* 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
We prevent merging a sparse-in/dense-out with dense-in
kernels because the result is usuall not sparsifiable.
Dense kernels and sparse kernels are still fused, obviously.
Reviewed By: Peiming
Differential Revision: https://reviews.llvm.org/D153077
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.
Caveats include:
- This clang-tidy script probably has more problems.
- This only touches C++ code, so nothing that is being generated.
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 first patch was created with the following steps. The intention is
to only do automated changes at first, so I waste less time if it's
reverted, and so the first mass change is more clear as an example to
other teams that will need to follow similar steps.
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:
https://github.com/llvm/llvm-project/compare/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.
4. Some changes have been deleted for the following reasons:
- Some files had a variable also named cast
- Some files had not included a header file that defines the cast
functions
- Some files are definitions of the classes that have the casting
methods, so the code still refers to the method instead of the
function without adding a prefix or removing the method declaration
at the same time.
```
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
git restore mlir/lib/IR mlir/lib/Dialect/DLTI/DLTI.cpp\
mlir/lib/Dialect/Complex/IR/ComplexDialect.cpp\
mlir/lib/**/IR/\
mlir/lib/Dialect/SparseTensor/Transforms/SparseVectorization.cpp\
mlir/lib/Dialect/Vector/Transforms/LowerVectorMultiReduction.cpp\
mlir/test/lib/Dialect/Test/TestTypes.cpp\
mlir/test/lib/Dialect/Transform/TestTransformDialectExtension.cpp\
mlir/test/lib/Dialect/Test/TestAttributes.cpp\
mlir/unittests/TableGen/EnumsGenTest.cpp\
mlir/test/python/lib/PythonTestCAPI.cpp\
mlir/include/mlir/IR/
```
Differential Revision: https://reviews.llvm.org/D150123
The collapsing dimensions transformation is limited to only those
cases where the sequence of dimensions are contiguous in all the
ranges of the indexing maps of the operation. Add this check before
applying the transformation.
Differential Revision: https://reviews.llvm.org/D150176
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 does not work by a mere composition of `enumerate` and `zip_equal`,
because C++17 does not allow for recursive expansion of structured
bindings.
This implementation uses `zippy` to manage the iteratees and adds the
stream of indices as the first zipped range. Because we have an upfront
assertion that all input ranges are of the same length, we only need to
check if the second range has ended during iteration.
As a consequence of using `zippy`, `enumerate` will now follow the
reference and lifetime semantics of the `zip*` family of functions. The
main difference is that `enumerate` exposes each tuple of references
through a new tuple-like type `enumerate_result`, with the familiar
`.index()` and `.value()` member functions.
Because the `enumerate_result` returned on dereference is a
temporary, enumeration result can no longer be used through an
lvalue ref.
Reviewed By: dblaikie, zero9178
Differential Revision: https://reviews.llvm.org/D144503
This replacement can be used to eliminate all uses of the
producer/consumer for case where producer/consumer has other uses
outside of the producer/consumer pair. This makes the
producer/consumer dead.
Add test and minor fixup to the test harness.
Reviewed By: hanchung
Differential Revision: https://reviews.llvm.org/D142848
The rewrite driver is typically applied to a single region or all regions of the same op. There is no longer an overload to apply the rewrite driver to a list of regions.
This simplifies the rewrite driver implementation because the scope is now a single region as opposed to a list of regions.
Note: This change is not NFC because `config.maxIterations` and `config.maxNumRewrites` is now counted for each region separately. Furthermore, worklist filtering (`scope`) is now applied to each region separately.
Differential Revision: https://reviews.llvm.org/D142611
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
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.
Incrementing `counter` variable is inside the if statement. If the code does not enter there, the while loop will iterate infinitely. This revision moves the codes outside of if statement.
Reviewed By: mravishankar
Differential Revision: https://reviews.llvm.org/D139005
This patch mechanically replaces None with std::nullopt where the
compiler would warn if None were deprecated. The intent is to reduce
the amount of manual work required in migrating from Optional to
std::optional.
This is part of an effort to migrate from llvm::Optional to
std::optional:
https://discourse.llvm.org/t/deprecating-llvm-optional-x-hasvalue-getvalue-getvalueor/63716
Relax linalg elementwise fusion check to allow mixed consumers. Producer is still required to be fully tensor to avoid potential memref aliasing.
Differential Revision: https://reviews.llvm.org/D138759
This revision exports `collapseGenericOpIterationDims` to a header so it can be used outside of the pattern. We have use-case where we want to call this function directly.
Reviewed By: springerm
Differential Revision: https://reviews.llvm.org/D138697
Elementwise op fusion conserves the result of the producer in the
fused op, relying on later clean up patterns to drop unused results of
the fused op. Instead, if the producer result has no other use apart
from the consumer op, avoid making the producer result available in
the fused node. This saves some unnecessary IR manipulations.
Differential Revision: https://reviews.llvm.org/D138096
The patterns to remove dead arguments and results of `linalg.generic`
operations are not necessarily canonicalizations. Instead a new entry
point `populateEraseUnusedOperandsAndResults` is added to allow using
these patterns when needed. The transformations that rely on this
pattern for cleanup now include these patterns explicitly.
Differential Revision: https://reviews.llvm.org/D138085
During elementwise fusion the fillOp's value was directly
referred without casting which can create mismatching dtypes.
Reviewed By: mravishankar, ThomasRaoux
Differential Revision: https://reviews.llvm.org/D137447
[RFC: EnumAttr for iterator types in Linalg](https://discourse.llvm.org/t/rfc-enumattr-for-iterator-types-in-linalg/64535)
This affect touches and probably breaks most of the code that creates `linalg.generic`. A fix would be to replace calls to `getParallelIteratorTypeName/getReductionIteratorTypeName` with `mlir::utils::IteratorType::parallel/reduction` and types from `StringRef` to `mlir::utils::IteratorType`.
Due to limitations of tablegen, shared C++ definition of IteratorType enum lives in StructuredOpsUtils.td, but each dialect should have it's own EnumAttr wrapper. To avoid conflict, all enums in a dialect are put into a separate file with a separate tablegen rule.
Test dialect td files are refactored a bit.
Printed format of `linalg.generic` temporarily remains unchanged to avoid breaking code and tests in the same change.
Differential Revision: https://reviews.llvm.org/D137658
tensor.empty/linalg.init_tensor produces an uninititalized tensor that can be used as a destination operand for destination-style ops (ops that implement `DestinationStyleOpInterface`).
This change makes it possible to implement `TilingInterface` for non-destination-style ops without depending on the Linalg dialect.
RFC: https://discourse.llvm.org/t/rfc-add-tensor-from-shape-operation/65101
Differential Revision: https://reviews.llvm.org/D135129
Summary:
Most of the code that gets `iterator_types` from LinalgInterface is forced to
extract values from an `Attribute`. As a result, the usage pattern looks like
this:
```
SmallVector<StringRef> iterators = llvm::to_vector<4>(linalgOp.iterator_types().getAsValueRange<StringAttr>());
```
It also forces all operations that implement LinalgOp interface to have
`iterator_types` attribute even when the information can be easily infered from
other parameters.
In perfect future, `getIteratorTypeArray` should be the only method to get
iterator types from the interface. The default implementation can rely on
`iterator_types` attribute though.
The name `getIteratorTypeArray` was picked to be consistent with existing
`getIndexingMapsArray`.
This patch add a few sample usages. More cleanups will follow.
Differential Revision: https://reviews.llvm.org/D134729
The patch introduces the required changes to update the pass declarations and definitions to use the new autogenerated files and allow dropping the old infrastructure.
Reviewed By: mehdi_amini, rriddle
Differential Review: https://reviews.llvm.org/D132838
The patch introduces the required changes to update the pass declarations and definitions to use the new autogenerated files and allow dropping the old infrastructure.
Reviewed By: mehdi_amini, rriddle
Differential Review: https://reviews.llvm.org/D132838
Previous change (a7bfdc23ab) added
support for fusion of `linalg.generic` op with `tensor.expand_shape`
op when the former had multiple results. Fix a bug related to this
that resulted in a segfault.
Reviewed By: hanchung
Differential Revision: https://reviews.llvm.org/D132631
This drops the artificial requirement of producers having a single
result value to be able to fuse with consumers.
The current default also only fuses producer with consumer when the
producer has a single use. This is a simplifying assumption. There are
legitimate use cases where a producer can be fused with consumer and
the fused o pcould be used to replace the uses of the producer as
well. This needs to be done with care to avoid use-def violations. To
allow for downstream users to explore more fusion opportunities, the
core transformation method is exposed as a utility function.
This patch also modifies the control function to take just the fused
operand as the argument. This is enough information for the callers to
get the producer and the consumer operations being considered to
fuse. It also provides information of which producer result is used.
Differential Revision: https://reviews.llvm.org/D132301
This patch removes the `type` field from `Attribute` along with the
`Attribute::getType` accessor.
Going forward, this means that attributes in MLIR will no longer have
types as a first-class concept. This patch lays the groundwork to
incrementally remove or refactor code that relies on generic attributes
being typed. The immediate impact will be on attributes that rely on
`Attribute` containing a type, such as `IntegerAttr`,
`DenseElementsAttr`, and `ml_program::ExternAttr`, which will now need
to define a type parameter on their storage classes. This will save
memory as all other attribute kinds will no longer contain a type.
Moreover, it will not be possible to generically query the type of an
attribute directly. This patch provides an attribute interface
`TypedAttr` that implements only one method, `getType`, which can be
used to generically query the types of attributes that implement the
interface. This interface can be used to retain the concept of a "typed
attribute". The ODS-generated accessor for a `type` parameter
automatically implements this method.
Next steps will be to refactor the assembly formats of certain operations
that rely on `parseAttribute(type)` and `printAttributeWithoutType` to
remove special handling of type elision until `type` can be removed from
the dialect parsing hook entirely; and incrementally remove uses of
`TypedAttr`.
Reviewed By: lattner, rriddle, jpienaar
Differential Revision: https://reviews.llvm.org/D130092
While most of methods in ViewLikeInterface accept an `OpFoldResult` for
the offset/size/stride that may be static, represented as `Attribute`,
or dynamic, represented as `Value`, the `Range` abstraction only
accepted `Values`. This can often lead to known-constant
offset/size/strides being materialized into constant operations and
hinder further constant propagation without explicitly running the
constant folding pass. This often leads to a more complicated than
necessary addressing code being emitted. Switch `Range` to use
`OpFoldResult`. Code that uses `Range` currently keeps materializing the
constants to minimize the effect of this change on the IR. Further
commits will make use of this.
Reviewed By: nicolasvasilache, mravishankar
Differential Revision: https://reviews.llvm.org/D129633
This one required more changes than ideal due to overlapping generated name
with different return types. Changed getIndexingMaps to getIndexingMapsArray to
move it out of the way/highlight that it returns (more expensively) a
SmallVector and uses the prefixed name for the Attribute.
Differential Revision: https://reviews.llvm.org/D129919