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[mlir][transform] Consistent linalg transform op syntax for dynamic index lists (#90897)

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This patch is a first pass at making consistent syntax across the
`LinalgTransformOp`s that use dynamic index lists for size parameters.
Previously, there were two different forms: inline types in the list, or
place them in the functional style tuple. This patch goes for the
latter.

In order to do this, the `printPackedOrDynamicIndexList`,
`printDynamicIndexList` and their `parse` counterparts were modified so
that the types can be optionally provided to the corresponding custom
directives.

All affected ops now use tablegen `assemblyFormat`, so custom
`parse`/`print` functions have been removed. There are a couple ops that
will likely add dynamic size support, and once that happens it should be
made sure that the assembly remains consistent with the changes in this
patch.

The affected ops are as follows: `pack`, `pack_greedily`,
`tile_using_forall`. The `tile_using_for` and `vectorize` ops already
used this syntax, but their custom assembly was removed.

---------

Co-authored-by: Oleksandr "Alex" Zinenko <ftynse@gmail.com>
This commit is contained in:
srcarroll
2024-05-08 09:11:53 -05:00
committed by GitHub
parent c6efcc925c
commit 2c1c67674c
53 changed files with 210 additions and 323 deletions
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41
mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td
View File

@@ -783,10 +783,9 @@ def PackOp : Op<Transform_Dialect, "structured.pack", [
let assemblyFormat = [{
$target
`packed_sizes` `=` custom<DynamicIndexList>($packed_sizes,
$static_packed_sizes,
type($packed_sizes))
$static_packed_sizes)
attr-dict
`:` functional-type($target, results)
`:` functional-type(operands, results)
}];
let builders = [
@@ -890,14 +889,13 @@ def PackGreedilyOp : Op<Transform_Dialect, "structured.pack_greedily", [
$target
oilist(
`matmul_packed_sizes` `=` custom<DynamicIndexList>($matmul_packed_sizes,
$static_matmul_packed_sizes,
type($matmul_packed_sizes))
$static_matmul_packed_sizes)
(`matmul_padded_sizes_next_multiple_of` `=`
$matmul_padded_sizes_next_multiple_of^)?
`matmul_inner_dims_order` `=` $matmul_inner_dims_order
)
attr-dict
`:` functional-type($target, results)
`:` functional-type(operands, results)
}];
let hasVerifier = 1;
@@ -1899,7 +1897,17 @@ def TileUsingForOp : Op<Transform_Dialect, "structured.tile_using_for",
$scalableSizes)>,
];
let hasCustomAssemblyFormat = 1;
let assemblyFormat = [{
$target
`tile_sizes` custom<DynamicIndexList>(
$dynamic_sizes,
$static_sizes,
$scalable_sizes)
(`interchange` `=` $interchange^)?
attr-dict
`:` functional-type(operands, results)
}];
let hasVerifier = 1;
let extraClassDeclaration = [{
@@ -2017,17 +2025,13 @@ def TileUsingForallOp :
let assemblyFormat = [{
$target oilist(
`num_threads` custom<PackedOrDynamicIndexList>($packed_num_threads,
type($packed_num_threads),
$num_threads,
type($num_threads),
$static_num_threads) |
`tile_sizes` custom<PackedOrDynamicIndexList>($packed_tile_sizes,
type($packed_tile_sizes),
$tile_sizes,
type($tile_sizes),
$static_tile_sizes))
(`(` `mapping` `=` $mapping^ `)`)? attr-dict
`:` functional-type($target, results)
`:` functional-type(operands, results)
}];
let hasVerifier = 1;
@@ -2162,7 +2166,18 @@ def VectorizeOp : Op<Transform_Dialect, "structured.vectorize",
let results = (outs);
let hasCustomAssemblyFormat = 1;
// We use oilist here to elide the optional `vector_sizes` when empty list
// is passed.
let assemblyFormat = [{
$target oilist(
`vector_sizes` custom<DynamicIndexList>(
$vector_sizes,
$static_vector_sizes,
$scalable_sizes))
attr-dict
`:` type($target)(`,`type($vector_sizes)^)?
}];
let hasVerifier = 1;
let extraClassDeclaration = [{

16
mlir/include/mlir/Dialect/Transform/Utils/Utils.h
View File

@@ -37,6 +37,12 @@ void printPackedOrDynamicIndexList(OpAsmPrinter &printer, Operation *op,
Value packed, Type packedType,
OperandRange values, TypeRange valueTypes,
DenseI64ArrayAttr integers);
inline void printPackedOrDynamicIndexList(OpAsmPrinter &printer, Operation *op,
Value packed, OperandRange values,
DenseI64ArrayAttr integers) {
printPackedOrDynamicIndexList(printer, op, packed, Type(), values,
TypeRange{}, integers);
}
/// Parser hook for custom directive in assemblyFormat.
///
@@ -47,7 +53,15 @@ void printPackedOrDynamicIndexList(OpAsmPrinter &printer, Operation *op,
ParseResult parsePackedOrDynamicIndexList(
OpAsmParser &parser, std::optional<OpAsmParser::UnresolvedOperand> &packed,
Type &packedType, SmallVectorImpl<OpAsmParser::UnresolvedOperand> &values,
SmallVectorImpl<Type> &valueTypes, DenseI64ArrayAttr &integers);
SmallVectorImpl<Type> *valueTypes, DenseI64ArrayAttr &integers);
inline ParseResult parsePackedOrDynamicIndexList(
OpAsmParser &parser, std::optional<OpAsmParser::UnresolvedOperand> &packed,
SmallVectorImpl<OpAsmParser::UnresolvedOperand> &values,
DenseI64ArrayAttr &integers) {
Type packedType;
return parsePackedOrDynamicIndexList(parser, packed, packedType, values,
nullptr, integers);
}
} // namespace transform
} // namespace mlir

11
mlir/include/mlir/Interfaces/ViewLikeInterface.h
View File

@@ -106,9 +106,16 @@ public:
/// empty then assume that all indices are non-scalable.
void printDynamicIndexList(
OpAsmPrinter &printer, Operation *op, OperandRange values,
ArrayRef<int64_t> integers, TypeRange valueTypes = TypeRange(),
ArrayRef<bool> scalables = {},
ArrayRef<int64_t> integers, ArrayRef<bool> scalables,
TypeRange valueTypes = TypeRange(),
AsmParser::Delimiter delimiter = AsmParser::Delimiter::Square);
inline void printDynamicIndexList(
OpAsmPrinter &printer, Operation *op, OperandRange values,
ArrayRef<int64_t> integers, TypeRange valueTypes = TypeRange(),
AsmParser::Delimiter delimiter = AsmParser::Delimiter::Square) {
return printDynamicIndexList(printer, op, values, integers, {}, valueTypes,
delimiter);
}
/// Parser hook for custom directive in assemblyFormat.
///

154
mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
View File

@@ -2823,86 +2823,6 @@ SmallVector<OpFoldResult> transform::TileUsingForOp::getMixedSizes() {
return results;
}
// We want to parse `DenseI64ArrayAttr` using the short form without the
// `array` prefix to be consistent in the IR with `parseDynamicIndexList`.
ParseResult parseOptionalInterchange(OpAsmParser &parser,
OperationState &result) {
if (failed(parser.parseOptionalKeyword("interchange")))
return success();
if (failed(parser.parseEqual()))
return failure();
result.addAttribute(
transform::TileUsingForOp::getInterchangeAttrName(result.name),
DenseI64ArrayAttr::parse(parser, Type{}));
return success();
}
void printOptionalInterchange(OpAsmPrinter &p,
ArrayRef<int64_t> interchangeVals) {
if (!interchangeVals.empty()) {
p << " interchange = [";
llvm::interleaveComma(interchangeVals, p,
[&](int64_t integer) { p << integer; });
p << "]";
}
}
ParseResult transform::TileUsingForOp::parse(OpAsmParser &parser,
OperationState &result) {
OpAsmParser::UnresolvedOperand target;
SmallVector<OpAsmParser::UnresolvedOperand> dynamicSizes;
DenseI64ArrayAttr staticSizes;
FunctionType functionalType;
llvm::SMLoc operandLoc;
DenseBoolArrayAttr scalableVals;
if (parser.parseOperand(target) || parser.getCurrentLocation(&operandLoc) ||
parseDynamicIndexList(parser, dynamicSizes, staticSizes, scalableVals) ||
parseOptionalInterchange(parser, result) ||
parser.parseOptionalAttrDict(result.attributes) ||
parser.parseColonType(functionalType))
return ParseResult::failure();
size_t numExpectedLoops =
staticSizes.size() - llvm::count(staticSizes.asArrayRef(), 0);
if (functionalType.getNumResults() != numExpectedLoops + 1) {
return parser.emitError(parser.getNameLoc())
<< "expected " << (numExpectedLoops + 1) << " result type(s)";
}
if (functionalType.getNumInputs() != dynamicSizes.size() + 1) {
return parser.emitError(operandLoc)
<< "expected " << dynamicSizes.size() + 1 << " operand type(s)";
}
if (parser.resolveOperand(target, functionalType.getInputs().front(),
result.operands) ||
parser.resolveOperands(dynamicSizes,
functionalType.getInputs().drop_front(),
operandLoc, result.operands)) {
return failure();
}
result.addAttribute(getScalableSizesAttrName(result.name), scalableVals);
result.addAttribute(getStaticSizesAttrName(result.name), staticSizes);
result.addTypes(functionalType.getResults());
return success();
}
void TileUsingForOp::print(OpAsmPrinter &p) {
p << ' ' << getTarget();
printDynamicIndexList(p, getOperation(), getDynamicSizes(), getStaticSizes(),
/*valueTypes=*/{}, getScalableSizesAttr(),
OpAsmParser::Delimiter::Square);
printOptionalInterchange(p, getInterchange());
p.printOptionalAttrDict(
(*this)->getAttrs(),
/*elidedAttrs=*/{getInterchangeAttrName(getOperation()->getName()),
getScalableSizesAttrName(getOperation()->getName()),
getStaticSizesAttrName(getOperation()->getName())});
p << " : ";
p.printFunctionalType(getOperands().getTypes(), getResults().getTypes());
}
void transform::TileUsingForOp::getEffects(
SmallVectorImpl<MemoryEffects::EffectInstance> &effects) {
consumesHandle(getTarget(), effects);
@@ -3219,80 +3139,6 @@ transform::VectorizeChildrenAndApplyPatternsOp::applyToOne(
// VectorizeOp
//===----------------------------------------------------------------------===//
static const StringLiteral kVectorSizesKeyword = "vector_sizes";
ParseResult transform::VectorizeOp::parse(OpAsmParser &parser,
OperationState &result) {
OpAsmParser::UnresolvedOperand target;
SmallVector<OpAsmParser::UnresolvedOperand> dynamicSizes;
DenseI64ArrayAttr staticSizes;
SmallVector<Type> operandTypes;
llvm::SMLoc operandLoc;
DenseBoolArrayAttr scalableVals;
if (parser.parseOperand(target) || parser.getCurrentLocation(&operandLoc))
return ParseResult::failure();
if (succeeded(parser.parseOptionalKeyword(kVectorSizesKeyword))) {
if (failed(parseDynamicIndexList(parser, dynamicSizes, staticSizes,
scalableVals)))
return ParseResult::failure();
}
if (succeeded(parser.parseOptionalKeyword(
getVectorizeNdExtractAttrName(result.name))))
result.addAttribute(getVectorizeNdExtractAttrName(result.name),
parser.getBuilder().getUnitAttr());
if (parser.parseOptionalAttrDict(result.attributes) ||
parser.parseColonTypeList(operandTypes))
return ParseResult::failure();
if (operandTypes.size() != dynamicSizes.size() + 1) {
return parser.emitError(operandLoc)
<< "expected " << dynamicSizes.size() + 1 << " operand type(s)";
}
if (parser.resolveOperand(target, operandTypes.front(), result.operands) ||
parser.resolveOperands(dynamicSizes, ArrayRef(operandTypes).drop_front(),
operandLoc, result.operands)) {
return failure();
}
if (scalableVals)
result.addAttribute(getScalableSizesAttrName(result.name), scalableVals);
if (staticSizes)
result.addAttribute(getStaticVectorSizesAttrName(result.name), staticSizes);
return success();
}
void transform::VectorizeOp::print(OpAsmPrinter &p) {
p << ' ' << getTarget() << ' ';
if (!getMixedVectorSizes().empty()) {
p << kVectorSizesKeyword << ' ';
printDynamicIndexList(p, getOperation(), getVectorSizes(),
getStaticVectorSizesAttr(),
/*valueTypes=*/{}, getScalableSizesAttr(),
OpAsmParser::Delimiter::Square);
}
if (getVectorizeNdExtract())
p << getVectorizeNdExtractAttrName() << ' ';
p.printOptionalAttrDict(
(*this)->getAttrs(),
/*elidedAttrs=*/{
getScalableSizesAttrName(getOperation()->getName()),
getStaticVectorSizesAttrName(getOperation()->getName())});
p << " : ";
p << getTarget().getType();
if (!getVectorSizes().empty()) {
p << ", ";
llvm::interleaveComma(getVectorSizes(), p,
[&](Value operand) { p << operand.getType(); });
}
}
DiagnosedSilenceableFailure transform::VectorizeOp::apply(
transform::TransformRewriter &rewriter,
mlir::transform::TransformResults &transformResults,

19
mlir/lib/Dialect/Transform/Utils/Utils.cpp
View File

@@ -20,7 +20,11 @@ void mlir::transform::printPackedOrDynamicIndexList(
if (packed) {
assert(values.empty() && (!integers || integers.empty()) &&
"expected no values/integers");
printer << "*(" << packed << " : " << packedType << ")";
printer << "*(" << packed;
if (packedType) {
printer << " : " << packedType;
}
printer << ")";
return;
}
printDynamicIndexList(printer, op, values, integers, valueTypes);
@@ -29,19 +33,20 @@ void mlir::transform::printPackedOrDynamicIndexList(
ParseResult mlir::transform::parsePackedOrDynamicIndexList(
OpAsmParser &parser, std::optional<OpAsmParser::UnresolvedOperand> &packed,
Type &packedType, SmallVectorImpl<OpAsmParser::UnresolvedOperand> &values,
SmallVectorImpl<Type> &valueTypes, DenseI64ArrayAttr &integers) {
SmallVectorImpl<Type> *valueTypes, DenseI64ArrayAttr &integers) {
OpAsmParser::UnresolvedOperand packedOperand;
if (parser.parseOptionalStar().succeeded()) {
if (parser.parseLParen().failed() ||
parser.parseOperand(packedOperand).failed() ||
parser.parseColonType(packedType).failed() ||
parser.parseRParen().failed()) {
parser.parseOperand(packedOperand).failed())
return failure();
if (packedType && (parser.parseColonType(packedType).failed()))
return failure();
if (parser.parseRParen().failed())
return failure();
}
packed.emplace(packedOperand);
integers = parser.getBuilder().getDenseI64ArrayAttr({});
return success();
}
return parseDynamicIndexList(parser, values, integers, &valueTypes);
return parseDynamicIndexList(parser, values, integers, valueTypes);
}

2
mlir/lib/Interfaces/ViewLikeInterface.cpp
View File

@@ -113,7 +113,7 @@ static char getRightDelimiter(AsmParser::Delimiter delimiter) {
void mlir::printDynamicIndexList(OpAsmPrinter &printer, Operation *op,
OperandRange values,
ArrayRef<int64_t> integers,
TypeRange valueTypes, ArrayRef<bool> scalables,
ArrayRef<bool> scalables, TypeRange valueTypes,
AsmParser::Delimiter delimiter) {
char leftDelimiter = getLeftDelimiter(delimiter);
char rightDelimiter = getRightDelimiter(delimiter);

2
mlir/test/Dialect/LLVM/transform-e2e.mlir
View File

@@ -15,7 +15,7 @@ func.func @matmul_tensors(
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%module_op: !transform.any_op {transform.consumed}) {
%0 = transform.structured.match ops{["linalg.matmul"]} in %module_op : (!transform.any_op) -> !transform.any_op
%1, %loops:3 = transform.structured.tile_using_for %0 [2, 2, 2] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:3 = transform.structured.tile_using_for %0 tile_sizes [2, 2, 2] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%2 = transform.get_parent_op %1 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
transform.structured.vectorize_children_and_apply_patterns %2 : (!transform.any_op) -> !transform.any_op
%b = transform.bufferization.one_shot_bufferize layout{IdentityLayoutMap}

6
mlir/test/Dialect/Linalg/generalize-tensor-pack-tile.mlir
View File

@@ -27,7 +27,7 @@ func.func @KCRS_to_KCRSsr(%arg0: tensor<1x1x128x64xf32>, %arg1: tensor<1x1x4x8x8
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.pack"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:4 = transform.structured.tile_using_for %0 [1, 1, 1, 1] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:4 = transform.structured.tile_using_for %0 tile_sizes [1, 1, 1, 1] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -54,7 +54,7 @@ func.func @pad_and_pack(%arg0: tensor<13x15xf32>, %arg1: tensor<2x8x8x2xf32>, %a
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.pack"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.tile_using_for %0 [1, 1] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:2 = transform.structured.tile_using_for %0 tile_sizes [1, 1] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -85,7 +85,7 @@ func.func @KC_to_CKkc(%arg0: tensor<128x256xf32>, %arg1: tensor<32x4x32x8xf32>)
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.pack"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.tile_using_for %0 [1, 1] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:2 = transform.structured.tile_using_for %0 tile_sizes [1, 1] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}

6
mlir/test/Dialect/Linalg/generalize-tensor-unpack-tile.mlir
View File

@@ -8,7 +8,7 @@ func.func @KCRSsr_to_KCRS(%arg0: tensor<1x1x4x8x8x32xf32>, %arg1: tensor<1x1x128
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.unpack"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:4 = transform.structured.tile_using_for %0 [1, 1, 32, 8] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:4 = transform.structured.tile_using_for %0 tile_sizes [1, 1, 32, 8] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -68,7 +68,7 @@ func.func @unpack_and_extract_slice(%arg0: tensor<2x8x8x2xf32>, %arg1: tensor<13
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.unpack"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.tile_using_for %0 [8, 2] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:2 = transform.structured.tile_using_for %0 tile_sizes [8, 2] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -100,7 +100,7 @@ func.func @CKkc_to_KC(%arg0: tensor<32x4x32x8xf32>, %arg1: tensor<128x256xf32>)
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.unpack"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.tile_using_for %0 [32, 8] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:2 = transform.structured.tile_using_for %0 tile_sizes [32, 8] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}

4
mlir/test/Dialect/Linalg/matmul-shared-memory-padding.mlir
View File

@@ -52,7 +52,7 @@ module attributes {transform.with_named_sequence} {
: (!transform.any_op, !transform.any_op) -> (!transform.any_op, !transform.any_op)
// Tile linalg.matmul a second time.
%tiled_linalg_op, %loops = transform.structured.tile_using_for %tiled_matmul_op[0, 0, 16] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%tiled_linalg_op, %loops = transform.structured.tile_using_for %tiled_matmul_op tile_sizes [0, 0, 16] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
// Pad linalg.matmul.
%padded, %pad, %copy_back = transform.structured.pad %tiled_linalg_op
@@ -171,7 +171,7 @@ module attributes {transform.with_named_sequence} {
: (!transform.any_op, !transform.any_op) -> (!transform.any_op, !transform.any_op)
// Tile linalg.matmul a second time.
%tiled_linalg_op, %loops = transform.structured.tile_using_for %tiled_matmul_op[0, 0, 16] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%tiled_linalg_op, %loops = transform.structured.tile_using_for %tiled_matmul_op tile_sizes [0, 0, 16] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
// Pad linalg.matmul.
%padded, %pad, %copy_back = transform.structured.pad %tiled_linalg_op

16
mlir/test/Dialect/Linalg/multisize-tiling-full.mlir
View File

@@ -8,13 +8,13 @@ module attributes {transform.with_named_sequence} {
%1:3 = transform.structured.multitile_sizes %0 { dimension = 0, target_size = 3} : (!transform.any_op) -> !transform.any_op
%t:3 = transform.structured.multitile_sizes %0 { dimension = 1, target_size = 10} : (!transform.any_op) -> !transform.any_op
%2:2 = transform.structured.split %0 after %1#2 { dimension = 0 } : !transform.any_op, !transform.any_op
%3:2 = transform.structured.tile_using_for %2#0 [%1#0] : (!transform.any_op, !transform.any_op) -> (!transform.any_op, !transform.any_op)
%4:2 = transform.structured.tile_using_for %2#1 [%1#1] : (!transform.any_op, !transform.any_op) -> (!transform.any_op, !transform.any_op)
%3:2 = transform.structured.tile_using_for %2#0 tile_sizes [%1#0] : (!transform.any_op, !transform.any_op) -> (!transform.any_op, !transform.any_op)
%4:2 = transform.structured.tile_using_for %2#1 tile_sizes [%1#1] : (!transform.any_op, !transform.any_op) -> (!transform.any_op, !transform.any_op)
%5 = transform.merge_handles %3#0, %4#0 : !transform.any_op
%tt:3 = transform.replicate num(%5) %t#0, %t#1, %t#2 : !transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op
%6:2 = transform.structured.split %5 after %tt#2 { dimension = 1 } : !transform.any_op, !transform.any_op
transform.structured.tile_using_for %6#0 [0, %tt#0] : (!transform.any_op, !transform.any_op) -> (!transform.any_op, !transform.any_op)
transform.structured.tile_using_for %6#1 [0, %tt#1] : (!transform.any_op, !transform.any_op) -> (!transform.any_op, !transform.any_op)
transform.structured.tile_using_for %6#0 tile_sizes [0, %tt#0] : (!transform.any_op, !transform.any_op) -> (!transform.any_op, !transform.any_op)
transform.structured.tile_using_for %6#1 tile_sizes [0, %tt#1] : (!transform.any_op, !transform.any_op) -> (!transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -110,13 +110,13 @@ module attributes {transform.with_named_sequence} {
%1:3 = transform.structured.multitile_sizes %0 { dimension = 0, target_size = 3} : (!transform.any_op) -> !transform.param<i64>
%t:3 = transform.structured.multitile_sizes %0 { dimension = 1, target_size = 10} : (!transform.any_op) -> !transform.param<i64>
%2:2 = transform.structured.split %0 after %1#2 { dimension = 0 } : !transform.any_op, !transform.param<i64>
%3:2 = transform.structured.tile_using_for %2#0 [%1#0] : (!transform.any_op, !transform.param<i64>) -> (!transform.any_op, !transform.any_op)
%4:2 = transform.structured.tile_using_for %2#1 [%1#1] : (!transform.any_op, !transform.param<i64>) -> (!transform.any_op, !transform.any_op)
%3:2 = transform.structured.tile_using_for %2#0 tile_sizes [%1#0] : (!transform.any_op, !transform.param<i64>) -> (!transform.any_op, !transform.any_op)
%4:2 = transform.structured.tile_using_for %2#1 tile_sizes [%1#1] : (!transform.any_op, !transform.param<i64>) -> (!transform.any_op, !transform.any_op)
%5 = transform.merge_handles %3#0, %4#0 : !transform.any_op
%tt:3 = transform.replicate num(%5) %t#0, %t#1, %t#2 : !transform.any_op, !transform.param<i64>, !transform.param<i64>, !transform.param<i64>
%6:2 = transform.structured.split %5 after %tt#2 { dimension = 1 } : !transform.any_op, !transform.param<i64>
transform.structured.tile_using_for %6#0 [0, %tt#0] : (!transform.any_op, !transform.param<i64>) -> (!transform.any_op, !transform.any_op)
transform.structured.tile_using_for %6#1 [0, %tt#1] : (!transform.any_op, !transform.param<i64>) -> (!transform.any_op, !transform.any_op)
transform.structured.tile_using_for %6#0 tile_sizes [0, %tt#0] : (!transform.any_op, !transform.param<i64>) -> (!transform.any_op, !transform.any_op)
transform.structured.tile_using_for %6#1 tile_sizes [0, %tt#1] : (!transform.any_op, !transform.param<i64>) -> (!transform.any_op, !transform.any_op)
transform.yield
}
}

4
mlir/test/Dialect/Linalg/promote.mlir
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@@ -183,7 +183,7 @@ func.func @gemm_shared(%a : memref<?x?xf32>, %b : memref<?x?xf32>, %c : memref<?
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:3 = transform.structured.tile_using_for %0 [16, 16, 16] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:3 = transform.structured.tile_using_for %0 tile_sizes [16, 16, 16] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%2 = transform.structured.promote %1 { operands_to_promote = [0, 1], mapping = [#gpu.memory_space<workgroup>] } : (!transform.any_op) -> !transform.any_op
transform.yield
}
@@ -227,7 +227,7 @@ func.func @gemm_private(%a : memref<?x?xf32>, %b : memref<?x?xf32>, %c : memref<
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:3 = transform.structured.tile_using_for %0 [16, 16, 16] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:3 = transform.structured.tile_using_for %0 tile_sizes [16, 16, 16] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%2 = transform.structured.promote %1 { operands_to_promote = [0, 1], mapping = [#gpu.memory_space<private>] } : (!transform.any_op) -> !transform.any_op
transform.yield
}

2
mlir/test/Dialect/Linalg/promotion_options.mlir
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@@ -37,7 +37,7 @@ func.func @gemm(%a : memref<?x?xf32>, %b : memref<?x?xf32>, %c : memref<?x?xf32>
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:3 = transform.structured.tile_using_for %0 [16, 16, 16] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:3 = transform.structured.tile_using_for %0 tile_sizes [16, 16, 16] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%2 = transform.structured.promote %1 { operands_to_promote = [0, 2], force_full_tiles = [false, false], use_full_tiles_by_default } : (!transform.any_op) -> !transform.any_op
transform.yield
}

2
mlir/test/Dialect/Linalg/tile-conv.mlir
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@@ -12,7 +12,7 @@ func.func @conv(%arg0 : memref<?x?xf32>, %arg1 : memref<?x?xf32>, %arg2 : memref
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.conv_2d"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loop:2 = transform.structured.tile_using_for %0 [2, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loop:2 = transform.structured.tile_using_for %0 tile_sizes [2, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}

4
mlir/test/Dialect/Linalg/tile-indexed.mlir
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@@ -14,7 +14,7 @@ func.func @indexed_vector(%arg0: memref<50xindex>) {
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loop = transform.structured.tile_using_for %0 [10] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%1, %loop = transform.structured.tile_using_for %0 tile_sizes [10] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -46,7 +46,7 @@ func.func @indexed_matrix(%arg0: memref<50x50xindex>) {
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loop:2 = transform.structured.tile_using_for %0 [10, 25] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loop:2 = transform.structured.tile_using_for %0 tile_sizes [10, 25] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}

4
mlir/test/Dialect/Linalg/tile-softmax.mlir
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@@ -39,7 +39,7 @@ func.func @softmax(%arg0: tensor<16x64x256xf32>) -> tensor<16x64x256xf32> {
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.softmax"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loop:2 = transform.structured.tile_using_for %0 [2, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loop:2 = transform.structured.tile_using_for %0 tile_sizes [2, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -149,7 +149,7 @@ func.func @softmax_memref(%arg0: memref<16x64x256xf32>, %arg1: memref<16x64x256x
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.softmax"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loop:2 = transform.structured.tile_using_for %0 [2, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loop:2 = transform.structured.tile_using_for %0 tile_sizes [2, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}

8
mlir/test/Dialect/Linalg/tile-tensors.mlir
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@@ -30,7 +30,7 @@ func.func @matmul_tensors(
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:3 = transform.structured.tile_using_for %0 [2, 3, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:3 = transform.structured.tile_using_for %0 tile_sizes [2, 3, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -57,7 +57,7 @@ func.func @matmul_tensors_with_size_zeros(
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1 = transform.structured.tile_using_for %0 [0, 0, 0] : (!transform.any_op) -> (!transform.any_op)
%1 = transform.structured.tile_using_for %0 tile_sizes [0, 0, 0] : (!transform.any_op) -> (!transform.any_op)
transform.yield
}
}
@@ -90,7 +90,7 @@ func.func @generic_op_tensors(
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:3 = transform.structured.tile_using_for %0 [2, 3, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:3 = transform.structured.tile_using_for %0 tile_sizes [2, 3, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -163,7 +163,7 @@ func.func @fold_extract_slice(
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:3 = transform.structured.tile_using_for %0 [2, 3, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:3 = transform.structured.tile_using_for %0 tile_sizes [2, 3, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}

24
mlir/test/Dialect/Linalg/tile-to-forall.mlir
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@@ -130,8 +130,8 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%sz = transform.structured.match ops{["test.dummy"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1:2 = transform.structured.tile_using_forall %0 tile_sizes *(%sz : !transform.any_op)
: (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%1:2 = transform.structured.tile_using_forall %0 tile_sizes *(%sz)
: (!transform.any_op, !transform.any_op) -> (!transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -333,8 +333,8 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%sz = transform.structured.match ops{["test.dummy"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1:2 = transform.structured.tile_using_forall %0 tile_sizes [%sz : !transform.any_op, 20]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%1:2 = transform.structured.tile_using_forall %0 tile_sizes [%sz, 20]
: (!transform.any_op, !transform.any_op) -> (!transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -492,8 +492,8 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%sz = transform.param.constant 10 : i64 -> !transform.param<i64>
%1:2 = transform.structured.tile_using_forall %0 tile_sizes [%sz : !transform.param<i64>, 20]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%1:2 = transform.structured.tile_using_forall %0 tile_sizes [%sz, 20]
: (!transform.any_op, !transform.param<i64>) -> (!transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -513,8 +513,8 @@ module attributes {transform.with_named_sequence} {
%c20 = transform.param.constant 20 : i64 -> !transform.param<i64>
%sz = transform.merge_handles %c10, %c20 : !transform.param<i64>
// expected-error @below {{requires exactly one parameter associated}}
%1:2 = transform.structured.tile_using_forall %0 tile_sizes [%sz : !transform.param<i64>, 20]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%1:2 = transform.structured.tile_using_forall %0 tile_sizes [%sz, 20]
: (!transform.any_op, !transform.param<i64>) -> (!transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -562,8 +562,8 @@ module attributes {transform.with_named_sequence} {
%c10 = transform.param.constant 10 : i64 -> !transform.any_param
%c20 = transform.param.constant 20 : i64 -> !transform.any_param
%sz = transform.merge_handles %c10, %c20 : !transform.any_param
%1:2 = transform.structured.tile_using_forall %0 tile_sizes *(%sz : !transform.any_param)
: (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%1:2 = transform.structured.tile_using_forall %0 tile_sizes *(%sz)
: (!transform.any_op, !transform.any_param) -> (!transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -581,8 +581,8 @@ module attributes {transform.with_named_sequence} {
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%sz = transform.param.constant "[10 : i64, 20 : i64]" -> !transform.any_param
// expected-error @below {{expected the parameter to be associated with an integer attribute}}
%1:2 = transform.structured.tile_using_forall %0 tile_sizes *(%sz : !transform.any_param)
: (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%1:2 = transform.structured.tile_using_forall %0 tile_sizes *(%sz)
: (!transform.any_op, !transform.any_param) -> (!transform.any_op, !transform.any_op)
transform.yield
}
}

4
mlir/test/Dialect/Linalg/transform-op-compose-masked-vectorize-and-cleanups.mlir
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@@ -22,9 +22,9 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%module: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.matmul"]} in %module
: (!transform.any_op) -> !transform.any_op
%tiled_linalg_op, %loops:3 = transform.structured.tile_using_for %0[64, 128, 256]
%tiled_linalg_op, %loops:3 = transform.structured.tile_using_for %0 tile_sizes [64, 128, 256]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%tiled_linalg_op_0, %loops_1:3 = transform.structured.tile_using_for %tiled_linalg_op[8, 8, 8]
%tiled_linalg_op_0, %loops_1:3 = transform.structured.tile_using_for %tiled_linalg_op tile_sizes [8, 8, 8]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.structured.vectorize %tiled_linalg_op_0 vector_sizes [8, 8, 8]
: !transform.any_op

2
mlir/test/Dialect/Linalg/transform-op-fuse.mlir
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@@ -95,7 +95,7 @@ module attributes {transform.with_named_sequence} {
%0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.fuse %0 {tile_sizes = [5, 0, 7], tile_interchange = [0, 2, 1]}
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%2, %loops_2 = transform.structured.tile_using_for %1 [0, 4]
%2, %loops_2 = transform.structured.tile_using_for %1 tile_sizes [0, 4]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op)
transform.yield
}

10
mlir/test/Dialect/Linalg/transform-op-hoist-pad-build-packing-loop-nest.mlir
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@@ -15,7 +15,7 @@ module attributes {transform.with_named_sequence} {
%matmul = transform.structured.match ops{["linalg.matmul"]} in %arg1
: (!transform.any_op) -> !transform.any_op
%matmul_l1, %loops_l1 = transform.structured.tile_using_for %matmul [5] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%matmul_l1, %loops_l1 = transform.structured.tile_using_for %matmul tile_sizes [5] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%matmul_padded, %0, %copy_back = transform.structured.pad %matmul_l1 {
padding_values=[0.0: f32, 0.0 : f32, 0.0 : f32],
@@ -49,7 +49,7 @@ module attributes {transform.with_named_sequence} {
%matmul = transform.structured.match ops{["linalg.matmul"]} in %arg1
: (!transform.any_op) -> !transform.any_op
%matmul_l1, %loops_l1 = transform.structured.tile_using_for %matmul [5] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%matmul_l1, %loops_l1 = transform.structured.tile_using_for %matmul tile_sizes [5] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%matmul_padded, %0, %copy_back = transform.structured.pad %matmul_l1 {
padding_values=[0.0: f32, 0.0 : f32, 0.0 : f32],
@@ -89,7 +89,7 @@ module attributes {transform.with_named_sequence} {
%matmul = transform.structured.match ops{["linalg.matmul"]} in %arg1
: (!transform.any_op) -> !transform.any_op
%matmul_l1, %loops_l1 = transform.structured.tile_using_for %matmul [5] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%matmul_l1, %loops_l1 = transform.structured.tile_using_for %matmul tile_sizes [5] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%matmul_padded, %0, %copy_back = transform.structured.pad %matmul_l1 {
padding_values=[0.0: f32, 0.0 : f32, 0.0 : f32],
@@ -129,7 +129,7 @@ module attributes {transform.with_named_sequence} {
%matmul = transform.structured.match ops{["linalg.matmul"]} in %arg1
: (!transform.any_op) -> !transform.any_op
%matmul_l1, %loops_l1 = transform.structured.tile_using_for %matmul [5] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%matmul_l1, %loops_l1 = transform.structured.tile_using_for %matmul tile_sizes [5] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%matmul_padded, %0, %copy_back = transform.structured.pad %matmul_l1 {
padding_values=[0.0: f32, 0.0 : f32, 0.0 : f32],
@@ -167,7 +167,7 @@ module attributes {transform.with_named_sequence} {
%matmul = transform.structured.match ops{["linalg.matmul"]} in %arg1
: (!transform.any_op) -> !transform.any_op
%matmul_l1, %loops_l1:2 = transform.structured.tile_using_for %matmul [5, 0, 7] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%matmul_l1, %loops_l1:2 = transform.structured.tile_using_for %matmul tile_sizes [5, 0, 7] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%matmul_padded, %0, %copy_back = transform.structured.pad %matmul_l1 {
padding_values=[0.0: f32, 0.0 : f32, 0.0 : f32],

10
mlir/test/Dialect/Linalg/transform-op-hoist-pad.mlir
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@@ -15,7 +15,7 @@ module attributes {transform.with_named_sequence} {
: (!transform.any_op) -> !transform.any_op
%matmul_l1, %loops_l1 = transform.structured.tile_using_for %matmul [5] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%matmul_l1, %loops_l1 = transform.structured.tile_using_for %matmul tile_sizes [5] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%matmul_padded, %0, %copy_back = transform.structured.pad %matmul_l1 {
padding_values=[0.0: f32, 0.0 : f32, 0.0 : f32],
@@ -53,7 +53,7 @@ module attributes {transform.with_named_sequence} {
: (!transform.any_op) -> !transform.any_op
%matmul_l1, %loops_l1 = transform.structured.tile_using_for %matmul [5] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%matmul_l1, %loops_l1 = transform.structured.tile_using_for %matmul tile_sizes [5] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%matmul_padded, %0, %copy_back = transform.structured.pad %matmul_l1 {
padding_values=[0.0: f32, 0.0 : f32, 0.0 : f32],
@@ -98,7 +98,7 @@ module attributes {transform.with_named_sequence} {
: (!transform.any_op) -> !transform.any_op
%matmul_l1, %loops_l1 = transform.structured.tile_using_for %matmul [5] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%matmul_l1, %loops_l1 = transform.structured.tile_using_for %matmul tile_sizes [5] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%matmul_padded, %0, %copy_back = transform.structured.pad %matmul_l1 {
padding_values=[0.0: f32, 0.0 : f32, 0.0 : f32],
@@ -145,7 +145,7 @@ module attributes {transform.with_named_sequence} {
: (!transform.any_op) -> !transform.any_op
%matmul_l1, %loops_l1 = transform.structured.tile_using_for %matmul [5] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%matmul_l1, %loops_l1 = transform.structured.tile_using_for %matmul tile_sizes [5] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%matmul_padded, %0, %copy_back = transform.structured.pad %matmul_l1 {
padding_values=[0.0: f32, 0.0 : f32, 0.0 : f32],
@@ -191,7 +191,7 @@ module attributes {transform.with_named_sequence} {
: (!transform.any_op) -> !transform.any_op
%matmul_l1, %loops_l1:2 = transform.structured.tile_using_for %matmul [5, 0, 7] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%matmul_l1, %loops_l1:2 = transform.structured.tile_using_for %matmul tile_sizes [5, 0, 7] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%matmul_padded, %0, %copy_back = transform.structured.pad %matmul_l1 {
padding_values=[0.0: f32, 0.0 : f32, 0.0 : f32],

4
mlir/test/Dialect/Linalg/transform-op-mmt4d-to-fma.mlir
View File

@@ -20,10 +20,10 @@ module attributes {transform.with_named_sequence} {
// Step 1: Tile
// Tile parallel dims
%tiled_linalg_op_p, %loops:4 = transform.structured.tile_using_for %mmt4d[1, 1, 0, 8, 8, 0]
%tiled_linalg_op_p, %loops:4 = transform.structured.tile_using_for %mmt4d tile_sizes [1, 1, 0, 8, 8, 0]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
// Tile reduction dims
%tiled_linalg_op_r, %loops2:2 = transform.structured.tile_using_for %tiled_linalg_op_p[0, 0, 1, 0, 0, 1]
%tiled_linalg_op_r, %loops2:2 = transform.structured.tile_using_for %tiled_linalg_op_p tile_sizes [0, 0, 1, 0, 0, 1]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
// Step 2: Vectorize

4
mlir/test/Dialect/Linalg/transform-op-pack.mlir
View File

@@ -372,8 +372,8 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%sz = transform.structured.match ops{["some_tile_size"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1 = transform.structured.pack %0 packed_sizes = [0, %sz : !transform.any_op, %sz : !transform.any_op]
: (!transform.any_op) -> (!transform.op<"linalg.generic">)
%1 = transform.structured.pack %0 packed_sizes = [0, %sz, %sz]
: (!transform.any_op, !transform.any_op, !transform.any_op) -> (!transform.op<"linalg.generic">)
transform.yield
}
}

4
mlir/test/Dialect/Linalg/transform-op-peel-and-vectorize-conv.mlir
View File

@@ -61,11 +61,11 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%root: !transform.any_op {transform.consume}) {
// 1. Tile parallel dims
%1 = transform.structured.match ops{["linalg.depthwise_conv_2d_nhwc_hwc"]} in %root : (!transform.any_op) -> !transform.any_op
%tiled_linalg_op_0, %loops_1:4 = transform.structured.tile_using_for %1[1, 1, 4, [4], 0, 0] : (!transform.any_op) -> (!transform.any_op, !transform.op<"scf.for">, !transform.op<"scf.for">, !transform.op<"scf.for">, !transform.op<"scf.for">)
%tiled_linalg_op_0, %loops_1:4 = transform.structured.tile_using_for %1 tile_sizes [1, 1, 4, [4], 0, 0] : (!transform.any_op) -> (!transform.any_op, !transform.op<"scf.for">, !transform.op<"scf.for">, !transform.op<"scf.for">, !transform.op<"scf.for">)
// 2. Tile reduction dims
%2 = transform.structured.match ops{["linalg.depthwise_conv_2d_nhwc_hwc"]} in %loops_1#3 : (!transform.op<"scf.for">) -> !transform.any_op
%tiled_linalg_op_1, %loops_2:2 = transform.structured.tile_using_for %2[0, 0, 0, 0, 1, 1] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%tiled_linalg_op_1, %loops_2:2 = transform.structured.tile_using_for %2 tile_sizes [0, 0, 0, 0, 1, 1] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
// 3. Decompose 2D conv into 2 x 1D conv
%3 = transform.structured.match ops{["linalg.depthwise_conv_2d_nhwc_hwc"]} in %loops_1#3 : (!transform.op<"scf.for">) -> !transform.any_op

2
mlir/test/Dialect/Linalg/transform-op-peel-and-vectorize.mlir
View File

@@ -67,7 +67,7 @@ module attributes {transform.with_named_sequence} {
%matmul = transform.structured.match ops{["linalg.matmul"]} in %root : (!transform.any_op) -> !transform.any_op
// 1. Scalable tiling
%_, %loop_1, %loop_2, %loop_3 =
transform.structured.tile_using_for %matmul [8, [16], 1] : (!transform.any_op)
transform.structured.tile_using_for %matmul tile_sizes [8, [16], 1] : (!transform.any_op)
-> (!transform.any_op, !transform.op<"scf.for">, !transform.op<"scf.for">,!transform.op<"scf.for">)
// 2. Loop peeling (only the middle dimension)

2
mlir/test/Dialect/Linalg/transform-op-scalarize.mlir
View File

@@ -21,7 +21,7 @@ func.func @scalarize(%arg0: tensor<24x12xf32>,
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops = transform.structured.tile_using_for %0 [10, 0, 0] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%1, %loops = transform.structured.tile_using_for %0 tile_sizes [10, 0, 0] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%2 = transform.structured.scalarize %1 : (!transform.any_op) -> !transform.any_op
transform.yield
}

14
mlir/test/Dialect/Linalg/transform-op-tile.mlir
View File

@@ -3,7 +3,7 @@
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:3 = transform.structured.tile_using_for %0 [4, 4, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:3 = transform.structured.tile_using_for %0 tile_sizes [4, 4, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -42,7 +42,7 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1 = transform.structured.match ops{["func.call"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%2, %loops:3 = transform.structured.tile_using_for %0 [%1, %1, 4] : (!transform.any_op, !transform.any_op, !transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%2, %loops:3 = transform.structured.tile_using_for %0 tile_sizes [%1, %1, 4] : (!transform.any_op, !transform.any_op, !transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -86,7 +86,7 @@ module attributes {transform.with_named_sequence} {
// expected-note @below {{for this parameter}}
%1 = transform.test_produce_param (0 : i64) : !transform.param<i64>
// expected-error @below {{expected as many parameter values (0) as target ops (2)}}
transform.structured.tile_using_for %0 [%1, %1, %1]
transform.structured.tile_using_for %0 tile_sizes [%1, %1, %1]
: (!transform.any_op, !transform.param<i64>, !transform.param<i64>, !transform.param<i64>)
-> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
@@ -113,7 +113,7 @@ module attributes {transform.with_named_sequence} {
// expected-note @below {{for this handle}}
%1 = transform.structured.match ops{["arith.constant"]} in %arg1 : (!transform.any_op) -> !transform.any_op
// expected-error @below {{expected as many dynamic size-producing operations (0) as target ops (2)}}
transform.structured.tile_using_for %0 [%1, %1, 1]
transform.structured.tile_using_for %0 tile_sizes [%1, %1, 1]
: (!transform.any_op, !transform.any_op, !transform.any_op)
-> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
@@ -194,7 +194,7 @@ module {
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loop = transform.structured.tile_using_for %0 [[4]] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%1, %loop = transform.structured.tile_using_for %0 tile_sizes [[4]] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -230,7 +230,7 @@ func.func @scalable_and_fixed_length_tile(
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:3 = transform.structured.tile_using_for %0 [4, 4, [4]] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:3 = transform.structured.tile_using_for %0 tile_sizes [4, 4, [4]] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -249,7 +249,7 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
// expected-error @below {{too many tiles provided, expected at most 3 found 4}}
%1, %loops = transform.structured.tile_using_for %0 [1, 0, 0, 0] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%1, %loops = transform.structured.tile_using_for %0 tile_sizes [1, 0, 0, 0] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
transform.yield
}
}

2
mlir/test/Dialect/Linalg/transform-ops-invalid.mlir
View File

@@ -77,7 +77,7 @@ transform.sequence failures(propagate) {
transform.sequence failures(propagate) {
^bb0(%arg0: !transform.any_op):
%0 = transform.param.constant 2 : i64 -> !transform.param<i64>
// expected-error@below {{custom op 'transform.structured.vectorize' expected 2 operand type(s)}}
// expected-error@below {{custom op 'transform.structured.vectorize' 1 operands present, but expected 2}}
transform.structured.vectorize %arg0 vector_sizes [%0, 2] : !transform.any_op, !transform.param<i64>, !transform.param<i64>
}

6
mlir/test/Dialect/Linalg/transform-ops.mlir
View File

@@ -3,7 +3,7 @@
transform.sequence failures(propagate) {
^bb1(%arg0: !transform.any_op):
// CHECK %{{.*}}, %{{.*}}:2 = transform.structured.tile
%0, %1:2 = transform.structured.tile_using_for %arg0 [2, 0, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%0, %1:2 = transform.structured.tile_using_for %arg0 tile_sizes [2, 0, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
}
// check that the Attributes of `tile_using_for` are preserved through printing
@@ -11,9 +11,9 @@ transform.sequence failures(propagate) {
transform.sequence failures(propagate) {
^bb1(%arg0: !transform.any_op):
// CHECK %{{.*}}, %{{.*}}:2 = transform.structured.tile %arg0 [2, 0, 3] interchange = [2, 1] {test_attr1 = 1 : i64, test_attr2}
%0, %1:2 = transform.structured.tile_using_for %arg0 [2, 0, 3] interchange = [2, 1] {test_attr1 = 1 : i64, test_attr2}: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%0, %1:2 = transform.structured.tile_using_for %arg0 tile_sizes [2, 0, 3] interchange = [2, 1] {test_attr1 = 1 : i64, test_attr2}: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
// CHECK %{{.*}}, %{{.*}}:2 = transform.structured.tile %arg0 [4, 5, 3] {test_attr3 = 1 : i64, test_attr4}
%2, %3:2 = transform.structured.tile_using_for %0 [0, 5, 3] {test_attr3 = 1 : i64, test_attr4}: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%2, %3:2 = transform.structured.tile_using_for %0 tile_sizes [0, 5, 3] {test_attr3 = 1 : i64, test_attr4}: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
}
transform.sequence failures(propagate) {

20
mlir/test/Dialect/Linalg/transform-patterns.mlir
View File

@@ -12,7 +12,7 @@ func.func @dot(%x: memref<?xf32, strided<[1], offset: ?>>,
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.dot"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loop = transform.structured.tile_using_for %0 [8000] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%1, %loop = transform.structured.tile_using_for %0 tile_sizes [8000] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -38,7 +38,7 @@ func.func @matvec(%A: memref<?x?xf32, strided<[?, 1], offset: ?>>,
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.matvec"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.tile_using_for %0 [5, 6] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:2 = transform.structured.tile_using_for %0 tile_sizes [5, 6] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -67,10 +67,10 @@ func.func @matmul(%A: memref<?x?xf32, strided<[?, 1], offset: ?>>,
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:3 = transform.structured.tile_using_for %0 [2000, 3000, 4000] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%2, %loops_2:3 = transform.structured.tile_using_for %1 [200, 300, 400] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%3, %loops_3:3 = transform.structured.tile_using_for %2 [20, 30, 40] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%4, %loops_4:3 = transform.structured.tile_using_for %3 [2, 3, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:3 = transform.structured.tile_using_for %0 tile_sizes [2000, 3000, 4000] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%2, %loops_2:3 = transform.structured.tile_using_for %1 tile_sizes [200, 300, 400] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%3, %loops_3:3 = transform.structured.tile_using_for %2 tile_sizes [20, 30, 40] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%4, %loops_4:3 = transform.structured.tile_using_for %3 tile_sizes [2, 3, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -170,7 +170,7 @@ func.func @matvec_perm(%A: memref<?x?xf32, strided<[?, 1], offset: ?>>,
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.matvec"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.tile_using_for %0 [5, 6] interchange = [1, 0] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:2 = transform.structured.tile_using_for %0 tile_sizes [5, 6] interchange = [1, 0] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -199,9 +199,9 @@ func.func @matmul_perm(%A: memref<?x?xf32, strided<[?, 1], offset: ?>>,
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:3 = transform.structured.tile_using_for %0 [2000, 3000, 4000] interchange = [1, 2, 0] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%2, %loops_2:3 = transform.structured.tile_using_for %1 [200, 300, 400] interchange = [1, 0, 2] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%3, %loops_3:3 = transform.structured.tile_using_for %2 [20, 30, 40] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:3 = transform.structured.tile_using_for %0 tile_sizes [2000, 3000, 4000] interchange = [1, 2, 0] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%2, %loops_2:3 = transform.structured.tile_using_for %1 tile_sizes [200, 300, 400] interchange = [1, 0, 2] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%3, %loops_3:3 = transform.structured.tile_using_for %2 tile_sizes [20, 30, 40] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}

12
mlir/test/Dialect/Linalg/vectorize-tensor-extract-masked.mlir
View File

@@ -28,7 +28,7 @@ func.func @masked_static_vectorize_nd_tensor_extract_with_affine_apply_contiguou
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
transform.structured.vectorize %0 vector_sizes [1, 4] vectorize_nd_extract : !transform.any_op
transform.structured.vectorize %0 vector_sizes [1, 4] {vectorize_nd_extract} : !transform.any_op
transform.yield
}
}
@@ -85,7 +85,7 @@ func.func @masked_dynamic_vectorize_nd_tensor_extract_with_affine_apply_contiguo
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
transform.structured.vectorize %0 vector_sizes [1, 4] vectorize_nd_extract : !transform.any_op
transform.structured.vectorize %0 vector_sizes [1, 4] {vectorize_nd_extract} : !transform.any_op
transform.yield
}
}
@@ -125,7 +125,7 @@ func.func @masked_vectorize_nd_tensor_extract_with_affine_apply_gather(%6: tenso
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
transform.structured.vectorize %0 vector_sizes [1, 4] vectorize_nd_extract : !transform.any_op
transform.structured.vectorize %0 vector_sizes [1, 4] {vectorize_nd_extract} : !transform.any_op
transform.yield
}
}
@@ -182,7 +182,7 @@ func.func @masked_dynamic_vectorize_nd_tensor_extract_with_affine_apply_gather(%
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
transform.structured.vectorize %0 vector_sizes [1, 4] vectorize_nd_extract : !transform.any_op
transform.structured.vectorize %0 vector_sizes [1, 4] {vectorize_nd_extract} : !transform.any_op
transform.yield
}
}
@@ -234,7 +234,7 @@ func.func @extract_masked_vectorize(%arg0: tensor<?x?xf32>, %arg1: tensor<?x?xf3
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
transform.structured.vectorize %0 vector_sizes [3, 3] vectorize_nd_extract : !transform.any_op
transform.structured.vectorize %0 vector_sizes [3, 3] {vectorize_nd_extract} : !transform.any_op
transform.yield
}
}
@@ -279,7 +279,7 @@ func.func @tensor_extract_dynamic_shape(%arg1: tensor<123x321xf32>, %arg2: tenso
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
transform.structured.vectorize %0 vector_sizes [1, 3, 8] vectorize_nd_extract : !transform.any_op
transform.structured.vectorize %0 vector_sizes [1, 3, 8] {vectorize_nd_extract} : !transform.any_op
transform.yield
}
}

34
mlir/test/Dialect/Tensor/tiling.mlir
View File

@@ -34,7 +34,7 @@ func.func @dynamic_pad_tensor_3_4(%input_tensor: tensor<?x?xf32>,
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.tile_using_for %0 [2, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:2 = transform.structured.tile_using_for %0 tile_sizes [2, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -73,7 +73,7 @@ func.func @dynamic_pad_tensor_0_3(%input_tensor: tensor<?x?xf32>,
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loop = transform.structured.tile_using_for %0 [0, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%1, %loop = transform.structured.tile_using_for %0 tile_sizes [0, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -109,7 +109,7 @@ func.func @static_pad_tensor_3_4(%input_tensor: tensor<7x9xf32>,
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.tile_using_for %0 [2, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:2 = transform.structured.tile_using_for %0 tile_sizes [2, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -142,7 +142,7 @@ func.func @static_pad_tensor_0_3(%input_tensor: tensor<7x9xf32>,
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loop = transform.structured.tile_using_for %0 [0, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%1, %loop = transform.structured.tile_using_for %0 tile_sizes [0, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -179,7 +179,7 @@ func.func @static_pad_tile_evenly_0_3(%input_tensor: tensor<7x9xf32>,
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.pad"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loop = transform.structured.tile_using_for %0 [0, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%1, %loop = transform.structured.tile_using_for %0 tile_sizes [0, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -217,7 +217,7 @@ func.func @NC_to_NCnc(%arg0: tensor<128x256xf32>, %arg1: tensor<4x8x32x32xf32>)
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.pack"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.tile_using_for %0 [2, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:2 = transform.structured.tile_using_for %0 tile_sizes [2, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -247,7 +247,7 @@ func.func @KC_to_CKkc(%arg0: tensor<128x256xf32>, %arg1: tensor<32x4x32x8xf32>)
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.pack"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.tile_using_for %0 [2, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:2 = transform.structured.tile_using_for %0 tile_sizes [2, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -284,7 +284,7 @@ func.func @pad_and_pack_static(%input: tensor<13x15xf32>, %output: tensor<2x8x8x
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.pack"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.tile_using_for %0 [2, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:2 = transform.structured.tile_using_for %0 tile_sizes [2, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -335,7 +335,7 @@ func.func @pad_and_pack_partially_dynamic(%input: tensor<?x?xf32>, %output: tens
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.pack"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.tile_using_for %0 [2, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:2 = transform.structured.tile_using_for %0 tile_sizes [2, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -391,7 +391,7 @@ func.func @pad_and_pack_fully_dynamic(%source: tensor<?x?xf32>, %dest: tensor<?x
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.pack"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.tile_using_for %0 [2, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:2 = transform.structured.tile_using_for %0 tile_sizes [2, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -440,7 +440,7 @@ func.func @NCnc_to_NC(%source: tensor<8x8x32x16xf32>, %dest: tensor<256x128xf32>
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.unpack"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.tile_using_for %0 [2, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:2 = transform.structured.tile_using_for %0 tile_sizes [2, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -488,7 +488,7 @@ func.func @CKkc_to_KC(%source: tensor<32x4x32x8xf32>, %dest: tensor<128x256xf32>
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.unpack"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.tile_using_for %0 [2, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:2 = transform.structured.tile_using_for %0 tile_sizes [2, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -526,7 +526,7 @@ func.func @perfect_CKkc_to_KC(%source: tensor<32x4x2x4xf32>, %dest: tensor<8x128
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.unpack"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.tile_using_for %0 [2, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:2 = transform.structured.tile_using_for %0 tile_sizes [2, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -570,7 +570,7 @@ func.func @dynamic_perfect_CKkc_to_KC(%source: tensor<?x?x2x2xf32>, %dest: tenso
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.unpack"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.tile_using_for %0 [2, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:2 = transform.structured.tile_using_for %0 tile_sizes [2, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -607,7 +607,7 @@ func.func @perfect_NKPQk_to_NPQK(%source: tensor<1x4x6x6x2xf32>, %dest: tensor<1
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.unpack"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:4 = transform.structured.tile_using_for %0 [1, 1, 1, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:4 = transform.structured.tile_using_for %0 tile_sizes [1, 1, 1, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -635,7 +635,7 @@ func.func @fully_dynamic_unpack(%source: tensor<?x?x?x?xf32>, %dest: tensor<?x?x
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.unpack"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.tile_using_for %0 [4, 8] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:2 = transform.structured.tile_using_for %0 tile_sizes [4, 8] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}
@@ -671,7 +671,7 @@ func.func @perfect_NPQK_to_NKPQk(%source: tensor<1x6x6x8xf32>, %dest: tensor<1x4
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["tensor.pack"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:4 = transform.structured.tile_using_for %0 [1, 1, 1, 1] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:4 = transform.structured.tile_using_for %0 tile_sizes [1, 1, 1, 1] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}

8
mlir/test/Dialect/Transform/ops.mlir
View File

@@ -101,19 +101,19 @@ transform.sequence failures(propagate) {
}
// CHECK: transform.sequence
// CHECK: transform.structured.tile_using_for %0[4, 4, [4]]
// CHECK: transform.structured.tile_using_for %0 tile_sizes [4, 4, [4]]
transform.sequence failures(propagate) {
^bb0(%arg1: !transform.any_op):
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
transform.structured.tile_using_for %0 [4, 4, [4]] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.structured.tile_using_for %0 tile_sizes [4, 4, [4]] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
}
// CHECK: transform.sequence
// CHECK: transform.structured.tile_using_for %0{{\[}}[2], 4, 8]
// CHECK: transform.structured.tile_using_for %0 tile_sizes {{\[}}[2], 4, 8]
transform.sequence failures(propagate) {
^bb0(%arg1: !transform.any_op):
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
transform.structured.tile_using_for %0 [[2], 4, 8] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.structured.tile_using_for %0 tile_sizes [[2], 4, 8] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
}
// CHECK: transform.sequence

2
mlir/test/Dialect/Transform/selective-targeting.mlir
View File

@@ -79,7 +79,7 @@ module attributes {transform.with_named_sequence} {
transform.sequence %arg0 : !transform.any_op failures(propagate) {
^bb1(%arg1: !transform.any_op):
%0 = pdl_match @pdl_target_attrA in %arg1 : (!transform.any_op) -> !transform.any_op
transform.structured.tile_using_for %0 [4, 4, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.structured.tile_using_for %0 tile_sizes [4, 4, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%1 = pdl_match @pdl_target_attrC in %arg1 : (!transform.any_op) -> !transform.any_op
%2 = get_parent_op %1 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
transform.structured.vectorize_children_and_apply_patterns %2 : (!transform.any_op) -> !transform.any_op

2
mlir/test/Dialect/Vector/transform-vector.mlir
View File

@@ -16,7 +16,7 @@ func.func @matmul_tensors(
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%module_op: !transform.any_op {transform.consumed}) {
%0 = transform.structured.match ops{["linalg.matmul"]} in %module_op : (!transform.any_op) -> !transform.any_op
%1, %loops:3 = transform.structured.tile_using_for %0 [8, 4, 2]
%1, %loops:3 = transform.structured.tile_using_for %0 tile_sizes [8, 4, 2]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%2 = transform.get_parent_op %1 {isolated_from_above} : (!transform.any_op) -> !transform.any_op
transform.structured.vectorize_children_and_apply_patterns %2 : (!transform.any_op) -> !transform.any_op

2
mlir/test/Integration/Dialect/Linalg/CPU/ArmSME/matmul-transpose-a.mlir
View File

@@ -61,7 +61,7 @@ module attributes {transform.with_named_sequence} {
// Step 1: Tile for size [4] x [4], which corresponds to SVLs x SVLs, where
// SVLs is the number of 32-bit elements in a vector of SVL bits.
%tiled_linalg_op, %loops:3 = transform.structured.tile_using_for %matmul_transpose_a[[4], [4], 1]
%tiled_linalg_op, %loops:3 = transform.structured.tile_using_for %matmul_transpose_a tile_sizes [[4], [4], 1]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
// Step 2: Vectorize.

2
mlir/test/Integration/Dialect/Linalg/CPU/ArmSME/matmul.mlir
View File

@@ -59,7 +59,7 @@ module attributes {transform.with_named_sequence} {
// Step 1: Tile for size [4] x [4], which corresponds to SVLs x SVLs, where
// SVLs is the number of 32-bit elements in a vector of SVL bits.
%tiled_linalg_op, %loops:3 = transform.structured.tile_using_for %matmul[[4], [4], 1]
%tiled_linalg_op, %loops:3 = transform.structured.tile_using_for %matmul tile_sizes [[4], [4], 1]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
// Step 2: Vectorize.

2
mlir/test/Integration/Dialect/Linalg/CPU/ArmSME/multi-tile-matmul-mixed-types.mlir
View File

@@ -84,7 +84,7 @@ module attributes {transform.with_named_sequence} {
// Step 1: Tile for size [8] x [8] (unrolled by 4), which corresponds to
// (2 x SVLs) x (2 x SVLs), where SVLs is the number of 32-bit elements in a
// vector of SVL bits. This uses all four 32-bit SME virtual tiles.
%tiled_linalg_op, %loop_i, %loop_j, %loop_k = transform.structured.tile_using_for %matmul[[8], [8], 4]
%tiled_linalg_op, %loop_i, %loop_j, %loop_k = transform.structured.tile_using_for %matmul tile_sizes [[8], [8], 4]
: (!transform.any_op) -> (!transform.any_op, !transform.op<"scf.for">, !transform.op<"scf.for">, !transform.op<"scf.for">)
// Step 2: Vectorize.

2
mlir/test/Integration/Dialect/Linalg/CPU/ArmSME/multi-tile-matmul.mlir
View File

@@ -72,7 +72,7 @@ module attributes {transform.with_named_sequence} {
// Step 1: Tile for size [8] x [8] (unrolled by 4), which corresponds to
// (2 x SVLs) x (2 x SVLs), where SVLs is the number of 32-bit elements in a
// vector of SVL bits. This uses all four 32-bit SME virtual tiles.
%tiled_linalg_op, %loop_i, %loop_j, %loop_k = transform.structured.tile_using_for %matmul[[8], [8], 4]
%tiled_linalg_op, %loop_i, %loop_j, %loop_k = transform.structured.tile_using_for %matmul tile_sizes [[8], [8], 4]
: (!transform.any_op) -> (!transform.any_op, !transform.op<"scf.for">, !transform.op<"scf.for">, !transform.op<"scf.for">)
// Step 2: Vectorize.

2
mlir/test/Integration/Dialect/Linalg/CPU/ArmSVE/matmul.mlir
View File

@@ -96,7 +96,7 @@ module attributes {transform.with_named_sequence} {
: (!transform.op<"func.func">) -> !transform.any_op
// Step 1: Tile
%tiled_matmul, %loops:3 = transform.structured.tile_using_for %matmul [2, [4], 1]
%tiled_matmul, %loops:3 = transform.structured.tile_using_for %matmul tile_sizes [2, [4], 1]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
// Step 2: Vectorize

4
mlir/test/Integration/Dialect/Linalg/CPU/mmt4d.mlir
View File

@@ -70,10 +70,10 @@ module @transforms attributes { transform.with_named_sequence } {
// Step 1: Tile
// Tile parallel dims
%tiled_linalg_op_p, %loops:4 = transform.structured.tile_using_for %mmt4d[1, 1, 0, 3, 3, 0]
%tiled_linalg_op_p, %loops:4 = transform.structured.tile_using_for %mmt4d tile_sizes [1, 1, 0, 3, 3, 0]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
// Tile reduction dims
%tiled_linalg_op_r, %loops2:2 = transform.structured.tile_using_for %tiled_linalg_op_p[0, 0, 1, 0, 0, 1]
%tiled_linalg_op_r, %loops2:2 = transform.structured.tile_using_for %tiled_linalg_op_p tile_sizes [0, 0, 1, 0, 0, 1]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
// Step 2: Vectorize

4
mlir/test/Integration/Dialect/Linalg/CPU/pack-unpack-mmt4d.mlir
View File

@@ -107,10 +107,10 @@ module @transforms attributes { transform.with_named_sequence } {
// Step 1: Tile
// Tile parallel dims
%tiled_linalg_op_p, %loops:4 = transform.structured.tile_using_for %mmt4d[1, 1, 0, 8, 8, 0]
%tiled_linalg_op_p, %loops:4 = transform.structured.tile_using_for %mmt4d tile_sizes [1, 1, 0, 8, 8, 0]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
// Tile reduction dims
%tiled_linalg_op_r, %loops2:2 = transform.structured.tile_using_for %tiled_linalg_op_p[0, 0, 1, 0, 0, 1]
%tiled_linalg_op_r, %loops2:2 = transform.structured.tile_using_for %tiled_linalg_op_p tile_sizes [0, 0, 1, 0, 0, 1]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
// Step 2: Vectorize

2
mlir/test/Integration/Dialect/Linalg/CPU/test-conv-1d-call.mlir
View File

@@ -27,7 +27,7 @@ func.func @conv_1d(%arg0: memref<?xf32>, %arg1: memref<?xf32>, %arg2: memref<?xf
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.conv_1d"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loop = transform.structured.tile_using_for %0 [4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
%1, %loop = transform.structured.tile_using_for %0 tile_sizes [4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
transform.yield
}
}

2
mlir/test/Integration/Dialect/Linalg/CPU/test-conv-1d-nwc-wcf-call.mlir
View File

@@ -29,7 +29,7 @@ func.func @conv_1d_nwc_wcf(%arg0: memref<?x?x?xf32>, %arg1: memref<?x?x?xf32>, %
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.conv_1d_nwc_wcf"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.tile_using_for %0 [2, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:2 = transform.structured.tile_using_for %0 tile_sizes [2, 4] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}

2
mlir/test/Integration/Dialect/Linalg/CPU/test-conv-2d-call.mlir
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@@ -27,7 +27,7 @@ func.func @conv_2d(%arg0: memref<?x?xf32>, %arg1: memref<?x?xf32>, %arg2: memref
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.conv_2d"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:2 = transform.structured.tile_using_for %0 [2, 2] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:2 = transform.structured.tile_using_for %0 tile_sizes [2, 2] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}

2
mlir/test/Integration/Dialect/Linalg/CPU/test-conv-2d-nhwc-hwcf-call.mlir
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@@ -29,7 +29,7 @@ func.func @conv_2d_nhwc_hwcf(%arg0: memref<?x?x?x?xf32>, %arg1: memref<?x?x?x?xf
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.conv_2d_nhwc_hwcf"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:4 = transform.structured.tile_using_for %0 [2, 3, 3, 2] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:4 = transform.structured.tile_using_for %0 tile_sizes [2, 3, 3, 2] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}

2
mlir/test/Integration/Dialect/Linalg/CPU/test-conv-3d-call.mlir
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@@ -27,7 +27,7 @@ func.func @conv_3d(%arg0: memref<?x?x?xf32>, %arg1: memref<?x?x?xf32>, %arg2: me
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.conv_3d"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:3 = transform.structured.tile_using_for %0 [2, 2, 2] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:3 = transform.structured.tile_using_for %0 tile_sizes [2, 2, 2] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}

2
mlir/test/Integration/Dialect/Linalg/CPU/test-conv-3d-ndhwc-dhwcf-call.mlir
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@@ -29,7 +29,7 @@ func.func @conv_3d_ndhwc_dhwcf(%arg0: memref<?x?x?x?x?xf32>, %arg1: memref<?x?x?
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.conv_3d_ndhwc_dhwcf"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:3 = transform.structured.tile_using_for %0 [0, 5, 5, 5] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:3 = transform.structured.tile_using_for %0 tile_sizes [0, 5, 5, 5] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}

2
mlir/test/Integration/Dialect/Linalg/CPU/test-tensor-matmul.mlir
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@@ -39,7 +39,7 @@ func.func @main() {
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:3 = transform.structured.tile_using_for %0 [1, 2, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
%1, %loops:3 = transform.structured.tile_using_for %0 tile_sizes [1, 2, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}

12
mlir/test/Interfaces/TilingInterface/tile-pad-using-interface.mlir
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@@ -14,7 +14,7 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1 : !transform.any_op {transform.readonly}) {
%pad = transform.structured.match ops{["tensor.pad"]} in %arg1
: (!transform.any_op) -> !transform.any_op
%a, %b, %c = transform.structured.tile_using_for %pad [2, 3]
%a, %b, %c = transform.structured.tile_using_for %pad tile_sizes [2, 3]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
@@ -57,7 +57,7 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1 : !transform.any_op {transform.readonly}) {
%pad = transform.structured.match ops{["tensor.pad"]} in %arg1
: (!transform.any_op) -> !transform.any_op
%a, %b = transform.structured.tile_using_for %pad [0, 3]
%a, %b = transform.structured.tile_using_for %pad tile_sizes [0, 3]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op)
transform.yield
}
@@ -97,7 +97,7 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1 : !transform.any_op {transform.readonly}) {
%pad = transform.structured.match ops{["tensor.pad"]} in %arg1
: (!transform.any_op) -> !transform.any_op
%a, %b, %c = transform.structured.tile_using_for %pad [2, 3]
%a, %b, %c = transform.structured.tile_using_for %pad tile_sizes [2, 3]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
@@ -134,7 +134,7 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1 : !transform.any_op {transform.readonly}) {
%pad = transform.structured.match ops{["tensor.pad"]} in %arg1
: (!transform.any_op) -> !transform.any_op
%a, %b = transform.structured.tile_using_for %pad [0, 3]
%a, %b = transform.structured.tile_using_for %pad tile_sizes [0, 3]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op)
transform.yield
}
@@ -170,7 +170,7 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1 : !transform.any_op {transform.readonly}) {
%pad = transform.structured.match ops{["tensor.pad"]} in %arg1
: (!transform.any_op) -> !transform.any_op
%a, %b, %c = transform.structured.tile_using_for %pad [2, 3]
%a, %b, %c = transform.structured.tile_using_for %pad tile_sizes [2, 3]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
@@ -192,7 +192,7 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1 : !transform.any_op {transform.readonly}) {
%pad = transform.structured.match ops{["tensor.pad"]} in %arg1
: (!transform.any_op) -> !transform.any_op
%a, %b = transform.structured.tile_using_for %pad [0, 3]
%a, %b = transform.structured.tile_using_for %pad tile_sizes [0, 3]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op)
transform.yield
}

18
mlir/test/Interfaces/TilingInterface/tile-using-interface.mlir
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@@ -11,7 +11,7 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1 : !transform.any_op {transform.readonly}) {
%matmul = transform.structured.match ops{["linalg.matmul"]} in %arg1
: (!transform.any_op) -> !transform.any_op
%a, %b, %c = transform.structured.tile_using_for %matmul [10, 20]
%a, %b, %c = transform.structured.tile_using_for %matmul tile_sizes [10, 20]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
@@ -63,7 +63,7 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1 : !transform.any_op {transform.readonly}) {
%matmul = transform.structured.match ops{["linalg.matmul"]} in %arg1
: (!transform.any_op) -> !transform.any_op
%a, %b, %c, %d = transform.structured.tile_using_for %matmul [10, 20, 30]
%a, %b, %c, %d = transform.structured.tile_using_for %matmul tile_sizes [10, 20, 30]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
@@ -122,7 +122,7 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1 : !transform.any_op {transform.readonly}) {
%generic = transform.structured.match ops{["linalg.generic"]} in %arg1
: (!transform.any_op) -> !transform.any_op
%a, %b, %c = transform.structured.tile_using_for %generic [10, 0, 20]
%a, %b, %c = transform.structured.tile_using_for %generic tile_sizes [10, 0, 20]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
@@ -175,7 +175,7 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1 : !transform.any_op {transform.readonly}) {
%conv = transform.structured.match ops{["linalg.conv_2d_nhwc_hwcf"]} in %arg1
: (!transform.any_op) -> !transform.any_op
%a, %b, %c, %d = transform.structured.tile_using_for %conv [0, 0, 0, 0, 10, 20, 30]
%a, %b, %c, %d = transform.structured.tile_using_for %conv tile_sizes [0, 0, 0, 0, 10, 20, 30]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
@@ -254,7 +254,7 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1 : !transform.any_op {transform.readonly}) {
%generic = transform.structured.match ops{["linalg.generic"]} in %arg1
: (!transform.any_op) -> !transform.any_op
%a, %b, %c = transform.structured.tile_using_for %generic [10, 20]
%a, %b, %c = transform.structured.tile_using_for %generic tile_sizes [10, 20]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
@@ -282,7 +282,7 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1 : !transform.any_op {transform.readonly}) {
%matmul = transform.structured.match ops{["linalg.matmul"]} in %arg1
: (!transform.any_op) -> !transform.any_op
%a, %b, %c, %d = transform.structured.tile_using_for %matmul [10, 20, 30] interchange = [1, 2, 0]
%a, %b, %c, %d = transform.structured.tile_using_for %matmul tile_sizes [10, 20, 30] interchange = [1, 2, 0]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
@@ -338,7 +338,7 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1 : !transform.any_op {transform.readonly}) {
%copy = transform.structured.match ops{["linalg.copy"]} in %arg1
: (!transform.any_op) -> !transform.any_op
%a, %b, %c = transform.structured.tile_using_for %copy [10, 20]
%a, %b, %c = transform.structured.tile_using_for %copy tile_sizes [10, 20]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
@@ -369,7 +369,7 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1 : !transform.any_op {transform.readonly}) {
%generic = transform.structured.match ops{["linalg.generic"]} in %arg1
: (!transform.any_op) -> !transform.any_op
%a = transform.structured.tile_using_for %generic []
%a = transform.structured.tile_using_for %generic tile_sizes []
: (!transform.any_op) -> (!transform.any_op)
transform.yield
}
@@ -396,7 +396,7 @@ module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1 : !transform.any_op {transform.readonly}) {
%generic = transform.structured.match ops{["linalg.generic"]} in %arg1
: (!transform.any_op) -> !transform.any_op
%a = transform.structured.tile_using_for %generic []
%a = transform.structured.tile_using_for %generic tile_sizes []
: (!transform.any_op) -> (!transform.any_op)
transform.yield
}

4
mlir/test/python/dialects/transform_structured_ext.py
View File

@@ -501,7 +501,7 @@ def testTileToForallMixedDynamic(target):
structured.TileUsingForallOp(target, num_threads=[n, 3, 4])
# CHECK-LABEL: TEST: testTileToForallMixedDynamic
# CHECK: = transform.structured.tile_using_forall
# CHECK-SAME: num_threads [%{{.*}} : !transform.any_op, 3, 4]
# CHECK-SAME: num_threads [%{{.*}}, 3, 4] : (!transform.any_op, !transform.any_op)
@run
@@ -511,7 +511,7 @@ def testTileToForallPackedDynamic(target):
structured.TileUsingForallOp(target, num_threads=n)
# CHECK-LABEL: TEST: testTileToForallPackedDynamic
# CHECK: = transform.structured.tile_using_forall
# CHECK-SAME: num_threads *(%0 : !transform.any_op)
# CHECK-SAME: num_threads *(%0) : (!transform.any_op, !transform.any_op)
@run