docs/developers/developing_iree/llvm_version_bump.md - 3p/openxla/iree - Git at Google

 # Notes on integrating LLVM from the OSS side

 This is a work in progress guide on how to bump versions of LLVM and related
 dependencies. In the recent past, we did this in a different system and this
 is just to get us by until we get it better scripted/automated.

 Note that scripts referenced in this guide are temporarily hosted in the
 [iree-samples repository](https://github.com/google/iree-samples/tree/main/scripts/integrate).
 This is because it is very non-user friendly to have branch and submodule
 management scripts in the repository being managed, and we don't have an
 immediately better place. In this guide, we reference this location as
 `$SCRIPTS`.

 ## Advancing the mainline branch in forks

 The IREE team maintains fork repositories for both llvm-project and mlir-hlo,
 allowing them to be patched out of band. These repositories are:

 * https://github.com/google/iree-llvm-fork (`main` branch)
 * https://github.com/google/iree-mhlo-fork (`master` branch)
 * https://github.com/google/iree-tf-fork (`master` branch)

 By the time you read this, they may be on a cron to advance automatically, but
 even so, it is a good idea to advance them prior to any integrate activities
 so that you have freshest commits available. Iree repository has an
 action named [Advance Upstream Forks](https://github.com/google/iree/actions/workflows/advance_upstream_forks.yml)
 to update the forks. Just select `Run Workflow` on that action and give it a
 minute. You should see the fork repository mainline branch move forward.

 ## Bumping LLVM and Dependent Projects

 ### Strategy 1: Bump third_party/llvm-project in isolation

 It is very common to only bump llvm-project and not sync to new versions of
 mlir-hlo and tensorflow. However, as we need to periodically integrate those
 as well, if the Google repositories are up to date and you have the option
 to integrate to a common LLVM commit, bringing mlir-hlo and tensorflow up
 to date as well, it can save some cycles overall.

 In order to bump to the current ToT commit, simply run:

 ```
 $SCRIPTS/bump_llvm.py
 ```

 This will create a branch in the main repository like `bump-llvm-YYYYMMDD`.
 If you need to specify a branch name, use the `--branch-name=` argument.
 A specific upstream commit can be selected with `--llvm-commit=`.

 It will print what it is doing, and at the end will show the usual GitHub
 "create a PR" banner for the branch created. Open that, create a PR, patch
 until green and merge. If it takes a long time and `main` has moved forward,
 you likely need to pull updates:

 ```
 git pull --rebase origin main
 git push -f
 ```

 If you have sharded out integrate work, coordinate with others on the #builds
 channel before force pushing a rebase.

 Actually applying necessary patches to upgrade the project is an art form.
 It is usually reasonable to focus on build breaks first, and starting with
 Bazel can help, especially for catching nit-picky strict things:

 ```
 bazel build iree/tools:iree-compile
 bazel test iree/compiler/...
 ```

 Once Bazel is good, remember to run
 `./build_tools/bazel_to_cmake/bazel_to_cmake.py` and keep working on the
 rest of the build.

 For easy integrates, it can sometimes be easy enough to just spot the issue on
 the CI and fix it directly. But if dealing with some large/breaking changes,
 be prepared to settle in for a bit and play a triage role, working to get things
 minimally to a point that you can shard failures to others.

 Note that if not bumping mlir-hlo, then it is likely that you will hit a
 compiler error in mlir-hlo at some point and will need to fix it. Advancing
 it to HEAD is always an option, if that contains the fix, but this dependency
 is unstable and should be maintained version locked with the integrations
 directory. It is possible to advance it, but only if integrations tests pass,
 and even then there is the chance for untested compatibility issues.

 Typically, for the parts of mlir-hlo that we use, changes can be trivial (a
 few lines, likely that you have already patched something similar in IREE).
 Just make the changes in your submodule, commit them and push to a patch
 branch with:

 ```
 $SCRIPTS/patch_module.py --module_name=mlir-hlo
 ```

 You can just do this in your integrate branch and incorporate the changes.
 Typically, you will want to hold off on running `patch_module` until you are
 ready to push the overall integrate branch and have some confidence that your
 local fixes are sound. See the "Cherry-Picking" section below for more
 details.

 Good luck!

 ### Strategy 2: Sync everything to a Google/TensorFlow commit

 TODO: Add a script for this. Also note that there is a forked copy of
 `iree-dialects` in integrations/tensorflow. When bumping that dependency,
 the main-project version should be copied over the integrations version.

 ```
 cd ~/src
 git clone --branch master https://github.com/google/iree-tf-fork.git
 git clone --branch master https://github.com/google/iree-mhlo-fork.git
 ```

 Get MHLO's published version:

 We use this one because it is the easiest to get at and most of the
 activity is LLVM integrates.

 ```
 cat mlir-hlo/build_tools/llvm_version.txt
 ```

 Or `git log` to find a commit like:

 ```
 commit f9f696890acbe198b6164a7ca43523e2bddd630a (HEAD -> master, origin/master, origin/HEAD)
 Author: Stephan Herhut <herhut@google.com>
 Date:   Wed Jan 12 08:00:24 2022 -0800

     Integrate LLVM at llvm/llvm-project@c490f8feb71e

     Updates LLVM usage to match
     [c490f8feb71e](https://github.com/llvm/llvm-project/commit/c490f8feb71e)

     PiperOrigin-RevId: 421298939
 ```

 You can correlate this with a tensorflow commit by searching TensorFlow commits
 for the `PiperOrigin-RevId`, which is shared between them. While not strictly
 necessary to keep all of this in sync, if doing so, it will yield fewer
 surprises.

 An example of a corresponding commit in the tensorflow repo:

 ```
 commit a20bfc24dfbc34ef4de644e6bf46b41e6e57b878
 Author: Stephan Herhut <herhut@google.com>
 Date:   Wed Jan 12 08:00:24 2022 -0800

     Integrate LLVM at llvm/llvm-project@c490f8feb71e

     Updates LLVM usage to match
     [c490f8feb71e](https://github.com/llvm/llvm-project/commit/c490f8feb71e)

     PiperOrigin-RevId: 421298939
     Change-Id: I7e6c1c25d42f6936f626550930957f5ee522b645
 ```

 From this example:

 ```
 LLVM_COMMIT="c490f8feb71e"
 MHLO_COMMIT="f9f696890acbe198b6164a7ca43523e2bddd630a"
 TF_COMMIT="a20bfc24dfbc34ef4de644e6bf46b41e6e57b878"
 ```

 Apply:

 ```
 cd ~/src/iree
 git fetch
 (cd third_party/llvm-project && git checkout $LLVM_COMMIT)
 (cd third_party/mlir-hlo && git checkout $MHLO_COMMIT)
 sed -i "s/^TENSORFLOW_COMMIT = .*$/TENSORFLOW_COMMIT = \"$TF_COMMIT\"/" integrations/tensorflow/WORKSPACE

 # git status should show:
 #        modified:   integrations/tensorflow/WORKSPACE
 #        modified:   third_party/llvm-project (new commits)
 #        modified:   third_party/mlir-hlo (new commits)
 ```

 Make a patch:

 ```
 git add -A
 git commit
 # Message like:
 #    Integrate llvm-project and bump dependencies.
 #
 #    * llvm-project: c490f8feb71e
 #    * mlir-hlo: f9f696890acbe198b6164a7ca43523e2bddd630a
 #    * tensorflow: a20bfc24dfbc34ef4de644e6bf46b41e6e57b878
 ```

 Either Yolo and send a PR to have the CI run it or do a local build. I will
 typically only build integrations/tensorflow if the CI indicates there is an
 issue.

 ```
 # Push to the main repo so that we can better collaboratively apply fixes.
 # If there are failures, feel free to call people in who know areas for help.
 git push origin HEAD:llvm-bump
 ```

 Either fix any issues or get people to do so and land patches until the
 PR is green.

 A script from [iree-samples](https://github.com/google/iree-samples/blob/main/scripts/integrate/bump_llvm.py)
 repository can help with bumping the LLVM version and creating a PR.
 To use the script the steps are

 ```
 cd ~/src/iree
 $SCRIPTS/bump_llvm.py --llvm-commit $LLVM_COMMIT
 ```

 This creates a new in IREE repository (named bump-llvm-yyyymmdd). A PR can
 be created from that. Following that MHLO and TF can be bumped the same way

 ```
 (cd third_party/mlir-hlo && git checkout $MHLO_COMMIT)
 sed -i "s/^TENSORFLOW_COMMIT = .*$/TENSORFLOW_COMMIT = \"$TF_COMMIT\"/" integrations/tensorflow/WORKSPACE
 git add -A
 git commit ...
 git push UPSTREAM_AUTOMATION bump-llvm-...
 ```

 ## Cherry-picking

 We support cherry-picking specific commits in to both llvm-project and mlir-hlo.
 This should only ever be done to incorporate patches that enable further
 development and which will resolve automatically as part of a future
 integrate of the respective module: make sure that you are only cherry-picking
 changes that have been (or will be immediately) committed upstream. For
 experimental changes, feel free to push a personal branch to the fork repo
 with such changes, which will let you use the CI -- but please do not commit
 experimental, non-upstream committed commits to the main project.

 The process for cherry-picking into llvm-project or mlir-hlo uses the same
 script. The first step is to prepare a patch branch and reset your local
 submodule to track it:

 ```
 $SCRIPTS/patch_module.py --module={llvm-project|mlir-hlo}
 ```

 If successful, this will allocate a new branch in the fork repo with a name
 like `patched-llvm-project-YYYYMMDD[.index]`, push the current submodule
 commit to it and switch your submodule to a local copy of the branch, setup
 for pushing.

 If you have already committed changes to your branch, it should be fine to
 run the script and they will be incorporated into your new patch branch.

 Push any changes in your submodule as needed, and then when ready, create
 a patch in the main IREE project which includes the submodule updates. In the
 GitHub UI, it should show a nice drill-down of the submodule with the changes.

 Note that cherry-picking is a racey process: if two people cross each other,
 one of them will conflict and then Master-Git will likely need to be called.
 Coordinate on cherry-picks on the #builds channel.

 A submodule can receive an arbitrary number of cherry-picks. This will just
 yield more patch branches to track the reachable set. (TODO: this is not
 strictly true with the current script -- it will extend the current patch
 branch. But we should change it to just always create a new branch as there
 is less room for error).

 Undoing a sequence of cherry-picks is done by integrating to a new upstream
 version, presumably one that includes the commits.
	# Notes on integrating LLVM from the OSS side

	This is a work in progress guide on how to bump versions of LLVM and related
	dependencies. In the recent past, we did this in a different system and this
	is just to get us by until we get it better scripted/automated.

	Note that scripts referenced in this guide are temporarily hosted in the
	[iree-samples repository](https://github.com/google/iree-samples/tree/main/scripts/integrate).
	This is because it is very non-user friendly to have branch and submodule
	management scripts in the repository being managed, and we don't have an
	immediately better place. In this guide, we reference this location as
	`$SCRIPTS`.

	## Advancing the mainline branch in forks

	The IREE team maintains fork repositories for both llvm-project and mlir-hlo,
	allowing them to be patched out of band. These repositories are:

	* https://github.com/google/iree-llvm-fork (`main` branch)
	* https://github.com/google/iree-mhlo-fork (`master` branch)
	* https://github.com/google/iree-tf-fork (`master` branch)

	By the time you read this, they may be on a cron to advance automatically, but
	even so, it is a good idea to advance them prior to any integrate activities
	so that you have freshest commits available. Iree repository has an
	action named [Advance Upstream Forks](https://github.com/google/iree/actions/workflows/advance_upstream_forks.yml)
	to update the forks. Just select `Run Workflow` on that action and give it a
	minute. You should see the fork repository mainline branch move forward.

	## Bumping LLVM and Dependent Projects

	### Strategy 1: Bump third_party/llvm-project in isolation

	It is very common to only bump llvm-project and not sync to new versions of
	mlir-hlo and tensorflow. However, as we need to periodically integrate those
	as well, if the Google repositories are up to date and you have the option
	to integrate to a common LLVM commit, bringing mlir-hlo and tensorflow up
	to date as well, it can save some cycles overall.

	In order to bump to the current ToT commit, simply run:

	```
	$SCRIPTS/bump_llvm.py
	```

	This will create a branch in the main repository like `bump-llvm-YYYYMMDD`.
	If you need to specify a branch name, use the `--branch-name=` argument.
	A specific upstream commit can be selected with `--llvm-commit=`.

	It will print what it is doing, and at the end will show the usual GitHub
	"create a PR" banner for the branch created. Open that, create a PR, patch
	until green and merge. If it takes a long time and `main` has moved forward,
	you likely need to pull updates:

	```
	git pull --rebase origin main
	git push -f
	```

	If you have sharded out integrate work, coordinate with others on the #builds
	channel before force pushing a rebase.

	Actually applying necessary patches to upgrade the project is an art form.
	It is usually reasonable to focus on build breaks first, and starting with
	Bazel can help, especially for catching nit-picky strict things:

	```
	bazel build iree/tools:iree-compile
	bazel test iree/compiler/...
	```

	Once Bazel is good, remember to run
	`./build_tools/bazel_to_cmake/bazel_to_cmake.py` and keep working on the
	rest of the build.

	For easy integrates, it can sometimes be easy enough to just spot the issue on
	the CI and fix it directly. But if dealing with some large/breaking changes,
	be prepared to settle in for a bit and play a triage role, working to get things
	minimally to a point that you can shard failures to others.

	Note that if not bumping mlir-hlo, then it is likely that you will hit a
	compiler error in mlir-hlo at some point and will need to fix it. Advancing
	it to HEAD is always an option, if that contains the fix, but this dependency
	is unstable and should be maintained version locked with the integrations
	directory. It is possible to advance it, but only if integrations tests pass,
	and even then there is the chance for untested compatibility issues.

	Typically, for the parts of mlir-hlo that we use, changes can be trivial (a
	few lines, likely that you have already patched something similar in IREE).
	Just make the changes in your submodule, commit them and push to a patch
	branch with:

	```
	$SCRIPTS/patch_module.py --module_name=mlir-hlo
	```

	You can just do this in your integrate branch and incorporate the changes.
	Typically, you will want to hold off on running `patch_module` until you are
	ready to push the overall integrate branch and have some confidence that your
	local fixes are sound. See the "Cherry-Picking" section below for more
	details.

	Good luck!

	### Strategy 2: Sync everything to a Google/TensorFlow commit

	TODO: Add a script for this. Also note that there is a forked copy of
	`iree-dialects` in integrations/tensorflow. When bumping that dependency,
	the main-project version should be copied over the integrations version.

	```
	cd ~/src
	git clone --branch master https://github.com/google/iree-tf-fork.git
	git clone --branch master https://github.com/google/iree-mhlo-fork.git
	```

	Get MHLO's published version:

	We use this one because it is the easiest to get at and most of the
	activity is LLVM integrates.

	```
	cat mlir-hlo/build_tools/llvm_version.txt
	```

	Or `git log` to find a commit like:

	```
	commit f9f696890acbe198b6164a7ca43523e2bddd630a (HEAD -> master, origin/master, origin/HEAD)
	Author: Stephan Herhut <herhut@google.com>
	Date: Wed Jan 12 08:00:24 2022 -0800

	Integrate LLVM at llvm/llvm-project@c490f8feb71e

	Updates LLVM usage to match
	[c490f8feb71e](https://github.com/llvm/llvm-project/commit/c490f8feb71e)

	PiperOrigin-RevId: 421298939
	```

	You can correlate this with a tensorflow commit by searching TensorFlow commits
	for the `PiperOrigin-RevId`, which is shared between them. While not strictly
	necessary to keep all of this in sync, if doing so, it will yield fewer
	surprises.

	An example of a corresponding commit in the tensorflow repo:

	```
	commit a20bfc24dfbc34ef4de644e6bf46b41e6e57b878
	Author: Stephan Herhut <herhut@google.com>
	Date: Wed Jan 12 08:00:24 2022 -0800

	Integrate LLVM at llvm/llvm-project@c490f8feb71e

	Updates LLVM usage to match
	[c490f8feb71e](https://github.com/llvm/llvm-project/commit/c490f8feb71e)

	PiperOrigin-RevId: 421298939
	Change-Id: I7e6c1c25d42f6936f626550930957f5ee522b645
	```

	From this example:

	```
	LLVM_COMMIT="c490f8feb71e"
	MHLO_COMMIT="f9f696890acbe198b6164a7ca43523e2bddd630a"
	TF_COMMIT="a20bfc24dfbc34ef4de644e6bf46b41e6e57b878"
	```

	Apply:

	```
	cd ~/src/iree
	git fetch
	(cd third_party/llvm-project && git checkout $LLVM_COMMIT)
	(cd third_party/mlir-hlo && git checkout $MHLO_COMMIT)
	sed -i "s/^TENSORFLOW_COMMIT = .*$/TENSORFLOW_COMMIT = \"$TF_COMMIT\"/" integrations/tensorflow/WORKSPACE

	# git status should show:
	# modified: integrations/tensorflow/WORKSPACE
	# modified: third_party/llvm-project (new commits)
	# modified: third_party/mlir-hlo (new commits)
	```

	Make a patch:

	```
	git add -A
	git commit
	# Message like:
	# Integrate llvm-project and bump dependencies.
	#
	# * llvm-project: c490f8feb71e
	# * mlir-hlo: f9f696890acbe198b6164a7ca43523e2bddd630a
	# * tensorflow: a20bfc24dfbc34ef4de644e6bf46b41e6e57b878
	```

	Either Yolo and send a PR to have the CI run it or do a local build. I will
	typically only build integrations/tensorflow if the CI indicates there is an
	issue.

	```
	# Push to the main repo so that we can better collaboratively apply fixes.
	# If there are failures, feel free to call people in who know areas for help.
	git push origin HEAD:llvm-bump
	```

	Either fix any issues or get people to do so and land patches until the
	PR is green.

	A script from [iree-samples](https://github.com/google/iree-samples/blob/main/scripts/integrate/bump_llvm.py)
	repository can help with bumping the LLVM version and creating a PR.
	To use the script the steps are

	```
	cd ~/src/iree
	$SCRIPTS/bump_llvm.py --llvm-commit $LLVM_COMMIT
	```

	This creates a new in IREE repository (named bump-llvm-yyyymmdd). A PR can
	be created from that. Following that MHLO and TF can be bumped the same way

	```
	(cd third_party/mlir-hlo && git checkout $MHLO_COMMIT)
	sed -i "s/^TENSORFLOW_COMMIT = .*$/TENSORFLOW_COMMIT = \"$TF_COMMIT\"/" integrations/tensorflow/WORKSPACE
	git add -A
	git commit ...
	git push UPSTREAM_AUTOMATION bump-llvm-...
	```

	## Cherry-picking

	We support cherry-picking specific commits in to both llvm-project and mlir-hlo.
	This should only ever be done to incorporate patches that enable further
	development and which will resolve automatically as part of a future
	integrate of the respective module: make sure that you are only cherry-picking
	changes that have been (or will be immediately) committed upstream. For
	experimental changes, feel free to push a personal branch to the fork repo
	with such changes, which will let you use the CI -- but please do not commit
	experimental, non-upstream committed commits to the main project.

	The process for cherry-picking into llvm-project or mlir-hlo uses the same
	script. The first step is to prepare a patch branch and reset your local
	submodule to track it:

	```
	$SCRIPTS/patch_module.py --module={llvm-project\|mlir-hlo}
	```

	If successful, this will allocate a new branch in the fork repo with a name
	like `patched-llvm-project-YYYYMMDD[.index]`, push the current submodule
	commit to it and switch your submodule to a local copy of the branch, setup
	for pushing.

	If you have already committed changes to your branch, it should be fine to
	run the script and they will be incorporated into your new patch branch.

	Push any changes in your submodule as needed, and then when ready, create
	a patch in the main IREE project which includes the submodule updates. In the
	GitHub UI, it should show a nice drill-down of the submodule with the changes.

	Note that cherry-picking is a racey process: if two people cross each other,
	one of them will conflict and then Master-Git will likely need to be called.
	Coordinate on cherry-picks on the #builds channel.

	A submodule can receive an arbitrary number of cherry-picks. This will just
	yield more patch branches to track the reachable set. (TODO: this is not
	strictly true with the current script -- it will extend the current patch
	branch. But we should change it to just always create a new branch as there
	is less room for error).

	Undoing a sequence of cherry-picks is done by integrating to a new upstream
	version, presumably one that includes the commits.