Commit Graph

8 Commits (f83a90585682c25367565fe8d612dd600e27ee04)

Author SHA1 Message Date
Sean Silva 31727f81d8 torch_mlir.compile: Allow ignoring traced shapes
In some cases, users know that a traced graph is valid for a wider set
of shapes than they originally traced it with. Provide an option for
users to ignore the shapes in the traced graph when they know it is
legal.

Fixes #997
2022-08-04 10:18:34 -07:00
Ziheng Jiang c61c99e887
[MHLO] Init MHLO integration. (#1083)
Co-authored-by: Bairen Yi <yibairen.byron@bytedance.com>
Co-authored-by: Jiawei Wu <xremold@gmail.com>
Co-authored-by: Tianyou Guo <tianyou.gty@alibaba-inc.com>
Co-authored-by: Xu Yan <yancey.yx@alibaba-inc.com>
Co-authored-by: Ziheng Jiang <ziheng.jiang@bytedance.com>
2022-07-20 16:18:16 -07:00
Sean Silva 93f1c3138b torch_mlir.compile: Allow OutputType as a string.
A lot of code was super verbose with `torch_mlir.OutputType.XYZ`. Now,
you can simply do `"xyz"`. I updated a few examples.
2022-07-08 17:37:27 -07:00
Sean Silva ccc858f531 torch_mlir.compile: Fix API footgun
use_tracing=True was behaving unexpectedly because the handling of
single arguments was happening after the torch.jit.trace call.

This also fixes the check to specifically test for a torch.Tensor or
TensorPlaceholder so that both lists and tuples would be correctly
handled.
2022-06-05 18:10:07 -07:00
Sean Silva 2af53ce434 torch_mlir.compile: Add OutputType.RAW
This can help with development and reporting bugs.
2022-05-19 03:41:43 -07:00
Sean Silva ef9e4c95f2 torch_mlir.compile: add support for dynamic sizes.
We do this by inroducing a TensorPlaceholder class, which can be used to
specify dynamic sizes. Internally, we canonicalize all example inputs
to TensorPlaceholder's.

This commit also adds some basic testing, which was missing before.
2022-05-17 07:02:32 -07:00
Sean Silva ab5ad7af09 Add tracing suport to `torch_mlir.compile`.
This also has a fix for the adjustment of types of TupleConstruct
inputs, which I found when using this new functionality on a model.

Some scenarios in tracing create situations where the output of
TupleConstruct has a more refined type than the inputs.

This introduces a helper `adjustStaticInformationForValues` which
subsumes the `derefineValues` helper and the tensor static information
adjustment we were doing.
2022-05-03 09:08:40 -07:00
Sean Silva 075464fa74 Add a new `torch_mlir.compile` method.
This makes it much easier to convert models and hides all the
ClassAnnotator complexity.

This also adds a new example `torchscript_resnet18_all_output_types.py`
which shows the ResNet18 IR for all output types.

Also,

- This moves `run_pipeline_with_repro_report` to
  `torch_mlir.compiler_utils`.
2022-04-20 10:06:01 -07:00