RFC:
https://discourse.llvm.org/t/rfc-deprecate-linalg-elemwise-unary-and-elemwise-binary/87144
Remove the two operations and fix the tests by:
* Cleaning simple operation tests of the old ops
* Changing `linalg.elemwise_{u|bi}nary` with `linalg.{exp|add}` on
transform tests
* Changing some of the tests with `linalg.elementwise` instead, to
broaden test coverage
* Surgically removing the `elemwise_*` part in the Python tests
* Update MLIR transform examples (text and tests) with
`linalg.elementwise` instead
Nothing else changed.
Buffer deallocation pipeline previously was incorrect when applied to
functions. It has since been fixed. Make sure it is exercised in the
tutorial to avoid leaking allocations.
Rename and restructure tiling-related transform ops from the structured
extension to be more homogeneous. In particular, all ops now follow a
consistent naming scheme:
- `transform.structured.tile_using_for`;
- `transform.structured.tile_using_forall`;
- `transform.structured.tile_reduction_using_for`;
- `transform.structured.tile_reduction_using_forall`.
This drops the "_op" naming artifact from `tile_to_forall_op` that
shouldn't have been included in the first place, consistently specifies
the name of the control flow op to be produced for loops (instead of
`tile_reduction_using_scf` since `scf.forall` also belongs to `scf`),
and opts for the `using` connector to avoid ambiguity.
The loops produced by tiling are now systematically placed as *trailing*
results of the transform op. While this required changing 3 out of 4 ops
(except for `tile_using_for`), this is the only choice that makes sense
when producing multiple `scf.for` ops that can be associated with a
variadic number of handles. This choice is also most consistent with
*other* transform ops from the structured extension, in particular with
fusion ops, that produce the structured op as the leading result and the
loop as the trailing result.
This chapter demonstrates how one can replicate Halide DSL
transformations using transform dialect operations transforming payload
expressed using Linalg. This was a part of the live tutorial presented
at EuroLLVM 2023.
