Despite using sudo to delete the workspace directory, we still
occasionally run into checkout errors. This patch thus drops the
deletion of the workspace prior to checkout. It also restricts the
number of parallel jobs in the submodule fetch step to just one, to try
and resolve the checkout issue ("index.lock: File exists.").
We have recently started seeing errors like:
```
Synchronizing submodule url for 'externals/llvm-project'
Synchronizing submodule url for 'externals/mlir-hlo'
/usr/bin/git -c protocol.version=2 submodule update --init --force --depth=1
Error: fatal: Unable to create '/home/anush/actions-runner/_work/torch-mlir/torch-mlir/.git/modules/externals/llvm-project/index.lock': File exists.
```
As a workaround, this patch removes the workspace directory before the
checkout step.
The RollPyTorch action needs the `unzip` command to peek into WHL files
for fetching metadata. This patch makes sure that the command is
installed before referencing it.
We want to ensure that pip packages required for building torch-mlir
should be included in the dependencies of torch-mlir, but we don't want
the pip packages required for _testing_ of torch-mlir to be included
among the dependencies. To be able to specify and install one set of
dependencies and not the other, this patch separates the pip packages
into two files: build-requirements.txt and test-requirements.txt.
This patch also updates references to the requirements.txt file so that
CI builds that run end-to-end tests install test-related pip
dependencies while everything else (including WHL builds) sticks to just
the build-related pip dependencies.
Despite this change, this patch should not affect a torch-mlir
developer's workflow. More precisely, since this patch makes the
top-level requirements.txt file refer to both build-requirements.txt and
test-requirements.txt files, a torch-mlir developer should be able to
continue referring to the requirements.txt file without any impact.
Now that the RollPyTorch tracker issue exists, we can automate the job
of notifying folks of failures instead of having to do it manually.
This patch adds a step to the workflow to post such a message.
The RollPyTorch action often takes more than 1.5 hours to finish.
During this time, if another PR is merged, then the RollPyTorch action
needs to first pull the merged changes before committing the updates to
the PyTorch commit hash and version files. This patch adds the required
`git pull` statement, without which, the subsequent `git push` statement
fails, causing the RollPyTorch action to fail as well.
* [custom op] Generalize shape library logic to work with dtypes
This commit generalizes the shape library logic, so that dtype rules
for ops can also be expressed using the same mechanism. In other
words, each op can now have a shape function and a dtype function
specified in Python that is imported during lowering to calculate the
shapes and dtypes throught a program. For more information about how
to specify a dtype function, see the updated
`docs/adding_a_shape_and_dtype_function.md`.
For those not familiar with how the shape library works, the file
`docs/calculations_lib.md` provides an overview.
Until recently, the metadata file in the torchvision package included
the nightly version of the torch package, but since that is no longer
the case, our RollPyTorch workflow is broken.
As a workaround, this patch uses the `pip download` command's ability to
fetch the dependent torch package for the specified version of
torchvision, before peeking into the WHL file for the torch package to
determine the release version and the commit hash.
The upload timestamp of the nightly torchvision package has drifted
beyond the scheduled time of the RollPyTorch action because of the time
change due to daylight saving. As a result, the RollPyTorch action now
picks the torchvision package from a day earlier instead of the most
recent package.
This patch schedules the RollPyTorch action to start one hour later than
before so that it continues to pick the most recent nightly package.
We currently pin the `torch` package to the latest nightly version, but
since `torchvision` depends on the `torch` package, the pip resolver
then has to run through an extensive list of `torchvision` packages that
can be installed with the pinned `torch` package. This search fails in
the RollPyTorch action, causing pip to settle on an old version of
`torchvision` that does not work with our tests. In reality, we are
only interested in a specific version of the `torchvision` package.
To make the dependency explicit and to prevent test failures because of
incorrect package installations, this patch makes two key changes:
1. `torchvision` is now pinned to the latest nightly release in
pytorch-requirements.txt along with the version of `torch` that is
necessary to install the requested `torchvision` package
2. The RollPyTorch action now looks for the latest `torchvision` package
instead of the latest `torch` package before writing the version
numbers for pinning in pytorch-requirements.txt
This patch makes a few small, but key, changes to enable ccache on
Windows. First, it replaces the hendrikmuhs/ccache-action action with
command line invocations to the ccache binary, since the action has two
bugs, one of which causes CI to refer to different ccache artifacts
before versus after the build on Windows whereas the other bug can
sometimes cause the action to incorrectly infer that the cache is empty.
Second, this patch slightly alters the cache key, so that our old cache
artifacts, which have grown too big, are eventually discarded in favor
of the new, smaller cache artifacts. Along the way, this patch also
keeps the RollPyTorch's cache artifact separate from the regular build's
cache artifact so as to keep these artifacts small, and also because the
RollPyTorch action is off the critical path for most contributors.
Finally, this patch makes small changes to the CMake file so that on
Windows, the ccache binary is added as a prefix, as recommended on the
[ccache Wiki](https://github.com/ccache/ccache/wiki/MS-Visual-Studio).
Until recently, we had to either risk feature branches creating PyTorch
build caches (which were unusable by the main branch or other parallel
feature branches because of GitHub's rules around sharing caches among
branches) or we had to limit the PyTorch build caches to only the main
branch, causing CI runs on feature branches to be terribly slow because
they had to rebuild PyTorch each time.
This patch enables the best of both worlds, by using a fork
(github.com/ashay/cache) of the GitHub's cache action, where the fork
adds an option (called `save`) which, when set, uploads a new cache
entry. We thus set this `save` flag only when we're building PyTorch
from source in Torch-MLIR's main branch, whereas all other builds set
this `save` flag to `false`.
The ability to conditionally update the cache has been an oft-requested
feature on the original (github.com/actions/cache) repository and
multiple unmerged PRs exist to allow conditional cache updates, so it is
likely that using the fork is only a temporary solution.
This patch is part of a larger set of improvements to the CI/build
system. In the code, we refer to the version as the string that
contains the release identifier such as 1.14.0.dev20221028, so calling
the file that contains the commit hash as pytorch-version.txt creates
confusion. For the sake of simplicity, this patch renames that file to
be pytorch-hash.txt.
If PyTorch build caches are created on a branch other than the main
branch, then GitHub does not share those caches with the main branch,
making every CI run that runs for each PR slow. This patch resolves the
problem by letting only the main branch create and use PyTorch build
caches.
* ci: cache PyTorch source builds
This patch reduces the time spent in regular CI builds by caching
PyTorch source builds. Specifically, this patch:
1. Makes CI lookup the cache entry for the PyTorch commit hash in
pytorch-version.txt
2. If lookup was successful, CI fetches the previously-generated WHL
file into the build_tools/python/wheelhouse directory
3. CI sets the `TM_PYTORCH_INSTALL_WITHOUT_REBUILD` variable to `true`
4. The build_libtorch.sh script then uses the downloaded WHL file
instead of rebuilding PyTorch
* ci: warm up PyTorch source cache during daily RollPyTorch action
This patch makes the RollPyTorch action write the updated WHL file to
the cache, so that it can be later retrieved by CI that runs for each
PR. We deliberately add the caching step to the end of the action since
the RollPyTorch action never needs to read from the cache, although
executing this step earlier in the process should not cause problems
either.
Instead of letting the auto-update script either fail because of script
errors or letting it commit bad versions, this patch makes the update
process manual, for now. Once the script stabilizes, I will its
re-enable periodic execution.
Updating the PyTorch version may break the Torch-MLIR build, as it did
recently, since the PyTorch update caused the shape library to change,
but the shape library was not updated in the commit for updating
PyTorch.
This patch introduces a new default-off environment variable to the
build_linux_packages.sh script called `TM_UPDATE_ODS_AND_SHAPE_LIB`
which instructs the script to run the update_torch_ods.sh and
update_shape_lib.sh scripts.
However, running these scripts requires an in-tree build and the tests
that run for an in-tree build of Torch-MLIR are more comprehensive than
those that run for an out-of-tree build, so this patch also swaps out
the out-of-tree build for an in-tree build.
A bug in the CI script caused the entire script to fail if the exit code
of the command for comparing with the existing hash returned a non-zero
exit status. The non-zero exit status for this comparison does not
imply failed execution, since it only indicates that the hash has
changed.
* build: push directly from CI to main branch
This avoids the need to create, approve, and merge a separate PR, in
addition to avoiding unnecessary CI runs for the PyTorch version update.
* build: schedule cronjob to run RollPyTorch action
This patch schedules the RollPyTorch action to be run at noon UTC, which
roughly corresponds to 4am Pacific Time. We pick this time since the
commit for PyTorch nightly releases are picked just after midnight
Pacific Time and the nightly release artifacts are produced in about 2
to 3 hours after the commit is picked.
This patch fetches the most recent nightly (binary) build of PyTorch,
before pinning it in pytorch-requirements.txt, which is referenced in
the top-level requirements.txt file. This way, end users will continue
to be able to run `pip -r requirements.txt` without worrying whether
doing so will break their Torch-MLIR build.
This patch also fetches the git commit hash that corresponds to the
nightly release, and this hash is passed to the out-of-tree build so
that it can build PyTorch from source.
If we were to sort the torch versions as numbers (in the usual
descending order), then 1.9 appears before 1.13. To fix this problem,
we use the `--version-sort` flag (along with `--reverse` for specifying
a descending order). We also filter out lines that don't contain
version numbers by only considering lines that start with a digit.
As a matter of slight clarity, this patch renames the variable
`torch_from_src` to `torch_from_bin`, since that variable is initialized
to `TM_USE_PYTORCH_BINARY`.
Co-authored-by: powderluv <powderluv@users.noreply.github.com>
powderluv
Ashay Rane
Ramiro Leal-Cavazos