diff --git a/mlir/include/mlir/Conversion/LinalgToStandard/LinalgToStandard.h b/mlir/include/mlir/Conversion/LinalgToStandard/LinalgToStandard.h new file mode 100644 --- /dev/null +++ b/mlir/include/mlir/Conversion/LinalgToStandard/LinalgToStandard.h @@ -0,0 +1,29 @@ +//===- LinalgToStandard.h - Utils to convert from the linalg dialect ------===// +// +// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. +// See https://llvm.org/LICENSE.txt for license information. +// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception +// +//===----------------------------------------------------------------------===// + +#ifndef MLIR_CONVERSION_LINALGTOSTANDARD_LINALGTOSTANDARD_H_ +#define MLIR_CONVERSION_LINALGTOSTANDARD_LINALGTOSTANDARD_H_ + +#include "mlir/Transforms/DialectConversion.h" + +namespace mlir { +class MLIRContext; +class ModuleOp; +template +class OperationPass; + +/// Populate the given list with patterns that convert from Linalg to Standard. +void populateLinalgToStandardConversionPatterns( + OwningRewritePatternList &patterns, MLIRContext *ctx); + +/// Create a pass to convert Linalg operations to the Standard dialect. +std::unique_ptr> createConvertLinalgToStandardPass(); + +} // namespace mlir + +#endif // MLIR_CONVERSION_LINALGTOSTANDARD_LINALGTOSTANDARD_H_ diff --git a/mlir/include/mlir/Conversion/Passes.td b/mlir/include/mlir/Conversion/Passes.td --- a/mlir/include/mlir/Conversion/Passes.td +++ b/mlir/include/mlir/Conversion/Passes.td @@ -142,6 +142,16 @@ } //===----------------------------------------------------------------------===// +// LinalgToStandard +//===----------------------------------------------------------------------===// + +def ConvertLinalgToStandard : Pass<"convert-linalg-to-std", "ModuleOp"> { + let summary = "Convert the operations from the linalg dialect into the " + "Standard dialect"; + let constructor = "mlir::createConvertLinalgToStandardPass()"; +} + +//===----------------------------------------------------------------------===// // LinalgToSPIRV //===----------------------------------------------------------------------===// diff --git a/mlir/include/mlir/Dialect/StandardOps/IR/Ops.td b/mlir/include/mlir/Dialect/StandardOps/IR/Ops.td --- a/mlir/include/mlir/Dialect/StandardOps/IR/Ops.td +++ b/mlir/include/mlir/Dialect/StandardOps/IR/Ops.td @@ -1745,12 +1745,16 @@ The `memref_cast` operation converts a memref from one type to an equivalent type with a compatible shape. The source and destination types are compatible if: - a. both are ranked memref types with the same element type, affine mappings, - address space, and rank but where the individual dimensions may add or - remove constant dimensions from the memref type. + + a. Both are ranked memref types with the same element type, address space, + and rank and: + 1. Both have the same layout or both have compatible strided layouts. + 2. The individual sizes (resp. offset and strides in the case of strided + memrefs) may convert constant dimensions to dynamic dimensions and + vice-versa. If the cast converts any dimensions from an unknown to a known size, then it - acts as an assertion that fails at runtime of the dynamic dimensions + acts as an assertion that fails at runtime if the dynamic dimensions disagree with resultant destination size. Example: @@ -1772,7 +1776,7 @@ memref<12x4xf32, offset:?, strides: [?, ?]> ``` - b. either or both memref types are unranked with the same element type, and + b. Either or both memref types are unranked with the same element type, and address space. Example: diff --git a/mlir/include/mlir/IR/StandardTypes.h b/mlir/include/mlir/IR/StandardTypes.h --- a/mlir/include/mlir/IR/StandardTypes.h +++ b/mlir/include/mlir/IR/StandardTypes.h @@ -723,6 +723,10 @@ /// `t` with simplified layout. MemRefType canonicalizeStridedLayout(MemRefType t); +/// Return a version of `t` with a layout that has all dynamic offset and +/// strides. This is used to erase the static layout. +MemRefType eraseStridedLayout(MemRefType t); + /// Given MemRef `sizes` that are either static or dynamic, returns the /// canonical "contiguous" strides AffineExpr. Strides are multiplicative and /// once a dynamic dimension is encountered, all canonical strides become diff --git a/mlir/include/mlir/InitAllPasses.h b/mlir/include/mlir/InitAllPasses.h --- a/mlir/include/mlir/InitAllPasses.h +++ b/mlir/include/mlir/InitAllPasses.h @@ -22,6 +22,7 @@ #include "mlir/Conversion/GPUToVulkan/ConvertGPUToVulkanPass.h" #include "mlir/Conversion/LinalgToLLVM/LinalgToLLVM.h" #include "mlir/Conversion/LinalgToSPIRV/LinalgToSPIRVPass.h" +#include "mlir/Conversion/LinalgToStandard/LinalgToStandard.h" #include "mlir/Conversion/LoopToStandard/ConvertLoopToStandard.h" #include "mlir/Conversion/LoopsToGPU/LoopsToGPUPass.h" #include "mlir/Conversion/StandardToLLVM/ConvertStandardToLLVMPass.h" diff --git a/mlir/lib/Conversion/CMakeLists.txt b/mlir/lib/Conversion/CMakeLists.txt --- a/mlir/lib/Conversion/CMakeLists.txt +++ b/mlir/lib/Conversion/CMakeLists.txt @@ -7,6 +7,7 @@ add_subdirectory(GPUToVulkan) add_subdirectory(LinalgToLLVM) add_subdirectory(LinalgToSPIRV) +add_subdirectory(LinalgToStandard) add_subdirectory(LoopsToGPU) add_subdirectory(LoopToStandard) add_subdirectory(StandardToLLVM) diff --git a/mlir/lib/Conversion/LinalgToLLVM/LinalgToLLVM.cpp b/mlir/lib/Conversion/LinalgToLLVM/LinalgToLLVM.cpp --- a/mlir/lib/Conversion/LinalgToLLVM/LinalgToLLVM.cpp +++ b/mlir/lib/Conversion/LinalgToLLVM/LinalgToLLVM.cpp @@ -349,205 +349,6 @@ }; } // namespace -template -static SmallVector ExtractOperandTypes(Operation *op) { - return SmallVector{op->getOperandTypes()}; -} - -template <> -SmallVector ExtractOperandTypes(Operation *op) { - auto ctx = op->getContext(); - auto indexedGenericOp = cast(op); - auto numLoops = indexedGenericOp.getNumLoops(); - - SmallVector result; - result.reserve(numLoops + op->getNumOperands()); - for (unsigned i = 0; i < numLoops; ++i) { - result.push_back(IndexType::get(ctx)); - } - for (auto type : op->getOperandTypes()) { - result.push_back(type); - } - return result; -} - -// Get a SymbolRefAttr containing the library function name for the LinalgOp. -// If the library function does not exist, insert a declaration. -template -static FlatSymbolRefAttr getLibraryCallSymbolRef(Operation *op, - PatternRewriter &rewriter) { - auto linalgOp = cast(op); - auto fnName = linalgOp.getLibraryCallName(); - if (fnName.empty()) { - op->emitWarning("No library call defined for: ") << *op; - return {}; - } - - // fnName is a dynamic std::String, unique it via a SymbolRefAttr. - FlatSymbolRefAttr fnNameAttr = rewriter.getSymbolRefAttr(fnName); - auto module = op->getParentOfType(); - if (module.lookupSymbol(fnName)) { - return fnNameAttr; - } - - SmallVector inputTypes(ExtractOperandTypes(op)); - assert(op->getNumResults() == 0 && - "Library call for linalg operation can be generated only for ops that " - "have void return types"); - auto libFnType = FunctionType::get(inputTypes, {}, rewriter.getContext()); - - OpBuilder::InsertionGuard guard(rewriter); - // Insert before module terminator. - rewriter.setInsertionPoint(module.getBody(), - std::prev(module.getBody()->end())); - FuncOp funcOp = - rewriter.create(op->getLoc(), fnNameAttr.getValue(), libFnType, - ArrayRef{}); - // Insert a function attribute that will trigger the emission of the - // corresponding `_mlir_ciface_xxx` interface so that external libraries see - // a normalized ABI. This interface is added during std to llvm conversion. - funcOp.setAttr("llvm.emit_c_interface", UnitAttr::get(op->getContext())); - return fnNameAttr; -} - -namespace { - -// LinalgOpConversion creates a new call to the -// `LinalgOp::getLibraryCallName()` function. -// The implementation of the function can be either in the same module or in an -// externally linked library. -template -class LinalgOpConversion : public OpRewritePattern { -public: - using OpRewritePattern::OpRewritePattern; - - LogicalResult matchAndRewrite(LinalgOp op, - PatternRewriter &rewriter) const override { - auto libraryCallName = getLibraryCallSymbolRef(op, rewriter); - if (!libraryCallName) - return failure(); - - rewriter.replaceOpWithNewOp( - op, libraryCallName.getValue(), ArrayRef{}, op.getOperands()); - return success(); - } -}; - -/// Conversion pattern specialization for CopyOp. This kicks in when both input -/// and output permutations are left unspecified or are the identity. -template <> class LinalgOpConversion : public OpRewritePattern { -public: - using OpRewritePattern::OpRewritePattern; - - LogicalResult matchAndRewrite(CopyOp op, - PatternRewriter &rewriter) const override { - auto inputPerm = op.inputPermutation(); - if (inputPerm.hasValue() && !inputPerm->isIdentity()) - return failure(); - auto outputPerm = op.outputPermutation(); - if (outputPerm.hasValue() && !outputPerm->isIdentity()) - return failure(); - - auto libraryCallName = getLibraryCallSymbolRef(op, rewriter); - if (!libraryCallName) - return failure(); - - rewriter.replaceOpWithNewOp( - op, libraryCallName.getValue(), ArrayRef{}, op.getOperands()); - return success(); - } -}; - -/// Conversion pattern specialization for IndexedGenericOp. -template <> -class LinalgOpConversion - : public OpRewritePattern { -public: - using OpRewritePattern::OpRewritePattern; - - LogicalResult matchAndRewrite(IndexedGenericOp op, - PatternRewriter &rewriter) const override { - auto libraryCallName = - getLibraryCallSymbolRef(op, rewriter); - if (!libraryCallName) - return failure(); - - // TODO(pifon, ntv): Use induction variables values instead of zeros, when - // IndexedGenericOp is tiled. - auto zero = rewriter.create( - op.getLoc(), rewriter.getIntegerAttr(rewriter.getIndexType(), 0)); - auto indexedGenericOp = cast(op); - auto numLoops = indexedGenericOp.getNumLoops(); - SmallVector operands; - operands.reserve(numLoops + op.getNumOperands()); - for (unsigned i = 0; i < numLoops; ++i) { - operands.push_back(zero); - } - for (auto operand : op.getOperands()) { - operands.push_back(operand); - } - rewriter.replaceOpWithNewOp(op, libraryCallName.getValue(), - ArrayRef{}, operands); - return success(); - } -}; - -/// A non-conversion rewrite pattern kicks in to convert CopyOp with -/// permutations into a sequence of TransposeOp and permutation-free CopyOp. -/// This interplays together with TransposeOpConversion and -/// LinalgConversion to create a path to the LLVM dialect. -class CopyTransposeConversion : public OpRewritePattern { -public: - using OpRewritePattern::OpRewritePattern; - - LogicalResult matchAndRewrite(CopyOp op, - PatternRewriter &rewriter) const override { - Value in = op.input(), out = op.output(); - - // If either inputPerm or outputPerm are non-identities, insert transposes. - auto inputPerm = op.inputPermutation(); - if (inputPerm.hasValue() && !inputPerm->isIdentity()) - in = rewriter.create(op.getLoc(), in, - AffineMapAttr::get(*inputPerm)); - auto outputPerm = op.outputPermutation(); - if (outputPerm.hasValue() && !outputPerm->isIdentity()) - out = rewriter.create( - op.getLoc(), out, AffineMapAttr::get(*outputPerm)); - - // If nothing was transposed, fail and let the conversion kick in. - if (in == op.input() && out == op.output()) - return failure(); - - rewriter.replaceOpWithNewOp(op, in, out); - return success(); - } -}; - -/// Populate the given list with patterns that convert from Linalg to Standard. -static void -populateLinalgToStandardConversionPatterns(OwningRewritePatternList &patterns, - MLIRContext *ctx) { - // TODO(ntv) ConvOp conversion needs to export a descriptor with relevant - // attribute values such as kernel striding and dilation. - // clang-format off - patterns.insert< - CopyTransposeConversion, - LinalgOpConversion, - LinalgOpConversion, - LinalgOpConversion, - LinalgOpConversion, - LinalgOpConversion, - LinalgOpConversion, - LinalgOpConversion, - LinalgOpConversion, - LinalgOpConversion, - LinalgOpConversion, - LinalgOpConversion>(ctx); - // clang-format on -} - -} // namespace - /// Populate the given list with patterns that convert from Linalg to LLVM. void mlir::populateLinalgToLLVMConversionPatterns( LLVMTypeConverter &converter, OwningRewritePatternList &patterns, @@ -579,7 +380,6 @@ populateVectorToLoopsConversionPatterns(patterns, &getContext()); populateVectorToLLVMMatrixConversionPatterns(converter, patterns); populateVectorToLLVMConversionPatterns(converter, patterns); - populateLinalgToStandardConversionPatterns(patterns, &getContext()); populateLinalgToLLVMConversionPatterns(converter, patterns, &getContext()); LLVMConversionTarget target(getContext()); diff --git a/mlir/lib/Conversion/LinalgToStandard/CMakeLists.txt b/mlir/lib/Conversion/LinalgToStandard/CMakeLists.txt new file mode 100644 --- /dev/null +++ b/mlir/lib/Conversion/LinalgToStandard/CMakeLists.txt @@ -0,0 +1,19 @@ +add_mlir_conversion_library(MLIRLinalgToStandard + LinalgToStandard.cpp + + ADDITIONAL_HEADER_DIRS + ${MLIR_MAIN_INCLUDE_DIR}/mlir/Conversion/LinalgToStandard + + DEPENDS + MLIRConversionPassIncGen +) + +target_link_libraries(MLIRLinalgToStandard + PUBLIC + MLIREDSC + MLIRIR + MLIRLinalgOps + MLIRSCF + LLVMCore + LLVMSupport + ) diff --git a/mlir/lib/Conversion/LinalgToStandard/LinalgToStandard.cpp b/mlir/lib/Conversion/LinalgToStandard/LinalgToStandard.cpp new file mode 100644 --- /dev/null +++ b/mlir/lib/Conversion/LinalgToStandard/LinalgToStandard.cpp @@ -0,0 +1,271 @@ +//===- LinalgToStandard.cpp - conversion from Linalg to Standard dialect --===// +// +// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. +// See https://llvm.org/LICENSE.txt for license information. +// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception +// +//===----------------------------------------------------------------------===// + +#include "mlir/Conversion/LinalgToStandard/LinalgToStandard.h" + +#include "../PassDetail.h" +#include "mlir/Dialect/Affine/IR/AffineOps.h" +#include "mlir/Dialect/Linalg/IR/LinalgOps.h" +#include "mlir/Dialect/SCF/SCF.h" +#include "mlir/Dialect/StandardOps/IR/Ops.h" + +using namespace mlir; +using namespace mlir::linalg; + +/// Helper function to extract the operand types that are passed to the +/// generated CallOp. MemRefTypes have their layout canonicalized since the +/// information is not used in signature generation. +/// Note that static size information is not modified. +template +static SmallVector extractOperandTypes(Operation *op) { + SmallVector result; + result.reserve(op->getNumOperands()); + for (auto type : op->getOperandTypes()) { + // The underlying descriptor type (e.g. LLVM) does not have layout + // information. Canonicalizing the type at the level of std when going into + // a library call avoids needing to introduce DialectCastOp. + if (auto memrefType = type.dyn_cast()) + result.push_back(eraseStridedLayout(memrefType)); + else + result.push_back(type); + } + return result; +} + +template <> +SmallVector extractOperandTypes(Operation *op) { + auto *ctx = op->getContext(); + auto indexedGenericOp = cast(op); + auto numLoops = indexedGenericOp.getNumLoops(); + + SmallVector result(numLoops, IndexType::get(ctx)); + auto canonicalizedOperands = extractOperandTypes(op); + result.append(canonicalizedOperands.begin(), canonicalizedOperands.end()); + return result; +} + +// Get a SymbolRefAttr containing the library function name for the LinalgOp. +// If the library function does not exist, insert a declaration. +template +static FlatSymbolRefAttr getLibraryCallSymbolRef(Operation *op, + PatternRewriter &rewriter) { + auto linalgOp = cast(op); + auto fnName = linalgOp.getLibraryCallName(); + if (fnName.empty()) { + op->emitWarning("No library call defined for: ") << *op; + return {}; + } + + // fnName is a dynamic std::string, unique it via a SymbolRefAttr. + FlatSymbolRefAttr fnNameAttr = rewriter.getSymbolRefAttr(fnName); + auto module = op->getParentOfType(); + if (module.lookupSymbol(fnName)) { + return fnNameAttr; + } + + SmallVector inputTypes(extractOperandTypes(op)); + assert(op->getNumResults() == 0 && + "Library call for linalg operation can be generated only for ops that " + "have void return types"); + auto libFnType = FunctionType::get(inputTypes, {}, rewriter.getContext()); + + OpBuilder::InsertionGuard guard(rewriter); + // Insert before module terminator. + rewriter.setInsertionPoint(module.getBody(), + std::prev(module.getBody()->end())); + FuncOp funcOp = + rewriter.create(op->getLoc(), fnNameAttr.getValue(), libFnType, + ArrayRef{}); + // Insert a function attribute that will trigger the emission of the + // corresponding `_mlir_ciface_xxx` interface so that external libraries see + // a normalized ABI. This interface is added during std to llvm conversion. + funcOp.setAttr("llvm.emit_c_interface", UnitAttr::get(op->getContext())); + return fnNameAttr; +} + +namespace { + +SmallVector +createTypeCanonicalizedMemRefOperands(OpBuilder &b, Location loc, + ValueRange operands) { + SmallVector res; + res.reserve(operands.size()); + for (auto op : operands) { + auto memrefType = op.getType().dyn_cast(); + if (!memrefType) { + res.push_back(op); + continue; + } + Value cast = + b.create(loc, eraseStridedLayout(memrefType), op); + res.push_back(cast); + } + return res; +} + +// LinalgOpConversion creates a new call to the type-canonicalized +// `LinalgOp::getLibraryCallName()` function. +// The implementation of the function can be either in the same module or in an +// externally linked library. +template +class LinalgOpConversion : public OpRewritePattern { +public: + using OpRewritePattern::OpRewritePattern; + + LogicalResult matchAndRewrite(LinalgOp op, + PatternRewriter &rewriter) const override { + auto libraryCallName = getLibraryCallSymbolRef(op, rewriter); + if (!libraryCallName) + return failure(); + + rewriter.replaceOpWithNewOp( + op, libraryCallName.getValue(), ArrayRef{}, + createTypeCanonicalizedMemRefOperands(rewriter, op.getLoc(), + op.getOperands())); + return success(); + } +}; + +/// Conversion pattern specialization for CopyOp. This kicks in when both input +/// and output permutations are left unspecified or are the identity. +template <> +class LinalgOpConversion : public OpRewritePattern { +public: + using OpRewritePattern::OpRewritePattern; + + LogicalResult matchAndRewrite(CopyOp op, + PatternRewriter &rewriter) const override { + auto inputPerm = op.inputPermutation(); + if (inputPerm.hasValue() && !inputPerm->isIdentity()) + return failure(); + auto outputPerm = op.outputPermutation(); + if (outputPerm.hasValue() && !outputPerm->isIdentity()) + return failure(); + + auto libraryCallName = getLibraryCallSymbolRef(op, rewriter); + if (!libraryCallName) + return failure(); + + rewriter.replaceOpWithNewOp( + op, libraryCallName.getValue(), ArrayRef{}, + createTypeCanonicalizedMemRefOperands(rewriter, op.getLoc(), + op.getOperands())); + return success(); + } +}; + +/// Conversion pattern specialization for IndexedGenericOp. +template <> +class LinalgOpConversion + : public OpRewritePattern { +public: + using OpRewritePattern::OpRewritePattern; + + LogicalResult matchAndRewrite(IndexedGenericOp op, + PatternRewriter &rewriter) const override { + auto libraryCallName = + getLibraryCallSymbolRef(op, rewriter); + if (!libraryCallName) + return failure(); + + // TODO(pifon, ntv): Use induction variables values instead of zeros, when + // IndexedGenericOp is tiled. + auto zero = rewriter.create( + op.getLoc(), rewriter.getIntegerAttr(rewriter.getIndexType(), 0)); + auto indexedGenericOp = cast(op); + auto numLoops = indexedGenericOp.getNumLoops(); + SmallVector operands; + operands.reserve(numLoops + op.getNumOperands()); + for (unsigned i = 0; i < numLoops; ++i) + operands.push_back(zero); + for (auto operand : op.getOperands()) + operands.push_back(operand); + rewriter.replaceOpWithNewOp( + op, libraryCallName.getValue(), ArrayRef{}, + createTypeCanonicalizedMemRefOperands(rewriter, op.getLoc(), operands)); + return success(); + } +}; + +/// A non-conversion rewrite pattern kicks in to convert CopyOp with +/// permutations into a sequence of TransposeOp and permutation-free CopyOp. +/// This interplays together with TransposeOpConversion and +/// LinalgConversion to create a path to the LLVM dialect. +class CopyTransposeConversion : public OpRewritePattern { +public: + using OpRewritePattern::OpRewritePattern; + + LogicalResult matchAndRewrite(CopyOp op, + PatternRewriter &rewriter) const override { + Value in = op.input(), out = op.output(); + + // If either inputPerm or outputPerm are non-identities, insert transposes. + auto inputPerm = op.inputPermutation(); + if (inputPerm.hasValue() && !inputPerm->isIdentity()) + in = rewriter.create(op.getLoc(), in, + AffineMapAttr::get(*inputPerm)); + auto outputPerm = op.outputPermutation(); + if (outputPerm.hasValue() && !outputPerm->isIdentity()) + out = rewriter.create( + op.getLoc(), out, AffineMapAttr::get(*outputPerm)); + + // If nothing was transposed, fail and let the conversion kick in. + if (in == op.input() && out == op.output()) + return failure(); + + rewriter.replaceOpWithNewOp(op, in, out); + return success(); + } +}; +} // namespace + +/// Populate the given list with patterns that convert from Linalg to Standard. +void mlir::populateLinalgToStandardConversionPatterns( + OwningRewritePatternList &patterns, MLIRContext *ctx) { + // TODO(ntv) ConvOp conversion needs to export a descriptor with relevant + // attribute values such as kernel striding and dilation. + // clang-format off + patterns.insert< + CopyTransposeConversion, + LinalgOpConversion, + LinalgOpConversion, + LinalgOpConversion, + LinalgOpConversion, + LinalgOpConversion, + LinalgOpConversion, + LinalgOpConversion, + LinalgOpConversion, + LinalgOpConversion, + LinalgOpConversion, + LinalgOpConversion>(ctx); + // clang-format on +} + +namespace { +struct ConvertLinalgToStandardPass + : public ConvertLinalgToStandardBase { + void runOnOperation() override; +}; +} // namespace + +void ConvertLinalgToStandardPass::runOnOperation() { + auto module = getOperation(); + ConversionTarget target(getContext()); + target.addLegalDialect(); + target.addLegalOp(); + target.addLegalOp(); + OwningRewritePatternList patterns; + populateLinalgToStandardConversionPatterns(patterns, &getContext()); + if (failed(applyFullConversion(module, target, patterns))) + signalPassFailure(); +} + +std::unique_ptr> +mlir::createConvertLinalgToStandardPass() { + return std::make_unique(); +} diff --git a/mlir/lib/Conversion/StandardToLLVM/StandardToLLVM.cpp b/mlir/lib/Conversion/StandardToLLVM/StandardToLLVM.cpp --- a/mlir/lib/Conversion/StandardToLLVM/StandardToLLVM.cpp +++ b/mlir/lib/Conversion/StandardToLLVM/StandardToLLVM.cpp @@ -2003,15 +2003,14 @@ Type srcType = memRefCastOp.getOperand().getType(); Type dstType = memRefCastOp.getType(); - if (srcType.isa() && dstType.isa()) { - MemRefType sourceType = - memRefCastOp.getOperand().getType().cast(); - MemRefType targetType = memRefCastOp.getType().cast(); - return (isSupportedMemRefType(targetType) && - isSupportedMemRefType(sourceType)) - ? success() - : failure(); - } + // MemRefCastOp reduce to bitcast in the ranked MemRef case and can be used + // for type erasure. For now they must preserve underlying element type and + // require source and result type to have the same rank. Therefore, perform + // a sanity check that the underlying structs are the same. Once op + // semantics are relaxed we can revisit. + if (srcType.isa() && dstType.isa()) + return success(typeConverter.convertType(srcType) == + typeConverter.convertType(dstType)); // At least one of the operands is unranked type assert(srcType.isa() || @@ -2034,10 +2033,8 @@ auto targetStructType = typeConverter.convertType(memRefCastOp.getType()); auto loc = op->getLoc(); + // MemRefCastOp reduce to bitcast in the ranked MemRef case. if (srcType.isa() && dstType.isa()) { - // memref_cast is defined for source and destination memref types with the - // same element type, same mappings, same address space and same rank. - // Therefore a simple bitcast suffices. If not it is undefined behavior. rewriter.replaceOpWithNewOp(op, targetStructType, transformed.source()); } else if (srcType.isa() && dstType.isa()) { diff --git a/mlir/lib/IR/StandardTypes.cpp b/mlir/lib/IR/StandardTypes.cpp --- a/mlir/lib/IR/StandardTypes.cpp +++ b/mlir/lib/IR/StandardTypes.cpp @@ -764,6 +764,14 @@ return simplifyAffineExpr(expr, numDims, nSymbols); } +/// Return a version of `t` with a layout that has all dynamic offset and +/// strides. This is used to erase the static layout. +MemRefType mlir::eraseStridedLayout(MemRefType t) { + auto val = ShapedType::kDynamicStrideOrOffset; + return MemRefType::Builder(t).setAffineMaps(makeStridedLinearLayoutMap( + SmallVector(t.getRank(), val), val, t.getContext())); +} + AffineExpr mlir::makeCanonicalStridedLayoutExpr(ArrayRef sizes, MLIRContext *context) { SmallVector exprs; diff --git a/mlir/test/Conversion/StandardToLLVM/invalid.mlir b/mlir/test/Conversion/StandardToLLVM/invalid.mlir --- a/mlir/test/Conversion/StandardToLLVM/invalid.mlir +++ b/mlir/test/Conversion/StandardToLLVM/invalid.mlir @@ -1,18 +1,5 @@ // RUN: mlir-opt %s -convert-std-to-llvm -verify-diagnostics -split-input-file -#map1 = affine_map<(d0, d1)[s0, s1, s2] -> (d0 * s1 + s0 + d1 * s2)> - -func @invalid_memref_cast(%arg0: memref) { - %c1 = constant 1 : index - %c0 = constant 0 : index - // expected-error@+1 {{'std.memref_cast' op operand #0 must be unranked.memref of any type values or memref of any type values, but got '!llvm<"{ double*, double*, i64, [2 x i64], [2 x i64] }">'}} - %5 = memref_cast %arg0 : memref to memref - %25 = std.subview %5[%c0, %c0][%c1, %c1][1, 1] : memref to memref - return -} - -// ----- - func @mlir_cast_to_llvm(%0 : index) -> !llvm.i64 { // expected-error@+1 {{'llvm.mlir.cast' op type must be non-index integer types, float types, or vector of mentioned types}} %1 = llvm.mlir.cast %0 : index to !llvm.i64 diff --git a/mlir/test/Dialect/Linalg/llvm.mlir b/mlir/test/Dialect/Linalg/llvm.mlir --- a/mlir/test/Dialect/Linalg/llvm.mlir +++ b/mlir/test/Dialect/Linalg/llvm.mlir @@ -1,5 +1,4 @@ // RUN: mlir-opt %s -convert-linalg-to-llvm | FileCheck %s -// RUN: mlir-opt %s -convert-linalg-to-loops | FileCheck %s --check-prefix=LLVM-LOOPS func @range(%arg0: index) { %c0 = constant 0 : index @@ -48,16 +47,6 @@ // CHECK-NEXT: llvm.insertvalue %{{.*}}, %{{.*}}[3, 0] : !llvm<"{ float*, float*, i64, [1 x i64], [1 x i64] }"> // CHECK-NEXT: llvm.insertvalue %{{.*}}, %{{.*}}[4, 0] : !llvm<"{ float*, float*, i64, [1 x i64], [1 x i64] }"> -func @dot(%arg0: memref, %arg1: memref, %arg2: memref) { - linalg.dot(%arg0, %arg1, %arg2) : memref, memref, memref - return -} -// CHECK-LABEL: func @dot -// CHECK: llvm.call @linalg_dot_viewsxf32_viewsxf32_viewf32(%{{.*}}) : -// CHECK-SAME: !llvm<"float*">, !llvm<"float*">, !llvm.i64, !llvm.i64, !llvm.i64 -// CHECK-SAME: !llvm<"float*">, !llvm<"float*">, !llvm.i64, !llvm.i64, !llvm.i64 -// CHECK-SAME: !llvm<"float*">, !llvm<"float*">, !llvm.i64 - func @slice_with_range_and_index(%arg0: memref) { %c0 = constant 0 : index %c1 = constant 1 : index @@ -80,15 +69,6 @@ // CHECK: llvm.insertvalue %{{.*}}[3, 0] : !llvm<"{ double*, double*, i64, [1 x i64], [1 x i64] }"> // CHECK: llvm.insertvalue %{{.*}}[4, 0] : !llvm<"{ double*, double*, i64, [1 x i64], [1 x i64] }"> -func @copy(%arg0: memref, %arg1: memref) { - linalg.copy(%arg0, %arg1) : memref, memref - return -} -// CHECK-LABEL: func @copy -// CHECK: llvm.call @linalg_copy_viewsxsxsxf32_viewsxsxsxf32({{.*}}) : -// CHECK-SAME: !llvm<"float*">, !llvm<"float*">, !llvm.i64, !llvm.i64, !llvm.i64, !llvm.i64, !llvm.i64, !llvm.i64, !llvm.i64 -// CHECK-SAME: !llvm<"float*">, !llvm<"float*">, !llvm.i64, !llvm.i64, !llvm.i64, !llvm.i64, !llvm.i64, !llvm.i64, !llvm.i64 - func @transpose(%arg0: memref) { %0 = linalg.transpose %arg0 (i, j, k) -> (k, i, j) : memref return @@ -105,115 +85,6 @@ // CHECK: llvm.extractvalue {{.*}}[3, 2] : !llvm<"{ float*, float*, i64, [3 x i64], [3 x i64] }"> // CHECK: llvm.insertvalue {{.*}}[3, 1] : !llvm<"{ float*, float*, i64, [3 x i64], [3 x i64] }"> -func @copy_transpose(%arg0: memref, %arg1: memref) { - linalg.copy(%arg0, %arg1) {inputPermutation = affine_map<(i, j, k) -> (i, k, j)>, - outputPermutation = affine_map<(i, j, k) -> (k, j, i)>} - : memref, memref - return -} -// CHECK-LABEL: func @copy -// Transpose input -// CHECK: llvm.insertvalue {{.*}}[0] : !llvm<"{ float*, float*, i64, [3 x i64], [3 x i64] }"> -// CHECK: llvm.insertvalue {{.*}}[1] : !llvm<"{ float*, float*, i64, [3 x i64], [3 x i64] }"> -// CHECK: llvm.insertvalue {{.*}}[2] : !llvm<"{ float*, float*, i64, [3 x i64], [3 x i64] }"> -// CHECK: llvm.extractvalue {{.*}}[3, 0] : !llvm<"{ float*, float*, i64, [3 x i64], [3 x i64] }"> -// CHECK: llvm.insertvalue {{.*}}[3, 0] : !llvm<"{ float*, float*, i64, [3 x i64], [3 x i64] }"> -// CHECK: llvm.extractvalue {{.*}}[3, 1] : !llvm<"{ float*, float*, i64, [3 x i64], [3 x i64] }"> -// CHECK: llvm.insertvalue {{.*}}[3, 2] : !llvm<"{ float*, float*, i64, [3 x i64], [3 x i64] }"> -// CHECK: llvm.extractvalue {{.*}}[3, 2] : !llvm<"{ float*, float*, i64, [3 x i64], [3 x i64] }"> -// CHECK: llvm.insertvalue {{.*}}[3, 1] : !llvm<"{ float*, float*, i64, [3 x i64], [3 x i64] }"> -// Transpose output -// CHECK: llvm.insertvalue {{.*}}[0] : !llvm<"{ float*, float*, i64, [3 x i64], [3 x i64] }"> -// CHECK: llvm.insertvalue {{.*}}[1] : !llvm<"{ float*, float*, i64, [3 x i64], [3 x i64] }"> -// CHECK: llvm.insertvalue {{.*}}[2] : !llvm<"{ float*, float*, i64, [3 x i64], [3 x i64] }"> -// CHECK: llvm.extractvalue {{.*}}[3, 0] : !llvm<"{ float*, float*, i64, [3 x i64], [3 x i64] }"> -// CHECK: llvm.insertvalue {{.*}}[3, 2] : !llvm<"{ float*, float*, i64, [3 x i64], [3 x i64] }"> -// CHECK: llvm.extractvalue {{.*}}[3, 1] : !llvm<"{ float*, float*, i64, [3 x i64], [3 x i64] }"> -// CHECK: llvm.insertvalue {{.*}}[3, 1] : !llvm<"{ float*, float*, i64, [3 x i64], [3 x i64] }"> -// CHECK: llvm.extractvalue {{.*}}[3, 2] : !llvm<"{ float*, float*, i64, [3 x i64], [3 x i64] }"> -// CHECK: llvm.insertvalue {{.*}}[3, 0] : !llvm<"{ float*, float*, i64, [3 x i64], [3 x i64] }"> -// Call external copy. -// CHECK: llvm.call @linalg_copy_viewsxsxsxf32_viewsxsxsxf32 - -#matmul_accesses = [ - affine_map<(m, n, k) -> (m, k)>, - affine_map<(m, n, k) -> (k, n)>, - affine_map<(m, n, k) -> (m, n)> -] -#matmul_trait = { - args_in = 2, - args_out = 1, - iterator_types = ["parallel", "parallel", "reduction"], - indexing_maps = #matmul_accesses, - library_call = "external_outerproduct_matmul" -} - -!vector_type_A = type vector<4xf32> -!vector_type_B = type vector<4xf32> -!vector_type_C = type vector<4x4xf32> - -!matrix_type_A = type memref -!matrix_type_B = type memref -!matrix_type_C = type memref - -func @matmul_vec_impl(%A: !matrix_type_A, %B: !matrix_type_B, %C: !matrix_type_C) { - linalg.generic #matmul_trait %A, %B, %C { - ^bb0(%a: !vector_type_A, %b: !vector_type_B, %c: !vector_type_C): - %d = vector.outerproduct %a, %b, %c: !vector_type_A, !vector_type_B - linalg.yield %d: !vector_type_C - } : !matrix_type_A, !matrix_type_B, !matrix_type_C - - return -} -// CHECK-LABEL: func @matmul_vec_impl( -// CHECK: llvm.call @external_outerproduct_matmul(%{{.*}}) : -// CHECK-SAME: !llvm<"<4 x float>*">, !llvm<"<4 x float>*">, !llvm.i64, !llvm.i64, !llvm.i64, !llvm.i64, !llvm.i64 -// CHECK-SAME: !llvm<"<4 x float>*">, !llvm<"<4 x float>*">, !llvm.i64, !llvm.i64, !llvm.i64, !llvm.i64, !llvm.i64 -// CHECK-SAME: !llvm<"[4 x <4 x float>]*">, !llvm<"[4 x <4 x float>]*">, !llvm.i64, !llvm.i64, !llvm.i64, !llvm.i64, !llvm.i64 - -// LLVM-LOOPS-LABEL: func @matmul_vec_impl( -// LLVM-LOOPS-SAME: %[[A:.*0]]: memref>, -// LLVM-LOOPS-SAME: %[[B:.*1]]: memref>, -// LLVM-LOOPS-SAME: %[[C:.*2]]: memref>) -// LLVM-LOOPS: %[[C0:.*]] = constant 0 : index -// LLVM-LOOPS: %[[C1:.*]] = constant 1 : index -// LLVM-LOOPS: %[[T0:.*]] = dim %[[A]], 0 : memref> -// LLVM-LOOPS: %[[T1:.*]] = dim %[[A]], 1 : memref> -// LLVM-LOOPS: %[[T2:.*]] = dim %[[B]], 1 : memref> -// LLVM-LOOPS: scf.for %[[I:.*]] = %[[C0]] to %[[T0]] step %[[C1]] { -// LLVM-LOOPS: scf.for %[[J:.*]] = %[[C0]] to %[[T2]] step %[[C1]] { -// LLVM-LOOPS: scf.for %[[K:.*]] = %[[C0]] to %[[T1]] step %[[C1]] { -// LLVM-LOOPS: %[[T3:.*]] = load %[[A]][%[[I]], %[[K]]] : memref> -// LLVM-LOOPS: %[[T4:.*]] = load %[[B]][%[[K]], %[[J]]] : memref> -// LLVM-LOOPS: %[[T5:.*]] = load %[[C]][%[[I]], %[[J]]] : memref> -// LLVM-LOOPS: %[[T6:.*]] = vector.outerproduct %3, %4, %5 : vector<4xf32>, vector<4xf32> -// LLVM-LOOPS: store %[[T6]], %[[C]][%[[I]], %[[J]]] : memref> - -#indexed_matmul_trait = { - args_in = 2, - args_out = 1, - iterator_types = ["parallel", "parallel", "reduction"], - indexing_maps = #matmul_accesses, - library_call = "external_indexed_outerproduct_matmul" -} -func @matmul_vec_indexed(%A: !matrix_type_A, - %B: !matrix_type_B, - %C: !matrix_type_C) { - linalg.indexed_generic #indexed_matmul_trait %A, %B, %C { - ^bb0(%i: index, %j: index, %k: index, - %a: !vector_type_A, %b: !vector_type_B, %c: !vector_type_C): - %d = vector.outerproduct %a, %b, %c: !vector_type_A, !vector_type_B - linalg.yield %d: !vector_type_C - } : !matrix_type_A, !matrix_type_B, !matrix_type_C - return -} -// CHECK-LABEL: func @matmul_vec_indexed( -// CHECK: %[[ZERO:.*]] = llvm.mlir.constant(0 : index) : !llvm.i64 -// CHECK: llvm.call @external_indexed_outerproduct_matmul(%[[ZERO]], %[[ZERO]], %[[ZERO]], %{{.*}}) : -// CHECK-SAME: !llvm<"<4 x float>*">, !llvm<"<4 x float>*">, !llvm.i64, !llvm.i64, !llvm.i64, !llvm.i64, !llvm.i64 -// CHECK-SAME: !llvm<"<4 x float>*">, !llvm<"<4 x float>*">, !llvm.i64, !llvm.i64, !llvm.i64, !llvm.i64, !llvm.i64 -// CHECK-SAME: !llvm<"[4 x <4 x float>]*">, !llvm<"[4 x <4 x float>]*">, !llvm.i64, !llvm.i64, !llvm.i64, !llvm.i64, !llvm.i64 - func @reshape_static_expand(%arg0: memref<3x4x5xf32>) -> memref<1x3x4x1x5xf32> { // Reshapes that expand a contiguous tensor with some 1's. %0 = linalg.reshape %arg0 [affine_map<(i, j, k, l, m) -> (i, j)>, diff --git a/mlir/test/Dialect/Linalg/standard.mlir b/mlir/test/Dialect/Linalg/standard.mlir new file mode 100644 --- /dev/null +++ b/mlir/test/Dialect/Linalg/standard.mlir @@ -0,0 +1,122 @@ +// RUN: mlir-opt %s -convert-linalg-to-std | FileCheck %s + +// CHECK-DAG: #[[map0:.*]] = affine_map<(d0)[s0] -> (d0 + s0)> +// CHECK-DAG: #[[map1:.*]] = affine_map<(d0, d1, d2)[s0, s1, s2] -> (d0 * s1 + s0 + d1 * s2 + d2)> +// CHECK-DAG: #[[map2:.*]] = affine_map<(d0, d1, d2)[s0, s1, s2] -> (d0 * s1 + s0 + d2 * s2 + d1)> +// CHECK-DAG: #[[map3:.*]] = affine_map<(d0, d1, d2) -> (d0, d2, d1)> +// CHECK-DAG: #[[map4:.*]] = affine_map<(d0, d1, d2)[s0, s1, s2] -> (d2 * s1 + s0 + d1 * s2 + d0)> +// CHECK-DAG: #[[map5:.*]] = affine_map<(d0, d1, d2) -> (d2, d1, d0)> +// CHECK-DAG: #[[map6:.*]] = affine_map<(d0)[s0, s1] -> (d0 * s1 + s0)> +// CHECK-DAG: #[[map7:.*]] = affine_map<()[s0] -> (s0)> +// CHECK-DAG: #[[map8:.*]] = affine_map<(d0, d1, d2)[s0, s1, s2, s3] -> (d0 * s1 + s0 + d1 * s2 + d2 * s3)> + +func @dot(%arg0: memref, + %arg1: memref, + %arg2: memref) { + linalg.dot(%arg0, %arg1, %arg2) : memref, + memref, + memref + return +} +// CHECK-LABEL: func @dot( +// CHECK-SAME: %[[arg0:[a-zA-z0-9]*]]: memref, +// CHECK-SAME: %[[arg1:[a-zA-z0-9]*]]: memref, +// CHECK-SAME: %[[arg2:[a-zA-z0-9]*]]: memref) { +// CHECK: %[[o0:.*]] = memref_cast %[[arg0]] : +// CHECK-SAME: memref to memref +// CHECK: %[[o1:.*]] = memref_cast %[[arg1]] : +// CHECK-SAME: memref to memref +// CHECK: %[[o2:.*]] = memref_cast %[[arg2]] : +// CHECK-SAME: memref to memref +// CHECK: call @linalg_dot_viewsxf32_viewsxf32_viewf32( +// CHECK-SAME: %[[o0]], %[[o1]], %[[o2]]) : +// CHECK-SAME: memref, memref, memref + +func @copy(%arg0: memref, %arg1: memref) { + linalg.copy(%arg0, %arg1) : memref, memref + return +} +// CHECK-LABEL: func @copy( +// CHECK-SAME: %[[arg0:[a-zA-z0-9]*]]: memref, +// CHECK-SAME: %[[arg1:[a-zA-z0-9]*]]: memref) { +// CHECK: %[[o0:.*]] = memref_cast %[[arg0]] : +// CHECK-SAME: memref to memref +// CHECK: %[[o1:.*]] = memref_cast %[[arg1]] : +// CHECK-SAME: memref to memref +// CHECK: call @linalg_copy_viewsxsxsxf32_viewsxsxsxf32(%[[o0]], %[[o1]]) : +// CHECK-SAME: memref, memref + +func @copy_transpose(%arg0: memref, %arg1: memref) { + linalg.copy(%arg0, %arg1) {inputPermutation = affine_map<(i, j, k) -> (i, k, j)>, + outputPermutation = affine_map<(i, j, k) -> (k, j, i)>} + : memref, memref + return +} +// CHECK-LABEL: func @copy_transpose( +// CHECK-SAME: %[[arg0:[a-zA-z0-9]*]]: memref, +// CHECK-SAME: %[[arg1:[a-zA-z0-9]*]]: memref) { +// CHECK: %[[t0:.*]] = linalg.transpose %[[arg0]] +// CHECK-SAME: (d0, d1, d2) -> (d0, d2, d1) : memref +// CHECK: %[[t1:.*]] = linalg.transpose %[[arg1]] +// CHECK-SAME: (d0, d1, d2) -> (d2, d1, d0) : memref +// CHECK: %[[o0:.*]] = memref_cast %[[t0]] : +// CHECK-SAME: memref to memref +// CHECK: %[[o1:.*]] = memref_cast %[[t1]] : +// CHECK-SAME: memref to memref +// CHECK: call @linalg_copy_viewsxsxsxf32_viewsxsxsxf32(%[[o0]], %[[o1]]) : +// CHECK-SAME: memref, memref + +#matmul_accesses = [ + affine_map<(m, n, k) -> (m, k)>, + affine_map<(m, n, k) -> (k, n)>, + affine_map<(m, n, k) -> (m, n)> +] +#matmul_trait = { + args_in = 2, + args_out = 1, + iterator_types = ["parallel", "parallel", "reduction"], + indexing_maps = #matmul_accesses, + library_call = "external_outerproduct_matmul" +} + +!vector_type_A = type vector<4xf32> +!vector_type_B = type vector<4xf32> +!vector_type_C = type vector<4x4xf32> + +!matrix_type_A = type memref +!matrix_type_B = type memref +!matrix_type_C = type memref + +func @matmul_vec_impl(%A: !matrix_type_A, %B: !matrix_type_B, %C: !matrix_type_C) { + linalg.generic #matmul_trait %A, %B, %C { + ^bb0(%a: !vector_type_A, %b: !vector_type_B, %c: !vector_type_C): + %d = vector.outerproduct %a, %b, %c: !vector_type_A, !vector_type_B + linalg.yield %d: !vector_type_C + } : !matrix_type_A, !matrix_type_B, !matrix_type_C + + return +} +// CHECK-LABEL: func @matmul_vec_impl( +// CHECK: call @external_outerproduct_matmul(%{{.*}}) : + +#indexed_matmul_trait = { + args_in = 2, + args_out = 1, + iterator_types = ["parallel", "parallel", "reduction"], + indexing_maps = #matmul_accesses, + library_call = "external_indexed_outerproduct_matmul" +} +func @matmul_vec_indexed(%A: !matrix_type_A, + %B: !matrix_type_B, + %C: !matrix_type_C) { + linalg.indexed_generic #indexed_matmul_trait %A, %B, %C { + ^bb0(%i: index, %j: index, %k: index, + %a: !vector_type_A, %b: !vector_type_B, %c: !vector_type_C): + %d = vector.outerproduct %a, %b, %c: !vector_type_A, !vector_type_B + linalg.yield %d: !vector_type_C + } : !matrix_type_A, !matrix_type_B, !matrix_type_C + return +} +// CHECK-LABEL: func @matmul_vec_indexed( +// CHECK: %[[ZERO:.*]] = constant 0 : index +// CHECK: call @external_indexed_outerproduct_matmul(%[[ZERO]], %[[ZERO]], %[[ZERO]], %{{.*}}) diff --git a/mlir/test/mlir-cpu-runner/linalg_integration_test.mlir b/mlir/test/mlir-cpu-runner/linalg_integration_test.mlir --- a/mlir/test/mlir-cpu-runner/linalg_integration_test.mlir +++ b/mlir/test/mlir-cpu-runner/linalg_integration_test.mlir @@ -1,24 +1,24 @@ -// RUN: mlir-opt %s -convert-linalg-to-llvm \ +// RUN: mlir-opt %s -convert-linalg-to-std -convert-linalg-to-llvm \ // RUN: | mlir-cpu-runner -e dot -entry-point-result=f32 -shared-libs=%linalg_test_lib_dir/libmlir_test_cblas%shlibext,%linalg_test_lib_dir/libmlir_test_cblas_interface%shlibext \ // RUN: | FileCheck %s -// RUN: mlir-opt %s -convert-linalg-to-loops -convert-linalg-to-llvm \ +// RUN: mlir-opt %s -convert-linalg-to-loops -convert-linalg-to-std -convert-linalg-to-llvm \ // RUN: | mlir-cpu-runner -e dot -entry-point-result=f32 -shared-libs=%linalg_test_lib_dir/libmlir_test_cblas%shlibext,%linalg_test_lib_dir/libmlir_test_cblas_interface%shlibext \ // RUN: | FileCheck %s -// RUN: mlir-opt %s -convert-linalg-to-llvm \ +// RUN: mlir-opt %s -convert-linalg-to-std -convert-linalg-to-llvm \ // RUN: | mlir-cpu-runner -e matmul -entry-point-result=f32 -shared-libs=%linalg_test_lib_dir/libmlir_test_cblas%shlibext,%linalg_test_lib_dir/libmlir_test_cblas_interface%shlibext \ // RUN: | FileCheck %s -// RUN: mlir-opt %s -convert-linalg-to-loops -convert-linalg-to-llvm \ +// RUN: mlir-opt %s -convert-linalg-to-loops -convert-linalg-to-std -convert-linalg-to-llvm \ // RUN: | mlir-cpu-runner -e matmul -entry-point-result=f32 -shared-libs=%linalg_test_lib_dir/libmlir_test_cblas%shlibext,%linalg_test_lib_dir/libmlir_test_cblas_interface%shlibext \ // RUN: | FileCheck %s -// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=2,3,4" -linalg-promote-subviews -convert-linalg-to-loops -convert-linalg-to-llvm \ +// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=2,3,4" -linalg-promote-subviews -convert-linalg-to-loops -convert-linalg-to-std -convert-linalg-to-llvm \ // RUN: | mlir-cpu-runner -e matmul -entry-point-result=f32 -shared-libs=%linalg_test_lib_dir/libmlir_test_cblas%shlibext,%linalg_test_lib_dir/libmlir_test_cblas_interface%shlibext \ // RUN: | FileCheck %s -// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=2,3,4" -linalg-promote-subviews -convert-linalg-to-llvm \ +// RUN: mlir-opt %s -linalg-tile="linalg-tile-sizes=2,3,4" -linalg-promote-subviews -convert-linalg-to-std -convert-linalg-to-llvm \ // RUN: | mlir-cpu-runner -e matmul -entry-point-result=f32 -shared-libs=%linalg_test_lib_dir/libmlir_test_cblas%shlibext,%linalg_test_lib_dir/libmlir_test_cblas_interface%shlibext \ // RUN: | FileCheck %s