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
We previously only support packing two array (values and coordinates) into COO tensors.
This patch allows packing inputs into arbitrary sparse tensor format.
It also deletes the "implicit" data canonicalization performed inside sparse compiler,
but instead requires users to canonicalize the data before passing it to the sparse compiler.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D150916
This commit is part of the migration of towards the new STEA syntax/design. In particular, this commit includes the following changes:
* Renaming compiler-internal functions/methods:
* `SparseTensorEncodingAttr::{getDimLevelType => getLvlTypes}`
* `Merger::{getDimLevelType => getLvlType}` (for consistency)
* `sparse_tensor::{getDimLevelType => buildLevelType}` (to help reduce confusion vs actual getter methods)
* Renaming external facets to match:
* the STEA parser and printer
* the C and Python bindings
* PyTACO
However, the actual renaming of the `DimLevelType` itself (along with all the "dlt" names) will be handled in a separate commit.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D150330
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 name "coords" should be used for the complete tuple of Dimension-/Level-many "crd" values associated with a single element. Whereas the name "coordinates" should only be used for collections of "crd" values which span several elements (e.g., the tensor's coordinates buffer for a single level).
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D147291
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
The old "pointer/index" names often cause confusion since these names clash with names of unrelated things in MLIR; so this change rectifies this by changing everything to use "position/coordinate" terminology instead.
In addition to the basic terminology, there have also been various conventions for making certain distinctions like: (1) the overall storage for coordinates in the sparse-tensor, vs the particular collection of coordinates of a given element; and (2) particular coordinates given as a `Value` or `TypedValue<MemRefType>`, vs particular coordinates given as `ValueRange` or similar. I have striven to maintain these distinctions
as follows:
* "p/c" are used for individual position/coordinate values, when there is no risk of confusion. (Just like we use "d/l" to abbreviate "dim/lvl".)
* "pos/crd" are used for individual position/coordinate values, when a longer name is helpful to avoid ambiguity or to form compound names (e.g., "parentPos"). (Just like we use "dim/lvl" when we need a longer form of "d/l".)
I have also used these forms for a handful of compound names where the old name had been using a three-letter form previously, even though a longer form would be more appropriate. I've avoided renaming these to use a longer form purely for expediency sake, since changing them would require a cascade of other renamings. They should be updated to follow the new naming scheme, but that can be done in future patches.
* "coords" is used for the complete collection of crd values associated with a single element. In the runtime library this includes both `std::vector` and raw pointer representations. In the compiler, this is used specifically for buffer variables with C++ type `Value`, `TypedValue<MemRefType>`, etc.
The bare form "coords" is discouraged, since it fails to make the dim/lvl distinction; so the compound names "dimCoords/lvlCoords" should be used instead. (Though there may exist a rare few cases where is is appropriate to be intentionally ambiguous about what coordinate-space the coords live in; in which case the bare "coords" is appropriate.)
There is seldom the need for the pos variant of this notion. In most circumstances we use the term "cursor", since the same buffer is reused for a 'moving' pos-collection.
* "dcvs/lcvs" is used in the compiler as the `ValueRange` analogue of "dimCoords/lvlCoords". (The "vs" stands for "`Value`s".) I haven't found the need for it, but "pvs" would be the obvious name for a pos-`ValueRange`.
The old "ind"-vs-"ivs" naming scheme does not seem to have been sustained in more recent code, which instead prefers other mnemonics (e.g., adding "Buf" to the end of the names for `TypeValue<MemRefType>`). I have cleaned up a lot of these to follow the "coords"-vs-"cvs" naming scheme, though haven't done an exhaustive cleanup.
* "positions/coordinates" are used for larger collections of pos/crd values; in particular, these are used when referring to the complete sparse-tensor storage components.
I also prefer to use these unabbreviated names in the documentation, unless there is some specific reason why using the abbreviated forms helps resolve ambiguity.
In addition to making this terminology change, this change also does some cleanup along the way:
* correcting the dim/lvl terminology in certain places.
* adding `const` when it requires no other code changes.
* miscellaneous cleanup that was entailed in order to make the proper distinctions. Most of these are in CodegenUtils.{h,cpp}
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D144773
Rewrite a NewOp into a NewOp of a sorted COO tensor and a ConvertOp for
converting the sorted COO tensor to the destination tensor type.
Codegen a NewOp of a sorted COO tensor to use the new bulk reader API and sort
the elements only when the input is not sorted.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D144504
This change adds a new `SparseTensorType` class for making the "dim" vs "lvl" distinction more overt, and for abstracting over the differences between sparse-tensors and dense-tensors. In addition, this change also adds new type aliases `Dimension`, `Level`, and `FieldIndex` to make code more self-documenting.
Although the diff is very large, the majority of the changes are mechanical in nature (e.g., changing types to use the new aliases, updating variable names to match, etc). Along the way I also made many variables `const` when they could be; the majority of which required only adding the keyword. A few places had conditional definitions of these variables, requiring actual code changes; however, that was only done when the overall change was extremely local and easy to extract. All these changes are included in the current patch only because it would be too onerous to split them off into a separate patch.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D143800
UnpackOp Converter used to create reallocOp unconditionally, but it might cause issue when the requested memory size is smaller than the actually storage.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D144065
This adds the hint to a number of tensor allocations in codegens,
shaving off quite some time from e.g. reading in sparse matrices
due to zero-reallocation scheme. Note that we can probably provide
hints on all allocations, and refine the heuristics that use them
for general tensors.
Reviewed By: bixia
Differential Revision: https://reviews.llvm.org/D143309
Even though we introduced the size_hint, we never used it.
This is a very first step, using the hint during the codegen path.
Note that we can refine the heuristics. Also, we need to start
adding the hint on all allocation generated for reading tensors,
converting tensors, etc.
Reviewed By: Peiming, bixia
Differential Revision: https://reviews.llvm.org/D143292
Currently, all the non-stable sorting algorithms are implemented via the
straightforward quick sort. This will be fixed in the following PR.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D142678
Use SparseTensorDescriptor whenever not calling setters, to avoid needing to create a temporal buffer for simple query purposes.
Reviewed By: bixia, wrengr
Differential Revision: https://reviews.llvm.org/D141953
Previously, we rely on the InsertOp to gradually increase the size of the
storage for all sparse tensors. We now allocate the full size values buffer
for annotated all dense tensors when we first allocate the tensor. This avoids
the cost of gradually increasing the buffer and allows accessing the values
buffer as if it were a dense tensor.
Reviewed By: Peiming
Differential Revision: https://reviews.llvm.org/D141516
Previously, we generate AOS subviews for indices buffers when constructing an
immutable sparse tensor descriptor. We now only generate such subviews when
getIdxMemRefOrView is requested.
Reviewed By: Peiming
Differential Revision: https://reviews.llvm.org/D141325
Use an array of structures to represent the indices for the tailing COO region
of a sparse tensor.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D140870
