torch-mlir

Commit Graph

Author	SHA1	Message	Date
penguin_wwy	1f544c37d0	[NFC] Remove unused header files (#3386 )	2024-05-30 14:30:36 +08:00
Rob Suderman	f97cd4893f	[torch] Improve shape inference for dynamic shapes (#3091 ) Shapes can be processed as tensors to represent the set of dimensions. As reshapes take a list of scalars this can result in a single dynamic dimension blocking the adjacent static dimensions. This pass attempts to de-couple tensor computations related to shapes and propagate values to better support lowering scalar tensor computations.	2024-04-02 16:19:57 -07:00
Rob Suderman	14b548f968	[torch] Improve shape inference for `torch-to-linalg` path for reshapes (#3055 ) Reshaping tensors depend on directly matching individual dimensions to their corresponding dim in the `torch.view` reshape dimensions. This involves decoupling dynamic dimensions from their static counterparts and support cleanup / canonicalization.	2024-03-26 12:41:40 -07:00

Author

SHA1

Message

Date

penguin_wwy

1f544c37d0

[NFC] Remove unused header files (#3386 )

2024-05-30 14:30:36 +08:00

Rob Suderman

f97cd4893f

[torch] Improve shape inference for dynamic shapes (#3091 )

Shapes can be processed as tensors to represent the set of dimensions.
As reshapes take a list of scalars this can result in a single dynamic
dimension blocking the adjacent static dimensions.

This pass attempts to de-couple tensor computations related to shapes
and propagate values to better support lowering scalar tensor
computations.

2024-04-02 16:19:57 -07:00

Rob Suderman

14b548f968

[torch] Improve shape inference for `torch-to-linalg` path for reshapes (#3055 )

Reshaping tensors depend on directly matching individual dimensions to
their corresponding dim in the `torch.view` reshape dimensions. This
involves decoupling dynamic dimensions from their static counterparts
and support cleanup / canonicalization.

2024-03-26 12:41:40 -07:00

3 Commits (2f231f394e39458df7eaa55c5af1d1929a6acd77)