This patch addresses a crash that occurs when negative dynamic sizes are
provided in tensor.emptyOp by adding a check to ensure that dynamic
sizes are non-negative.
Fixes#64064
This enables canonicalization to fold away unnecessary tensor.dim ops
which in turn enables folding away of other operations, as can be seen
in conv_tensors_dynamic where affine.min operations were folded away.
* Move `foldDynamicIndexList` to `DialectUtils` and simplify function.
* Move `OpWithOffsetSizesAndStridesConstantArgumentFolder` to `ViewLikeInterface` and add documentation.
Differential Revision: https://reviews.llvm.org/D156581
In https://reviews.llvm.org/D151611, a check was added to the tensor verifier to
emit an error on negative tensor dimensions. This check allowed for dynamic
dimensions, hence negative dimensions were still able to get through the verifier.
This is a problem in situations such as #60558, where the dynamic dimension is
converted to a static (and possibly negative) dimension by another pass in the
compiler. This patch fixes that by doing another check during the
`StaticTensorGenerate` conversion, and return a failure if the dimension is
negative.
As a side-note, I have to admit that I do not know why returning a failure in
`StaticTensorGenerate` gives a nice "tensor dimensions must be non-negative"
error. I suspect that the verifier runs again when `return failure()` is called,
but I am not sure.
Fixes#60558.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D155728
* Remove duplicate functions. `tensor::getMixedSize` and `tensor::getMixedSizes` should be used.
* Use `tensor::getMixedSize` instead of `createOrFold<tensor::DimOp>`. This is more efficient. `createOrFold` will create an op an immediately try to fold it. In case of a static dimension size, an attribute can be used directly.
Differential Revision: https://reviews.llvm.org/D153332
The MLIR classes Type/Attribute/Operation/Op/Value support
cast/dyn_cast/isa/dyn_cast_or_null functionality through llvm's doCast
functionality in addition to defining methods with the same name.
This change begins the migration of uses of the method to the
corresponding function call as has been decided as more consistent.
Note that there still exist classes that only define methods directly,
such as AffineExpr, and this does not include work currently to support
a functional cast/isa call.
Context:
- https://mlir.llvm.org/deprecation/ at "Use the free function variants
for dyn_cast/cast/isa/…"
- Original discussion at https://discourse.llvm.org/t/preferred-casting-style-going-forward/68443
Implementation:
This patch updates all remaining uses of the deprecated functionality in
mlir/. This was done with clang-tidy as described below and further
modifications to GPUBase.td and OpenMPOpsInterfaces.td.
Steps are described per line, as comments are removed by git:
0. Retrieve the change from the following to build clang-tidy with an
additional check:
main...tpopp:llvm-project:tidy-cast-check
1. Build clang-tidy
2. Run clang-tidy over your entire codebase while disabling all checks
and enabling the one relevant one. Run on all header files also.
3. Delete .inc files that were also modified, so the next build rebuilds
them to a pure state.
```
ninja -C $BUILD_DIR clang-tidy
run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\
-header-filter=mlir/ mlir/* -fix
rm -rf $BUILD_DIR/tools/mlir/**/*.inc
```
Differential Revision: https://reviews.llvm.org/D151542
The MLIR classes Type/Attribute/Operation/Op/Value support
cast/dyn_cast/isa/dyn_cast_or_null functionality through llvm's doCast
functionality in addition to defining methods with the same name.
This change begins the migration of uses of the method to the
corresponding function call as has been decided as more consistent.
Note that there still exist classes that only define methods directly,
such as AffineExpr, and this does not include work currently to support
a functional cast/isa call.
Context:
* https://mlir.llvm.org/deprecation/ at "Use the free function variants for dyn_cast/cast/isa/…"
* Original discussion at https://discourse.llvm.org/t/preferred-casting-style-going-forward/68443
Implementation:
This follows a previous patch that updated calls
`op.cast<T>()-> cast<T>(op)`. However some cases could not handle an
unprefixed `cast` call due to occurrences of variables named cast, or
occurring inside of class definitions which would resolve to the method.
All C++ files that did not work automatically with `cast<T>()` are
updated here to `llvm::cast` and similar with the intention that they
can be easily updated after the methods are removed through a
find-replace.
See https://github.com/llvm/llvm-project/compare/main...tpopp:llvm-project:tidy-cast-check
for the clang-tidy check that is used and then update printed
occurrences of the function to include `llvm::` before.
One can then run the following:
```
ninja -C $BUILD_DIR clang-tidy
run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\
-export-fixes /tmp/cast/casts.yaml mlir/*\
-header-filter=mlir/ -fix
rm -rf $BUILD_DIR/tools/mlir/**/*.inc
```
Differential Revision: https://reviews.llvm.org/D150348
Add tensor.bitcast operator to bitcast between two tensors of compatible shape
and same bit width. This can be use to reinterpret an unsigned integer as a
signed integer or vice versa.
Reviewed By: rsuderman
Differential Revision: https://reviews.llvm.org/D149608
Removed builder is the same as default builder, with the added benefit that python bindings will be generated for the default builder.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D149508
This adds `arith::ConstantOp::materialize`, which builds a constant from
an attribute and type only if it would result in a valid op. This is
useful for dialect `materializeConstant` hooks, and allows for removing
the previous `Attribute, Type` builder which was only used during
materialization.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D148491
This patch recognizes when tensor.pack/unpack operations are simple
tensor.pad/unpad (a.k.a. tensor.extract_slice) and lowers them in a simpler
sequence of instruction.
For pack, instead of doing:
```
pad
expand_shape
transpose
```
we do
```
pad
insert_slice
```
For unpack, instead of doing:
```
transpose
collapse_shape
extract_slice
```
we do
```
extract_slice
```
Note: returning nullptr for the transform dialect is fine. The related
handles are just ignored by the following transformation.
Differential Revision: https://reviews.llvm.org/D148159
Allows pack propagation through non-elementwise generics as long as all
tiled dimensions have parallel iterator types and are only indexed with
affine dim expressions by any of the operands.
This enables unpack propagation cases where the result type is different
from the current unpack destination tensor and thus motivates a similar
helper as the for pack for creating a destination tensor based on
pack information.
Outer dim permutations are allowed to permute reduction dims, however
remains unsupported for non-affine dim indexing map results.
Additionally ops with gather semantics now explicitly prohibit propagation.
Pack/unpack propagation through reductions may not always be beneficial
so user control over propagation decisions is made available through
a control function similar to the one for fusion.
Differential Revision: https://reviews.llvm.org/D147508
`RankedTensorOf` and `TensorRankOf` (in Tablegen files) now generate code that uses `RankedTensorType` instead of `TensorType`. This gives us more accurate type information (e.g., when calling `op.getType()`).
Also use restrict tensor.expand_shape/tensor.collapse_shape/tensor.pad to ranked tensors. Only cast ops should deal with unranked tensors.
Also improves a few places in the code base (e.g., Toy tutorial) where a ranked tensor is assumed (e.g., because `getRank` is called) but a `TensorType` is currently used: cast to `RankedTensorType` directly, so that the assertion is triggered directly at the cast.
Differential Revision: https://reviews.llvm.org/D147149
When low/high padding is folded in padOp, there should be inserted a
tensor.cast back to the original result type. Right now, there is a no-op
tensor.cast from new type to new type...
Differential Revision: https://reviews.llvm.org/D147210
This helper function is used for both ExtractSliceOp and InsertSliceOp. Also fixes a bug in the implementation of `InsertSliceOp::getDroppedDims`.
Differential Revision: https://reviews.llvm.org/D147048
These patterns follow FoldMemRefAliasOps which is further refactored for reuse.
In the process, fix FoldMemRefAliasOps handling of strides for vector.transfer ops which was previously incorrect.
These opt-in patterns generalize the existing canonicalizations on vector.transfer ops.
In the future the blanket canonicalizations will be retired.
They are kept for now to minimize porting disruptions.
Differential Revision: https://reviews.llvm.org/D146624
Replace references to enumerate results with either result_pairs
(reference wrapper type) or structured bindings. I did not use
structured bindings everywhere as it wasn't clear to me it would
improve readability.
This is in preparation to the switch to zip semantics which won't
support non-const lvalue reference to elements:
https://reviews.llvm.org/D144503.
I chose to use values instead of const lvalue-refs because MLIR is
biased towards avoiding `const` local variables. This won't degrade
performance because currently `result_pair` is cheap to copy (size_t
+ iterator), and in the future, the enumerator iterator dereference
will return temporaries anyway.
Reviewed By: dblaikie
Differential Revision: https://reviews.llvm.org/D146006
This change adds a new helper function `mlir::reifyResultShapes` that calls the corresponding interface method and also checks the result produced by the implementation when running in debug mode. Bugs due to incorrect interface implementations can be difficult to debug.
This helper function also reduces the amount of code needed at call sites: the cast to `ReifyRankedShapedTypeOpInterface` is done in the helper function.
Differential Revision: https://reviews.llvm.org/D145777
`reifyResultShapes` should return an IntegerAttr if and only if the corresponding dimension is static.
Differential Revision: https://reviews.llvm.org/D145702
It also simplifies the implementation of the method. The map is not needed in the check.
Reviewed By: chelini
Differential Revision: https://reviews.llvm.org/D145522
`reifyResultShapes` now returns `OpFoldResult`s instead of `Value`s. This is often more efficient because many transformations immediately attempt to extract a constant from the reified values.
Differential Revision: https://reviews.llvm.org/D145250
This revision cleans up the implementation of hoist padding and extends it to also work in the
absence of packing loops.
This allows better composition when hoisting the padded result of a DPS operation.
A systematic usage of RewriterBase is applied to the implementation.
Depends on: D144856
Differential Revision: https://reviews.llvm.org/D144855
Although specifying an index that is out of bounds for both `memref.dim`
and `tensor.dim` produces an undefined behavior, this is still valid IR.
In particular, we could expose an out of bound index because of some
optimizations, for instance as demonstrated with
https://github.com/llvm/llvm-project/issues/60295, and this shouldn't
cause the compiler to abort.
This patch removes the overzealous verifier checks and properly handles
out of bound indices (as in it doesn't crash the compiler, but still
produces UB).
This fixes https://github.com/llvm/llvm-project/issues/60295.
Note: That `shape.dim` has a similar problem but we're not supposed to
produce UB in this case. Instead we're supposed to propagate an error in
the resulting value and I don't know how to do that at the moment. Hence I
left this part out of the patch.
Differential Revision: https://reviews.llvm.org/D143999
This commit adds a canonicalization pattern for tensor.pad which changes the output type to static at each dimension where the input shape is static and the high and low operands are constants. This corrects an issue arising in Torch-MLIR where pad ops would sometimes introduce dynamic shapes unnecessarily.
Reviewed By: raikonenfnu
Differential Revision: https://reviews.llvm.org/D143135
This revision introduces `transform.structured.lower_pack` which allows
rewriting a `tensor.pack` to `tensor.pad` + `tensor.expand_shape` + `linalg.transpose`.
The implementation is currently limited to static pack ops that do not have outer_dims permutations.
Differential Revision: https://reviews.llvm.org/D142881
This transform is complementary to the `structured.pack` op which
allows packing a whole op but does not allow transposes on the individual
operands.
`structured.pack_transpose` allows transposing single operands connected to
pack or unpack ops after the fact.
This makes the system overall more composable than e.g. a giant transform
op with all permutation specified at once.
Differential Revision: https://reviews.llvm.org/D142053
The patch adds operations to `BlockAndValueMapping` and renames it to `IRMapping`. When operations are cloned, old operations are mapped to the cloned operations. This allows mapping from an operation to a cloned operation. Example:
```
Operation *opWithRegion = ...
Operation *opInsideRegion = &opWithRegion->front().front();
IRMapping map
Operation *newOpWithRegion = opWithRegion->clone(map);
Operation *newOpInsideRegion = map.lookupOrNull(opInsideRegion);
```
Migration instructions:
All includes to `mlir/IR/BlockAndValueMapping.h` should be replaced with `mlir/IR/IRMapping.h`. All uses of `BlockAndValueMapping` need to be renamed to `IRMapping`.
Reviewed By: rriddle, mehdi_amini
Differential Revision: https://reviews.llvm.org/D139665
- Fold an unpack(pack(x)) to x.
- Rewrite a `tensor.pack` to an `tensor.expand_shape` if only one
dimension is packed.
Reviewed By: tyb0807, hanchung, mravishankar
Differential Revision: https://reviews.llvm.org/D141123
Collapsing / expanding a splatted value can be replaced with a single `tensor.splat` operation. Replace
these cases with a simple `tensor.splat` operation.
Reviewed By: rsuderman
Differential Revision: https://reviews.llvm.org/D140552
std::optional::value() has undesired exception checking semantics and is
unavailable in older Xcode (see _LIBCPP_AVAILABILITY_BAD_OPTIONAL_ACCESS). The
call sites block std::optional migration.
This is part of an effort to migrate from llvm::Optional to
std::optional. This patch changes the way mlir-tblgen generates .inc
files, and modifies tests and documentation appropriately. It is a "no
compromises" patch, and doesn't leave the user with an unpleasant mix of
llvm::Optional and std::optional.
A non-trivial change has been made to ControlFlowInterfaces to split one
constructor into two, relating to a build failure on Windows.
See also: https://discourse.llvm.org/t/deprecating-llvm-optional-x-hasvalue-getvalue-getvalueor/63716
Signed-off-by: Ramkumar Ramachandra <r@artagnon.com>
Differential Revision: https://reviews.llvm.org/D138934
