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add 'preparatory' changes for binary releases
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‎.dev-scripts/README.md‎

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# Development Scripts
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To publish a binary release with docker (for CUDA), run (replace engine version and cuda version):
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```bash
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./.dev-scripts/publish-with-docker.sh v0.2.3 11.8
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```

‎.dev-scripts/extract_install_cmd.py‎

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@@ -7,7 +7,7 @@
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parser.add_argument("custom_pytorch_path", help="Path to custom PyTorch wheel")
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args = parser.parse_args()
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BLOCK_HEADER_START = "### Conda on Linux"
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BLOCK_HEADER_START = "#### Conda on Linux"
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with open("README.md") as infile:
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content = infile.readlines()
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FILE_INTRO = """#!/usr/bin/env bash
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function check_error() {
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# shows and then runs a command. if the exit code is not zero, aborts the script
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# usage: check_error mv foo bar
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trap exit INT
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set -o errexit
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set -o xtrace
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echo + $@
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"$@"
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local exit_code=$?
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if [ "${exit_code}" -ne 0 ]; then
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echo "! > An error occured, aborting."
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exit 1
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fi
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}
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"""
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EXTRA_CONDA_INSTRUCTION = """# extra step for bash script (not required in a proper command line):
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eval "$(conda shell.bash hook)"
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# replace some line contents and add some lines
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if "conda activate" in line:
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line = EXTRA_CONDA_INSTRUCTION + "check_error " + line
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line = EXTRA_CONDA_INSTRUCTION + line
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if "export BITORCH_WORKSPACE" in line:
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line = line.replace("${HOME}", "$(pwd)")
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if line.startswith("pip install torch-"):
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line = "pip install {}\n".format(args.custom_pytorch_path)
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# decide how to write line
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line_format = "check_error {line}"
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line_format = "{line}"
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if line.startswith("#"):
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line_format = "{line}"
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if insert_block_pause:

‎.dev-scripts/publish-docker-internal.sh‎

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#!/usr/bin/env bash
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function usage() {
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echo "./.dev-scripts/publish-docker-internal.sh OPTION"
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echo "builds a package and publishes it to (test-)pypi"
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echo
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echo "OPTION must be either 'pre-release' or 'release'."
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}
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if ! [ "$#" = "1" ] || [ "${1}" = "-h" ]; then
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usage
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exit
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fi
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if ! [ "${1}" = "release" ] && ! [ "${1}" = "pre-release" ]; then
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usage
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exit
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fi
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trap exit INT
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function check_yes() {
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# asks the given yes or no question, returns true if they answer YES
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# usage:
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# if check_yes "Do you really want to delete foo?"; then
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# rm foo
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# fi
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local prompt="${1}"
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read -p "${prompt} [y/N] " REPLY
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echo ""
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if [[ ! "${REPLY}" =~ ^[Yy]$ ]]; then
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return 1
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fi
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return 0
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}
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function check_no() {
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# asks the given yes or no question, returns false if they answer NO
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# usage:
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# if check_no "Do you want to exit the script?"; then
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# exit 0
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# fi
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local prompt="${1}"
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read -p "${prompt} [Y/n] " REPLY
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echo ""
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if [[ "${REPLY}" =~ ^[Nn]$ ]]; then
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return 1
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fi
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return 0
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}
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function check_error() {
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# shows and then runs a command. if the exit code is not zero, asks the user whether to continue
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# usage: check_error mv foo bar
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echo + $@
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"$@"
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local exit_code=$?
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if [ "${exit_code}" -ne 0 ]; then
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if ! check_yes "! > An error occurred, continue with the script?"; then
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if [ "${1}" = "pre-release" ]; then
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git checkout "${version_file}"
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fi
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exit 1
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fi
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fi
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}
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SRC_ROOT="${BITORCH_ENGINE_ROOT:-/bitorch-engine}"
72+
check_error [ -f "${SRC_ROOT}/setup.py" ]
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cd "${SRC_ROOT}"
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# main script content
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if [ -z "$(git status --porcelain)" ]; then
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echo "Git seems clean."
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else
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if check_yes "Git not clean. Do you want to see the diff to proceed?"; then
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git diff
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if ! check_yes "Proceed with these differences?"; then
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echo "There are uncommitted changes, aborting."
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exit 1
85+
fi
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else
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echo "Git not clean, aborting."
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exit 1
89+
fi
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fi
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if [ "${1}" = "release" ]; then
93+
version_file="${SRC_ROOT}/version.txt"
94+
version_content="$(cat "${version_file}")"
95+
major_minor_patch="$(cut -d '.' -f 1,2,3 <<< "${version_content}")"
96+
version_str="${major_minor_patch}"
97+
else
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version_file="${SRC_ROOT}/version.txt"
99+
version_content="$(cat "${version_file}")"
100+
major_minor_patch="$(cut -d '.' -f 1,2,3 <<< "${version_content}")"
101+
date_str="$(date +"%Y%m%d")"
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git_ref="$(git rev-parse --short HEAD)"
103+
version_str="${major_minor_patch}.dev${date_str}+${git_ref}"
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fi
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106+
if [ "${1}" = "release" ] && ! [ "${version_content}" = "${version_str}" ]; then
107+
echo "The file version.txt does not seem to contain a release version."
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exit 1
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fi
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echo "Building version ${version_str}."
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if [ "${1}" = "pre-release" ]; then
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echo "${version_str}" > "${version_file}"
115+
fi
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pip install build
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#check_error pytest .
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check_error python3 -m build --no-isolation --wheel
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echo "To publish to real PyPI use:"
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echo " python3 -m twine dist-${PUBLISH_BIE_VERSION}/*"
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echo "To publish to test PyPI use:"
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echo " python3 -m twine upload --repository testpypi dist-${PUBLISH_BIE_VERSION}/*"
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if [ "${1}" = "pre-release" ]; then
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git checkout "${version_file}"
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fi

‎.dev-scripts/publish-with-docker.sh‎

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#!/usr/bin/env bash
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set -o xtrace
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function usage() {
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echo "./.dev-scripts/publish-with-docker.sh BIE_VERSION [CUDA_VERSION]"
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echo "builds a package and publishes it to (test-)pypi"
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echo
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echo "BIE_VERSION must be a version string like 'v1.2.3'."
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echo "optional: CUDA_VERSION can be either '11.8' (default) or '12.1'."
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}
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trap exit INT
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if ! ((1 <= $# && $# <= 2)) || [ "${1}" = "-h" ]; then
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usage
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exit
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fi
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export PUBLISH_BIE_VERSION="${1}"
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CUDA_VERSION="${2:-11.8}"
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if ! [[ "${PUBLISH_BIE_VERSION}" =~ ^v[0-9].[0-9].[0-9]$ ]]; then
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echo "Invalid BIE_VERSION '${PUBLISH_BIE_VERSION}' given."
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echo
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usage
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exit
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fi
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cuda_known="false"
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add_build_arg=""
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cuda_abbrev="unknown"
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if [ "${CUDA_VERSION}" = "11.8" ]; then
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cuda_known="true"
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cuda_abbrev="cu118"
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torch_requirement="torch==2.2.2"
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fi
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if [ "${CUDA_VERSION}" = "12.1" ]; then
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cuda_known="true"
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cuda_abbrev="cu121"
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add_build_arg="--build-arg FROM_IMAGE=pytorch/pytorch:2.2.0-cuda12.1-cudnn8-devel"
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torch_requirement="torch==2.2.2"
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fi
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if [ "${cuda_known}" = "false" ]; then
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echo "Unknown CUDA_VERSION '${CUDA_VERSION}' given."
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echo
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usage
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exit
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fi
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echo "building bitorch engine ${PUBLISH_BIE_VERSION}"
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echo "building for cuda ${CUDA_VERSION}"
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bie_image_tag="bitorch/engine:publish-${cuda_abbrev}-${PUBLISH_BIE_VERSION}"
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bie_container_name="bie-${cuda_abbrev}-${PUBLISH_BIE_VERSION}"
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output_folder="./dist/${cuda_abbrev}"
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# build/tag docker image
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pushd docker
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docker build --target no-examples ${add_build_arg} --build-arg GIT_BRANCH="${PUBLISH_BIE_VERSION}" -t "${bie_image_tag}" .
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popd
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63+
docker container create -it \
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--rm \
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-it \
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-v "${output_folder}:/bitorch-engine/dist" \
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--name "${bie_container_name}" \
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-e PUBLISH_BIE_VERSION \
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-e BIE_FORCE_CUDA="true" \
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-e BIE_SKIP_BUILD="true" \
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-e BIE_TORCH_REQUIREMENT="${torch_requirement}" \
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-e BIE_WHEEL_PLATFORM="linux_x86_64" \
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-w /bitorch-engine \
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"${bie_image_tag}" \
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/workspace/publish-docker-internal.sh release
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# make sure correct version is set
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echo "${PUBLISH_BIE_VERSION#v}" > version.txt && docker container cp version.txt "${bie_container_name}":/bitorch-engine
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docker container cp .dev-scripts/publish-docker-internal.sh "${bie_container_name}":/workspace
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# for previous versions, we need to manually overwrite setup.py:
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# TODO: can (hopefully) be removed later on
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docker container cp setup.py "${bie_container_name}":/bitorch-engine
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docker start -ai "${bie_container_name}"

‎CHANGELOG.md‎

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and this project adheres to [Semantic Versioning](http://semver.org/).
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## [0.2.5] - 2024/05/24
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### Added
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- Development scripts for preparing binary releases
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### Changed
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- Updated build instructions to clarify torchvision installation
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- Adapted `setup.py` logic for preparing binary releases
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### Fixed
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- Broken build process by setting setuptools version
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## [0.2.4] - 2024/05/23
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### Added

‎README.md‎

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- **[MLX](https://github.com/ml-explore/mlx)** for mlx-based layers on MacOS
5050
- **[CUTLASS](https://github.com/NVIDIA/cutlass)** for cutlass-based layers
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52-
Currently, the engine **needs to be built from source**.
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### Binary Releases (coming soon)
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We are currently preparing experimental binary releases.
55+
Their installation will be documented in this section.
56+
For now, please follow the guide below to build from source.
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### Build From Source
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5360
We provide instructions for the following options:
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5562
- Conda + Linux (with CUDA and cutlass)
@@ -60,7 +67,7 @@ We recommend managing your BITorch Engine installation in a conda environment (o
6067
You may want to keep everything (environment, code, etc.) in one directory or use the default directory for conda environments.
6168
You may wish to adapt the CUDA version to 12.1 where applicable.
6269

63-
### Conda on Linux (with CUDA)
70+
#### Conda on Linux (with CUDA)
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To use these instructions, you need to have [conda](https://conda.io/projects/conda/en/latest/user-guide/getting-started.html) and a suitable C++ compiler installed.
6673

@@ -73,11 +80,12 @@ conda activate bitorch-engine
7380
```bash
7481
conda install -y -c "nvidia/label/cuda-11.8.0" cuda-toolkit
7582
```
76-
3. [Download customized Torch 2.1.0](https://drive.google.com/drive/folders/1T22b8JhN-E3xbn3h332rI1VjqXONZeB7?usp=sharing) (it allows gradients on INT tensors, built for Python 3.9 and CUDA 11.8) and install it with pip:
83+
3. Download our customized torch for CUDA 11.8 and Python 3.9, it allows gradients on INT tensors and install it with pip (you can find other versions [here](https://packages.greenbit.ai/whl/)):
7784
```bash
78-
pip install torch-2.1.0-cp39-cp39-linux_x86_64.whl
79-
# optional: install corresponding torchvision (check https://github.com/pytorch/vision?tab=readme-ov-file#installation in the future)
85+
pip install "https://packages.greenbit.ai/whl/cu118/torch/torch-2.1.0-cp39-cp39-linux_x86_64.whl"
86+
# as bitorch currently requires torchvision, we need to install a version for our correct CUDA (otherwise it will reinstall torch)
8087
pip install "torchvision==0.16.0" --index-url https://download.pytorch.org/whl/cu118
88+
# (check https://github.com/pytorch/vision?tab=readme-ov-file#installation in the future)
8189
```
8290
4. To use cutlass layers, you should also install CUTLASS 2.8.0 (from source), adjust `CUTLASS_HOME` (this is where we clone and install cutlass)
8391
(if you have older or newer GPUs you may need to add your [CUDA compute capability](https://developer.nvidia.com/cuda-gpus) in `CUTLASS_NVCC_ARCHS`):
@@ -112,13 +120,12 @@ conda activate ./conda-env
112120
```bash
113121
conda install -y -c "nvidia/label/cuda-11.8.0" cuda-toolkit
114122
```
115-
3. [Download customized Torch 2.1.0](https://drive.google.com/drive/folders/1T22b8JhN-E3xbn3h332rI1VjqXONZeB7?usp=sharing),
116-
select the package fit for the cuda version you installed in the previous step
117-
(it allows gradients on INT tensors, built for Python 3.9 and CUDA 11.8) and install it with pip:
123+
3. Download our customized torch for CUDA 11.8 and Python 3.9, it allows gradients on INT tensors and install it with pip (you can find other versions [here](https://packages.greenbit.ai/whl/)):
118124
```bash
119-
pip install torch-2.1.0-cp39-cp39-linux_x86_64.whl
120-
# optional: install corresponding torchvision (check https://github.com/pytorch/vision?tab=readme-ov-file#installation in the future)
125+
pip install "https://packages.greenbit.ai/whl/cu118/torch/torch-2.1.0-cp39-cp39-linux_x86_64.whl"
126+
# as bitorch currently requires torchvision, we need to install a version for our correct CUDA (otherwise it will reinstall torch)
121127
pip install "torchvision==0.16.0" --index-url https://download.pytorch.org/whl/cu118
128+
# (check https://github.com/pytorch/vision?tab=readme-ov-file#installation in the future)
122129
```
123130
4. To use cutlass layers, you should also install CUTLASS 2.8.0
124131
(if you have older or newer GPUs you may need to add your [CUDA compute capability](https://developer.nvidia.com/cuda-gpus) in `CUTLASS_NVCC_ARCHS`):
@@ -149,7 +156,7 @@ cd bitorch-engine
149156
CPATH="${CUTLASS_HOME}/install/include" CUDA_HOME="${CONDA_PREFIX}" pip install -e . -v
150157
```
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### Docker (with CUDA)
159+
#### Docker (with CUDA)
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154161
You can also use our prepared Dockerfile to build a docker image (which includes building the engine under `/bitorch-engine`):
155162

@@ -161,7 +168,7 @@ docker run -it --rm --gpus all --volume "/path/to/your/project":"/workspace" bit
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Check the [docker readme](docker/README.md) for options and more details.
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164-
### Conda on MacOS (with MLX)
171+
#### Conda on MacOS (with MLX)
165172

166173
1. We recommend to create a virtual environment for and activate it. In the following example we use a conda environment for python 3.9,
167174
but virtualenv should work as well.
@@ -171,9 +178,11 @@ conda activate bitorch-engine
171178
```
172179
2. Download [customized Torch for MacOS/arm](https://drive.google.com/drive/folders/1T22b8JhN-E3xbn3h332rI1VjqXONZeB7?usp=sharing) (it allows gradients on INT tensors, built for Python 3.9 and CUDA 11.8) and install it with pip:
173180
```bash
174-
pip install path/to/torch-2.2.1-cp39-none-macosx_11_0_arm64.whl
175-
# optional: install corresponding torchvision (check https://github.com/pytorch/vision?tab=readme-ov-file#installation in the future)
181+
pip install "https://packages.greenbit.ai/whl/macosx/torch/torch-2.2.1-cp39-none-macosx_11_0_arm64.whl"
182+
# as bitorch currently requires torchvision, we need to install a version for our correct CUDA (otherwise it will reinstall torch)
176183
pip install "torchvision==0.17.1"
184+
# (check https://github.com/pytorch/vision?tab=readme-ov-file#installation in the future)
185+
177186
```
178187
3. For MacOS users and to use OpenMP acceleration, install OpenMP with Homebrew and configure the environment:
179188
```bash
@@ -224,6 +233,14 @@ you can still build the extensions that depend on CUDA, by setting `BIE_FORCE_CU
224233
BIE_FORCE_CUDA="true" pip install -e . -v
225234
```
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236+
### Skip Library File Building
237+
238+
If you just want to avoid rebuilding any files, you can set `BIE_SKIP_BUILD`:
239+
```bash
240+
BIE_SKIP_BUILD="true" python3 -m build --no-isolation --wheel
241+
```
242+
This would create a wheel and package `.so` files without trying to rebuild them.
243+
227244
## Development
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229246
To adjust the build options or address build failures, modify the configurations in

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