The call to 'multiply_transpose' in the initialization of the variable 'f' was
intended to have a shape mismatch. However the variable 'a' has shape <2, 3> and
the variable 'c' has shape <3, 2>, so the arguments 'transpose(a)' and 'c' have
in fact compatible shapes (<3, 2> both), the opposite of what is wanted here.
This commit removes the transpose so that arguments 'a' and 'c' have
incompatible shapes <2, 3> and <3, 2>, respectively.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D151897
This is an ongoing series of commits that are reformatting our
Python code.
Reformatting is done with `black`.
If you end up having problems merging this commit because you
have made changes to a python file, the best way to handle that
is to run git checkout --ours <yourfile> and then reformat it
with black.
If you run into any problems, post to discourse about it and
we will try to help.
RFC Thread below:
https://discourse.llvm.org/t/rfc-document-and-standardize-python-code-style
Differential Revision: https://reviews.llvm.org/D150782
In Toy tutorial chapter 1, multiply_transpose() is called with b<2, 3>
and c<3, 2> when both parameters should have the same shape. This commit
fixes this by instead using c and d as parameters and fix a comment typo
where c and d are mentioned to have shape <2, 2> when they actually have
shape <3, 2>.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D142622
This patch enhances the CSE pass to deal with simple cases of duplicated
operations with MemoryEffects.
It allows the CSE pass to remove safely duplicate operations with the
MemoryEffects::Read that have no other side-effecting operations in
between. Other MemoryEffects::Read operation are allowed.
The use case is pretty simple so far so we can build on top of it to add
more features.
This patch is also meant to avoid a dedicated CSE pass in FIR and was
brought together afetr discussion on https://reviews.llvm.org/D112711.
It does not currently cover the full range of use cases described in
https://reviews.llvm.org/D112711 but the idea is to gradually enhance
the MLIR CSE pass to handle common use cases that can be used by
other dialects.
This patch takes advantage of the new CSE capabilities in Fir.
Reviewed By: mehdi_amini, rriddle, schweitz
Differential Revision: https://reviews.llvm.org/D122801
FuncOp is being moved out of the builtin dialect, and defining a custom
toy operation showcases various aspects of defining function-like operation
(e.g. inlining, passes, etc.).
Differential Revision: https://reviews.llvm.org/D121264
Precursor: https://reviews.llvm.org/D110200
Removed redundant ops from the standard dialect that were moved to the
`arith` or `math` dialects.
Renamed all instances of operations in the codebase and in tests.
Reviewed By: rriddle, jpienaar
Differential Revision: https://reviews.llvm.org/D110797
This commit introduced a cyclic dependency:
Memref dialect depends on Standard because it used ConstantIndexOp.
Std depends on the MemRef dialect in its EDSC/Intrinsics.h
Working on a fix.
This reverts commit 8aa6c3765b.
Create the memref dialect and move several dialect-specific ops without
dependencies to other ops from std dialect to this dialect.
Moved ops:
AllocOp -> MemRef_AllocOp
AllocaOp -> MemRef_AllocaOp
DeallocOp -> MemRef_DeallocOp
MemRefCastOp -> MemRef_CastOp
GetGlobalMemRefOp -> MemRef_GetGlobalOp
GlobalMemRefOp -> MemRef_GlobalOp
PrefetchOp -> MemRef_PrefetchOp
ReshapeOp -> MemRef_ReshapeOp
StoreOp -> MemRef_StoreOp
TransposeOp -> MemRef_TransposeOp
ViewOp -> MemRef_ViewOp
The roadmap to split the memref dialect from std is discussed here:
https://llvm.discourse.group/t/rfc-split-the-memref-dialect-from-std/2667
Differential Revision: https://reviews.llvm.org/D96425
- Change syntax for FuncOp to be `func <visibility>? @name` instead of printing the
visibility in the attribute dictionary.
- Since printFunctionLikeOp() and parseFunctionLikeOp() are also used by other
operations, make the "inline visibility" an opt-in feature.
- Updated unit test to use and check the new syntax.
Differential Revision: https://reviews.llvm.org/D90859
Summary:
- Fix comments in several places
- Eliminate extra ' in AST dump and adjust tests accordingly
Differential Revision: https://reviews.llvm.org/D78399
Summary:
The tests referred to in Chapter 3 of the tutorial were missing from the tutorial test
directory; this adds those missing tests. This also cleans up some stale directory paths and code
snippets used throughout the tutorial.
Differential Revision: https://reviews.llvm.org/D76809
Summary:
The tests referred to in Chapter 3 of the tutorial were missing from the tutorial test
directory; this adds those missing tests. This also cleans up some stale directory paths and code
snippets used throughout the tutorial.
Differential Revision: https://reviews.llvm.org/D76809
Summary:
The tests referred to in Chapter 3 of the tutorial were missing from the tutorial test
directory; this adds those missing tests. This also cleans up some stale directory paths and code
snippets used throughout the tutorial.
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, aartbik, liufengdb, Joonsoo, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D76809
Summary:
Previously, we would, for an empty file, print the somewhat confusing
Assertion `tok == curTok [...]' failed.
With this change, we now print
Parse error [...]: expected 'def' [...]
This only affects the parser from chapters 1-6, since the more advanced
chapter 7 parser is actually able to generate an empty module from an
empty file. Nonetheless, this commit also adds the additional check to
the chapter 7 parser, for consistency.
Differential Revision: https://reviews.llvm.org/D75534
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
Summary:
The dead function elimination pass in toy was a temporary stopgap until we had proper dead function elimination support in MLIR. Now that this functionality is available, this pass is no longer necessary.
Differential Revision: https://reviews.llvm.org/D72483
This chapter adds a new composite type to Toy, and shows the process of adding a new type to the IR, adding and updating operations to use it, and constant folding operations producing it.
PiperOrigin-RevId: 279107885
This change rewrites Ch-4.md to introduced interfaces in a detailed step-by-step manner, adds examples, and fixes some errors.
PiperOrigin-RevId: 275887017
This chapters introduces the notion of a full conversion, and adds support for lowering down to the LLVM dialect, LLVM IR, and thus code generation.
PiperOrigin-RevId: 275337786
This chapter adds a partial lowering of toy operations, all but PrintOp, to a combination of the Affine and Std dialects. This chapter focuses on introducing the conversion framework, the benefits of partial lowering, and how easily dialects may co-exist in the IR.
PiperOrigin-RevId: 275150649
The GenericCallOp needed to have the CallOpInterface to be picked up by the inliner. This also adds a CastOp to perform shape casts that are generated during inlining. The casts generated by the inliner will be folded away after shape inference.
PiperOrigin-RevId: 275150438
This Chapter now introduces and makes use of the Interface concept
in MLIR to demonstrate ShapeInference.
END_PUBLIC
Closestensorflow/mlir#191
PiperOrigin-RevId: 275085151
This is using Table-driven Declarative Rewrite Rules (DRR), the previous
version of the tutorial only showed the C++ patterns.
Closestensorflow/mlir#187
PiperOrigin-RevId: 274852321
This effectively rewrites Ch.2 to introduce dialects, operations, and registration instead of deferring to Ch.3. This allows for introducing the best practices up front(using ODS, registering operations, etc.), and limits the opaque API to the chapter document instead of the code.
PiperOrigin-RevId: 274724289
Originally, the lowering of `alloc` operations has been computing the number of
bytes to allocate when lowering based on the properties of MLIR type. This does
not take into account type legalization that happens when compiling LLVM IR
down to target assembly. This legalization can widen the type, potentially
leading to out-of-bounds accesses to `alloc`ed data due to mismatches between
address computation that takes the widening into account and allocation that
does not. Use the LLVM IR's equivalent of `sizeof` to compute the number of
bytes to be allocated:
%0 = getelementptr %type* null, %indexType 0
%1 = ptrtoint %type* %0 to %indexType
adapted from
http://nondot.org/sabre/LLVMNotes/SizeOf-OffsetOf-VariableSizedStructs.txt
PiperOrigin-RevId: 274159900
The code and documentation for this chapter of the tutorial have been updated to follow the new flow. The toy 'array' type has been replaced by usages of the MLIR tensor type. The code has also been cleaned up and modernized.
Closestensorflow/mlir#101
PiperOrigin-RevId: 265744086
The current syntax separates the name and value with ':', but ':' is already overloaded by several other things(e.g. trailing types). This makes the syntax difficult to parse in some situtations:
Old:
"foo: 10 : i32"
New:
"foo = 10 : i32"
PiperOrigin-RevId: 255097928
This is the standard syntax for types on operations, and is also already used by IntegerAttr and FloatAttr.
Example:
dense<5> : tensor<i32>
dense<[3]> : tensor<1xi32>
PiperOrigin-RevId: 255069157
making the IR dumps much nicer.
This is part 2/3 of the path to making dialect types more nice. Part 3/3 will
slightly generalize the set of characters allowed in pretty types and make it
more principled.
--
PiperOrigin-RevId: 242249955
Mainly a missing dependency caused the tests to pass if one already built
the repo, but not from a clean (or incremental) build.
--
PiperOrigin-RevId: 241852313
