s4tf-build-script-macos-linux-2022.sh

tensorflow_version="2.9.1"
DESTDIR=${PWD}/Library/tensorflow-${tensorflow_version}

if [[ $(uname -s) == "Darwin" ]]; then
  lib_end="dylib" # macOS
else
  lib_end="so" # Linux
fi

# ===----------------------------------------------------------------------=== #
# Parse command-line arguments
# ===----------------------------------------------------------------------=== #

args=$@
args_str=" ${args[*]} "

if [[ $args_str =~ " --skip-ctensorflow " ]]; then
  compile_ctensorflow=0
else
  compile_ctensorflow=1
fi

if [[ $args_str =~ " --skip-tests " ]]; then
  run_tests=0
else
  run_tests=1
fi

if [[ $args_str =~ " --use-release-toolchain " ]]; then
  use_release_toolchain=1
else
  use_release_toolchain=0
fi

# ===----------------------------------------------------------------------=== #
# Build X10
# ===----------------------------------------------------------------------=== #

# Command-line flag: --skip-ctensorflow
#
# This makes incremental builds quicker because you don't have to scan Bazel
# build products that are fully built. Also, use this flag if you want to use
# an X10 binary downloaded from the internet instead of a locally built one.
# Just unzip the file into this directory beforehand.
if [[ $compile_ctensorflow == 1 ]]; then
  # Clone s4tf/s4tf.
  # NOTE: If there were commits to S4TF since you last ran this script, you must
  # update the local branch manually.
  git clone --depth 1 --no-single-branch https://github.com/s4tf/s4tf
  
  # Clone tensorflow/tensorflow.
  # NOTE: If the TF version changed since you last ran this script, you must
  # must delete the `tensorflow` directory.
  tensorflow_branch="v${tensorflow_version}"
  git clone --depth 1 --branch $tensorflow_branch https://github.com/tensorflow/tensorflow
  
  # Install Bazelisk on your system. It will automatically detect what Bazel
  # version you need.
  if [[ $(uname -s) == "Darwin" ]]; then
    brew install bazelisk
  else
    # If on Linux, install Bazelisk before running this script. See
    # https://github.com/bazelbuild/bazelisk for installation instructions.
    :
  fi
  
  # Ensure that Python dependencies are available.
  python3 -m pip install --user numpy six
  
  ln -sf $(pwd)/s4tf/Sources/CX10 $(pwd)/tensorflow/swift_bindings
  ln -sf $(pwd)/s4tf/Sources/x10/xla_client $(pwd)/tensorflow/tensorflow/compiler/xla/xla_client
  ln -sf $(pwd)/s4tf/Sources/x10/xla_tensor $(pwd)/tensorflow/tensorflow/compiler/tf2xla/xla_tensor
  rm $(pwd)/s4tf/Sources/CX10/CX10
  rm $(pwd)/s4tf/Sources/x10/xla_client/xla_client
  rm $(pwd)/s4tf/Sources/x10/xla_tensor/xla_tensor
  
  export USE_DEFAULT_PYTHON_LIB_PATH=1
  export TF_NEED_OPENCL_SYCL=0
  export TF_DOWNLOAD_CLANG=0
  export TF_SET_ANDROID_WORKSPACE=0
  export TF_CONFIGURE_IOS=0
  export TF_ENABLE_XLA=1
  export TF_NEED_ROCM=0
  export TF_NEED_CUDA=0
  export TF_CUDA_COMPUTE_CAPABILITIES=7.5
  export CC_OPT_FLAGS="-march=native"
  
  export PYTHON_BIN_PATH=$(which python3)
  python3 ./tensorflow/configure.py
  
  # Manually delete a cached build product. For an unknown reason, this file can
  # get corrupted, causing the OS to kill any process that opens it. Perhaps
  # it's because Bazel doesn't properly delete and re-create it during the build
  # process.
  rm -f tensorflow/bazel-bin/tensorflow/compiler/tf2xla/xla_tensor/libx10.${lib_end}
  
  # Must also delete whatever location the file is copied to, otherwise that
  # will also be corrupted.
  rm -rf $DESTDIR
  
  cd tensorflow
  bazel --output_user_root caches/bazel/tensorflow build -c opt --define \
    framework_shared_object=false --config short_logs --nocheck_visibility \
    //tensorflow:tensorflow //tensorflow/compiler/tf2xla/xla_tensor:x10
    
  # Terminate bazel daemon.
  bazel --output_user_root caches/bazel/tensorflow shutdown
  cd ../
fi

# ===----------------------------------------------------------------------=== #
# Construct "Library"
# ===----------------------------------------------------------------------=== #

# This operation should also not run if you're skipping CTensorFlow. Putting
# these commands under `--skip-ctensorflow` lets the script treat X10 binaries
# built locally the same as binaries downloaded from the internet.
if [[ $compile_ctensorflow == 1 ]]; then
  mkdir -p ${DESTDIR}/usr/lib
  
  # Permit overwriting the binary on subsequent script runs. Otherwise, there is
  # a "permission denied" error on the copy command directly below this line.
  chmod 755 ${DESTDIR}/usr/lib/libx10.${lib_end}
  cp tensorflow/bazel-bin/tensorflow/compiler/tf2xla/xla_tensor/libx10.${lib_end} ${DESTDIR}/usr/lib/
  
  mkdir -p ${DESTDIR}/usr/include/tensorflow/c
  cp tensorflow/tensorflow/c/c_api.h ${DESTDIR}/usr/include/tensorflow/c/
  cp tensorflow/tensorflow/c/c_api_experimental.h ${DESTDIR}/usr/include/tensorflow/c/
  cp tensorflow/tensorflow/c/c_api_macros.h ${DESTDIR}/usr/include/tensorflow/c/
  cp tensorflow/tensorflow/c/tf_attrtype.h ${DESTDIR}/usr/include/tensorflow/c/
  cp tensorflow/tensorflow/c/tf_datatype.h ${DESTDIR}/usr/include/tensorflow/c/
  cp tensorflow/tensorflow/c/tf_file_statistics.h ${DESTDIR}/usr/include/tensorflow/c/
  cp tensorflow/tensorflow/c/tf_status.h ${DESTDIR}/usr/include/tensorflow/c/
  cp tensorflow/tensorflow/c/tf_tensor.h ${DESTDIR}/usr/include/tensorflow/c/
  cp tensorflow/tensorflow/c/tf_tstring.h ${DESTDIR}/usr/include/tensorflow/c/
  
  mkdir -p ${DESTDIR}/usr/include/tensorflow/core/platform
  cp tensorflow/tensorflow/core/platform/ctstring.h ${DESTDIR}/usr/include/tensorflow/core/platform/
  cp tensorflow/tensorflow/core/platform/ctstring_internal.h ${DESTDIR}/usr/include/tensorflow/core/platform/
  
  mkdir -p ${DESTDIR}/usr/include/tensorflow/c/eager
  cp tensorflow/tensorflow/c/eager/c_api.h ${DESTDIR}/usr/include/tensorflow/c/eager/
fi

# ===----------------------------------------------------------------------=== #
# Build S4TF
# ===----------------------------------------------------------------------=== #

# S4TF should already be present if you ran without --skip-ctensorflow.
if [[ ! -d s4tf ]]; then
  git clone --depth 1 --no-single-branch https://github.com/s4tf/s4tf
fi

# Command-line flag: --use-release-toolchain
#
# Setting `TENSORFLOW_USE_RELEASE_TOOLCHAIN` tells the package manifest that
# this is a release toolchain, making it download philipturner/differentiation
# and philipturner/swift-reflection-mirror.
if [[ $use_release_toolchain == 1 ]]; then
  export TENSORFLOW_USE_RELEASE_TOOLCHAIN=1
else
  # Use the August 9, 2022 development snapshot. It must already be downloaded 
  # and installed on your system. Newer toolchains should work, but change 
  # `TOOLCHAINS` and `DYLD_LIBRARY_PATH` to reflect them.
  export TOOLCHAINS="org.swift.57202208091a"
fi

cd s4tf
swift build -Xcc -I${DESTDIR}/usr/include -Xlinker -L${DESTDIR}/usr/lib
build_return_code=$?

rm -f .build/debug/libx10.dylib
cp ${DESTDIR}/usr/lib/libx10.dylib .build/debug/libx10.dylib

# ===----------------------------------------------------------------------=== #
# Test S4TF
# ===----------------------------------------------------------------------=== #

# Command-line flag: --skip-tests
#
# Select whether to avoid running the test suite. It floods the terminal, making
# it difficult to view results of `swift build`. Also, tests from a previous
# test compilation may run regardless of whether the current compilation
# succeeded. This happens on macOS with dev toolchains because of the workaround
# below. The return code of `swift test` cannot be used because SR-14008 makes
# it zero, so instead it uses the return code of `swift build`.
if [[ $build_return_code == 0 && $run_tests == 1 ]]; then
  # This command fails on macOS on dev toolchains, but it builds the `.xctest`
  # file. The workaround below runs the `.xctest` file.
  swift test -Xcc -I${DESTDIR}/usr/include -Xlinker -L${DESTDIR}/usr/lib
  
  # (SR-14008) Workaround for `_Differentiation` loading error on development 
  # toolchains.
  if [[ $build_return_code == 0 && $(uname -s) == "Darwin" &&
    $use_release_toolchain == 0 ]];
  then
    toolchain="/Library/Developer/Toolchains/swift-DEVELOPMENT-SNAPSHOT-2022-08-09-a.xctoolchain"
    swift_libraries="/usr/lib/swift/macosx"
    export DYLD_LIBRARY_PATH="${toolchain}${swift_libraries}"
    
    /Applications/Xcode.app/Contents/Developer/usr/bin/xctest \
      .build/$(uname -m)-apple-macosx/debug/TensorFlowPackageTests.xctest
  fi
fi

How to compile S4TF now that it's active again

This script should work on macOS and Linux, but has not been tested on Linux/Docker yet. Read through the script's comments before executing it.

Usage:

build_script.sh [--skip-ctensorflow] [--skip-tests] [--use-release-toolchain]