[mlir][Linalg] NFC - Cleanup Linalg Declarative Transformations

[nicolasvasilache]

Summary

This is part of an ongoing cleanup and uniformization work.

This diff performs 3 types of cleanups:

1. Uniformize transformation names.
2. Replace all pattern operands that need not be captured by $_
3. Replace all usage of pattern captured op by the normalized op name (instead of positional parameters such as $0)

[merge_guards_bot]

Unit tests: pass. 61127 tests passed, 0 failed and 728 were skipped.

clang-tidy: fail. Please fix clang-tidy findings.

clang-format: pass.

Build artifacts: diff.json, clang-tidy.txt, clang-format.patch, CMakeCache.txt, console-log.txt, test-results.xml

mlir/include/mlir/Dialect/Linalg/Transforms/LinalgTransformPatterns.td

 #ifndef LINALG_TRANSFORMS
 #define LINALG_TRANSFORMS
 
 include "mlir/Dialect/Linalg/IR/LinalgOps.td"
 include "mlir/Dialect/Linalg/IR/LinalgStructuredOps.td"
 include "mlir/Dialect/AffineOps/AffineOps.td"
 
 def HasNoLinalgTransformMarker : CPred<[{
-  !$0.getAttrOfType<StringAttr>(LinalgTransforms::kLinalgTransformMarker)
+  !op.getAttrOfType<StringAttr>(LinalgTransforms::kLinalgTransformMarker)
 }]>;
 
 class HasLinalgTransformMarker<string str> : CPred<[{
-  $0.getAttrOfType<StringAttr>(
+  op.getAttrOfType<StringAttr>(
     LinalgTransforms::kLinalgTransformMarker) &&
-  $0.getAttrOfType<StringAttr>(
+  op.getAttrOfType<StringAttr>(
     LinalgTransforms::kLinalgTransformMarker).getValue() == "}] # str # [{"}]>;
 
 class IsProducedByOpOfType<string str> :
-  CPred<"isProducedByOpOfType<" # str # ">($0, $1)">;
+  CPred<"isProducedByOpOfType<" # str # ">(op, $0)">;
 
 class AffineMapDomainHasDim<int n> : CPred<[{
-  $0.getAttrOfType<ArrayAttr>(getIndexingMapsAttrName()).getValue()[0].
+  op.getAttrOfType<ArrayAttr>(getIndexingMapsAttrName()).getValue()[0].
   cast<AffineMapAttr>().getValue().getNumDims() ==}] # n # [{}]>;
 
 class HasOperandsOfType<string type>: CPred<[{
-    llvm::any_of($0.getOperands(),
+    llvm::any_of(op.getOperands(),
         [](Value v) {
           return dyn_cast_or_null<}] # type # [{>(v->getDefiningOp());
         })
 }]>;
 
 //===----------------------------------------------------------------------===//
 // Linalg fusion patterns.
 //===----------------------------------------------------------------------===//
 //
 // In the future, tile sizes should be derived from op properties + machine
 // description but we do not need to wait on this to start having useful
 // patterns.
 class TileAndFuseLinalgOp<
     list<int> sizes, list<int> operandIndices, string value> : NativeCodeCall<
-  "if (failed(tileAndFuseLinalgOpAndSetMarker($_builder, $0, {" #
+  "if (failed(tileAndFuseLinalgOpAndSetMarker($_builder, op, {" #
   StrJoinInt<sizes>.result # "}, {" # StrJoinInt<operandIndices>.result # "}," #
       " \"" # value # "\")))" #
   "  return matchFailure();">;
 
 //===----------------------------------------------------------------------===//
 // Linalg tiling patterns.
 //===----------------------------------------------------------------------===//
 //
 // In the future, tile sizes should be derived from op properties + machine
 // description but we do not need to wait on this to start having useful
 // patterns.
 // `permutation` is an optional parameter to specify the ordering of the
 // tiled loops. If provided, it must be a list of integers with the same number
 // of elements as `sizes`.
 class TileLinalgOp<list<int> sizes, string value, list<int> permutation=[]> :
   NativeCodeCall<
-    "if (failed(tileLinalgOpAndSetMarker($_builder, $0, {" #
+    "if (failed(tileLinalgOpAndSetMarker($_builder, op, {" #
     StrJoinInt<sizes>.result # "}, \"" # value # "\", {" #
     StrJoinInt<permutation>.result # "})))" #
     "  return matchFailure();">;
 
 //===----------------------------------------------------------------------===//
 // Linalg to loop patterns.
 //===----------------------------------------------------------------------===//
 class LinalgOpToLoops<string OpType> : NativeCodeCall<
-  "if (failed(linalgOpToLoops<" # OpType # ">($_builder, $0))) " #
+  "if (failed(linalgOpToLoops<" # OpType # ">($_builder, op))) " #
   "  return matchFailure();">;
 
 class LinalgOpToAffineLoops<string OpType> : NativeCodeCall<
-  "if (failed(linalgOpToAffineLoops<" # OpType # ">($_builder, $0))) " #
+  "if (failed(linalgOpToAffineLoops<" # OpType # ">($_builder, op))) " #
   "  return matchFailure();">;
 
 //===----------------------------------------------------------------------===//
 // Linalg to vector contraction patterns.
 //===----------------------------------------------------------------------===//
-class LinalgOpToVectorContraction<string OpType> : NativeCodeCall<
-  "if (failed(vectorizeGenericOp($_builder, $0))) " #
+class VectorizeGenericLinalgOp<string OpType> : NativeCodeCall<
+  "if (failed(vectorizeGenericLinalgOp($_builder, op))) " #
   "  return matchFailure();">;
 
 //===----------------------------------------------------------------------===//
 // Linalg generic permutation patterns.
 //===----------------------------------------------------------------------===//
 class PermuteGenericLinalgOp<list<int> permutation, string value> :
   NativeCodeCall<
-    "if (failed(permuteGenericLinalgOp($_builder, $0, {" #
+    "if (failed(permuteGenericLinalgOp($_builder, op, {" #
     StrJoinInt<permutation>.result # "}, \"" # value # "\"))) " #
     "  return matchFailure();">;
 
 //===----------------------------------------------------------------------===//
 // Linalg promote subview operands.
 //===----------------------------------------------------------------------===//
-class LinalgOpPromoteSubviews<string OpType> : NativeCodeCall<
-  "if (failed(linalgOpPromoteSubviews($_builder, $0))) " #
+class PromoteSubviewsLinalgOp<string OpType> : NativeCodeCall<
+  "if (failed(promoteSubviewsLinalgOp($_builder, op))) " #
   "  return matchFailure();">;
 #endif // LINALG_TRANSFORMS

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

 //===- LinalgTransforms.h - Linalg transformations as patterns --*- C++ -*-===//
 //
 // Part of the MLIR 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 DIALECT_LINALG_TRANSFORMS_LINALGTRANSFORMS_H_
 #define DIALECT_LINALG_TRANSFORMS_LINALGTRANSFORMS_H_
 
 #include "mlir/Dialect/Linalg/Analysis/DependenceAnalysis.h"
 #include "mlir/Dialect/Linalg/IR/LinalgOps.h"
 #include "mlir/Dialect/Linalg/Passes.h"
 #include "mlir/Dialect/Linalg/Utils/Utils.h"
 #include "mlir/IR/PatternMatch.h"
 #include "mlir/Pass/Pass.h"
 
 #include "llvm/ADT/STLExtras.h"
 

 template <typename ConcreteOp>
 LogicalResult linalgOpToLoops(PatternRewriter &rewriter, Operation *op);
 
 /// Emits a loop nest of `affine.for` with the proper body for `op`.
 template <typename ConcreteOp>
 LogicalResult linalgOpToAffineLoops(PatternRewriter &rewriter, Operation *op);
 
 /// Rewrite a linalg.generic into a suitable vector.contraction op.
-LogicalResult vectorizeGenericOp(PatternRewriter &rewriter, Operation *op);
+LogicalResult vectorizeGenericLinalgOp(PatternRewriter &rewriter,
+                                       Operation *op);
 
 /// Emits a `generic` or `indexed_generic` operation with the `indexing_maps`
 /// and `iterator_types` permutated according to `permutation`.
 LogicalResult permuteGenericLinalgOp(PatternRewriter &rewriter, Operation *op,
                                      ArrayRef<unsigned> permutation,
                                      StringRef linalgMarker);
 
 /// Promote std.subviews feeding linalg operations
-LogicalResult linalgOpPromoteSubviews(PatternRewriter &rewriter, Operation *op);
+LogicalResult promoteSubviewsLinalgOp(PatternRewriter &rewriter, Operation *op);
 
 } // namespace linalg
 } // namespace mlir
 
 #endif // DIALECT_LINALG_TRANSFORMS_LINALGTRANSFORMS_H_

mlir/lib/Dialect/Linalg/Transforms/LinalgTransforms.cpp

 //===- LinalgTransforms.cpp - Linalg transformations as patterns ----------===//
 //
 // Part of the MLIR 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
 //
 //===----------------------------------------------------------------------===//
 //
 // This file implements logic for transforming Linalg operations.
 //
 //===----------------------------------------------------------------------===//
 
 #include "mlir/Dialect/Linalg/Transforms/LinalgTransforms.h"
 #include "mlir/Dialect/Linalg/Analysis/DependenceAnalysis.h"
 #include "mlir/Dialect/Linalg/IR/LinalgOps.h"
 #include "mlir/Dialect/Linalg/Utils/Intrinsics.h"
 #include "mlir/Dialect/Linalg/Utils/Utils.h"
 #include "mlir/Dialect/VectorOps/VectorOps.h"
 #include "mlir/EDSC/Helpers.h"
 #include "mlir/IR/AffineExpr.h"
 #include "mlir/IR/Matchers.h"
static bool isMatmul(linalg::GenericOp genericOp) {
   auto mapA = AffineMapAttr::get(AffineMap::get(3, 0, {m, k}));
   auto mapB = AffineMapAttr::get(AffineMap::get(3, 0, {k, n}));
   auto mapC = AffineMapAttr::get(AffineMap::get(3, 0, {m, n}));
   auto maps = ArrayAttr::get({mapA, mapB, mapC}, ctx);
   return genericOp.getNumInputs() == 2 && genericOp.getNumOutputs() == 1 &&
          genericOp.indexing_maps() == maps && hasMultiplyAddBody(genericOp);
 }
 
-LogicalResult mlir::linalg::vectorizeGenericOp(PatternRewriter &rewriter,
+LogicalResult mlir::linalg::vectorizeGenericLinalgOp(PatternRewriter &rewriter,
                                                      Operation *op) {
   LLVM_DEBUG(dbgs() << "\n[" DEBUG_TYPE
                        "]: Rewrite linalg op as vector.contract: "
                     << *op << ":\n");
 
   // TODO(ntv): This is in fact much more general than just vectorization for
   // matmul ops.
   auto genericOp = dyn_cast<linalg::GenericOp>(op);
   if (!genericOp || !isMatmul(genericOp))
op->setAttr(getIndexingMapsAttrName(),
               rewriter.getAffineMapArrayAttr(newIndexingMap));
   op->setAttr(getIteratorTypesAttrName(), rewriter.getArrayAttr(itTypesVector));
   op->setAttr(LinalgTransforms::kLinalgTransformMarker,
               rewriter.getStringAttr(linalgMarker));
   linOp.clone(rewriter, linOp.getLoc(), op->getOperands());
   return success();
 }
 
-LogicalResult mlir::linalg::linalgOpPromoteSubviews(PatternRewriter &rewriter,
+LogicalResult mlir::linalg::promoteSubviewsLinalgOp(PatternRewriter &rewriter,
                                                     Operation *op) {
   LinalgOp linOp = dyn_cast<LinalgOp>(op);
   SetVector<Value> subViews;
   for (auto it : linOp.getInputsAndOutputs())
     if (auto sv = dyn_cast_or_null<SubViewOp>(it->getDefiningOp()))
       subViews.insert(sv);
   if (!subViews.empty()) {
     auto resOp = promoteSubViewOperands(rewriter, linOp, subViews);
     return success(resOp);
   }
   return failure();
 }

mlir/test/lib/DeclarativeTransforms/TestLinalgTransformPatterns.td

 #ifndef TEST_LINALG_TRANSFORMS_PATTERNS
 #define TEST_LINALG_TRANSFORMS_PATTERNS
 
 include "mlir/Dialect/Linalg/Transforms/LinalgTransformPatterns.td"
 
 //===----------------------------------------------------------------------===//
 // Test Linalg fusion patterns.
 //===----------------------------------------------------------------------===//
-def : Pat<(MatmulOp:$consumer $A, $B, $C),
-          (TileAndFuseLinalgOp<[100, 150], [0], "L1"> $consumer),
+def : Pat<(MatmulOp:$op $A, $_, $_),
+          (TileAndFuseLinalgOp<[100, 150], [0], "L1">),
           [
-            (Constraint<HasNoLinalgTransformMarker> $consumer),
-            (Constraint<IsProducedByOpOfType<"MatmulOp">> $consumer, $A),
+            (Constraint<HasNoLinalgTransformMarker>),
+            (Constraint<IsProducedByOpOfType<"MatmulOp">> $A),
           ],
           // In the buffer world there is no use-def chains or dags so benefits
           // cannot be computed automatically from the length of the matched
           // pattern. Instead we specify the benefit ourselves for now.
           // This is not expected to be a big challenge long-term because
           // pattern benefits are akin to feature engineering: features should
           // be learned.
           (addBenefit 1)>;
 
 //===----------------------------------------------------------------------===//
 // Linalg tiling patterns.
 //===----------------------------------------------------------------------===//
-def : Pat<(MatmulOp:$op $A, $B, $C),
-          (TileLinalgOp<[2000, 3000, 4000], "L3"> $op),
+def : Pat<(MatmulOp:$op $_, $_, $_),
+          (TileLinalgOp<[2000, 3000, 4000], "L3">),
           [(Constraint<Or<[HasNoLinalgTransformMarker,
-                           HasLinalgTransformMarker<"MEM">]>> $op)]>;
-def : Pat<(MatmulOp:$op $A, $B, $C),
-          (TileLinalgOp<[200, 300, 400], "L2"> $op),
-          [(Constraint<HasLinalgTransformMarker<"L3">> $op)]>;
-def : Pat<(MatmulOp:$op $A, $B, $C),
-          (TileLinalgOp<[20, 30, 40], "L1"> $op),
-          [(Constraint<HasLinalgTransformMarker<"L2">> $op)]>;
-def : Pat<(MatmulOp:$op $A, $B, $C),
-          (TileLinalgOp<[2, 3, 4], "REG"> $op),
-          [(Constraint<HasLinalgTransformMarker<"L1">> $op)]>;
-
-def : Pattern<(MatvecOp:$op $A, $b, $c),
-              [(TileLinalgOp<[5, 6], "L1"> $op)],
-              [(Constraint<HasNoLinalgTransformMarker> $op)]>;
+                           HasLinalgTransformMarker<"MEM">]>>)]>;
+def : Pat<(MatmulOp:$op $_, $_, $_),
+          (TileLinalgOp<[200, 300, 400], "L2">),
+          [(Constraint<HasLinalgTransformMarker<"L3">>)]>;
+def : Pat<(MatmulOp:$op $_, $_, $_),
+          (TileLinalgOp<[20, 30, 40], "L1">),
+          [(Constraint<HasLinalgTransformMarker<"L2">>)]>;
+def : Pat<(MatmulOp:$op $_, $_, $_),
+          (TileLinalgOp<[2, 3, 4], "REG">),
+          [(Constraint<HasLinalgTransformMarker<"L1">>)]>;
+
+def : Pattern<(MatvecOp:$op $_, $_, $_),
+              [(TileLinalgOp<[5, 6], "L1">)],
+              [(Constraint<HasNoLinalgTransformMarker>)]>;
 
-def : Pattern<(DotOp:$op $a, $b, $c),
-              [(TileLinalgOp<[8000], "L1"> $op)],
+def : Pattern<(DotOp:$op $_, $_, $_),
+              [(TileLinalgOp<[8000], "L1">)],
               [(Constraint<Or<[HasNoLinalgTransformMarker,
                                HasLinalgTransformMarker<"MEM">,
                                HasLinalgTransformMarker<"L3">,
-                               HasLinalgTransformMarker<"L2">]>> $op)]>;
-def : Pattern<(DotOp:$op $a, $b, $c),
-              [(TileLinalgOp<[8], "REG"> $op)],
-              [(Constraint<HasLinalgTransformMarker<"L1">> $op)]>;
+                               HasLinalgTransformMarker<"L2">]>>)]>;
+def : Pattern<(DotOp:$op $_, $_, $_),
+              [(TileLinalgOp<[8], "REG">)],
+              [(Constraint<HasLinalgTransformMarker<"L1">>)]>;
 
 //===----------------------------------------------------------------------===//
 // Linalg tiling and permutation patterns.
 //===----------------------------------------------------------------------===//
-def : Pat<(MatmulOp:$op $A, $B, $C),
-          (TileLinalgOp<[2000, 3000, 4000], "L2__with_perm__", [1,2,0]> $op),
-          [(Constraint<HasLinalgTransformMarker<"__with_perm__">> $op)]>;
-def : Pat<(MatmulOp:$op $A, $B, $C),
-          (TileLinalgOp<[200, 300, 400], "L1__with_perm__", [1,0,2]> $op),
-          [(Constraint<HasLinalgTransformMarker<"L2__with_perm__">> $op)]>;
-def : Pat<(MatmulOp:$op $A, $B, $C),
-          (TileLinalgOp<[20, 30, 40], "REG__with_perm__"> $op),
-          [(Constraint<HasLinalgTransformMarker<"L1__with_perm__">> $op)]>;
-
-
-def : Pattern<(MatvecOp:$op $A, $b, $c),
-              [(TileLinalgOp<[5, 6], "L1__with_perm__", [1,0]> $op)],
-              [(Constraint<HasLinalgTransformMarker<"__with_perm__">> $op)]>;
-
-def : Pattern<(DotOp:$op $a, $b, $c),
-              [(TileLinalgOp<[8000], "L1__with_perm__"> $op)],
-              [(Constraint<HasLinalgTransformMarker<"__with_perm__">> $op)]>;
-def : Pattern<(DotOp:$op $a, $b, $c),
-              [(TileLinalgOp<[8], "REG__with_perm__"> $op)],
-              [(Constraint<HasLinalgTransformMarker<"L1__with_perm__">> $op)]>;
+def : Pat<(MatmulOp:$op $_, $_, $_),
+          (TileLinalgOp<[2000, 3000, 4000], "L2__with_perm__", [1,2,0]>),
+          [(Constraint<HasLinalgTransformMarker<"__with_perm__">>)]>;
+def : Pat<(MatmulOp:$op $_, $_, $_),
+          (TileLinalgOp<[200, 300, 400], "L1__with_perm__", [1,0,2]>),
+          [(Constraint<HasLinalgTransformMarker<"L2__with_perm__">>)]>;
+def : Pat<(MatmulOp:$op $_, $_, $_),
+          (TileLinalgOp<[20, 30, 40], "REG__with_perm__">),
+          [(Constraint<HasLinalgTransformMarker<"L1__with_perm__">>)]>;
+
+
+def : Pattern<(MatvecOp:$op $_, $_, $_),
+              [(TileLinalgOp<[5, 6], "L1__with_perm__", [1,0]>)],
+              [(Constraint<HasLinalgTransformMarker<"__with_perm__">>)]>;
+
+def : Pattern<(DotOp:$op $_, $_, $_),
+              [(TileLinalgOp<[8000], "L1__with_perm__">)],
+              [(Constraint<HasLinalgTransformMarker<"__with_perm__">>)]>;
+def : Pattern<(DotOp:$op $_, $_, $_),
+              [(TileLinalgOp<[8], "REG__with_perm__">)],
+              [(Constraint<HasLinalgTransformMarker<"L1__with_perm__">>)]>;
 
 //===----------------------------------------------------------------------===//
 // Linalg to loops patterns.
 //===----------------------------------------------------------------------===//
-def : Pattern<(DotOp:$op $a, $b, $c),
-              [(LinalgOpToLoops<"DotOp"> $op)],
-              [(Constraint<HasLinalgTransformMarker<"REG">> $op)]>;
+def : Pattern<(DotOp:$op $_, $_, $_),
+              [(LinalgOpToLoops<"DotOp">)],
+              [(Constraint<HasLinalgTransformMarker<"REG">>)]>;
 
 //===----------------------------------------------------------------------===//
 // Linalg to vector contraction patterns.
 //===----------------------------------------------------------------------===//
-def : Pattern<(GenericOp:$op $_1, $_2, $_3, $_4, $_5, $_6, $_7, $_8),
-              [(LinalgOpToVectorContraction<"GenericOp"> $op)],
-              [(Constraint<HasLinalgTransformMarker<"_marked_matmul_">> $op)]>;
+def : Pattern<(GenericOp:$op $_, $_, $_, $_, $_, $_, $_, $_),
+              [(VectorizeGenericLinalgOp<"GenericOp">)],
+              [(Constraint<HasLinalgTransformMarker<"_marked_matmul_">>)]>;
 
 //===----------------------------------------------------------------------===//
 // Linalg generic permutation patterns.
 //===----------------------------------------------------------------------===//
-def : Pat<(GenericOp:$op $_1, $_2, $_3, $_4, $_5, $_6, $_7, $_8),
-              (PermuteGenericLinalgOp<[1,2,0],"PERMUTED"> $op),
+def : Pat<(GenericOp:$op $_, $_, $_, $_, $_, $_, $_, $_),
+              (PermuteGenericLinalgOp<[1,2,0],"PERMUTED">),
               [(Constraint<And<[HasNoLinalgTransformMarker,
-                           AffineMapDomainHasDim<3>]>> $op)]>;
+                           AffineMapDomainHasDim<3>]>>)]>;
 
-def : Pat<(IndexedGenericOp:$op $_1, $_2, $_3, $_4, $_5, $_6, $_7, $_8),
-              (PermuteGenericLinalgOp<[1,2,0],"PERMUTED"> $op),
+def : Pat<(IndexedGenericOp:$op $_, $_, $_, $_, $_, $_, $_, $_),
+              (PermuteGenericLinalgOp<[1,2,0],"PERMUTED">),
               [(Constraint<And<[HasNoLinalgTransformMarker,
-                           AffineMapDomainHasDim<3>]>> $op)]>;
+                           AffineMapDomainHasDim<3>]>>)]>;
 
 //===----------------------------------------------------------------------===//
 // Linalg subview operands promotion.
 //===----------------------------------------------------------------------===//
-def : Pat<(MatmulOp:$op $A, $B, $C),
-          (LinalgOpPromoteSubviews<"MatmulOp"> $op),
-          [(Constraint<HasOperandsOfType<"SubViewOp">> $op),
-          (Constraint<HasLinalgTransformMarker<"_promote_views_">> $op)]>;
+def : Pat<(MatmulOp:$op $_, $_, $_),
+          (PromoteSubviewsLinalgOp<"MatmulOp">),
+          [(Constraint<HasOperandsOfType<"SubViewOp">>),
+          (Constraint<HasLinalgTransformMarker<"_promote_views_">>)]>;
 #endif // TEST_LINALG_TRANSFORMS_PATTERNS