It replaces DenseMap output with a SmallVector and it
removes empty loop levels from the output.
Reviewed By: andydavis1, mehdi_amini
Differential Revision: https://reviews.llvm.org/D74658
Summary:
This revision refactors the TypeConverter class to not use inheritance to add type conversions. It instead moves to a registration based system, where conversion callbacks are added to the converter with `addConversion`. This method takes a conversion callback, which must be convertible to any of the following forms(where `T` is a class derived from `Type`:
* Optional<Type> (T type)
- This form represents a 1-1 type conversion. It should return nullptr
or `llvm::None` to signify failure. If `llvm::None` is returned, the
converter is allowed to try another conversion function to perform
the conversion.
* Optional<LogicalResult>(T type, SmallVectorImpl<Type> &results)
- This form represents a 1-N type conversion. It should return
`failure` or `llvm::None` to signify a failed conversion. If the new
set of types is empty, the type is removed and any usages of the
existing value are expected to be removed during conversion. If
`llvm::None` is returned, the converter is allowed to try another
conversion function to perform the conversion.
When attempting to convert a type, the TypeConverter walks each of the registered converters starting with the one registered most recently.
Differential Revision: https://reviews.llvm.org/D74584
This patch extends affine data copy optimization utility with an
optional memref filter argument. When the memref filter is used, data
copy optimization will only generate copies for such a memref.
Note: this patch is just porting the memref filter feature from Uday's
'hop' branch: https://github.com/bondhugula/llvm-project/tree/hop.
Reviewed By: bondhugula
Differential Revision: https://reviews.llvm.org/D74342
Summary:
This sets the basic framework for lowering vector.contract progressively
into simpler vector.contract operations until a direct vector.reduction
operation is reached. More details will be filled out progressively as well.
Reviewers: nicolasvasilache
Reviewed By: nicolasvasilache
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D74520
In the previous state, we were relying on forcing the linker to include
all libraries in the final binary and the global initializer to self-register
every piece of the system. This change help moving away from this model, and
allow users to compose pieces more freely. The current change is only "fixing"
the dialect registration and avoiding relying on "whole link" for the passes.
The translation is still relying on the global registry, and some refactoring
is needed to make this all more convenient.
Differential Revision: https://reviews.llvm.org/D74461
Summary:
Adds affine loop fusion transformation function to LoopFusionUtils.
Updates TestLoopFusion utility to run loop fusion transformation until a fixed point is reached.
Adds unit tests to test the transformation.
Includes ASAN bug fix for D73190.
Reviewers: bondhugula, dcaballe
Reviewed By: bondhugula, dcaballe
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D74330
Defines a tablegen class RankedIntElementsAttr. This is an integer
version of RankedFloatElementsAttr.
Differential Revision: https://reviews.llvm.org/D73764
This reverts commit 64871f778d.
ASAN indicates a use-after-free in in mlir::canFuseLoops(mlir::AffineForOp, mlir::AffineForOp, unsigned int, mlir::ComputationSliceState*) lib/Transforms/Utils/LoopFusionUtils.cpp:202:41
Summary:
Adds affine loop fusion transformation function to LoopFusionUtils.
Updates TestLoopFusion utility to run loop fusion transformation until a fixed point is reached.
Adds unit tests to test the transformation.
Reviewers: bondhugula, dcaballe, nicolasvasilache
Reviewed By: bondhugula, dcaballe
Subscribers: Joonsoo, merge_guards_bot, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D73190
Summary:
This breaks a cyclic library dependency where MLIRPass used the verifier
in MLIRAnalysis, but MLIRAnalysis also contained passes used for testing.
The presence of the test passes here is archaeology, predating
test/lib/Transform.
Reviewers: rriddle
Reviewed By: rriddle
Subscribers: merge_guards_bot, mgorny, mehdi_amini, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D74067
Summary:
This patch is a step towards enabling BUILD_SHARED_LIBS=on, which
builds most libraries as DLLs instead of statically linked libraries.
The main effect of this is that incremental build times are greatly
reduced, since usually only one library need be relinked in response
to isolated code changes.
The bulk of this patch is fixing incorrect usage of cmake, where library
dependencies are listed under add_dependencies rather than under
target_link_libraries or under the LINK_LIBS tag. Correct usage should be
like this:
add_dependencies(MLIRfoo MLIRfooIncGen)
target_link_libraries(MLIRfoo MLIRlib1 MLIRlib2)
A separate issue is that in cmake, dependencies between static libraries
are automatically included in dependencies. In the above example, if MLIBlib1
depends on MLIRlib2, then it is sufficient to have only MLIRlib1 in the
target_link_libraries. When compiling with shared libraries, it is necessary
to have both MLIRlib1 and MLIRlib2 specified if MLIRfoo uses symbols from both.
Reviewers: mravishankar, antiagainst, nicolasvasilache, vchuravy, inouehrs, mehdi_amini, jdoerfert
Reviewed By: nicolasvasilache, mehdi_amini
Subscribers: Joonsoo, merge_guards_bot, jholewinski, mgorny, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, csigg, arpith-jacob, mgester, lucyrfox, herhut, aartbik, liufengdb, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D73653
Summary:
This revision add support, and testing, for generating the parser and printer from the declarative operation format.
Differential Revision: https://reviews.llvm.org/D73406
Summary:
This diff adds a transformation patter to rewrite linalg.fill as broadcasting a scaler into a vector.
It uses the same preconditioning as matmul (memory is contiguous).
Reviewers: nicolasvasilache
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D73391
Summary: This revision refactors the implementation of the symbol use-list functionality to be a bit cleaner, as well as easier to reason about. Aside from code cleanup, this revision updates the user contract to never recurse into operations if they define a symbol table. The current functionality, which does recurse, makes it difficult to examine the uses held by a symbol table itself. Moving forward users may provide a specific region to examine for uses instead.
Differential Revision: https://reviews.llvm.org/D73427
Summary: The new internal representation of operation results now allows for accessing the result types to be more efficient. Changing the API to ArrayRef is more efficient and removes the need to explicitly materialize vectors in several places.
Differential Revision: https://reviews.llvm.org/D73429
Summary: This allows for providing a default "catchall" legality check that is not dependent on specific operations or dialects. For example, this can be useful to check legality based on the specific types of operation operands or results.
Differential Revision: https://reviews.llvm.org/D73379
Summary:
Rewrites the extract/insert_slices operation in terms of
strided_slice/insert_strided_slice ops with intermediate
tuple uses (that should get optimimized away with typical
usage). This is done in a separate "pass" to enable testing
this particular rewriting in isolation.
Reviewers: nicolasvasilache, andydavis1, ftynse
Reviewed By: nicolasvasilache
Subscribers: merge_guards_bot, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, arpith-jacob, mgester, lucyrfox, liufengdb, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D73295
Summary:
Add method in ODS to specify verification for operations implementing a
OpInterface. Use this with infer type op interface to verify that the
inferred type matches the return type and remove special case in
TestPatterns.
This could also have been achieved by using OpInterfaceMethod but verify
seems pretty common and it is not an arbitrary method that just happened
to be named verifyTrait, so having it be defined in special way seems
appropriate/better documenting.
Differential Revision: https://reviews.llvm.org/D73122
Summary:
Generalize broadcastable trait to variadic operands. Update the
documentation that still talked about element type as part of
broadcastable trait (that bug was already fixed). Also rename
Broadcastable to ResultBroadcastableShape to be more explicit that the
trait affects the result shape (it is possible for op to allow
broadcastable operands but not have result shape that is broadcast
compatible with operands).
Doing some intermediate work to have getBroadcastedType take an optional
elementType as input and use that if specified, instead of the common
element type of type1 and type2 in this function.
Differential Revision: https://reviews.llvm.org/D72559
Summary:
This is a simple extension to allow vectorization to work not only on GenericLinalgOp
but more generally across named ops too.
For now, this still only vectorizes matmul-like ops but is a step towards more
generic vectorization of Linalg ops.
Reviewers: ftynse
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D72942
Summary:
First step towards the consolidation
of a lot of vector related utilities
that are now all over the place
(or even duplicated).
Reviewers: nicolasvasilache, andydavis1
Reviewed By: nicolasvasilache, andydavis1
Subscribers: merge_guards_bot, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, arpith-jacob, mgester, lucyrfox, liufengdb, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D72955
Summary:
* Add shaped container type interface which allows infering the shape, element
type and attribute of shaped container type separately. Show usage by way of
tensor type inference trait which combines the shape & element type in
infering a tensor type;
- All components need not be specified;
- Attribute is added to allow for layout attribute that was previously
discussed;
* Expand the test driver to make it easier to test new creation instances
(adding new operands or ops with attributes or regions would trigger build
functions/type inference methods);
- The verification part will be moved out of the test and to verify method
instead of ops implementing the type inference interface in a follow up;
* Add MLIRContext as arg to possible to create type for ops without arguments,
region or location;
* Also move out the section in OpDefinitions doc to separate ShapeInference doc
where the shape function requirements can be captured;
- Part of this would move to the shape dialect and/or shape dialect ops be
included as subsection of this doc;
* Update ODS's variable usage to match camelBack format for builder,
state and arg variables;
- I could have split this out, but I had to make some changes around
these and the inconsistency bugged me :)
Differential Revision: https://reviews.llvm.org/D72432
Summary:
The visibility defines the structural reachability of the symbol within the IR. Symbols can define one of three visibilities:
* Public
The symbol \may be accessed from outside of the visible IR. We cannot assume that we can observe all of the uses of this symbol.
* Private
The symbol may only be referenced from within the operations in the current symbol table, via SymbolRefAttr.
* Nested
The symbol may be referenced by operations in symbol tables above the current symbol table, as long as each symbol table parent also defines a non-private symbol. This allows or referencing the symbol from outside of the defining symbol table, while retaining the ability for the compiler to see all uses.
These properties help to reason about the properties of a symbol, and will be used in a follow up to implement a dce pass on dead symbols.
A few examples of what this would look like in the IR are shown below:
module @public_module {
// This function can be accessed by 'live.user'
func @nested_function() attributes { sym_visibility = "nested" }
// This function cannot be accessed outside of 'public_module'
func @private_function() attributes { sym_visibility = "private" }
}
// This function can only be accessed from within this module.
func @private_function() attributes { sym_visibility = "private" }
// This function may be referenced externally.
func @public_function()
"live.user"() {uses = [@public_module::@nested_function,
@private_function,
@public_function]} : () -> ()
Depends On D72043
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D72044
Summary:
This enables tracking calls that cross symbol table boundaries. It also simplifies some of the implementation details of CallableOpInterface, i.e. there can only be one region within the callable operation.
Depends On D72042
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D72043
Summary: This updates the use list algorithms to support querying from a specific symbol, allowing for the collection and detection of nested references. This works by walking the parent "symbol scopes" and applying the existing algorithm at each level.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D72042
Summary: Introduce m_Constant() which allows matching a constant operation without forcing the user also to capture the attribute value.
Differential Revision: https://reviews.llvm.org/D72397
Introduce a set of function that promote a memref argument of a `gpu.func` to
workgroup memory using memory attribution. The promotion boils down to
additional loops performing the copy from the original argument to the
attributed memory in the beginning of the function, and back at the end of the
function using all available threads. The loop bounds are specified so as to
adapt to any size of the workgroup. These utilities are intended to compose
with other existing utilities (loop coalescing and tiling) in cases where the
distribution of work across threads is uneven, e.g. copying a 2D memref with
only the threads along the "x" dimension. Similarly, specialization of the
kernel to specific launch sizes should be implemented as a separate pass
combining constant propagation and canonicalization.
Introduce a simple attribute-driven pass to test the promotion transformation
since we don't have a heuristic at the moment.
Differential revision: https://reviews.llvm.org/D71904
Summary:
This changes the implementation of OpResult to have some of the results be represented inline in Value, via a pointer int pair of Operation*+result number, and the rest being trailing objects on the main operation. The full details of the new representation is detailed in the proposal here:
https://groups.google.com/a/tensorflow.org/g/mlir/c/XXzzKhqqF_0/m/v6bKb08WCgAJ
The only difference between here and the above proposal is that we only steal 2-bits for the Value kind instead of 3. This means that we can only fit 2-results inline instead of 6. This allows for other users to steal the final bit for PointerUnion/etc. If necessary, we can always steal this bit back in the future to save more space if 3-6 results are common enough.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D72020
Summary:
This diff adds support to allow `linalg.generic` and
`linalg.indexed_generic` to take tensor input and output
arguments.
The subset of output tensor operand types must appear
verbatim in the result types after an arrow. The parser,
printer and verifier are extended to accomodate this
behavior.
The Linalg operations now support variadic ranked tensor
return values. This extension exhibited issues with the
current handling of NativeCall in RewriterGen.cpp. As a
consequence, an explicit cast to `SmallVector<Value, 4>`
is added in the proper place to support the new behavior
(better suggestions are welcome).
Relevant cleanups and name uniformization are applied.
Relevant invalid and roundtrip test are added.
Reviewers: mehdi_amini, rriddle, jpienaar, antiagainst, ftynse
Subscribers: burmako, shauheen, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D72022
Summary:
This is part of an ongoing cleanup and uniformization work.
This diff performs 3 types of cleanups:
1. Uniformize transformation names.
2. Replace all pattern operands that need not be captured by `$_`
3. Replace all usage of pattern captured op by the normalized `op` name (instead of positional parameters such as `$0`)
Reviewers: ftynse
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D72081
This change refactors pass options to be more similar to how statistics are modeled. More specifically, the options are specified directly on the pass instead of in a separate options class. (Note that the behavior and specification for pass pipelines remains the same.) This brings about several benefits:
* The specification of options is much simpler
* The round-trip format of a pass can be generated automatically
* This gives a somewhat deeper integration with "configuring" a pass, which we could potentially expose to users in the future.
PiperOrigin-RevId: 286953824
This is an initial step to refactoring the representation of OpResult as proposed in: https://groups.google.com/a/tensorflow.org/g/mlir/c/XXzzKhqqF_0/m/v6bKb08WCgAJ
This change will make it much simpler to incrementally transition all of the existing code to use value-typed semantics.
PiperOrigin-RevId: 286844725
This is the block argument equivalent of the existing `getAsmResultNames` hook.
Closestensorflow/mlir#329
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/329 from plaidml:flaub-region-arg-names fc7876f2d1335024e441083cd25263fd6247eb7d
PiperOrigin-RevId: 286523299
This enables providing a default implementation of an interface method. This method is defined on the Trait that is attached to the operation, and thus has all of the same constraints and properties as any other interface method. This allows for interface authors to provide a conservative default implementation for certain methods, without requiring that all users explicitly define it. The default implementation can be specified via the argument directly after the interface method body:
StaticInterfaceMethod<
/*desc=*/"Returns whether two array of types are compatible result types for an op.",
/*retTy=*/"bool",
/*methodName=*/"isCompatibleReturnTypes",
/*args=*/(ins "ArrayRef<Type>":$lhs, "ArrayRef<Type>":$rhs),
/*methodBody=*/[{
return ConcreteOp::isCompatibleReturnTypes(lhs, rhs);
}],
/*defaultImplementation=*/[{
/// Returns whether two arrays are equal as strongest check for
/// compatibility by default.
return lhs == rhs;
}]
PiperOrigin-RevId: 286226054
This PR targest issue tensorflow/mlir#295. It exposes the already existing
subiew promotion pass as a declarative pattern
Change-Id: If901ebef9fb53fcd0b12ecc536f6b174ce320b92
Closestensorflow/mlir#315
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/315 from tetuante:issue295 8e5f268b6d85f31015c33505329dbd7a4db97ac5
PiperOrigin-RevId: 285801463
This change allows for DialectConversion to attempt folding as a mechanism to legalize illegal operations. This also expands folding support in OpBuilder::createOrFold to generate new constants when folding, and also enables it to work in the context of a PatternRewriter.
PiperOrigin-RevId: 285448440
Diego Caballero