https://github.com/srcarroll updated
https://github.com/llvm/llvm-project/pull/80466
>From f51bb7b15be55e682be76f2289b991ed42ab4d41 Mon Sep 17 00:00:00 2001
From: Sam <srcarroll...@gmail.com>
Date: Fri, 2 Feb 2024 11:37:03 -0600
Subject: [PATCH 1/3] [mlir][linalg]Implement canonicalizer for
`linalg::BroadCastOp` on tensors
---
.../mlir/Dialect/Linalg/IR/LinalgStructuredOps.td | 1 +
mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp | 14 ++++++++++++++
2 files changed, 15 insertions(+)
diff --git a/mlir/include/mlir/Dialect/Linalg/IR/LinalgStructuredOps.td
b/mlir/include/mlir/Dialect/Linalg/IR/LinalgStructuredOps.td
index 751edd0228830..11b6f50032c09 100644
--- a/mlir/include/mlir/Dialect/Linalg/IR/LinalgStructuredOps.td
+++ b/mlir/include/mlir/Dialect/Linalg/IR/LinalgStructuredOps.td
@@ -531,6 +531,7 @@ def BroadcastOp : LinalgStructuredBase_Op<"broadcast", [
let hasCustomAssemblyFormat = 1;
let hasVerifier = 1;
+ let hasCanonicalizeMethod = 1;
}
//===----------------------------------------------------------------------===//
diff --git a/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
b/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
index e86b9762d8581..cddb0671dd58f 100644
--- a/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
+++ b/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
@@ -1907,6 +1907,20 @@ void BroadcastOp::getEffects(
getDpsInits());
}
+LogicalResult BroadcastOp::canonicalize(BroadcastOp op,
+ PatternRewriter &rewriter) {
+ // For tensor semantics, if op's input and init are same shape, it is a no
op.
+ // Otherwise, with buffer semantics, the op does a copy and we don't
+ // canonicalize.
+ if (op.hasPureTensorSemantics() &&
+ (op.getInput().getType() == op.getInit().getType())) {
+ rewriter.replaceAllUsesWith(op.getResult(), op.getInput());
+ rewriter.eraseOp(op);
+ return success();
+ }
+ return failure();
+}
+
//===----------------------------------------------------------------------===//
// YieldOp
//===----------------------------------------------------------------------===//
>From c40476b2b7a186af7237a3fdc1599a129d65f749 Mon Sep 17 00:00:00 2001
From: Sam <srcarroll...@gmail.com>
Date: Fri, 2 Feb 2024 11:51:52 -0600
Subject: [PATCH 2/3] Add regression test
---
mlir/test/Dialect/Linalg/canonicalize.mlir | 12 ++++++++++++
1 file changed, 12 insertions(+)
diff --git a/mlir/test/Dialect/Linalg/canonicalize.mlir
b/mlir/test/Dialect/Linalg/canonicalize.mlir
index 052dc367ca677..a2777a035320f 100644
--- a/mlir/test/Dialect/Linalg/canonicalize.mlir
+++ b/mlir/test/Dialect/Linalg/canonicalize.mlir
@@ -1017,3 +1017,15 @@ func.func @canonicalize_fill_to_copy_dest(%arg0 :
tensor<?x?xf32>, %arg1 : tenso
%copy = linalg.copy ins(%arg1 : tensor<?x?xf32>) outs(%fill :
tensor<?x?xf32>) -> tensor<?x?xf32>
return %copy : tensor<?x?xf32>
}
+
+// -----
+
+// CHECK-LABEL: func @broadcast_same_shape(
+// CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: tensor<2x3xf32>
+// CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: tensor<2x3xf32>)
+// CHECK-NOT: linalg.broadcast
+// CHECK: return %[[ARG0]] : tensor<2x3xf32>
+func.func @broadcast_same_shape(%input: tensor<2x3xf32>, %init:
tensor<2x3xf32>) -> tensor<2x3xf32> {
+ %0 = linalg.broadcast ins(%input: tensor<2x3xf32>) outs(%init:
tensor<2x3xf32>) dimensions = []
+ return %0 : tensor<2x3xf32>
+}
\ No newline at end of file
>From 458e93a3a6cf1f4b28984ff9d1d7da2e9ce60a30 Mon Sep 17 00:00:00 2001
From: Sam <srcarroll...@gmail.com>
Date: Fri, 2 Feb 2024 19:24:07 -0600
Subject: [PATCH 3/3] Refactor EraseIdentityGenericOp to be reused by any
LinalgOp
---
.../Dialect/Linalg/IR/LinalgStructuredOps.td | 2 +-
mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp | 54 ++++++++-----------
2 files changed, 24 insertions(+), 32 deletions(-)
diff --git a/mlir/include/mlir/Dialect/Linalg/IR/LinalgStructuredOps.td
b/mlir/include/mlir/Dialect/Linalg/IR/LinalgStructuredOps.td
index 11b6f50032c09..272bc3116c5fd 100644
--- a/mlir/include/mlir/Dialect/Linalg/IR/LinalgStructuredOps.td
+++ b/mlir/include/mlir/Dialect/Linalg/IR/LinalgStructuredOps.td
@@ -531,7 +531,7 @@ def BroadcastOp : LinalgStructuredBase_Op<"broadcast", [
let hasCustomAssemblyFormat = 1;
let hasVerifier = 1;
- let hasCanonicalizeMethod = 1;
+ let hasCanonicalizer = 1;
}
//===----------------------------------------------------------------------===//
diff --git a/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
b/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
index cddb0671dd58f..a0f02f6a7f259 100644
--- a/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
+++ b/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
@@ -1087,24 +1087,25 @@ LogicalResult GenericOp::verify() { return success(); }
namespace {
-/// Remove generic operations (on tensors) that are just copying
+/// Remove any linalg operation (on tensors) that are just copying
/// the values from inputs to the results. Requirements are
/// 1) All iterator types are parallel
/// 2) The body contains just a yield operation with the yielded values being
/// the arguments corresponding to the operands.
-struct EraseIdentityGenericOp : public OpRewritePattern<GenericOp> {
- using OpRewritePattern<GenericOp>::OpRewritePattern;
+template <typename OpTy>
+struct EraseIdentityLinalgOp : public OpRewritePattern<OpTy> {
+ using OpRewritePattern<OpTy>::OpRewritePattern;
- LogicalResult matchAndRewrite(GenericOp genericOp,
+ LogicalResult matchAndRewrite(OpTy linalgOp,
PatternRewriter &rewriter) const override {
// Check all indexing maps are identity.
- if (llvm::any_of(genericOp.getIndexingMapsArray(),
+ if (llvm::any_of(linalgOp.getIndexingMapsArray(),
[](AffineMap map) { return !map.isIdentity(); }))
return failure();
// Check that the body of the linalg operation is just a linalg.yield
// operation.
- Block &body = genericOp.getRegion().front();
+ Block &body = linalgOp->getRegion(0).front();
if (!llvm::hasSingleElement(body))
return failure();
auto yieldOp = dyn_cast<linalg::YieldOp>(body.getTerminator());
@@ -1112,18 +1113,18 @@ struct EraseIdentityGenericOp : public
OpRewritePattern<GenericOp> {
return failure();
// In the buffer case, we need to check exact buffer equality.
- if (genericOp.hasPureBufferSemantics()) {
- if (genericOp.getNumDpsInputs() == 1 && genericOp.getNumDpsInits() == 1
&&
- genericOp.getDpsInputOperand(0)->get() ==
- genericOp.getDpsInitOperand(0)->get()) {
- rewriter.eraseOp(genericOp);
+ if (linalgOp.hasPureBufferSemantics()) {
+ if (linalgOp.getNumDpsInputs() == 1 && linalgOp.getNumDpsInits() == 1 &&
+ linalgOp.getDpsInputOperand(0)->get() ==
+ linalgOp.getDpsInitOperand(0)->get()) {
+ rewriter.eraseOp(linalgOp);
return success();
}
return failure();
}
// Mixed semantics is not supported yet.
- if (!genericOp.hasPureTensorSemantics())
+ if (!linalgOp.hasPureTensorSemantics())
return failure();
// Get the argument number of the returned values. That is the operand
@@ -1134,8 +1135,8 @@ struct EraseIdentityGenericOp : public
OpRewritePattern<GenericOp> {
if (!yieldArg || yieldArg.getOwner() != &body)
return failure();
unsigned argumentNumber = yieldArg.getArgNumber();
- Value returnedArg = genericOp->getOperand(argumentNumber);
- Type resultType = genericOp->getResult(yieldVal.index()).getType();
+ Value returnedArg = linalgOp->getOperand(argumentNumber);
+ Type resultType = linalgOp->getResult(yieldVal.index()).getType();
// The input can have a different type than the result, e.g. a dynamic
// input dimension can be turned into a static output dimension.
Type returnType = returnedArg.getType();
@@ -1145,21 +1146,21 @@ struct EraseIdentityGenericOp : public
OpRewritePattern<GenericOp> {
if (sparse_tensor::getSparseTensorEncoding(returnType) ||
sparse_tensor::getSparseTensorEncoding(resultType))
returnedArg = rewriter.create<sparse_tensor::ConvertOp>(
- genericOp.getLoc(), resultType, returnedArg);
+ linalgOp.getLoc(), resultType, returnedArg);
else {
if (!tensor::CastOp::areCastCompatible(returnedArg.getType(),
resultType))
return failure();
returnedArg = rewriter.create<tensor::CastOp>(
- genericOp.getLoc(), resultType, returnedArg);
+ linalgOp.getLoc(), resultType, returnedArg);
}
}
returnedArgs.push_back(returnedArg);
}
- if (returnedArgs.size() != genericOp->getNumResults())
+ if (returnedArgs.size() != linalgOp->getNumResults())
return failure();
- rewriter.replaceOp(genericOp, returnedArgs);
+ rewriter.replaceOp(linalgOp, returnedArgs);
return success();
}
};
@@ -1168,7 +1169,7 @@ struct EraseIdentityGenericOp : public
OpRewritePattern<GenericOp> {
void GenericOp::getCanonicalizationPatterns(RewritePatternSet &results,
MLIRContext *context) {
- results.add<EraseIdentityGenericOp>(context);
+ results.add<EraseIdentityLinalgOp<GenericOp>>(context);
}
LogicalResult GenericOp::fold(FoldAdaptor, SmallVectorImpl<OpFoldResult> &) {
@@ -1907,18 +1908,9 @@ void BroadcastOp::getEffects(
getDpsInits());
}
-LogicalResult BroadcastOp::canonicalize(BroadcastOp op,
- PatternRewriter &rewriter) {
- // For tensor semantics, if op's input and init are same shape, it is a no
op.
- // Otherwise, with buffer semantics, the op does a copy and we don't
- // canonicalize.
- if (op.hasPureTensorSemantics() &&
- (op.getInput().getType() == op.getInit().getType())) {
- rewriter.replaceAllUsesWith(op.getResult(), op.getInput());
- rewriter.eraseOp(op);
- return success();
- }
- return failure();
+void BroadcastOp::getCanonicalizationPatterns(RewritePatternSet &results,
+ MLIRContext *context) {
+ results.add<EraseIdentityLinalgOp<BroadcastOp>>(context);
}
//===----------------------------------------------------------------------===//
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