Opaque attributes that currently contain string literals can't currently be properly roundtripped as they are not printed as escaped strings. This leads to incorrect tokens being generated and the parser to almost certainly fail. This patch simply uses llvm::printEscapedString from LLVM. It escapes all non printable characters and quotes to \xx hex literals, and backslashes to two backslashes. This syntax is supported by MLIRs Lexer as well. The same function is also currently in use for the same purpose in printSymbolReference, printAttribute for StringAttr and many more in AsmPrinter.cpp.
Differential Revision: https://reviews.llvm.org/D105405
Different constraints may share the same predicate, in this case, we
will generate duplicate ODS verification function.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D104369
Remove `getDynOperands` and `createOrFoldDimOp` from MemRef.h to decouple MemRef a bit from Tensor. These two functions are used in other dialects/transforms.
Differential Revision: https://reviews.llvm.org/D105260
Basically every kind of parseOptional* method in DialectAsmParser has a corresponding parse* method which will emit an error if the requested token has not been found. An odd one out of this rule is parseOptionalString which does not have a corresponding parseString method.
This patch adds that method and implements it in basically the same fashion as parseKeyword, by first going through parseOptionalString and emitting an error on failure.
Differential Revision: https://reviews.llvm.org/D105406
Same as other CreateLoad-style APIs, these need an explicit type
argument to support opaque pointers.
Differential Revision: https://reviews.llvm.org/D105395
This revision extends the sparse compiler support from fp/int addition and multiplication to fp/int negation and subtraction, thereby increasing the scope of sparse kernels that can be compiled.
Reviewed By: gussmith23
Differential Revision: https://reviews.llvm.org/D105306
The implementation has become too unwieldy and cognitive overhead wins.
Instead compress the implementation in preparation for additional lowering paths.
This is a resubmit of https://reviews.llvm.org/D105359 without ordering ambiguities.
Differential Revision: https://reviews.llvm.org/D105367
Fusion by linearization should not happen when
- The reshape is expanding and it is a consumer
- The reshape is collapsing and is a producer.
The bug introduced in this logic by some recent refactoring resulted
in a crash.
To enforce this (negetive) use case, add a test that reproduces the
error and verifies the fix.
Differential Revision: https://reviews.llvm.org/D104970
The implementation has become too unwieldy and cognitive overhead wins.
Instead compress the implementation in preparation for additional lowering paths.
Differential Revision: https://reviews.llvm.org/D105359
Add the min operation to OpDSL and introduce a min pooling operation to test the implementation. The patch is a sibling of the max operation patch https://reviews.llvm.org/D105203 and the min operation is again lowered to a compare and select pair.
Differential Revision: https://reviews.llvm.org/D105345
To make TensorExp clearer, this change refactors the e0/e1 fields into a union: e0/e1 for a binary op tensor expression, and tensor_num for a tensor-kinded tensor expression.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D105303
Introduce an integration test folder in the test/python subfolder and move the opsrun.py test into the newly created folder. The test verifies named operations end-to-end using both the yaml and the python path.
Differential Revision: https://reviews.llvm.org/D105276
Add the max operation to the OpDSL and introduce a max pooling operation to test the implementation. As MLIR has no builtin max operation, the max function is lowered to a compare and select pair.
Differential Revision: https://reviews.llvm.org/D105203
Tosa's PassDetail.h may be used in non-TOSA transforms. Include
TosaDialect to avoid transient dependency.
Differential Revision: https://reviews.llvm.org/D105324
Added InferReturnTypeComponents for NAry operations, reshape, and reverse.
With the additional tosa-infer-shapes pass, we can infer/propagate shapes
across a set of TOSA operations. Current version does not modify the
FuncOp type by inserting an unrealized conversion cast prior to any new
non-matchin returns.
Differential Revision: https://reviews.llvm.org/D105312
The context can be created with threading disabled, to avoid creating a thread pool
that may be destroyed when injecting another one later.
Differential Revision: https://reviews.llvm.org/D105302
Affine scalar replacement (and other affine passes, though not fixed here) don't properly handle operations with nested regions. This patch fixes the pass and two affine utilities to function properly given a non-affine internal region
This patch prevents the pass from throwing an internal compiler error when running on the added test case.
Differential Revision: https://reviews.llvm.org/D105058
Synchronizing multiple custom targets requires not only target but also
file dependencies. Building Linalg involves running yaml-gen followed by
tablegen. Currently, these custom targets are only synchronized using a
target dependency resulting in issues in specific incremental build
setups (https://llvm.discourse.group/t/missing-build-cmake-tblgen-dependency/3727/10).
This patch introduces a novel LLVM_TARGET_DEPENDS variable to the
TableGen.cmake file to provide a way to specify file dependencies.
Additionally, it adapts the Linalg CMakeLists.txt to introduce the
necessary file dependency between yaml-gen and tablegen.
Differential Revision: https://reviews.llvm.org/D105272
This results in significant deduplication of code. This patch is not expected to change any functionality, it's just some simplification in preparation for future work. Also slightly simplified some code that was being touched anyway and added some unit tests for some functions that were touched.
Reviewed By: bondhugula
Differential Revision: https://reviews.llvm.org/D105152
Rationale:
Follow-up on migrating lattice and tensor expression related methods into the new utility.
This also prepares the next step of generalizing the op kinds that are handled.
Reviewed By: gussmith23
Differential Revision: https://reviews.llvm.org/D105219
ConstantOp are only supported in the ModulePass because they require a GlobalCreator object that must be constructed from a ModuleOp.
If the standlaone FunctionPass encounters a ConstantOp, bufferization fails.
Differential revision: https://reviews.llvm.org/D105156
This revision drops the comprehensive bufferization Function pass, which has issues when trying to bufferize constants.
Instead, only support the comprehensive-module-bufferize by default.
Differential Revision: https://reviews.llvm.org/D105228
Also add an integration test that connects all the dots end to end, including with cast to unranked tensor for external library calls.
Differential Revision: https://reviews.llvm.org/D105106
Cross function boundary bufferization support is added.
This is enabled by cross-function boundary alias analysis, for which the bufferization process is extended: it can now modify the BufferizationAliasInfo as new ops are introduced.
A number of simplifying assumptions are made:
1. by default we bufferize to the most dynamic strided memref type, further memref::CastOp canonicalizations are expected to clean up the IR.
2. in the current implementation, the stride information is always erased at function boundaries. A subsequent pass will be required to analyze the meet of all call ops to a function and decide whether more static buffer types can be used. This will potentially clone functions when it is deemed profitable to do so (e.g. when the stride-1 dimension may vary).
3. external function always bufferize to the most dynamic strided memref version. This may require special annotations for specifying that particular operands of top-level functions have contiguous buffer layout.
An alternative to point 3. would be to support tensor layout annotations, which is currently not supported in MLIR.
Differential revision: https://reviews.llvm.org/D104873
Move the OpDSL doc to a linalg sub folder and updated the integration in the main linalg documentation.
Differential Revision: https://reviews.llvm.org/D105188
Add helpers to facilitate adding arguments and results to operations
that implement the `FunctionLike` trait. These operations already have a
convenient argument and result *erasure* mechanism, but a corresopnding
utility for insertion is missing. This introduces such a utility.
* Split memref.dim into two operations: memref.dim and tensor.dim. Both ops have the same builder interface and op argument names, so that they can be used with templates in patterns that apply to both tensors and memrefs (e.g., some patterns in Linalg).
* Add constant materializer to TensorDialect (needed for folding in affine.apply etc.).
* Remove some MemRefDialect dependencies, make some explicit.
Differential Revision: https://reviews.llvm.org/D105165
Uses elementwise interface to generalize canonicalization pattern and add a new
pattern for vector.contract case.
Differential Revision: https://reviews.llvm.org/D104343
Similarly to batch_mat vec outer most dim is a batching dim
and this op does |b| matrix-vector-products :
C[b, i] = sum_k(A[b, i, k] * B[b, k])
Reviewed By: rsuderman
Differential Revision: https://reviews.llvm.org/D104739
The executeregionop is used to allow multiple blocks within SCF constructs. If the container allows multiple blocks, inline the region
Differential Revision: https://reviews.llvm.org/D104960
Deduce circumstances where an affine load could not possibly be read by an operation (such as an affine load), and if so, eliminate the load
Differential Revision: https://reviews.llvm.org/D105041
Update the OpDSL documentation to reflect recent changes. In particular, the updated documentation discusses:
- Attributes used to parameterize index expressions
- Shape-only tensor support
- Scalar parameters
Differential Revision: https://reviews.llvm.org/D105123
Extend the OpDSL syntax with an optional `domain` function to specify an explicit dimension order. The extension is needed to provide more control over the dimension order instead of deducing it implicitly depending on the formulation of the tensor comprehension. Additionally, the patch also ensures the symbols are ordered according to the operand definitions of the operation.
Differential Revision: https://reviews.llvm.org/D105117
This was missing and also there was a bug in the lowering itself, which went unnoticed due to it.
Differential Revision: https://reviews.llvm.org/D105122
Fix generateCopyForMemRefRegion for a missing check: in some cases, when
the thing to generate copies for itself is empty, no fast buffer/copy
loops would have been allocated/generated. Add an extra assertion there
while at this.
Differential Revision: https://reviews.llvm.org/D105170
Adrian Kuegel