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Differential D110214

[mlir][linalg] Merge all tiling passes into a single one.
ClosedPublic

Authored by springerm on Sep 21 2021, 7:18 PM.

Details

Reviewers
pifon2a
nicolasvasilache
Commits
rG8dc16ba8d2b4: [mlir][linalg] Merge all tiling passes into a single one.
Summary

Passes such as linalg-tile-to-tiled-loop are merged into linalg-tile.

Diff Detail

Event Timeline

springerm created this revision.Sep 21 2021, 7:18 PM
Herald added subscribers: wenzhicui, wrengr, Chia-hungDuan and 21 others. · View Herald TranscriptSep 21 2021, 7:18 PM
springerm requested review of this revision.Sep 21 2021, 7:18 PM
Herald added a project: Restricted Project. · View Herald TranscriptSep 21 2021, 7:18 PM
Herald added subscribers: limo1996, stephenneuendorffer. · View Herald Transcript
Harbormaster completed remote builds in B125031: Diff 374092.Sep 21 2021, 7:31 PM
springerm added a child revision: D110220: [mlir][linalg] Support tile+peel with TiledLoopOp.Sep 21 2021, 10:44 PM
nicolasvasilache accepted this revision.Sep 22 2021, 4:26 AM

thanks!

This revision is now accepted and ready to land.Sep 22 2021, 4:26 AM
Closed by commit rG8dc16ba8d2b4: [mlir][linalg] Merge all tiling passes into a single one. (authored by springerm). · Explain WhySep 23 2021, 6:21 PM
This revision was automatically updated to reflect the committed changes.
springerm added a commit: rG8dc16ba8d2b4: [mlir][linalg] Merge all tiling passes into a single one..

Revision Contents

PathSize
mlir/
include/
mlir/
Dialect/
Linalg/
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42 lines
Transforms/
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Utils/
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lib/
Dialect/
Linalg/
Transforms/
114 lines
test/
Dialect/
Linalg/
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6 lines
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Integration/
Dialect/
Linalg/
CPU/
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Diff 374092

mlir/include/mlir/Dialect/Linalg/Passes.h

//===- Passes.h - Linalg pass entry points ----------------------*- C++ -*-===// //===- Passes.h - Linalg pass entry points ----------------------*- C++ -*-===//
// //
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information. // See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
// //
//===----------------------------------------------------------------------===// //===----------------------------------------------------------------------===//
// //
// This header file defines prototypes that expose pass constructors. // This header file defines prototypes that expose pass constructors.
// //
//===----------------------------------------------------------------------===// //===----------------------------------------------------------------------===//
#ifndef MLIR_DIALECT_LINALG_PASSES_H_ #ifndef MLIR_DIALECT_LINALG_PASSES_H_
#define MLIR_DIALECT_LINALG_PASSES_H_ #define MLIR_DIALECT_LINALG_PASSES_H_
#include "mlir/Dialect/Linalg/Utils/Utils.h"
#include "mlir/Pass/Pass.h" #include "mlir/Pass/Pass.h"
namespace mlir { namespace mlir {
std::unique_ptr<OperationPass<FuncOp>> createConvertElementwiseToLinalgPass(); std::unique_ptr<OperationPass<FuncOp>> createConvertElementwiseToLinalgPass();
std::unique_ptr<OperationPass<FuncOp>> createLinalgFoldUnitExtentDimsPass(); std::unique_ptr<OperationPass<FuncOp>> createLinalgFoldUnitExtentDimsPass();
std::unique_ptr<Pass> createLinalgElementwiseOpFusionPass(); std::unique_ptr<Pass> createLinalgElementwiseOpFusionPass();
std::unique_ptr<Pass> createFoldReshapeOpsByLinearizationPass(); std::unique_ptr<Pass> createFoldReshapeOpsByLinearizationPass();
std::unique_ptr<OperationPass<FuncOp>> std::unique_ptr<OperationPass<FuncOp>> createLinalgTilingPass(
createLinalgTilingPass(ArrayRef<int64_t> tileSizes = {}); ArrayRef<int64_t> tileSizes = {},
linalg::LinalgTilingLoopType loopType = linalg::LinalgTilingLoopType::Loops,
std::unique_ptr<OperationPass<FuncOp>>
createLinalgTilingToParallelLoopsPass(ArrayRef<int64_t> tileSizes = {});
std::unique_ptr<OperationPass<FuncOp>>
createLinalgTilingToTiledLoopPass(ArrayRef<int64_t> tileSizes = {},
ArrayRef<StringRef> distributionTypes = {}); ArrayRef<StringRef> distributionTypes = {});
std::unique_ptr<OperationPass<FuncOp>> std::unique_ptr<OperationPass<FuncOp>>
createLinalgPromotionPass(bool dynamicBuffers, bool useAlloca); createLinalgPromotionPass(bool dynamicBuffers, bool useAlloca);
std::unique_ptr<OperationPass<FuncOp>> createLinalgPromotionPass(); std::unique_ptr<OperationPass<FuncOp>> createLinalgPromotionPass();
std::unique_ptr<OperationPass<FuncOp>> createLinalgInlineScalarOperandsPass(); std::unique_ptr<OperationPass<FuncOp>> createLinalgInlineScalarOperandsPass();
/// Create a pass to convert Linalg tiled loops to `scf.for` and `scf.parallel` /// Create a pass to convert Linalg tiled loops to `scf.for` and `scf.parallel`
▲ Show 20 Lines • Show All 48 Lines • Show Last 20 Lines

mlir/include/mlir/Dialect/Linalg/Passes.td

Show First 20 Lines • Show All 163 Lines • ▼ Show 20 Linesdef LinalgTiling : FunctionPass<"linalg-tile"> {
let constructor = "mlir::createLinalgTilingPass()"; let constructor = "mlir::createLinalgTilingPass()";
let dependentDialects = [ let dependentDialects = [
"AffineDialect", "AffineDialect",
"linalg::LinalgDialect", "linalg::LinalgDialect",
"memref::MemRefDialect", "memref::MemRefDialect",
"scf::SCFDialect" "scf::SCFDialect"
]; ];
let options = [ let options = [
ListOption<"tileSizes", "linalg-tile-sizes", "int64_t", "Tile sizes", ListOption<"tileSizes", "tile-sizes", "int64_t", "Tile sizes",
"llvm::cl::ZeroOrMore, llvm::cl::MiscFlags::CommaSeparated">
];
}
def LinalgTilingToParallelLoops
: FunctionPass<"linalg-tile-to-parallel-loops"> {
let summary = "Tile operations in the linalg dialect to parallel loops";
let constructor = "mlir::createLinalgTilingToParallelLoopsPass()";
let options = [
ListOption<"tileSizes", "linalg-tile-sizes", "int64_t", "Tile sizes",
"llvm::cl::ZeroOrMore, llvm::cl::MiscFlags::CommaSeparated">
];
let dependentDialects = [
"AffineDialect",
"linalg::LinalgDialect",
"memref::MemRefDialect",
"scf::SCFDialect"
];
}
def LinalgTilingToTiledLoops
: FunctionPass<"linalg-tile-to-tiled-loop"> {
let summary = "Tile operations in the linalg dialect to linalg.tiled_loop";
let constructor = "mlir::createLinalgTilingToTiledLoopPass()";
let options = [
ListOption<"tileSizes", "linalg-tile-sizes", "int64_t", "Tile sizes",
"llvm::cl::ZeroOrMore, llvm::cl::MiscFlags::CommaSeparated">, "llvm::cl::ZeroOrMore, llvm::cl::MiscFlags::CommaSeparated">,
ListOption<"distributionTypes", "linalg-distribution-types", "std::string", Option<"loopType", "loop-type", "std::string", /*default=*/"\"for\"",
"DistributionTypes", "Specify the type of loops to generate: for, parallel or "
"tiled_loop">,
ListOption<"distributionTypes", "distribution-types", "std::string",
"DistributionTypes (if loop-type=tiled_loop)",
"llvm::cl::ZeroOrMore, llvm::cl::MiscFlags::CommaSeparated"> "llvm::cl::ZeroOrMore, llvm::cl::MiscFlags::CommaSeparated">
];
let dependentDialects = [
"AffineDialect",
"linalg::LinalgDialect",
"memref::MemRefDialect",
"scf::SCFDialect"
]; ];
} }
def LinalgGeneralization : FunctionPass<"linalg-generalize-named-ops"> { def LinalgGeneralization : FunctionPass<"linalg-generalize-named-ops"> {
let summary = "Convert named ops into generic ops"; let summary = "Convert named ops into generic ops";
let constructor = "mlir::createLinalgGeneralizationPass()"; let constructor = "mlir::createLinalgGeneralizationPass()";
let dependentDialects = ["linalg::LinalgDialect"]; let dependentDialects = ["linalg::LinalgDialect"];
} }
Show All 30 Lines

mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h

Show First 20 Lines • Show All 429 Lines • ▼ Show 20 Linesstruct LinalgTransformationFilter {
} }
private: private:
SmallVector<FilterFunction> filters; SmallVector<FilterFunction> filters;
SmallVector<Identifier> matchDisjunction; SmallVector<Identifier> matchDisjunction;
Optional<Identifier> replacement; Optional<Identifier> replacement;
}; };
///
/// Linalg tiling patterns.
///
/// Apply the `tileLinalgOp` transformation as a pattern.
/// `filter` controls LinalgTransformMarker matching and update when specified.
/// See `tileLinalgOp` for more details.
enum class LinalgTilingLoopType {
Loops = 0,
AffineLoops = 1,
ParallelLoops = 2,
TiledLoops = 3,
};
using TileSizeComputationFunction = using TileSizeComputationFunction =
std::function<SmallVector<Value, 4>(OpBuilder &, Operation *)>; std::function<SmallVector<Value, 4>(OpBuilder &, Operation *)>;
/// Specify the padding value for an OpOperand. This should be a function of /// Specify the padding value for an OpOperand. This should be a function of
/// both the operation and the operand type. /// both the operation and the operand type.
using PaddingValueComputationFunction = using PaddingValueComputationFunction =
std::function<Value(OpBuilder &, OpOperand &)>; std::function<Value(OpBuilder &, OpOperand &)>;
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mlir/include/mlir/Dialect/Linalg/Utils/Utils.h

Show First 20 Lines • Show All 70 Lines • ▼ Show 20 Lines
/// %1 = tensor.extract_slice %arg0[3, 9][3, 4][1, 1] : tensor<64x64xf32> to /// %1 = tensor.extract_slice %arg0[3, 9][3, 4][1, 1] : tensor<64x64xf32> to
/// tensor<3x4xf32> /// tensor<3x4xf32>
/// ``` /// ```
tensor::ExtractSliceOp makeComposedExtractSliceOp( tensor::ExtractSliceOp makeComposedExtractSliceOp(
OpBuilder &b, Location loc, Value source, ArrayRef<OpFoldResult> offsets, OpBuilder &b, Location loc, Value source, ArrayRef<OpFoldResult> offsets,
ArrayRef<OpFoldResult> sizes, ArrayRef<OpFoldResult> strides); ArrayRef<OpFoldResult> sizes, ArrayRef<OpFoldResult> strides);
//===----------------------------------------------------------------------===// //===----------------------------------------------------------------------===//
// Fusion utilities // Fusion / Tiling utilities
//===----------------------------------------------------------------------===// //===----------------------------------------------------------------------===//
/// The type of loops to be generated during tiling.
enum class LinalgTilingLoopType {
Loops = 0,
AffineLoops = 1,
ParallelLoops = 2,
TiledLoops = 3,
};
/// Checks whether the specific `producer` is the last write to exactly the /// Checks whether the specific `producer` is the last write to exactly the
/// whole `consumedView`. This checks structural dominance, that the dependence /// whole `consumedView`. This checks structural dominance, that the dependence
/// is a RAW without any interleaved write to any piece of `consumedView`. /// is a RAW without any interleaved write to any piece of `consumedView`.
bool isProducerLastWriteOfView(const LinalgDependenceGraph &graph, bool isProducerLastWriteOfView(const LinalgDependenceGraph &graph,
LinalgOp consumer, Value consumedView, LinalgOp consumer, Value consumedView,
LinalgOp producer); LinalgOp producer);
/// Checks whether fusing the specific `producer` of the `consumedView` is /// Checks whether fusing the specific `producer` of the `consumedView` is
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mlir/lib/Dialect/Linalg/Transforms/Tiling.cpp

Show First 20 Lines • Show All 502 Lines • ▼ Show 20 Linesstatic void applyExtractSliceOfPadTensorSwapPattern(FuncOp funcOp) {
MLIRContext *ctx = funcOp.getContext(); MLIRContext *ctx = funcOp.getContext();
RewritePatternSet patterns(ctx); RewritePatternSet patterns(ctx);
patterns.add<ExtractSliceOfPadTensorSwapPattern>(patterns.getContext()); patterns.add<ExtractSliceOfPadTensorSwapPattern>(patterns.getContext());
(void)applyPatternsAndFoldGreedily(funcOp, std::move(patterns)); (void)applyPatternsAndFoldGreedily(funcOp, std::move(patterns));
(void)applyPatternsAndFoldGreedily( (void)applyPatternsAndFoldGreedily(
funcOp, getLinalgTilingCanonicalizationPatterns(ctx)); funcOp, getLinalgTilingCanonicalizationPatterns(ctx));
} }
static void namespace {
applyTilingToLoopPatterns(LinalgTilingLoopType loopType, FuncOp funcOp, struct LinalgTilingPass : public LinalgTilingBase<LinalgTilingPass> {
ArrayRef<int64_t> tileSizes, LinalgTilingPass() = default;
ArrayRef<StringRef> distributionTypes = {}) { LinalgTilingPass(ArrayRef<int64_t> tileSizes, LinalgTilingLoopType loopType,
ArrayRef<StringRef> distributionTypes) {
this->tileSizes = tileSizes;
this->loopType = "";
this->loopTypeEnum = loopType;
this->distributionTypes = llvm::to_vector<2>(llvm::map_range(
distributionTypes, [](StringRef ref) { return ref.str(); }));
}
void runOnFunction() override {
FuncOp funcOp = getFunction();
LinalgTilingLoopType type =
llvm::StringSwitch<LinalgTilingLoopType>(loopType)
.Case("for", LinalgTilingLoopType::Loops)
.Case("affine", LinalgTilingLoopType::AffineLoops)
.Case("parallel", LinalgTilingLoopType::ParallelLoops)
.Case("tiled_loop", LinalgTilingLoopType::TiledLoops)
.Default(loopTypeEnum);
auto distTypes = llvm::to_vector<2>(llvm::map_range(
distributionTypes, [](std::string &str) { return StringRef(str); }));
auto options = LinalgTilingOptions() auto options = LinalgTilingOptions()
.setTileSizes(tileSizes) .setTileSizes(tileSizes)
.setLoopType(loopType) .setLoopType(type)
.setDistributionTypes(distributionTypes); .setDistributionTypes(distTypes);
MLIRContext *ctx = funcOp.getContext(); MLIRContext *ctx = funcOp.getContext();
RewritePatternSet patterns(ctx); RewritePatternSet patterns(ctx);
insertTilingPatterns(patterns, options); insertTilingPatterns(patterns, options);
scf::populateSCFForLoopCanonicalizationPatterns(patterns); scf::populateSCFForLoopCanonicalizationPatterns(patterns);
(void)applyPatternsAndFoldGreedily(funcOp, std::move(patterns)); (void)applyPatternsAndFoldGreedily(funcOp, std::move(patterns));
(void)applyPatternsAndFoldGreedily( (void)applyPatternsAndFoldGreedily(
funcOp, getLinalgTilingCanonicalizationPatterns(ctx)); funcOp, getLinalgTilingCanonicalizationPatterns(ctx));
// Drop the marker. // Drop the marker.
funcOp.walk([](LinalgOp op) { funcOp.walk([](LinalgOp op) {
op->removeAttr(LinalgTransforms::kLinalgTransformMarker); op->removeAttr(LinalgTransforms::kLinalgTransformMarker);
}); });
// Apply swap pattern after generating loop nest and running // Apply swap pattern after generating loop nest and running
// canonicalizations. // canonicalizations.
applyExtractSliceOfPadTensorSwapPattern(funcOp); applyExtractSliceOfPadTensorSwapPattern(funcOp);
} }
namespace { LinalgTilingLoopType loopTypeEnum;
struct LinalgTilingPass : public LinalgTilingBase<LinalgTilingPass> {
LinalgTilingPass() = default;
LinalgTilingPass(ArrayRef<int64_t> sizes) { tileSizes = sizes; }
void runOnFunction() override {
applyTilingToLoopPatterns(LinalgTilingLoopType::Loops, getFunction(),
tileSizes);
}
};
struct LinalgTilingToParallelLoopsPass
: public LinalgTilingToParallelLoopsBase<LinalgTilingToParallelLoopsPass> {
LinalgTilingToParallelLoopsPass() = default;
LinalgTilingToParallelLoopsPass(ArrayRef<int64_t> sizes) {
tileSizes = sizes;
}
void runOnFunction() override {
applyTilingToLoopPatterns(LinalgTilingLoopType::ParallelLoops,
getFunction(), tileSizes);
}
};
struct LinalgTilingToTiledLoopsPass
: public LinalgTilingToTiledLoopsBase<LinalgTilingToTiledLoopsPass> {
LinalgTilingToTiledLoopsPass() = default;
LinalgTilingToTiledLoopsPass(ArrayRef<int64_t> sizes,
ArrayRef<StringRef> types) {
tileSizes = sizes;
distributionTypes = llvm::to_vector<2>(
llvm::map_range(types, [](StringRef ref) { return ref.str(); }));
}
void runOnFunction() override {
applyTilingToLoopPatterns(
LinalgTilingLoopType::TiledLoops, getFunction(), tileSizes,
llvm::to_vector<2>(
llvm::map_range(distributionTypes,
[](std::string &str) { return StringRef(str); })));
}
}; };
} // namespace } // namespace
std::unique_ptr<OperationPass<FuncOp>> std::unique_ptr<OperationPass<FuncOp>>
mlir::createLinalgTilingPass(ArrayRef<int64_t> tileSizes) { mlir::createLinalgTilingPass(ArrayRef<int64_t> tileSizes,
return std::make_unique<LinalgTilingPass>(tileSizes); linalg::LinalgTilingLoopType loopType,
}
std::unique_ptr<OperationPass<FuncOp>>
mlir::createLinalgTilingToParallelLoopsPass(ArrayRef<int64_t> tileSizes) {
return std::make_unique<LinalgTilingToParallelLoopsPass>(tileSizes);
}
std::unique_ptr<OperationPass<FuncOp>>
mlir::createLinalgTilingToTiledLoopPass(ArrayRef<int64_t> tileSizes,
ArrayRef<StringRef> distributionTypes) { ArrayRef<StringRef> distributionTypes) {
return std::make_unique<LinalgTilingToTiledLoopsPass>(tileSizes, return std::make_unique<LinalgTilingPass>(tileSizes, loopType,
distributionTypes); distributionTypes);
} }

mlir/test/Dialect/Linalg/tile-conv-padding.mlir

// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=2,3,0,0,4" | FileCheck %s -check-prefix=TILE-23004 // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,3,0,0,4" | FileCheck %s -check-prefix=TILE-23004
// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=2" | FileCheck %s -check-prefix=TILE-20000 // RUN: mlir-opt %s -linalg-tile="tile-sizes=2" | FileCheck %s -check-prefix=TILE-20000
// TILE-23004-DAG: #[[$strided4D:.*]] = affine_map<(d0, d1, d2, d3)[s0, s1, s2, s3] -> (d0 * s1 + s0 + d1 * s2 + d2 * s3 + d3)> // TILE-23004-DAG: #[[$strided4D:.*]] = affine_map<(d0, d1, d2, d3)[s0, s1, s2, s3] -> (d0 * s1 + s0 + d1 * s2 + d2 * s3 + d3)>
// TILE-20000-DAG: #[[$strided4D:.*]] = affine_map<(d0, d1, d2, d3)[s0, s1, s2, s3] -> (d0 * s1 + s0 + d1 * s2 + d2 * s3 + d3)> // TILE-20000-DAG: #[[$strided4D:.*]] = affine_map<(d0, d1, d2, d3)[s0, s1, s2, s3] -> (d0 * s1 + s0 + d1 * s2 + d2 * s3 + d3)>
// TILE-20000-DAG: #[[$minmap:.*]] = affine_map<(d0)[s0] -> (2, -d0 + s0)> // TILE-20000-DAG: #[[$minmap:.*]] = affine_map<(d0)[s0] -> (2, -d0 + s0)>
func @conv_padding(%arg0: memref<?x?x?x?xf32, offset: ?, strides: [?, ?, ?, 1]>, %arg1: memref<?x?x?x?xf32, offset: ?, strides: [?, ?, ?, 1]>, %arg2: memref<?x?x?x?xf32, offset: ?, strides: [?, ?, ?, 1]>) { func @conv_padding(%arg0: memref<?x?x?x?xf32, offset: ?, strides: [?, ?, ?, 1]>, %arg1: memref<?x?x?x?xf32, offset: ?, strides: [?, ?, ?, 1]>, %arg2: memref<?x?x?x?xf32, offset: ?, strides: [?, ?, ?, 1]>) {
linalg.conv(%arg0, %arg1, %arg2) {dilations = [10, 20], padding = dense<[[1, 1], [0, 1]]> : tensor<2x2xi64>, strides = [30, 40]} : memref<?x?x?x?xf32, offset: ?, strides: [?, ?, ?, 1]>, memref<?x?x?x?xf32, offset: ?, strides: [?, ?, ?, 1]>, memref<?x?x?x?xf32, offset: ?, strides: [?, ?, ?, 1]> linalg.conv(%arg0, %arg1, %arg2) {dilations = [10, 20], padding = dense<[[1, 1], [0, 1]]> : tensor<2x2xi64>, strides = [30, 40]} : memref<?x?x?x?xf32, offset: ?, strides: [?, ?, ?, 1]>, memref<?x?x?x?xf32, offset: ?, strides: [?, ?, ?, 1]>, memref<?x?x?x?xf32, offset: ?, strides: [?, ?, ?, 1]>
return return
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mlir/test/Dialect/Linalg/tile-conv.mlir

// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=2,3,0,0,4" | FileCheck %s -check-prefix=TILE-23004 // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,3,0,0,4" | FileCheck %s -check-prefix=TILE-23004
// TILE-23004-DAG: #[[$D0x30pS0x10:.*]] = affine_map<(d0) -> (d0 * 30)> // TILE-23004-DAG: #[[$D0x30pS0x10:.*]] = affine_map<(d0) -> (d0 * 30)>
// TILE-23004-DAG: #[[$S0x10p90D0x30pS1:.*]] = affine_map<(d0)[s0, s1] -> (s0 * 10 + 51, d0 * -30 + s0 * 10 + s1 * 30)> // TILE-23004-DAG: #[[$S0x10p90D0x30pS1:.*]] = affine_map<(d0)[s0, s1] -> (s0 * 10 + 51, d0 * -30 + s0 * 10 + s1 * 30)>
// TILE-23004-DAG: #[[$strided4D:.*]] = affine_map<(d0, d1, d2, d3)[s0, s1, s2, s3] -> (d0 * s1 + s0 + d1 * s2 + d2 * s3 + d3)> // TILE-23004-DAG: #[[$strided4D:.*]] = affine_map<(d0, d1, d2, d3)[s0, s1, s2, s3] -> (d0 * s1 + s0 + d1 * s2 + d2 * s3 + d3)>
// TILE-23004-DAG: #[[$bound_map_2:.*]] = affine_map<(d0)[s0] -> (2, -d0 + s0)> // TILE-23004-DAG: #[[$bound_map_2:.*]] = affine_map<(d0)[s0] -> (2, -d0 + s0)>
// TILE-23004-DAG: #[[$bound_map_3:.*]] = affine_map<(d0)[s0] -> (3, -d0 + s0)> // TILE-23004-DAG: #[[$bound_map_3:.*]] = affine_map<(d0)[s0] -> (3, -d0 + s0)>
// TILE-23004-DAG: #[[$bound_map_4:.*]] = affine_map<(d0)[s0] -> (4, -d0 + s0)> // TILE-23004-DAG: #[[$bound_map_4:.*]] = affine_map<(d0)[s0] -> (4, -d0 + s0)>
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mlir/test/Dialect/Linalg/tile-indexed.mlir

// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=10,25" -split-input-file | FileCheck %s -check-prefix=TILE-10n25 // RUN: mlir-opt %s -linalg-tile="tile-sizes=10,25" -split-input-file | FileCheck %s -check-prefix=TILE-10n25
// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=25,0" -split-input-file | FileCheck %s -check-prefix=TILE-25n0 // RUN: mlir-opt %s -linalg-tile="tile-sizes=25,0" -split-input-file | FileCheck %s -check-prefix=TILE-25n0
// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=0,25" -split-input-file | FileCheck %s -check-prefix=TILE-0n25 // RUN: mlir-opt %s -linalg-tile="tile-sizes=0,25" -split-input-file | FileCheck %s -check-prefix=TILE-0n25
func @indexed_vector(%arg0: memref<50xindex>) { func @indexed_vector(%arg0: memref<50xindex>) {
linalg.generic {indexing_maps = [affine_map<(i) -> (i)>], linalg.generic {indexing_maps = [affine_map<(i) -> (i)>],
iterator_types = ["parallel"]} iterator_types = ["parallel"]}
outs(%arg0 : memref<50xindex>) { outs(%arg0 : memref<50xindex>) {
^bb0(%a: index): ^bb0(%a: index):
%i = linalg.index 0 : index %i = linalg.index 0 : index
linalg.yield %i : index linalg.yield %i : index
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mlir/test/Dialect/Linalg/tile-pad-tensor-op.mlir

// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=2,3" -cse -split-input-file | \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,3" -cse -split-input-file | \
// RUN: FileCheck %s -check-prefix=TILE2 // RUN: FileCheck %s -check-prefix=TILE2
// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=0,3" -resolve-shaped-type-result-dims -cse -split-input-file | \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=0,3" -resolve-shaped-type-result-dims -cse -split-input-file | \
// RUN: FileCheck %s -check-prefix=TILE1 // RUN: FileCheck %s -check-prefix=TILE1
// TILE2-DAG: #[[MAP0:.*]] = affine_map<()[s0] -> (s0 + 8)> // TILE2-DAG: #[[MAP0:.*]] = affine_map<()[s0] -> (s0 + 8)>
// TILE2-DAG: #[[MAP1:.*]] = affine_map<()[s0] -> (s0 + 7)> // TILE2-DAG: #[[MAP1:.*]] = affine_map<()[s0] -> (s0 + 7)>
// TILE2: func @dynamic_pad_tensor( // TILE2: func @dynamic_pad_tensor(
// TILE2-SAME: %[[IN:.*]]: tensor<?x?xf32> // TILE2-SAME: %[[IN:.*]]: tensor<?x?xf32>
// TILE2-DAG: %[[C0:.*]] = constant 0 : index // TILE2-DAG: %[[C0:.*]] = constant 0 : index
// TILE2-DAG: %[[C1:.*]] = constant 1 : index // TILE2-DAG: %[[C1:.*]] = constant 1 : index
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mlir/test/Dialect/Linalg/tile-parallel-reduce.mlir

// RUN: mlir-opt %s -linalg-tile-to-parallel-loops="linalg-tile-sizes=2,4,8" -split-input-file | FileCheck %s // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,4,8 loop-type=parallel" -split-input-file | FileCheck %s
// RUN: mlir-opt %s -linalg-tile-to-parallel-loops="linalg-tile-sizes=2" -split-input-file | FileCheck %s -check-prefix=TILE1 // RUN: mlir-opt %s -linalg-tile="tile-sizes=2 loop-type=parallel" -split-input-file | FileCheck %s -check-prefix=TILE1
// RUN: mlir-opt %s -linalg-tile-to-parallel-loops="linalg-tile-sizes=2,4" -split-input-file | FileCheck %s -check-prefix=TILE2 // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,4 loop-type=parallel" -split-input-file | FileCheck %s -check-prefix=TILE2
func @gemm(%arg0 : memref<?x?xf32>, func @gemm(%arg0 : memref<?x?xf32>,
%arg1 : memref<?x?xf32>, %arg1 : memref<?x?xf32>,
%arg2 : memref<?x?xf32>) %arg2 : memref<?x?xf32>)
{ {
linalg.matmul ins(%arg0, %arg1: memref<?x?xf32>, memref<?x?xf32>) linalg.matmul ins(%arg0, %arg1: memref<?x?xf32>, memref<?x?xf32>)
outs(%arg2: memref<?x?xf32>) outs(%arg2: memref<?x?xf32>)
return return
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mlir/test/Dialect/Linalg/tile-parallel.mlir

// RUN: mlir-opt %s -linalg-tile-to-parallel-loops="linalg-tile-sizes=2" | FileCheck %s -check-prefix=TILE-2 // RUN: mlir-opt %s -linalg-tile="tile-sizes=2 loop-type=parallel" | FileCheck %s -check-prefix=TILE-2
// RUN: mlir-opt %s -linalg-tile-to-parallel-loops="linalg-tile-sizes=0,2" | FileCheck %s -check-prefix=TILE-02 // RUN: mlir-opt %s -linalg-tile="tile-sizes=0,2 loop-type=parallel" | FileCheck %s -check-prefix=TILE-02
// RUN: mlir-opt %s -linalg-tile-to-parallel-loops="linalg-tile-sizes=0,0,2" | FileCheck %s -check-prefix=TILE-002 // RUN: mlir-opt %s -linalg-tile="tile-sizes=0,0,2 loop-type=parallel" | FileCheck %s -check-prefix=TILE-002
// RUN: mlir-opt %s -linalg-tile-to-parallel-loops="linalg-tile-sizes=2,3,4" | FileCheck %s -check-prefix=TILE-234 // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,3,4 loop-type=parallel" | FileCheck %s -check-prefix=TILE-234
#id_2d = affine_map<(i, j) -> (i, j)> #id_2d = affine_map<(i, j) -> (i, j)>
#pointwise_2d_trait = { #pointwise_2d_trait = {
args_in = 2, args_in = 2,
args_out = 1, args_out = 1,
indexing_maps = [#id_2d, #id_2d, #id_2d], indexing_maps = [#id_2d, #id_2d, #id_2d],
iterator_types = ["parallel", "parallel"] iterator_types = ["parallel", "parallel"]
} }
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mlir/test/Dialect/Linalg/tile-simple-conv.mlir

// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=2,3,4" | FileCheck %s // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,3,4" | FileCheck %s
// CHECK-DAG: #[[MAP0:.*]] = affine_map<(d0)[s0] -> (2, -d0 + s0)> // CHECK-DAG: #[[MAP0:.*]] = affine_map<(d0)[s0] -> (2, -d0 + s0)>
// CHECK-DAG: #[[MAP1:.*]] = affine_map<(d0)[s0, s1] -> (s0 + 2, -d0 + s0 + s1)> // CHECK-DAG: #[[MAP1:.*]] = affine_map<(d0)[s0, s1] -> (s0 + 2, -d0 + s0 + s1)>
// CHECK-DAG: #[[MAP2:.*]] = affine_map<(d0)[s0, s1] -> (s0 + 3, -d0 + s0 + s1)> // CHECK-DAG: #[[MAP2:.*]] = affine_map<(d0)[s0, s1] -> (s0 + 3, -d0 + s0 + s1)>
// CHECK-DAG: #[[MAP4:.*]] = affine_map<(d0)[s0] -> (3, -d0 + s0)> // CHECK-DAG: #[[MAP4:.*]] = affine_map<(d0)[s0] -> (3, -d0 + s0)>
// CHECK-DAG: #[[MAP5:.*]] = affine_map<(d0)[s0] -> (4, -d0 + s0)> // CHECK-DAG: #[[MAP5:.*]] = affine_map<(d0)[s0] -> (4, -d0 + s0)>
func @conv(%arg0 : memref<?x?x?x?xf32>, %arg1 : memref<?x?x?x?xf32>, %arg2 : memref<?x?x?x?xf32>) { func @conv(%arg0 : memref<?x?x?x?xf32>, %arg1 : memref<?x?x?x?xf32>, %arg2 : memref<?x?x?x?xf32>) {
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mlir/test/Dialect/Linalg/tile-tensors.mlir

// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=2,3,4" -split-input-file | FileCheck %s // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,3,4" -split-input-file | FileCheck %s
// RUN: mlir-opt %s -linalg-tile-to-tiled-loop="linalg-tile-sizes=2,3,4 linalg-distribution-types=block_x,block_y,none" -split-input-file | FileCheck %s -check-prefix=TLOOP // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,3,4 loop-type=tiled_loop distribution-types=block_x,block_y,none" -split-input-file | FileCheck %s -check-prefix=TLOOP
// CHECK-LABEL: func @matmul_tensors( // CHECK-LABEL: func @matmul_tensors(
// CHECK-SAME: %[[TA:[0-9a-z]+]]: tensor<?x?xf32> // CHECK-SAME: %[[TA:[0-9a-z]+]]: tensor<?x?xf32>
// CHECK-SAME: %[[TB:[0-9a-z]+]]: tensor<?x?xf32> // CHECK-SAME: %[[TB:[0-9a-z]+]]: tensor<?x?xf32>
// CHECK-SAME: %[[TC:[0-9a-z]+]]: tensor<?x?xf32>) -> tensor<?x?xf32> { // CHECK-SAME: %[[TC:[0-9a-z]+]]: tensor<?x?xf32>) -> tensor<?x?xf32> {
func @matmul_tensors( func @matmul_tensors(
%arg0: tensor<?x?xf32>, %arg1: tensor<?x?xf32>, %arg2: tensor<?x?xf32>) %arg0: tensor<?x?xf32>, %arg1: tensor<?x?xf32>, %arg2: tensor<?x?xf32>)
-> tensor<?x?xf32> { -> tensor<?x?xf32> {
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mlir/test/Dialect/Linalg/tile.mlir

// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=2" -mlir-disable-threading=true | FileCheck %s -check-prefix=TILE-2 // RUN: mlir-opt %s -linalg-tile="tile-sizes=2" -mlir-disable-threading=true | FileCheck %s -check-prefix=TILE-2
// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=0,2" -mlir-disable-threading=true | FileCheck %s -check-prefix=TILE-02 // RUN: mlir-opt %s -linalg-tile="tile-sizes=0,2" -mlir-disable-threading=true | FileCheck %s -check-prefix=TILE-02
// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=0,0,2" -mlir-disable-threading=true | FileCheck %s -check-prefix=TILE-002 // RUN: mlir-opt %s -linalg-tile="tile-sizes=0,0,2" -mlir-disable-threading=true | FileCheck %s -check-prefix=TILE-002
// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=2,3,4" -mlir-disable-threading=true | FileCheck %s -check-prefix=TILE-234 // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,3,4" -mlir-disable-threading=true | FileCheck %s -check-prefix=TILE-234
// TILE-2-DAG: #[[$strided1D:.*]] = affine_map<(d0)[s0] -> (d0 + s0)> // TILE-2-DAG: #[[$strided1D:.*]] = affine_map<(d0)[s0] -> (d0 + s0)>
// TILE-02-DAG: #[[$strided1D:.*]] = affine_map<(d0)[s0] -> (d0 + s0)> // TILE-02-DAG: #[[$strided1D:.*]] = affine_map<(d0)[s0] -> (d0 + s0)>
// TILE-002-DAG: #[[$strided1D:.*]] = affine_map<(d0)[s0] -> (d0 + s0)> // TILE-002-DAG: #[[$strided1D:.*]] = affine_map<(d0)[s0] -> (d0 + s0)>
// TILE-234-DAG: #[[$strided1D:.*]] = affine_map<(d0)[s0] -> (d0 + s0)> // TILE-234-DAG: #[[$strided1D:.*]] = affine_map<(d0)[s0] -> (d0 + s0)>
// TILE-2-DAG: #[[$strided2D:.*]] = affine_map<(d0, d1)[s0, s1] -> (d0 * s1 + s0 + d1)> // TILE-2-DAG: #[[$strided2D:.*]] = affine_map<(d0, d1)[s0, s1] -> (d0 * s1 + s0 + d1)>
// TILE-02-DAG: #[[$strided2D:.*]] = affine_map<(d0, d1)[s0, s1] -> (d0 * s1 + s0 + d1)> // TILE-02-DAG: #[[$strided2D:.*]] = affine_map<(d0, d1)[s0, s1] -> (d0 * s1 + s0 + d1)>
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mlir/test/Integration/Dialect/Linalg/CPU/test-conv-1d-call.mlir

// RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-std -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-std -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=4" -convert-linalg-to-loops -convert-scf-to-std \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=4" -convert-linalg-to-loops -convert-scf-to-std \
// RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -test-conv-vectorization="tile-sizes=1,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -test-conv-vectorization="tile-sizes=1,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=4" \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=4" \
// RUN: -test-conv-vectorization="tile-sizes=1,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: -test-conv-vectorization="tile-sizes=1,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func private @print_memref_f32(memref<*xf32>) func private @print_memref_f32(memref<*xf32>)
// Creates and returns a 1-D buffer of size %s1 filled with the value %f // Creates and returns a 1-D buffer of size %s1 filled with the value %f
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mlir/test/Integration/Dialect/Linalg/CPU/test-conv-1d-nwc-wcf-call.mlir

// RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-std -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-std -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=2,4" -convert-linalg-to-loops -convert-scf-to-std \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,4" -convert-linalg-to-loops -convert-scf-to-std \
// RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -test-conv-vectorization="tile-sizes=1,1,1,3,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -test-conv-vectorization="tile-sizes=1,1,1,3,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=2,4" \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,4" \
// RUN: -test-conv-vectorization="tile-sizes=1,1,1,3,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: -test-conv-vectorization="tile-sizes=1,1,1,3,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func private @print_memref_f32(memref<*xf32>) func private @print_memref_f32(memref<*xf32>)
// Creates and returns 3-D buffer of size (%s1, %s2, %s3) filled with the value %f // Creates and returns 3-D buffer of size (%s1, %s2, %s3) filled with the value %f
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mlir/test/Integration/Dialect/Linalg/CPU/test-conv-2d-call.mlir

// RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-std -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-std -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=2,2" -convert-linalg-to-loops -convert-scf-to-std \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,2" -convert-linalg-to-loops -convert-scf-to-std \
// RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -test-conv-vectorization="tile-sizes=1,1,3,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -test-conv-vectorization="tile-sizes=1,1,3,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=2,2" \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,2" \
// RUN: -test-conv-vectorization="tile-sizes=1,1,3,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: -test-conv-vectorization="tile-sizes=1,1,3,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func private @print_memref_f32(memref<*xf32>) func private @print_memref_f32(memref<*xf32>)
// Creates and returns a 2-D buffer of size (%s1, %s2) filled with the value %f // Creates and returns a 2-D buffer of size (%s1, %s2) filled with the value %f
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mlir/test/Integration/Dialect/Linalg/CPU/test-conv-2d-nhwc-hwcf-call.mlir

// RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-std -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-std -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=2,3,3,2" -convert-linalg-to-loops -convert-scf-to-std \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,3,3,2" -convert-linalg-to-loops -convert-scf-to-std \
// RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -test-conv-vectorization="tile-sizes=1,1,1,1,3,3,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -test-conv-vectorization="tile-sizes=1,1,1,1,3,3,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=2,3,3,2" \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,3,3,2" \
// RUN: -test-conv-vectorization="tile-sizes=1,1,1,1,3,3,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: -test-conv-vectorization="tile-sizes=1,1,1,1,3,3,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func private @print_memref_f32(memref<*xf32>) func private @print_memref_f32(memref<*xf32>)
// Creates and returns 4-D buffer of size (%s1, %s2, %s3, %s4) filled with the value %f // Creates and returns 4-D buffer of size (%s1, %s2, %s3, %s4) filled with the value %f
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mlir/test/Integration/Dialect/Linalg/CPU/test-conv-3d-call.mlir

// RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-std -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-std -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=2,2,2" -convert-linalg-to-loops -convert-scf-to-std \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,2,2" -convert-linalg-to-loops -convert-scf-to-std \
// RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -test-conv-vectorization="tile-sizes=1,1,1,3,3,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -test-conv-vectorization="tile-sizes=1,1,1,3,3,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=2,2,2" \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,2,2" \
// RUN: -test-conv-vectorization="tile-sizes=1,1,1,3,3,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: -test-conv-vectorization="tile-sizes=1,1,1,3,3,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func private @print_memref_f32(memref<*xf32>) func private @print_memref_f32(memref<*xf32>)
// Creates and returns 3-D buffer of size (%s1, %s2, %s3) filled with the value %f // Creates and returns 3-D buffer of size (%s1, %s2, %s3) filled with the value %f
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mlir/test/Integration/Dialect/Linalg/CPU/test-conv-3d-ndhwc-dhwcf-call.mlir

// RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-std -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-std -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=0,5,5,5" -convert-linalg-to-loops -convert-scf-to-std \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=0,5,5,5" -convert-linalg-to-loops -convert-scf-to-std \
// RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -test-conv-vectorization="tile-sizes=1,1,1,1,1,3,3,3,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -test-conv-vectorization="tile-sizes=1,1,1,1,1,3,3,3,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=0,5,5,5" \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=0,5,5,5" \
// RUN: -test-conv-vectorization="tile-sizes=1,1,1,1,1,3,3,3,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: -test-conv-vectorization="tile-sizes=1,1,1,1,1,3,3,3,3" -convert-linalg-to-llvm -lower-affine -convert-scf-to-std -convert-vector-to-llvm --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func private @print_memref_f32(memref<*xf32>) func private @print_memref_f32(memref<*xf32>)
// Creates and returns 5-D buffer of size (%s1, %s2, %s3, %s4, %s5) filled with the value %f // Creates and returns 5-D buffer of size (%s1, %s2, %s3, %s4, %s5) filled with the value %f
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mlir/test/Integration/Dialect/Linalg/CPU/test-tensor-matmul.mlir

// RUN: mlir-opt %s -linalg-bufferize -std-bufferize -tensor-constant-bufferize \ // RUN: mlir-opt %s -linalg-bufferize -std-bufferize -tensor-constant-bufferize \
// RUN: -tensor-bufferize -func-bufferize -finalizing-bufferize -convert-linalg-to-loops -convert-scf-to-std \ // RUN: -tensor-bufferize -func-bufferize -finalizing-bufferize -convert-linalg-to-loops -convert-scf-to-std \
// RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=1,2,3" -linalg-bufferize \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=1,2,3" -linalg-bufferize \
// RUN: -scf-bufferize -std-bufferize -tensor-constant-bufferize -tensor-bufferize \ // RUN: -scf-bufferize -std-bufferize -tensor-constant-bufferize -tensor-bufferize \
// RUN: -func-bufferize \ // RUN: -func-bufferize \
// RUN: -finalizing-bufferize -convert-linalg-to-loops -convert-scf-to-std -convert-scf-to-std \ // RUN: -finalizing-bufferize -convert-linalg-to-loops -convert-scf-to-std -convert-scf-to-std \
// RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-std --convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
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