# IREE Repository Management

## Dependencies

As a project which brings together compiler, runtime and graphics systems,
dependency management is somewhat complex. We use git submodules for C++
dependencies and, where possible, language specific external package management
for other types of dependencies (i.e. Python).

In addition, the IREE Open Source project is actually downstream from its
"source of truth" within Google -- where dependencies are managed entirely
differently. This imposes constraints on repository management tasks that may
not be obvious.

Shortcut commands (read below for full documentation):

```shell
# Update SUBMODULE_VERSIONS from current git submodule pointers
./git_scripts/submodule_versions.py export

# Update current git submodule pointers based on SUBMODULE_VERSIONS
./git_scripts/submodule_versions.py import

# Bump TensorFlow and LLVM to (TensorFlow) head.
# (Also updates SUBMODULE_VERSIONS).
./git_scripts/update_tf_llvm_submodules.py
```

### The special relationship with LLVM and TensorFlow

Currently, the two most challenging projects to manage as dependencies are
TensorFlow and LLVM. Both are typically pinned to specific versions that are
integrated upstream at a cadence up to many times per day. Further, because LLVM
does not ship with Bazel BUILD files, IREE "borrows" the BUILD files from
TensorFlow (for building with Bazel). Just to make it more interesting, since
TensorFlow does not ship with CMakeLists, IREE uses overlay CMakeLists.txt to
build subsets of TensorFlow needed for the compiler (when built with CMake).
While these externally managed build files are written to be moderately generic,
they can and do break and require manual intervention at times (i.e. there is no
guarantee that updating to a new commit of either will not require some manual
work on the build files).

The only combination which is expected to work is the llvm-project commit noted
in the `LLVM_COMMIT` setting in
`third_party/tensorflow/tensorflow/workspace.bzl`. In reality, it is often
possible (especially with the CMake build) to use a newer llvm-project commit,
and private development forks should feel free to do this. However, to submit
upstream, we will need to integrate this newer commit in the internal Google
source of truth prior to accepting code that depends on it.

### Tasks:

#### Adding dependencies

In general, adding dependencies will require coordination with Google engineers
to make the dependency available in both upstream and downstream. It is
important to ask on the mailing list prior to expecting to contribute such
changes.

#### Pushing dependency changes

When working on a development branch, feel free to stage changes however makes
sense. However, when sending a PR, note that the upstream systems ignore any
submodule version updates when merging the commit. Our source of truth for
versions is in the `SUBMODULE_VERSIONS` file in the repository root. Here is an
example:

```text
6ec136281086b71da32b5fb068bd6e46b78a5c79 third_party/abseil-cpp
309de5988eb949a27e077a24a1d83c0687d10d57 third_party/benchmark
4c13807b7d43ff0946b7ffea0ae3aee9e611d778 third_party/dear_imgui
97f3aa91746a7d207513a73725e92cee7c35bb87 third_party/flatbuffers
dc69acdf61d7a64260ae0eb9c17421fef0488c02 third_party/gemmlowp
48233ad3d45b314a83474b3704ae09638e3e2621 third_party/glslang
495ced98de99a5895e484b2e09771edb42d3c7ab third_party/google_tracing_framework
f2fb48c3b3d79a75a88a99fba6576b25d42ec528 third_party/googletest
a21beccea2020f950845cbb68db663d0737e174c third_party/llvm-project
80d452484c5409444b0ec19383faa84bb7a4d351 third_party/pybind11
b73f111094da3e380a1774b56b15f16c90ae8e23 third_party/sdl2
b252a50953ac4375cb1864e94f4b0234db9d215d third_party/spirv_headers
feb154921397dc8c43c130a6b5c123efdb432a9b third_party/spirv_tools
6652f0b6428777b5a4a3d191cc30d8b31366b999 third_party/swiftshader
9b32b2db1142166b190ea30757f48d8dd0fb00e3 third_party/tensorflow
ba091ba6a947f79623b28fe8bfccdce1ab9fa467 third_party/vulkan_headers
909f36b714c9239ee0b112a321220213a474ba53 third_party/vulkan_memory_allocator
```

If bumping versions, you must include an update to this file with your commit.
To generate it, run:

```shell
# Performs a submodule sync+update and stages an updated SUBMODULE_VERSIONS
# file.
./git_scripts/submodule_versions.py export
```

If you don't know if this is required, you may run:

```shell
# The check command is intended to eventually be usable as a git hook
# for verification of consistency between SUBMODULE_VERSIONS and the
# corresponding local git state.
./git_scripts/submodule_versions.py check
```

#### Pulling dependency changes

If you pull a change to `SUBMODULE_VERSIONS` it is necessary to import it into
the current git state:

```shell
# Updates the commit hash of any entries in SUBMODULE_VERSIONS that differ
# and stages the changes.
./git_scripts/submodule_versions.py import
```

This will stage any needed changes to the submodules to bring them up to date
with the `SUBMODULE_VERSIONS`. If you have local changes, you may get conflicts
on the `submodule update` step at the end, and you will need to manually resolve
as usual.

Any CI systems or other things that retrieve an arbitrary commit should invoke
this prior to running just to make sure that their git view of the submodule
state is consistent.

TODO(laurenzo): Add a GitHub hook to auto-commit submodule updates on
`SUBMODULE_VERSIONS` file changes.

#### Updating TensorFlow and LLVM versions

```shell
# By default, updates third_party/tensorflow to the remote head and
# third_party/llvm-project to the commit that tensorflow references.
# Also updates the IREE mirrors of key build files. All changes will
# be staged for commit.
./git_scripts/update_tf_llvm_submodules.py

# You can also select various other options:
# Don't update the tensorflow commit, just bring LLVM to the correct
# linked commit.
./git_scripts/update_tf_llvm_submodules.py --tensorflow_commit=KEEP

# Don't update the LLVM commit.
./git_scripts/update_tf_llvm_submodules.py --llvm_commit=KEEP

# Update to a specific TensorFlow commit (and corresponding LLVM).
./git_scripts/update_tf_llvm_submodules.py --tensorflow_commit=<somehash>

# Update to a specific LLVM commit.
./git_scripts/update_tf_llvm_submodules.py --llvm_commit=<somehash>
```