* Add LazyGraphExecutor registration
* Update PyTorch version to 1.14.0.dev20221024
Co-authored-by: Roll PyTorch Action <torch-mlir@users.noreply.github.com>
Upstream PyTorch nightly page
[https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html]
somehow dropped the link for torch-1.14.0.dev20221018 for macOS but not
for Linux or Windows, whereas our RollPyTorch action assumes that if the
nightly version is available for Linux, it is also available for macOS.
This reverts the commit that changed the PyTorch version.
* build: disable LTC again so that we can bump PyTorch version
When built using PyTorch's master branch, the LTC code has been failing
to build for a few days. As a result, the PyTorch version referenced by
Torch-MLIR is stalled to the one from October 4th.
In an effort to advance to PyTorch version, this patch disables LTC, and
a subsequent patch will advance the PyTorch version.
* update PyTorch version to 1.14.0.dev20221010
Also disables the `UpSampleNearest2dDynamicFactor_basic` e2e test, since
the (PyTorch) oracle differs from the computed value for both the
refbackend and the eager_mode backends.
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>
Jae Hoon (Antonio) Kim
Roll PyTorch Action
Ashay Rane