The PR https://github.com/llvm/llvm-project/pull/162167 removed a
pattern to linearize vector.splat, without adding the equivalent pattern
for vector.broadcast. This PR adds such a pattern, hopefully brining
vector.broadcast up to full parity with vector.splat that has now been
removed.
---------
Signed-off-by: James Newling <james.newling@gmail.com>
This patch updates the following ops to use `source` (instead of
`vector`) as the name for their source argument:
* `vector.extract`
* `vector.scalable.extract`
* `vector.extract_strided_slice`
This change ensures naming consistency with the "builders" for these Ops
that already use the name `source` rather than `vector`. It also
addresses part of:
* https://github.com/llvm/llvm-project/issues/131602
Specifically, it ensures that we use `source` and `dest` for read and
write operations, respectively (as opposed to `vector` and `dest`).
This PR is a follow-up to #151175 that supported lowering
multi-dimensional `vector.from_elements` op to LLVM by introducing a
unrolling pattern.
## Changes
### Add `vector.shape_cast` based flattening pattern for
`vector.from_elements`
This change introduces a new linearization pattern that uses
`vector.shape_cast` to flatten multi-dimensional `vector.from_elements`
operations. This provides an alternative approach to the unrolling-based
method introduced in #151175.
**Example:**
```mlir
// Before
%v = vector.from_elements %e0, %e1, %e2, %e3 : vector<2x2xf32>
// After
%flat = vector.from_elements %e0, %e1, %e2, %e3 : vector<4xf32>
%result = vector.shape_cast %flat : vector<4xf32> to vector<2x2xf32>
```
---------
Co-authored-by: Yang Bai <yangb@nvidia.com>
Co-authored-by: James Newling <james.newling@gmail.com>
The revision adds isOneInteger helper, and simplifies the existing code
with the two methods. It removes some lambda, which makes code cleaner.
For downstream users, you can update the code with the below script.
```bash
sed -i "s/isZeroIndex/isZeroInteger/g" **/*.h
sed -i "s/isZeroIndex/isZeroInteger/g" **/*.cpp
```
---------
Signed-off-by: hanhanW <hanhan0912@gmail.com>
This PR adds some documentation to address comments in
https://github.com/llvm/llvm-project/pull/136581
This PR adds a test for linearization across scf.for. This new test
might be considered redundant by more experienced MLIRers, but might
help newer users understand how to linearize scf/cf/func operations
easily
The documentation added in this PR also tightens our definition of
linearization, to now exclude unrolling (which creates multiple ops from
1 op). We hadn't really specified what linearization meant before.
Extends the set of vector operations that we can linearize to include
vector.insert_strided_slice. The new pattern reuses the ideas from
vector.extract_strided_slice linearization.
In https://github.com/llvm/llvm-project/pull/136581 the bitwidth logic
was supposed to be completely removed from the linearization patterns.
But it was left in a few places. This PR removes the remainders (they
were default valued constructor arguments that were unused).
[NFC]
Vector linearization is a collection of rewrite patterns that reduce the
rank of vector operands and results.
In https://github.com/llvm/llvm-project/pull/83314 an option to ignore
(make 'legal') operations with large inner-most dimensions was added.
This current PR is a step towards making that option live outside of
upstream MLIR. The motivation is to remove non-core functionality (I
would like to use this pass, but would prefer not to deal with
'targetVectorBitWidth` at all).
As a follow-up to this PR, I propose that user(s) of the
`targetVectorBitWidth` move the relevant code (now in
mlir/test/lib/Dialect/Vector/TestVectorTransforms.cpp) to their code
bases, and then eventually remove it from upstream. In addition the tests need to
split out (I've intentionally not modified the lit tests here, to make
it easier to confirm that this is a NFC). I'm happy to help make it
easier to do this final step!
The approach I've used is to move the logic pertaining to
`targetVectorBitWidth` out the patterns, and into the conversion target,
which the end user can control outside of core MLIR.
This change standardises the naming convention for the argument
representing the value to store in various vector operations.
Specifically, it ensures that all vector ops storing a value—whether
into memory, a tensor, or another vector — use `valueToStore` for the
corresponding argument name.
Updated operations:
* `vector.transfer_write`, `vector.insert`, `vector.scalable_insert`,
`vector.insert_strided_slice`.
For reference, here are operations that currently use `valueToStore`:
* `vector.store` `vector.scatter`, `vector.compressstore`,
`vector.maskedstore`.
This change is non-functional (NFC) and does not affect the
functionality of these operations.
Implements #131602
This commit updates the internal `ConversionValueMapping` data structure
in the dialect conversion driver to support 1:N replacements. This is
the last major commit for adding 1:N support to the dialect conversion
driver.
Since #116470, the infrastructure already supports 1:N replacements. But
the `ConversionValueMapping` still stored 1:1 value mappings. To that
end, the driver inserted temporary argument materializations (converting
N SSA values into 1 value). This is no longer the case. Argument
materializations are now entirely gone. (They will be deleted from the
type converter after some time, when we delete the old 1:N dialect
conversion driver.)
Note for LLVM integration: Replace all occurrences of
`addArgumentMaterialization` (except for 1:N dialect conversion passes)
with `addSourceMaterialization`.
---------
Co-authored-by: Markus Böck <markus.boeck02@gmail.com>
This commit marks the type converter in `populate...` functions as
`const`. This is useful for debugging.
Patterns already take a `const` type converter. However, some
`populate...` functions do not only add new patterns, but also add
additional type conversion rules. That makes it difficult to find the
place where a type conversion was added in the code base. With this
change, all `populate...` functions that only populate pattern now have
a `const` type converter. Programmers can then conclude from the
function signature that these functions do not register any new type
conversion rules.
Also some minor cleanups around the 1:N dialect conversion
infrastructure, which did not always pass the type converter as a
`const` object internally.
Building on top of
[#88204](https://github.com/llvm/llvm-project/pull/88204), this PR adds
support for converting `vector.insert` into an equivalent
`vector.shuffle` operation that operates on linearized (1-D) vectors.
…ted. (#89998)" (#90250)
This partially reverts commit 7aedd7dc754c74a49fe84ed2640e269c25414087.
This change removes calls to the deprecated member functions. It does
not mark the functions deprecated yet and does not disable the
deprecation warning in TypeSwitch. This seems to cause problems with
MSVC.
This PR adds support for converting `vector.extract_strided_slice` and
`vector.extract` operations to equivalent `vector.shuffle` operations
that operates on linearized (1-D) vectors. `vector.shuffle` operations
operating on n-D (n > 1) are also converted to equivalent shuffle
operations working on linearized vectors.
Adds support for scalable vectors to patterns defined in
VectorLineralize.cpp.
Linearization is disable in 2 notable cases:
* vectors with more than 1 scalable dimension (we cannot represent
vscale^2),
* vectors initialised with arith.constant that's not a vector splat
(such arith.constant Ops cannot be flattened).
Common backends (LLVM, SPIR-V) only supports 1D vectors, LLVM conversion
handles ND vectors (N >= 2) as `array<array<... vector>>` and SPIR-V
conversion doesn't handle them at all at the moment. Sometimes it's
preferable to treat multidim vectors as linearized 1D. Add pass to do
this. Only constants and simple elementwise ops are supported for now.
@krzysz00 I've extracted yours result type conversion code from
LegalizeToF32 and moved it to common place.
Also, add ConversionPattern class operating on traits.
