Commit Graph

12 Commits (5eae0adff105a83f3b65fa000197f6339303b494)

Author SHA1 Message Date
Stella Laurenzo 5eae0adff1
Breakup python pytorch deps (#2582)
This lifts the core of the jit_ir_importer and ltc out of the pt1
project, making them peers to it. As a side-effect of this layering, now
the "MLIR bits" (dialects, etc) are not commingled with the various
parts of the pt1 project, allowing pt1 and ltc to overlay cleanly onto a
more fundamental "just MLIR" Python core. Prior to this, the Python
namespace was polluted to the point that this could not happen.

That "just MLIR" Python core will be introduced in a followup, which
will create the space to upstream the FX and ONNX pure Python importers.

This primary non-NFC change to the API is:

* `torch_mlir.dialects.torch.importer.jit_ir` ->
`torch_mlir.jit_ir_importer`.

The rest is source code layering so that we can make the pt1 project
optional without losing the other features.

Progress on #2546.
2023-11-19 12:10:19 -08:00
Yuanqiang Liu facbe5d96b
[Torch Dialect] support AtenArangeStartOutOp in ReduceOpVariants like… (#2563)
… AtenBernoulli_FloatOp

It fixing case like: `%2110 = torch.aten.arange.start_out %int1,
%int1517, %int1, %2109 : !torch.int, !torch.int, !torch.int,
!torch.tensor -> !torch.tensor`.
`aten.arange.start_out` doesn't have value semantics also, means`%2110`
is an alias for %2109.
So I decompose it to `aten.arange.start` + `torch.contents.overwrite`.  
The complex decomposition logic is target to handle cases like view and
dtype cast which I add in e2e tests.
2023-11-17 00:51:55 +08:00
James Newling dad1f012f6
Add verification for torch permute op (#2551)
- adds support for an optional verifier to the generated torch op
tablegen (GeneratedTorchOps.td)
- uses the above to add a verifier for the torch permute op. 

Motivation: I hit an unclear error from linalg while developing a
decomposition pass for pixel_shuffle. The error would have been clearer
if the problem had been detected earlier in the invalid aten.permute op.

Testing: new tests added. To run added tests, from the base directory
run

```
 ./build/bin/llvm-lit  test/Dialect/Torch/invalid.mlir
 ```
2023-11-15 11:47:54 -08:00
James Newling e81282ae8f
Support for prims collapse op (lowering to linalg) (#2572)
Steps taken:
1) add generator code to torch_ods_gen.py, run update_torch_ods.sh
2) add (custom) shape and type inference generator code to
abstract_interp_lib_gen.py, run update_abstract_interp_lib.sh
3) Implement lowering to tensor.collapse_dims. Requires the `start` and
`end` values to be constant, else lowering fails
4) Update xfail_sets.py (append to LTC_XFAIL_SET) after running
/tools/e2e_test.sh --filter Collapse --verbose -c XX for all support
backends (XX).

Motivation: 
- Supporting the collapse operation will be useful for lowering of
pixel_shuffle (see Issue #2559)
2023-11-15 08:34:38 -08:00
Shehroze Khan dde66e66b0
add bool scalar type to int implicit cast (#2571)
[LTC] Add bool scalar type to int implicit cast
2023-11-14 08:56:12 -05:00
Yuanqiang Liu 3ab790c50a
[Torch Dialect] add canonicalize for aten.numel (#2562) 2023-11-11 12:16:53 +08:00
Yuanqiang Liu 60effcee89
[Dtype Function] fix aten.div.Tensor_mode's dtype function (#2555) 2023-11-09 09:46:53 +08:00
James Newling b6e551c7b8
Decomposition of aten.pixel_shuffle with static input shape (#2550)
For static tests (that is when the shape is know) for example:

 ```
 @annotate_args([None, ([3, 18, 2, 2], torch.float32, True)])
 ```
 
The e2e passes. But only if the replacement op's return type is set as
undefined (optional shape and type must be explicitly made unset),
otherwise there's a error about the function return type.
 
 For dynamic cases, for example if the above is replaced with 
 
  ```
 @annotate_args([None, ([-1, -1, -1, -1], torch.float32, True)])
 ```

There is a failure to lower to linalg from torch ("view op explicitly
labelled as illegal"). This seems to be because the support for lowering
from torch to linalg with dynamic shapes is limited.
2023-11-08 08:52:44 -05:00
JianzheXiao a42d4c18ff
[Torch Dialect]Support aten.cosine_similarity (#2364)
As title, add support for aten.cosine_similarity, support broadcast
inputA/inputB to the same shape
2023-11-08 15:28:30 +08:00
Jiawei Wu d5ee8ee73a
[Torch Dialect] emit aten.reshape_as op and add decomposition pattern. (#2553) 2023-11-05 11:38:36 +08:00
Yuanqiang Liu 0378da0abd
[Torch Dialect] support aten.isinf (#2544)
Also fix linalg lowering from `UEQ` to `OEQ`.  
I will check other comparison's lowering later.
2023-11-04 22:26:01 +08:00
Stella Laurenzo 6961f0a247
Re-organize project structure to separate PyTorch dependencies from core project. (#2542)
This is a first step towards the structure we discussed here:
https://gist.github.com/stellaraccident/931b068aaf7fa56f34069426740ebf20

There are two primary goals:

1. Separate the core project (C++ dialects and conversions) from the
hard PyTorch dependencies. We move all such things into projects/pt1 as
a starting point since they are presently entangled with PT1-era APIs.
Additional work can be done to disentangle components from that
(specifically LTC is identified as likely ultimately living in a
`projects/ltc`).
2. Create space for native PyTorch2 Dynamo-based infra to be upstreamed
without needing to co-exist with the original TorchScript path.

Very little changes in this path with respect to build layering or
options. These can be updated in a followup without commingling
directory structure changes.

This also takes steps toward a couple of other layering enhancements:

* Removes the llvm-external-projects/torch-mlir-dialects sub-project,
collapsing it into the main tree.
* Audits and fixes up the core C++ build to account for issues found
while moving things. This is just an opportunistic pass through but
roughly ~halves the number of build actions for the project from the
high 4000's to the low 2000's.

It deviates from the discussed plan by having a `projects/` tree instead
of `compat/`. As I was thinking about it, this will better accommodate
the follow-on code movement.

Once things are roughly in place and the CI passing, followups will
focus on more in-situ fixes and cleanups.
2023-11-02 19:45:55 -07:00