[mlir] Fix broadcasting check with 1 values

The trait was inconsistent with the other broadcasting logic here. And
also fix printing here to use ? rather than -1 in the error.

Differential Revision

[mlir] Fix broadcasting check with 1 values

The trait was inconsistent with the other broadcasting logic here. And
also fix printing here to use ? rather than -1 in the error.

Differential Revision: https://reviews.llvm.org/D105748

show more ...

[mlir][Shape] Generalize cstr_broadcastable folding for n-ary broadcasts

This is still fairly tricky code, but I tried to untangle it a bit.

Differential Revision: https://reviews.llvm.org/D96800

[mlir][Types][NFC] Move all of the builtin Type classes to BuiltinTypes.h

This is part of a larger refactoring the better congregates the builtin structures under the BuiltinDialect. This also remov

[mlir][Types][NFC] Move all of the builtin Type classes to BuiltinTypes.h

This is part of a larger refactoring the better congregates the builtin structures under the BuiltinDialect. This also removes the problematic "standard" naming that clashes with the "standard" dialect, which is not defined within IR/. A temporary forward is placed in StandardTypes.h to allow time for downstream users to replaced references.

Differential Revision: https://reviews.llvm.org/D92435

show more ...

[mlir][Type] Remove usages of Type::getKind

This is in preparation for removing the use of "kinds" within attributes and types in MLIR.

Differential Revision: https://reviews.llvm.org/D85475

[mlir] Add additional Canonicalization of shape.cstr_broadcastable.

Summary:
Added canonicalization and folding was:
- Folding when either input is an attribute indicating a scalar input
which can a

[mlir] Add additional Canonicalization of shape.cstr_broadcastable.

Summary:
Added canonicalization and folding was:
- Folding when either input is an attribute indicating a scalar input
which can always be broadcasted.
- Canonicalization where it can be determined that either input shape is
a scalar.
- Canonicalization where the partially specified input shapes can be
proven to be broadcastable always.

Differential Revision: https://reviews.llvm.org/D83194

show more ...

[MLIR] Add variadic isa<> for Type, Value, and Attribute

- Also adopt variadic llvm::isa<> in more places.
- Fixes https://bugs.llvm.org/show_bug.cgi?id=46445

Differential Revision: https://reviews

[MLIR] Add variadic isa<> for Type, Value, and Attribute

- Also adopt variadic llvm::isa<> in more places.
- Fixes https://bugs.llvm.org/show_bug.cgi?id=46445

Differential Revision: https://reviews.llvm.org/D82769

show more ...

[mlir] NFC: fix trivial typo in source files

Summary: fix trivial typos in the source files

Reviewers: mravishankar, antiagainst, nicolasvasilache, herhut, rriddle, aartbik

Reviewed By: antiagains

[mlir] NFC: fix trivial typo in source files

Summary: fix trivial typos in the source files

Reviewers: mravishankar, antiagainst, nicolasvasilache, herhut, rriddle, aartbik

Reviewed By: antiagainst, rriddle

Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, csigg, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, Joonsoo, bader, llvm-commits

Tags: #llvm

Differential Revision: https://reviews.llvm.org/D76876

show more ...

Make llvm::StringRef to std::string conversions explicit.

This is how it should've been and brings it more in line with
std::string_view. There should be no functional change here.

This is mostly m

Make llvm::StringRef to std::string conversions explicit.

This is how it should've been and brings it more in line with
std::string_view. There should be no functional change here.

This is mostly mechanical from a custom clang-tidy check, with a lot of
manual fixups. It uncovers a lot of minor inefficiencies.

This doesn't actually modify StringRef yet, I'll do that in a follow-up.

show more ...

Mass update the MLIR license header to mention "Part of the LLVM project"

This is an artifact from merging MLIR into LLVM, the file headers are
now aligned with the rest of the project.

[mlir] Generalize broadcastable trait operands

Summary:
Generalize broadcastable trait to variadic operands. Update the
documentation that still talked about element type as part of
broadcastable tr

[mlir] Generalize broadcastable trait operands

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

show more ...

[mlir] NFC: Remove Value::operator* and Value::operator-> now that Value is properly value-typed.

Summary: These were temporary methods used to simplify the transition.

Reviewed By: antiagainst

Di

[mlir] NFC: Remove Value::operator* and Value::operator-> now that Value is properly value-typed.

Summary: These were temporary methods used to simplify the transition.

Reviewed By: antiagainst

Differential Revision: https://reviews.llvm.org/D72548

show more ...

[mlir] Fix -Wrange-loo-analysis warnings

for (const auto &x : llvm::zip(..., ...))

->

for (auto x : llvm::zip(..., ...))

The return type of zip() is a wrapper that wraps a tuple of references.

>

[mlir] Fix -Wrange-loo-analysis warnings

for (const auto &x : llvm::zip(..., ...))

->

for (auto x : llvm::zip(..., ...))

The return type of zip() is a wrapper that wraps a tuple of references.

> warning: loop variable 'p' is always a copy because the range of type 'detail::zippy<detail::zip_shortest, ArrayRef<long> &, ArrayRef<long> &>' does not return a reference [-Wrange-loop-analysis]

show more ...

Adjust License.txt file to use the LLVM license

PiperOrigin-RevId: 286906740

NFC: Remove unnecessary 'llvm::' prefix from uses of llvm symbols declared in `mlir` namespace.

Aside from being cleaner, this also makes the codebase more consistent.

PiperOrigin-RevId: 286206974

Switch C++14 std::equal usage to for-loop.

Version of std::equal used required C++14, switching to for-loop for now. Just a direct change from std::equal to the equivalent using for loop.

PiperOrig

Switch C++14 std::equal usage to for-loop.

Version of std::equal used required C++14, switching to for-loop for now. Just a direct change from std::equal to the equivalent using for loop.

PiperOrigin-RevId: 258970366

show more ...

Relax Broadcastable trait to only reject instances that are statically incompatible

Currently, Broadcastable trait also rejects instances when the op result has shape other than what can be statical

Relax Broadcastable trait to only reject instances that are statically incompatible

Currently, Broadcastable trait also rejects instances when the op result has shape other than what can be statically inferred based on the operand shapes even if the result shape is compatible with the inferred broadcasted shape.

For example,
(tensor<3x2xi32>, tensor<*xi32>) -> tensor<4x3x2xi32>
(tensor<2xi32>, tensor<2xi32>) -> tensor<*xi32>

PiperOrigin-RevId: 258647493

show more ...

Rename VectorOrTensorType to ShapedType

This is in preparation for making it also support/be a parent class of MemRefType. MemRefs have similar shape/rank/element semantics and it would be usefu

Rename VectorOrTensorType to ShapedType

This is in preparation for making it also support/be a parent class of MemRefType. MemRefs have similar shape/rank/element semantics and it would be useful to be able to use these same utilities for them.

This CL should not change any semantics and only change variables, types, string literals, and comments. In follow-up CLs I will prepare all callers to handle MemRef types or remove their dependence on ShapedType.

Discussion/Rationale in https://groups.google.com/a/tensorflow.org/forum/#!topic/mlir/cHLoyfGu8y8

--

PiperOrigin-RevId: 248476449

show more ...

Only forbid mixing tensor and vector when considering broadcasting behavior

The previous approach is too restrictive; we end up forbidding all dialect-specific
types as element types. Change

Only forbid mixing tensor and vector when considering broadcasting behavior

The previous approach is too restrictive; we end up forbidding all dialect-specific
types as element types. Changed to not consider element types entirely.

--

PiperOrigin-RevId: 247486537

show more ...

Simplify the emission of various diagnostics emitted by the different dialects (Affine/Standard/etc.) by using the new stream interface instead of Twine.

--

PiperOrigin-RevId: 246842016

Rewrite the verify hooks on operations to use LogicalResult instead of bool. This also changes the return of Operation::emitError/emitOpError to LogicalResult as well.

--

PiperOrigin-RevId: 2415880

Rewrite the verify hooks on operations to use LogicalResult instead of bool. This also changes the return of Operation::emitError/emitOpError to LogicalResult as well.

--

PiperOrigin-RevId: 241588075

show more ...

Replace remaining usages of the Instruction class with Operation.

PiperOrigin-RevId: 240777521

Remove const from Value, Instruction, Argument, and the various methods on the
*Op classes. This is a net reduction by almost 400LOC.

PiperOrigin-RevId: 239972443

Change getBroadcastedShape() to return result shape via parameter

This is a more efficient way than returning SmallVector directly.

PiperOrigin-RevId: 239407024

Allow input and output to have different element types for broadcastable ops

TensorFlow comparison ops like tf.Less supports broadcast behavior but the result
type have different element types as th

Allow input and output to have different element types for broadcastable ops

TensorFlow comparison ops like tf.Less supports broadcast behavior but the result
type have different element types as the input types. Extend broadcastable trait
to allow such cases. Added tf.Less to demonstrate it.

PiperOrigin-RevId: 237846127

show more ...

Pull shape broadcast out as a stand-alone utility function

So that we can use this function to deduce broadcasted shapes elsewhere.

Also added support for unknown dimensions, by following TensorFlo

Pull shape broadcast out as a stand-alone utility function

So that we can use this function to deduce broadcasted shapes elsewhere.

Also added support for unknown dimensions, by following TensorFlow behavior.

PiperOrigin-RevId: 237846065

show more ...