Summary:
* add missing comma.
* remove "having to register them here" phrasing, since register it
is what we're doing, which made the comment a bit confusing.
* remove duplicate code.
* clarify link to chapter 3, since "folder" doesn't appear in that
chapter.
Differential Revision: https://reviews.llvm.org/D75263
Summary:
* Use bold font (not monospace) for legal/illegal.
* Say a few words about operation<->dialect precedence.
* Omit duplicate code samples.
* Indent items in bullet-point list.
Differential Revision: https://reviews.llvm.org/D75262
Summary:
* Let's use "override" when we're just doing standard baseclassing.
("Specialization" makes it sound like template specialization, which
this is not.)
* CallInterfaces.td has an include guard, so #ifdef not needed anymore.
* Omit duplicate code in code samples.
* Clarify which algorithm we're talking about.
* Mention that the ShapeInference code is code a snippet that belongs to
algorithm discussed in the paragraph above it.
* Add missing definition for createShapeInferencePass.
Differential Revision: https://reviews.llvm.org/D75260
Summary:
This revision split out a new CRunnerUtils library that supports
MLIR execution on targets without a C++ runtime.
Differential Revision: https://reviews.llvm.org/D75257
Summary:
This change does not add any functionality but merely exposes existing
static functions to make the associated transformations available
outside of their testing passes.
Differential Revision: https://reviews.llvm.org/D75232
Display the list of dialects known to mlir-opt. This is useful
for ensuring that linkage has happened correctly, for instance.
Differential Revision: https://reviews.llvm.org/D74865
Summary:
AffineApplyNormalizer provides common logic for folding affine maps that appear
in affine.apply into other affine operations that use the result of said
affine.apply. In the process, affine maps of both operations are composed.
During the composition `A.compose(B)` the symbols from the map A are placed
before those of the map B in a single concatenated symbol list. However,
AffineApplyNormalizer was ordering the operands of the operation being
normalized by iteratively appending the symbols into a single list accoridng to
the operand order, regardless of whether these operands are symbols of the
current operation or of the map that is being folded into it. This could lead
to wrong order of symbols and, when the symbols were bound to constant values,
to visibly incorrect folding of constants into affine maps as reported in
PR45031. Make sure symbols operands to the current operation are always placed
before symbols coming from the folded maps.
Update the test that was exercising the incorrect folder behavior. For some
reason, the order of symbol operands was swapped in the test input compared to
the previous operations, making it easy to assume the correct maps were
produced whereas they were swapping the symbols back due to the problem
described above.
Closes https://bugs.llvm.org/show_bug.cgi?id=45031
Differential Revision: https://reviews.llvm.org/D75247
This commit handles folding spv.LogicalAnd/spv.LogicalOr when
one of the operands is constant true/false.
Differential Revision: https://reviews.llvm.org/D75195
This revision performs some basic refactoring towards more easily defining Linalg "named" ops. Such named ops form the backbone of operations that are ubiquitous in the ML application domain.
Summary: bfloat16 is stored internally as a double, so we can't direct use Type::getIntOrFloatBitWidth.
Differential Revision: https://reviews.llvm.org/D75133
Summary:
The original patch had TODOs to add support for step computations,
which this commit addresses. The computations are expressed using
affine expressions so that the affine canonicalizers can simplify
the full bound and index computations.
Also cleans up the code a little and exposes the pass in the
header file.
Differential Revision: https://reviews.llvm.org/D75052
Affine dialect already has a map+operand simplification infrastructure in
place. Plug the recently added affine.min/max operations into this
infrastructure and add a simple test. More complex behavior of the simplifier
is already tested by other ops.
Addresses https://bugs.llvm.org/show_bug.cgi?id=45008.
Differential Revision: https://reviews.llvm.org/D75058
Originally, intrinsics generator for the LLVM dialect has been producing
customized code fragments for the translation of MLIR operations to LLVM IR
intrinsics. LLVM dialect ODS now provides a generalized version of the
translation code, parameterizable with the properties of the operation.
Generate ODS that uses this version of the translation code instead of
generating a new version of it for each intrinsic.
Differential Revision: https://reviews.llvm.org/D74893
All LLVM IR intrinsics are constructed in a similar way. The ODS definition of
the LLVM dialect in MLIR also lists multiple intrinsics, many of which
reproduce the same (or similar enough) code stanza to translate the MLIR
operation into the LLVM IR intrinsic. Provide a single base class containing
parameterizable code to build LLVM IR intrinsics given their name and the lists
of overloadable operands and results. Use this class to remove (almost)
duplicate translations for intrinsics defined in LLVMOps.td.
Differential Revision: https://reviews.llvm.org/D74889
Summary:
The mapper assigns annotations to loop.parallel operations that
are compatible with the loop to gpu mapping pass. The outermost
loop uses the grid dimensions, followed by block dimensions. All
remaining loops are mapped to sequential loops.
Differential Revision: https://reviews.llvm.org/D74963
Summary:
The RFC for this op is here: https://llvm.discourse.group/t/rfc-add-std-atomic-rmw-op/489
The std.atmomic_rmw op provides a way to support read-modify-write
sequences with data race freedom. It is intended to be used in the lowering
of an upcoming affine.atomic_rmw op which can be used for reductions.
A lowering to LLVM is provided with 2 paths:
- Simple patterns: llvm.atomicrmw
- Everything else: llvm.cmpxchg
Differential Revision: https://reviews.llvm.org/D74401
Previously C++ test passes for SPIR-V were put under
test/Dialect/SPIRV. Move them to test/lib/Dialect/SPIRV
to create a better structure.
Also fixed one of the test pass to use new
PassRegistration mechanism.
Differential Revision: https://reviews.llvm.org/D75066
mlir/lib/Parser/Parser.cpp:4484:15: warning: 'parseAssignmentList' overrides a member function but is not marked 'override' [-Winconsistent-missing-override]
ParseResult parseAssignmentList(SmallVectorImpl<OperandType> &lhs,
^
mlir/include/mlir/IR/OpImplementation.h:662:3: note: overridden virtual function is here
parseAssignmentList(SmallVectorImpl<OperandType> &lhs,
^
mlir/lib/Parser/Parser.cpp:4488:12: warning: unused variable 'type' [-Wunused-variable]
Type type;
^
This exploits the fact that the iterations of parallel loops are
independent so tiling becomes just an index transformation. This pass
only tiles the innermost loop of a loop nest.
The ultimate goal is to allow vectorization of the tiled loops, but I
don't think we're there yet with the current rewriting, as the tiled
loops don't have a constant trip count.
Differential Revision: https://reviews.llvm.org/D74954
Summary:
This details the C++ format as well as the new declarative format. This has been one of the major missing pieces from the toy tutorial.
Differential Revision: https://reviews.llvm.org/D74938
This revision add support for formatting successor variables in a similar way to operands, attributes, etc.
Differential Revision: https://reviews.llvm.org/D74789
This revision add support in ODS for specifying the successors of an operation. Successors are specified via the `successors` list:
```
let successors = (successor AnySuccessor:$target, AnySuccessor:$otherTarget);
```
Differential Revision: https://reviews.llvm.org/D74783
This range is useful when an desired API expects a range or when comparing two different ranges for equality, but the underlying data is a splat. This range removes the need to explicitly construct a vector in those cases.
Differential Revision: https://reviews.llvm.org/D74683
This matches the '(print|parse)OptionalAttrDictWithKeyword' functionality provided by the assembly parser/printer.
Differential Revision: https://reviews.llvm.org/D74682
When operations have optional attributes, or optional operands(i.e. empty variadic operands), the assembly format often has an optional section to represent these arguments. This revision adds basic support for defining an "optional group" in the assembly format to support this. An optional group is defined by wrapping a set of elements in `()` followed by `?` and requires the following:
* The first element of the group must be either a literal or an operand argument.
- This is because the first element must be optionally parsable.
* There must be exactly one argument variable within the group that is marked as the anchor of the group. The anchor is the element whose presence controls whether the group should be printed/parsed. An element is marked as the anchor by adding a trailing `^`.
* The group must only contain literals, variables, and type directives.
- Any attribute variables may be used, but only optional attributes can be marked as the anchor.
- Only variadic, i.e. optional, operand arguments can be used.
- The elements of a type directive must be defined within the same optional group.
An example of this can be seen with the assembly format for ReturnOp, which has a variadic number of operands.
```
def ReturnOp : ... {
let arguments = (ins Variadic<AnyType>:$operands);
// We only print the operands+types if there are a non-zero number
// of operands.
let assemblyFormat = "attr-dict ($operands^ `:` type($operands))?";
}
```
Differential Revision: https://reviews.llvm.org/D74681
This allows for injecting type constraints that are not direct 1-1 mappings, for example when one type is equal to the element type of another. This allows for moving over several more parsers to the declarative form.
Differential Revision: https://reviews.llvm.org/D74648
Summary:
NFC - Moved StandardOps/Ops.h to a StandardOps/IR dir to better match surrounding
directories. This is to match other dialects, and prepare for moving StandardOps
related transforms in out for Transforms and into StandardOps/Transforms.
Differential Revision: https://reviews.llvm.org/D74940
This patch implements the RFCs proposed here:
https://llvm.discourse.group/t/rfc-modify-ifop-in-loop-dialect-to-yield-values/463https://llvm.discourse.group/t/rfc-adding-operands-and-results-to-loop-for/459/19.
It introduces the following changes:
- All Loop Ops region, except for ReduceOp, terminate with a YieldOp.
- YieldOp can have variadice operands that is used to return values out of IfOp and ForOp regions.
- Change IfOp and ForOp syntax and representation to define values.
- Add unit-tests and update .td documentation.
- YieldOp is a terminator to loop.for/if/parallel
- YieldOp custom parser and printer
Lowering is not supported at the moment, and will be in a follow-up PR.
Thanks.
Reviewed By: bondhugula, nicolasvasilache, rriddle
Differential Revision: https://reviews.llvm.org/D74174
Thus far IntegerType has been signless: a value of IntegerType does
not have a sign intrinsically and it's up to the specific operation
to decide how to interpret those bits. For example, std.addi does
two's complement arithmetic, and std.divis/std.diviu treats the first
bit as a sign.
This design choice was made some time ago when we did't have lots
of dialects and dialects were more rigid. Today we have much more
extensible infrastructure and different dialect may want different
modelling over integer signedness. So while we can say we want
signless integers in the standard dialect, we cannot dictate for
others. Requiring each dialect to model the signedness semantics
with another set of custom types is duplicating the functionality
everywhere, considering the fundamental role integer types play.
This CL extends the IntegerType with a signedness semantics bit.
This gives each dialect an option to opt in signedness semantics
if that's what they want and helps code sharing. The parser is
modified to recognize `si[1-9][0-9]*` and `ui[1-9][0-9]*` as
signed and unsigned integer types, respectively, leaving the
original `i[1-9][0-9]*` to continue to mean no indication over
signedness semantics. All existing dialects are not affected (yet)
as this is a feature to opt in.
More discussions can be found at:
https://groups.google.com/a/tensorflow.org/d/msg/mlir/XmkV8HOPWpo/7O4X0Nb_AQAJ
Differential Revision: https://reviews.llvm.org/D72533
Matthias Kramm