Commit Graph

3 Commits (bfb93cb99f259a614b4be7f6a4d04f6a07e4d395)

Author SHA1 Message Date
Dave Liddell 04be6ba773
Make the onnx importer more robust for internal/external and large models (#2794)
Fix for https://github.com/llvm/torch-mlir/issues/2765

The onnx docs say that you can't do shape inference using the in-memory
API for models > 2 GB. This fix replaces that API with the file-based
API. Since the new API generates an intermediate file, also added a
--keep switch to keep that file, which I delete by default.

---------

Co-authored-by: Dave Liddell <dliddell@xilinx.com>
2024-01-31 21:58:43 -08:00
Stella Laurenzo ed4df38e8d
[onnx] Add torch-mlir-import-onnx tool. (#2637)
Simple Python console script to import an ONNX protobuf to the torch
dialect for additional processing.

For installed wheels, this can be used with something like:

```
torch-mlir-import-onnx test/python/onnx_importer/LeakyReLU.onnx
```

Or from a dev setup:

```
python -m torch_mlir.tools.import_onnx ...
```
2023-12-12 22:01:30 -08:00
Stella Laurenzo 74f7a0c9d6
Upstream the ONNX importer. (#2636)
This is part 1 of 2, which will also include upstreaming the FX
importer. I started with ONNX because it forces some project layout
updates and is more self contained/easier as a first step.

Deviating somewhat from the RFCs on project layout, I made the following
decisions:

* Locating the `onnx_importer.py` into `torch_mlir.extras` as Maks
already has opened up that namespace and it seemed to fit. Better to
have fewer things at that level.
* Setup the build so that the root project only contains MLIR Python and
pure Python deps (like the importers), but this can be augmented with
the `projects/` adding more depending on which features are enabled.
* The default build continues to build everything whereas in
`TORCH_MLIR_ENABLE_ONLY_MLIR_PYTHON_BINDINGS=1` mode, it builds a
`torch-mlir-core` wheel with the pure contents only.

`onnx_importer.py` and `importer_smoke_test.py` are almost verbatim
copies from SHARK-Turbine. I made some minor local alterations to adapt
to paths and generalize the way they interact with the outer project. I
expect I can copy these back to Turbine verbatim from here. I also
updated the license boilerplate (they have the same license but slightly
different project norms for the headers) but retained the correct
copyright.

Other updates:

* Added the ONNX importer unit test (which also can generate test data)
in lit, conditioned on the availability of the Python `onnx` package. In
a followup once I know everything is stable, I'll add another env var
that the CI can set to always enable this so we know conclusively if
tests pass.
* Moved the ONNX conversion readme to `docs/`.
* Renamed CMake option `TORCH_MLIR_ENABLE_ONLY_MLIR_PYTHON_BINDINGS` ->
`TORCH_MLIR_ENABLE_PYTORCH_EXTENSIONS` and inverted the sense. Made the
JitIR importer and LTC options `cmake_dependent_options` for robustness.
2023-12-12 19:02:51 -08:00