Commit Graph

10 Commits (f6b6069a343ee640a91e9cabb884a01e052bc0c5)

Author SHA1 Message Date
Ramiro Leal-Cavazos a710237437
[custom op] Generalize shape library logic to work with dtypes (#1594)
* [custom op] Generalize shape library logic to work with dtypes

This commit generalizes the shape library logic, so that dtype rules
for ops can also be expressed using the same mechanism. In other
words, each op can now have a shape function and a dtype function
specified in Python that is imported during lowering to calculate the
shapes and dtypes throught a program. For more information about how
to specify a dtype function, see the updated
`docs/adding_a_shape_and_dtype_function.md`.

For those not familiar with how the shape library works, the file
`docs/calculations_lib.md` provides an overview.
2022-12-13 08:25:41 -08:00
Ramiro Leal-Cavazos dd35488da5
build: update llvm tag to 798fa4b4 (#1684)
- Support for non-prefixed accessors has been removed. See:
  https://reviews.llvm.org/D136727
- Rename `operands` to `methodOperands` in `prim.CallMethod` since the
  name `operands` overlaps with a builtin method name. See:
  https://reviews.llvm.org/D136727
- Add passes in refbackend to lower memref.subview. See:
  https://reviews.llvm.org/D136377
- Replace `CopyToValueTensorOps` first in `RewriteViewLikeSubgraph` in
  maximize-value-semantics.

  The current implementation of the `RewriteViewLikeSubgraph` pass in
  maximize-value-semantics creates temporarily invalid IR. In
  particular, given a forward slice starting from a
  `CopyToNonValueTensorOp` and ending in `CopyToValueTensorOp`s, the
  pass first replaces all uses of the `CopyToNonValueTensorOp` with
  its operand, which results in all the `CopyToValueTensorOp` users
  having their operand have type `!torch.vtensor`, which is invalid.

  The correct way to do things is to first replace all the
  `CopyToValueTensorOp`s with their operand, and then replace all uses
  of the `CopyToNonValueTensorOp` with its operand.

  This only started failing now because the generated accessor
  `getOperand` for the `CopyToValueTensorOp` now returns a
  `TypedValue<NonValueTensorType>`, which has an assert checking that
  the value returned is of the expected type.
2022-12-07 12:20:41 -08:00
Quinn Dawkins 11a8901078
[MLIR][TORCH] Add support for multiple indexing tensors for aten.index.Tensor (#1097)
- Includes a canonicalizer for `aten.add.t`needed for successfully lowering the shape function
 - Only offers support for statically sized index tensors when there is more than one
 - Dynamic shape support remains for single indexing tensors
2022-07-28 19:00:02 -04:00
Ashay Rane 9017be9e9e
torch: copy uses to prevent iterator invalidation (#1033)
Prior to this patch, the code in the `torch-simplify-shape-calculations`
pass iterated on the uses of an op's result while also modifying the
value.  This caused the iterator to get invalidated, thus terminating
the loop early and producing incorrect IR.  This patch makes use of
`llvm::make_early_inc_range()` to ensure that the iterator is not
invalidated while executing the loop body.
2022-07-11 18:47:04 -07:00
Ramiro Leal-Cavazos 6a72ab4502
Add basic support for list of optional tensors in reduce-op-variants (#971)
This commit adds support for lists of type `list<optional<tensor>>`
where each element in the list is either a `!torch.tensor` or a
`!torch.none`.
2022-07-08 11:12:15 -07:00
Ashay Rane 9208bf0eb6
llvm: bump tag to e1318078 (#781)
The updated LLVM code includes a patch to create bfloat16 array
attributes, thus enabling a different patch to torch-mlir to flesh out
support for the bfloat16 type.
2022-04-26 12:27:51 -07:00
Liam Fitzpatrick f2269ced80
Improve list index normalization SimplifyShapeCalculations. (#710)
The reified code to compute the shape of torch.aten.constant_pad_nd
uses negative indices when setting list elements. This was not
converted to a positive offset in one place in SimplifyShapeCalculations
which prevented computation of the static shape.
2022-03-29 22:21:47 +02:00
Sean Silva 776426ea4e [SimplifyShapeCalculations] Fix AbstractlyInterpretListOpsWithinABlock
The logic in the rewriting phase had a bug in case of a read-only op
coming before mutation ops. The logic would use the op itself as the
"latest literal", but that is not correct, because later on we replace
the op itself with the *final* "latest literal", assuming that all uses
of the op have been rewritten -- that was working in general, except for
any read-only ops at the beginning.

Big thanks to @ljfitz for the tiny reproducer!

Fixes #704
2022-03-28 13:18:35 -07:00
Vigilans 63fb1e5aad Bump LLVM at 8361c5da30588d3d4a48eae648f53be1feb5cfad 2022-03-18 13:16:14 -04:00
Sean Silva a5fe0cf063 Introduce new shape library design.
See the documentation in `docs/shape_lib.md` and
`docs/adding_a_shape_function.md` for an overview of the system.

This completely overhauls how we represent shape functions. In
particular, RefineTypes does not infer shapes anymore (only dtypes).
Shape functions are now written in (TorchScript'able) Python.

Recommended review order:

1. Read `docs/shape_lib.md` and `docs/adding_a_shape_function.md`.
1. Code and tests for ReifyShapeCalculations, DropShapeCalculations.
1. Code and tests for SimplifyShapeCalculations.
1. shape_lib_gen.py
1. Code and tests for new RefineTypes pass.
1. Random folders/canonicalizers in TorchOps.cpp and associated test in
   `canonicalize.mlir`.
1. New ReadOnly trait inferred from the registry.
1. Any miscellaneous remaining stuff.

Example `-print-ir-after-all` for ElementwiseUnaryModule:
[IR lowering dump](https://gist.github.com/silvasean/e4dc8cbc8d00aac7819602e3cbd8e212).

Example `-print-ir-after-all` for ElementwiseBinaryModule:
[IR lowering dump](https://gist.github.com/silvasean/daf6860ecced732af3568af6b1899113).
2022-03-15 12:41:58 -07:00