATH="$(python3 -c 'import torch as _; print(_.__path__[0])')"
+
 install_executorch_and_backend_lib() {
   echo "Installing executorch and xnnpack backend"
   clean_executorch_install_folders
@@ -22,6 +28,7 @@ install_executorch_and_backend_lib() {
     -DANDROID_ABI="${ANDROID_ABI}" \
     -DCMAKE_INSTALL_PREFIX=cmake-android-out \
     -DCMAKE_BUILD_TYPE=Release \
+    -DCMAKE_PREFIX_PATH="${CMAKE_PREFIX_PATH}" \
     -DEXECUTORCH_BUILD_EXTENSION_DATA_LOADER=ON \
     -DEXECUTORCH_BUILD_EXTENSION_MODULE=ON \
     -DEXECUTORCH_BUILD_EXTENSION_TENSOR=ON \
@@ -47,6 +54,7 @@ build_llama_runner() {
     -DEXECUTORCH_BUILD_KERNELS_OPTIMIZED=ON \
     -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON \
     -DEXECUTORCH_BUILD_KERNELS_CUSTOM=ON \
+    -DCMAKE_PREFIX_PATH="${CMAKE_PREFIX_PATH}" \
     -Bcmake-android-out/examples/models/llama examples/models/llama
 
     cmake --build cmake-android-out/examples/models/llama -j4 --config Release

.ci/scripts/test_llama.sh

@@ -154,6 +154,7 @@ cmake_install_executorch_libraries() {
     rm -rf cmake-out
     retry cmake \
         -DCMAKE_INSTALL_PREFIX=cmake-out \
+        -DCMAKE_PREFIX_PATH="$(python3 -c 'import torch as _; print(_.__path__[0])')" \
         -DCMAKE_BUILD_TYPE="$CMAKE_BUILD_TYPE" \
         -DEXECUTORCH_BUILD_EXTENSION_DATA_LOADER=ON \
         -DEXECUTORCH_BUILD_EXTENSION_MODULE=ON \

.ci/scripts/test_llava.sh

@@ -30,9 +30,11 @@ fi
 NPROC=8
 if hash nproc &> /dev/null; then NPROC=$(nproc); fi
 
+python_lib=$($PYTHON_EXECUTABLE -c 'from distutils.sysconfig import get_python_lib; print(get_python_lib())')
+CMAKE_PREFIX_PATH="$(python3 -c 'import torch as _; print(_.__path__[0])')"
 EXECUTORCH_COMMON_CMAKE_ARGS="                      \
         -DCMAKE_INSTALL_PREFIX=${BUILD_DIR}         \
-        -DCMAKE_BUILD_TYPE=${CMAKE_BUILD_TYPE}            \
+        -DCMAKE_BUILD_TYPE=${CMAKE_BUILD_TYPE}      \
         -DEXECUTORCH_ENABLE_LOGGING=ON              \
         -DEXECUTORCH_BUILD_EXTENSION_MODULE=ON      \
         -DEXECUTORCH_BUILD_EXTENSION_DATA_LOADER=ON \
@@ -46,6 +48,7 @@ EXECUTORCH_COMMON_CMAKE_ARGS="                      \
 cmake_install_executorch_libraries() {
     cmake                               \
         ${EXECUTORCH_COMMON_CMAKE_ARGS} \
+        "-DCMAKE_PREFIX_PATH=${CMAKE_PREFIX_PATH}" \
         -B${BUILD_DIR} .
 
     cmake --build ${BUILD_DIR} -j${NPROC} --target install --config ${CMAKE_BUILD_TYPE}
@@ -56,6 +59,7 @@ cmake_install_executorch_libraries_for_android() {
         -DCMAKE_TOOLCHAIN_FILE=$ANDROID_NDK/build/cmake/android.toolchain.cmake \
         -DANDROID_ABI=arm64-v8a                                                 \
         ${EXECUTORCH_COMMON_CMAKE_ARGS}                                         \
+        "-DCMAKE_PREFIX_PATH=${CMAKE_PREFIX_PATH}" \
         -B${BUILD_DIR} .
 
     cmake --build ${BUILD_DIR} -j${NPROC} --target install --config ${CMAKE_BUILD_TYPE}
@@ -76,7 +80,7 @@ cmake_build_llava_runner() {
 
     cmake                                 \
         ${LLAVA_COMMON_CMAKE_ARGS}        \
-        -DCMAKE_PREFIX_PATH="$python_lib" \
+        -DCMAKE_PREFIX_PATH="$python_lib;${CMAKE_PREFIX_PATH}" \
         -B${BUILD_DIR}/${dir}             \
         ${dir}
 
@@ -92,7 +96,7 @@ cmake_build_llava_runner_for_android() {
         -DCMAKE_TOOLCHAIN_FILE=$ANDROID_NDK/build/cmake/android.toolchain.cmake \
         -DANDROID_ABI=arm64-v8a                                                 \
         ${LLAVA_COMMON_CMAKE_ARGS}                                              \
-        -DCMAKE_PREFIX_PATH="$python_lib"                                       \
+        -DCMAKE_PREFIX_PATH="$python_lib;${CMAKE_PREFIX_PATH}"                  \
         -DLLAVA_RUNNER_NO_TORCH_DUMMY_IMAGE=ON                                  \
         -B${BUILD_DIR}/${dir}                                                   \
         ${dir}

.ci/scripts/test_model.sh

@@ -50,10 +50,12 @@ prepare_artifacts_upload() {
 
 build_cmake_executor_runner() {
   echo "Building executor_runner"
+  CMAKE_PREFIX_PATH="$(python3 -c 'import torch as _; print(_.__path__[0])')"
   rm -rf ${CMAKE_OUTPUT_DIR}
   cmake -DCMAKE_BUILD_TYPE=Debug \
       -DEXECUTORCH_BUILD_KERNELS_OPTIMIZED=ON \
       -DPYTHON_EXECUTABLE="$PYTHON_EXECUTABLE" \
+      -DCMAKE_PREFIX_PATH="$CMAKE_PREFIX_PATH" \
       -B${CMAKE_OUTPUT_DIR} .
 
   cmake --build ${CMAKE_OUTPUT_DIR} -j4 --config Debug
@@ -98,8 +100,7 @@ test_model() {
 
 build_cmake_xnn_executor_runner() {
   echo "Building xnn_executor_runner"
-  SITE_PACKAGES="$(${PYTHON_EXECUTABLE} -c 'from distutils.sysconfig import get_python_lib; print(get_python_lib())')"
-  CMAKE_PREFIX_PATH="${SITE_PACKAGES}/torch"
+  CMAKE_PREFIX_PATH="$(python3 -c 'import torch as _; print(_.__path__[0])')"
 
   (rm -rf ${CMAKE_OUTPUT_DIR} \
     && mkdir ${CMAKE_OUTPUT_DIR} \

.ci/scripts/test_phi_3_mini.sh

@@ -22,8 +22,10 @@ NPROC=8
 if hash nproc &> /dev/null; then NPROC=$(nproc); fi
 
 cmake_install_executorch_libraries() {
+  CMAKE_PREFIX_PATH="$(python3 -c 'import torch as _; print(_.__path__[0])')"
   cmake -DPYTHON_EXECUTABLE=python \
       -DCMAKE_INSTALL_PREFIX=${BUILD_DIR} \
+      -DCMAKE_PREFIX_PATH="${CMAKE_PREFIX_PATH}" \
       -DEXECUTORCH_ENABLE_LOGGING=1 \
       -DCMAKE_BUILD_TYPE=${BUILD_TYPE} \
       -DEXECUTORCH_BUILD_EXTENSION_DATA_LOADER=ON \
@@ -39,8 +41,10 @@ cmake_install_executorch_libraries() {
 }
 
 cmake_build_phi_3_mini() {
+  CMAKE_PREFIX_PATH="$(python3 -c 'import torch as _; print(_.__path__[0])')"
   cmake -DPYTHON_EXECUTABLE=$PYTHON_EXECUTABLE \
       -DCMAKE_INSTALL_PREFIX=${BUILD_DIR} \
+      -DCMAKE_PREFIX_PATH="${CMAKE_PREFIX_PATH}" \
       -DCMAKE_BUILD_TYPE=${BUILD_TYPE} \
       -DEXECUTORCH_BUILD_KERNELS_CUSTOM=ON \
       -DEXECUTORCH_BUILD_KERNELS_OPTIMIZED=ON \

.ci/scripts/test_qnn_static_llama.sh

@@ -0,0 +1,59 @@
+#!/bin/bash
+# Copyright (c) Qualcomm Innovation Center, Inc.
+# 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 -exu
+
+source "$(dirname "${BASH_SOURCE[0]}")/utils.sh"
+
+export EXECUTORCH_ROOT="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")/.." && pwd)"
+export QNN_SDK_ROOT=/tmp/qnn/2.28.0.241029
+export LD_LIBRARY_PATH="${QNN_SDK_ROOT}/lib/x86_64-linux-clang"
+export PYTHONPATH=".."
+cp schema/program.fbs exir/_serialize/program.fbs
+cp schema/scalar_type.fbs exir/_serialize/scalar_type.fbs
+cp -f build-x86/backends/qualcomm/PyQnnManagerAdaptor.cpython-310-x86_64-linux-gnu.so backends/qualcomm/python
+cp -f build-x86/backends/qualcomm/PyQnnWrapperAdaptor.cpython-310-x86_64-linux-gnu.so backends/qualcomm/python
+
+if [[ -z "${PYTHON_EXECUTABLE:-}" ]]; then
+  PYTHON_EXECUTABLE=python3
+fi
+
+which "${PYTHON_EXECUTABLE}"
+
+# Although static llama CI does not require graphviz, it is required by test_qnn_delegate.py
+pip install graphviz
+
+# Download stories llama110m artifacts
+download_stories_model_artifacts
+echo "Creating tokenizer.bin"
+$PYTHON_EXECUTABLE -m extension.llm.tokenizer.tokenizer -t tokenizer.model -o tokenizer.bin
+
+set +e
+# Compile only as weight sharing is not applicable on x86
+$PYTHON_EXECUTABLE backends/qualcomm/tests/test_qnn_delegate.py -k TestExampleScript.test_stories_single_llama --model SM8650 --build_folder build-android/ --executorch_root . --artifact_dir . --compile_only
+exit_code1=$?
+
+# Checks accuracy with weight sharing disabled since x86 does not support weight sharing.
+$PYTHON_EXECUTABLE backends/qualcomm/tests/test_qnn_delegate.py -k TestExampleScript.test_stories_single_llama --model SM8650 --build_folder build-x86/ --executorch_root . --artifact_dir . --enable_x86_64
+exit_code2=$?
+
+# Check the exit codes and print messages
+if [ $exit_code1 -ne 0 ]; then
+    echo "Static Llama compile only with weight sharing test failed. $exit_code1."
+fi
+
+if [ $exit_code2 -ne 0 ]; then
+    echo "Static Llama accuracy test failed. $exit_code2."
+fi
+
+# Return failure if either program failed
+if [ $exit_code1 -ne 0 ] || [ $exit_code2 -ne 0 ]; then
+    exit 1
+else
+    exit 0
+fi
+set -e

.ci/scripts/utils.sh

@@ -136,6 +136,7 @@ cmake_install_executorch_lib() {
   clean_executorch_install_folders
   retry cmake -DBUCK2="$BUCK" \
           -DCMAKE_INSTALL_PREFIX=cmake-out \
+          -DCMAKE_PREFIX_PATH="$($PYTHON_EXECUTABLE -c 'import torch as _; print(_.__path__[0])')" \
           -DCMAKE_BUILD_TYPE=Release \
           -DPYTHON_EXECUTABLE="$PYTHON_EXECUTABLE" \
           -Bcmake-out .

.github/scripts/propose_ghstack_orig_pr.py

@@ -101,7 +101,7 @@ def create_prs_for_orig_branch(pr_stack: List[int], repo: Repository):
         # gh/user/x/orig is the clean diff between gh/user/x/base <- gh/user/x/head
         orig_branch_merge_head = pr.base.ref.replace("base", "orig")
         bot_metadata = f"""This PR was created by the merge bot to help merge the original PR into the main branch.
-ghstack PR number: https://github.com/pytorch/executorch/pull/{pr.number}
+ghstack PR number: https://github.com/pytorch/executorch/pull/{pr.number} by @{pr.user.login}
 ^ Please use this as the source of truth for the PR details, comments, and reviews
 ghstack PR base: https://github.com/pytorch/executorch/tree/{pr.base.ref}
 ghstack PR head: https://github.com/pytorch/executorch/tree/{pr.head.ref}

.github/workflows/android-perf.yml

@@ -222,6 +222,7 @@ jobs:
                       --preq_mode 8da4w_output_8da8w \
                       --preq_group_size 32 \
                       --max_seq_length 2048 \
+                      --max_context_length 2048 \
                       --output_name "${OUT_ET_MODEL_NAME}.pte" \
                       -kv \
                       -d fp32 \
@@ -253,6 +254,7 @@ jobs:
                       --xnnpack-extended-ops \
                       -d fp32 \
                       --max_seq_length 2048 \
+                      --max_context_length 2048 \
                       --output_name "${OUT_ET_MODEL_NAME}.pte" \
                       --metadata '{"get_bos_id":128000, "get_eos_ids":[128009, 128001]}'
                     ls -lh "${OUT_ET_MODEL_NAME}.pte"

.github/workflows/apple-perf.yml

@@ -233,6 +233,7 @@ jobs:
                 --preq_mode 8da4w_output_8da8w \
                 --preq_group_size 32 \
                 --max_seq_length 2048 \
+                --max_context_length 2048 \
                 --output_name "${OUT_ET_MODEL_NAME}.pte" \
                 -kv \
                 -d fp32 \
@@ -264,6 +265,7 @@ jobs:
                 --xnnpack-extended-ops \
                 -d fp32 \
                 --max_seq_length 2048 \
+                --max_context_length 2048 \
                 --output_name "${OUT_ET_MODEL_NAME}.pte" \
                 --metadata '{"get_bos_id":128000, "get_eos_ids":[128009, 128001]}'
               ls -lh "${OUT_ET_MODEL_NAME}.pte"