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[mlir][tensor] Fold unpadding collapse_shape into extract_slice (#93554)

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Adam Siemieniuk 2024-05-31 13:29:40 +02:00 committed by GitHub
parent 189efb0fbb
commit 8f4d5a32ac
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2 changed files with 132 additions and 16 deletions
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46
mlir/lib/Dialect/Tensor/Transforms/ReshapePatterns.cpp
View File

@ -48,6 +48,39 @@ struct FoldExpandOfRankReducingExtract
}
};
/// Fold collapse_shape which only removes static dimensions of size `1`
/// into extract_slice.
struct FoldUnPaddingCollapseIntoExtract
: public OpRewritePattern<tensor::CollapseShapeOp> {
using OpRewritePattern<tensor::CollapseShapeOp>::OpRewritePattern;
LogicalResult matchAndRewrite(tensor::CollapseShapeOp collapseShapeOp,
PatternRewriter &rewriter) const override {
auto extractSliceOp =
collapseShapeOp.getSrc().getDefiningOp<tensor::ExtractSliceOp>();
// Collapse cannot be folded away with multiple users of the extract slice
// and it is not necessarily beneficial to only convert the collapse into
// another extract slice.
if (!extractSliceOp || !extractSliceOp->hasOneUse())
return failure();
// Only fold away simple collapse where all removed dimensions have static
// size `1`.
SliceVerificationResult res = isRankReducedType(
collapseShapeOp.getSrcType(), collapseShapeOp.getResultType());
if (res != SliceVerificationResult::Success)
return rewriter.notifyMatchFailure(collapseShapeOp,
"expected unpadding collapse");
Value unPaddedExtractSlice = rewriter.create<tensor::ExtractSliceOp>(
extractSliceOp.getLoc(), collapseShapeOp.getResultType(),
extractSliceOp.getSource(), extractSliceOp.getMixedOffsets(),
extractSliceOp.getMixedSizes(), extractSliceOp.getMixedStrides());
rewriter.replaceOp(collapseShapeOp, unPaddedExtractSlice);
return success();
}
};
/// Fold insert_slice(collapse_shape) ops that cancel itself out.
template <typename OpTy>
struct FoldInsertOfRankReducingInsert : public OpRewritePattern<OpTy> {
@ -111,10 +144,11 @@ struct FoldPaddingExpandIntoInsert : public OpRewritePattern<OpTy> {
void mlir::tensor::populateReassociativeReshapeFoldingPatterns(
RewritePatternSet &patterns) {
patterns.add<FoldExpandOfRankReducingExtract,
FoldInsertOfRankReducingInsert<tensor::InsertSliceOp>,
FoldInsertOfRankReducingInsert<tensor::ParallelInsertSliceOp>,
FoldPaddingExpandIntoInsert<tensor::InsertSliceOp>,
FoldPaddingExpandIntoInsert<tensor::ParallelInsertSliceOp>>(
patterns.getContext());
patterns
.add<FoldExpandOfRankReducingExtract, FoldUnPaddingCollapseIntoExtract,
FoldInsertOfRankReducingInsert<tensor::InsertSliceOp>,
FoldInsertOfRankReducingInsert<tensor::ParallelInsertSliceOp>,
FoldPaddingExpandIntoInsert<tensor::InsertSliceOp>,
FoldPaddingExpandIntoInsert<tensor::ParallelInsertSliceOp>>(
patterns.getContext());
}

102
mlir/test/Dialect/Tensor/fold-reassociative-reshapes.mlir
View File

@ -2,8 +2,10 @@
// CHECK-LABEL: func @expand_shape_of_rank_reducing_extract(
// CHECK-SAME: %[[t:.*]]: tensor<?x?x?x?xf32>
// CHECK-DAG: %[[extract1:.*]] = tensor.extract_slice %{{.*}}[0, 0, 0, 0] [%{{.*}}, 1, 1, 5] [1, 1, 1, 1] : tensor<?x?x?x?xf32> to tensor<?x1x1x5xf32>
// CHECK-DAG: %[[extract2:.*]] = tensor.extract_slice %{{.*}}[0, 0, 0, 0] [%{{.*}}, 1, 1, 5] [1, 1, 1, 1] : tensor<?x?x?x?xf32> to tensor<?x1x1x5xf32>
// CHECK-DAG: %[[extract1:.*]] = tensor.extract_slice %{{.*}}[0, 0, 0, 0]
// CHECK-SAME: [%{{.*}}, 1, 1, 5] [1, 1, 1, 1] : tensor<?x?x?x?xf32> to tensor<?x1x1x5xf32>
// CHECK-DAG: %[[extract2:.*]] = tensor.extract_slice %{{.*}}[0, 0, 0, 0]
// CHECK-SAME: [%{{.*}}, 1, 1, 5] [1, 1, 1, 1] : tensor<?x?x?x?xf32> to tensor<?x1x1x5xf32>
// CHECK: return %[[extract1]], %[[extract2]]
func.func @expand_shape_of_rank_reducing_extract(
%t: tensor<?x?x?x?xf32>, %idx: index)
@ -22,9 +24,82 @@ func.func @expand_shape_of_rank_reducing_extract(
// -----
// CHECK-LABEL: func @unpadding_collapse_of_extract_slice(
// CHECK-SAME: %[[t:.*]]: tensor<?x?x?x?xf32>
// CHECK-SAME: %[[x:[a-zA-Z0-9_]+]]: index
// CHECK-SAME: %[[y:[a-zA-Z0-9_]+]]: index
// CHECK: %[[extract:.*]] = tensor.extract_slice %[[t]][%[[x]], %[[y]], 0, 0]
// CHECK-SAME: [1, %{{.*}}, 1, %{{.*}}] [1, 1, 1, 1] : tensor<?x?x?x?xf32> to tensor<?x?xf32>
// CHECK: return %[[extract]]
func.func @unpadding_collapse_of_extract_slice(
%t: tensor<?x?x?x?xf32>, %x: index, %y: index)
-> tensor<?x?xf32> {
%c1 = arith.constant 1 : index
%c3 = arith.constant 3 : index
%sz0 = tensor.dim %t, %c1 : tensor<?x?x?x?xf32>
%sz1 = tensor.dim %t, %c3 : tensor<?x?x?x?xf32>
%0 = tensor.extract_slice %t[%x, %y, 0, 0] [1, %sz0, 1, %sz1] [1, 1, 1, 1]
: tensor<?x?x?x?xf32> to tensor<1x?x1x?xf32>
%1 = tensor.collapse_shape %0 [[0, 1], [2, 3]]
: tensor<1x?x1x?xf32> into tensor<?x?xf32>
return %1 : tensor<?x?xf32>
}
// -----
// CHECK-LABEL: func @non_unpadding_collapse_of_extract_slice(
// CHECK-SAME: %[[t:.*]]: tensor<?x?x?x?xf32>
// CHECK-SAME: %[[x:[a-zA-Z0-9_]+]]: index
// CHECK-SAME: %[[y:[a-zA-Z0-9_]+]]: index
// CHECK-SAME: %[[sz:[a-zA-Z0-9_]+]]: index
// CHECK: %[[extract:.*]] = tensor.extract_slice %[[t]][%[[x]], %[[y]], 0, 0]
// CHECK-SAME: [%{{.*}}, %{{.*}}, %[[sz]], 1] [1, 1, 1, 1] : tensor<?x?x?x?xf32> to tensor<?x?x?xf32>
// CHECK: %[[collapse:.*]] = tensor.collapse_shape %[[extract]] {{\[}}[0], [1, 2]] : tensor<?x?x?xf32> into tensor<?x?xf32>
// CHECK: return %[[collapse]]
func.func @non_unpadding_collapse_of_extract_slice(
%t: tensor<?x?x?x?xf32>, %x: index, %y: index, %sz: index)
-> tensor<?x?xf32> {
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
%sz0 = tensor.dim %t, %c0 : tensor<?x?x?x?xf32>
%sz1 = tensor.dim %t, %c1 : tensor<?x?x?x?xf32>
%0 = tensor.extract_slice %t[%x, %y, 0, 0] [%sz0, %sz1, %sz, 1] [1, 1, 1, 1]
: tensor<?x?x?x?xf32> to tensor<?x?x?xf32>
%1 = tensor.collapse_shape %0 [[0], [1, 2]]
: tensor<?x?x?xf32> into tensor<?x?xf32>
return %1 : tensor<?x?xf32>
}
// -----
// CHECK-LABEL: func @unpadding_collapse_of_extract_slice_with_multiple_users(
// CHECK-SAME: %[[t:.*]]: tensor<?x?x?x?xf32>
// CHECK-SAME: %[[x:[a-zA-Z0-9_]+]]: index
// CHECK-SAME: %[[y:[a-zA-Z0-9_]+]]: index
// CHECK: %[[extract:.*]] = tensor.extract_slice %[[t]][%[[x]], %[[y]], 0, 0]
// CHECK-SAME: [1, %{{.*}}, 1, %{{.*}}] [1, 1, 1, 1] : tensor<?x?x?x?xf32> to tensor<1x?x1x?xf32>
// CHECK: %[[collapse:.*]] = tensor.collapse_shape %[[extract]] {{\[}}[0, 1], [2, 3]] : tensor<1x?x1x?xf32> into tensor<?x?xf32>
// CHECK: return %[[extract]], %[[collapse]]
func.func @unpadding_collapse_of_extract_slice_with_multiple_users(
%t: tensor<?x?x?x?xf32>, %x: index, %y: index)
-> (tensor<1x?x1x?xf32>, tensor<?x?xf32>) {
%c1 = arith.constant 1 : index
%c3 = arith.constant 3 : index
%sz0 = tensor.dim %t, %c1 : tensor<?x?x?x?xf32>
%sz1 = tensor.dim %t, %c3 : tensor<?x?x?x?xf32>
%0 = tensor.extract_slice %t[%x, %y, 0, 0] [1, %sz0, 1, %sz1] [1, 1, 1, 1]
: tensor<?x?x?x?xf32> to tensor<1x?x1x?xf32>
%1 = tensor.collapse_shape %0 [[0, 1], [2, 3]]
: tensor<1x?x1x?xf32> into tensor<?x?xf32>
return %0, %1 : tensor<1x?x1x?xf32>, tensor<?x?xf32>
}
// -----
// CHECK-LABEL: func @rank_reducing_insert_of_collapse_shape(
// CHECK-SAME: %[[t:.*]]: tensor<?x1x1x5xf32>
// CHECK: %[[insert:.*]] = tensor.insert_slice %[[t]] into %{{.*}}[0, 0, 0, 0] [%{{.*}}, 1, 1, 5] [1, 1, 1, 1] : tensor<?x1x1x5xf32> into tensor<?x?x?x?xf32>
// CHECK: %[[insert:.*]] = tensor.insert_slice %[[t]] into %{{.*}}[0, 0, 0, 0]
// CHECK-SAME: [%{{.*}}, 1, 1, 5] [1, 1, 1, 1] : tensor<?x1x1x5xf32> into tensor<?x?x?x?xf32>
// CHECK: return %[[insert]]
func.func @rank_reducing_insert_of_collapse_shape(
%t: tensor<?x1x1x5xf32>, %d: tensor<?x?x?x?xf32>, %sz: index)
@ -40,7 +115,8 @@ func.func @rank_reducing_insert_of_collapse_shape(
// CHECK-LABEL: func @rank_reducing_parallel_insert_of_collapse_shape(
// CHECK-SAME: %[[t:.*]]: tensor<?x1x1x5xf32>
// CHECK: tensor.parallel_insert_slice %[[t]] into %{{.*}}[0, 0, 0, 0] [%{{.*}}, 1, 1, 5] [1, 1, 1, 1] : tensor<?x1x1x5xf32> into tensor<?x?x?x?xf32>
// CHECK: tensor.parallel_insert_slice %[[t]] into %{{.*}}[0, 0, 0, 0]
// CHECK-SAME: [%{{.*}}, 1, 1, 5] [1, 1, 1, 1] : tensor<?x1x1x5xf32> into tensor<?x?x?x?xf32>
func.func @rank_reducing_parallel_insert_of_collapse_shape(
%t: tensor<?x1x1x5xf32>, %d: tensor<?x?x?x?xf32>, %sz: index, %thr: index)
-> tensor<?x?x?x?xf32> {
@ -62,7 +138,8 @@ func.func @rank_reducing_parallel_insert_of_collapse_shape(
// CHECK-SAME: %[[d:.*]]: tensor<?x?x?x?xf32>
// CHECK-SAME: %[[x:[a-zA-Z0-9_]+]]: index
// CHECK-SAME: %[[y:[a-zA-Z0-9_]+]]: index
// CHECK: %[[insert:.*]] = tensor.insert_slice %[[t]] into %[[d]][%[[x]], %[[y]], 0, 0] [1, %{{.*}}, 1, %{{.*}}] [1, 1, 1, 1] : tensor<?x?xf32> into tensor<?x?x?x?xf32>
// CHECK: %[[insert:.*]] = tensor.insert_slice %[[t]] into %[[d]][%[[x]], %[[y]], 0, 0]
// CHECK-SAME: [1, %{{.*}}, 1, %{{.*}}] [1, 1, 1, 1] : tensor<?x?xf32> into tensor<?x?x?x?xf32>
// CHECK: return %[[insert]]
func.func @insert_of_padding_expand_shape(
%t: tensor<?x?xf32>, %d: tensor<?x?x?x?xf32>, %x: index, %y: index)
@ -86,8 +163,10 @@ func.func @insert_of_padding_expand_shape(
// CHECK-SAME: %[[x:[a-zA-Z0-9_]+]]: index
// CHECK-SAME: %[[y:[a-zA-Z0-9_]+]]: index
// CHECK-SAME: %[[sz:[a-zA-Z0-9_]+]]: index
// CHECK: %[[expand:.*]] = tensor.expand_shape %[[t]] {{\[}}[0, 1], [2]] output_shape [%[[sz]], %{{.*}}, %{{.*}}] : tensor<?x?xf32> into tensor<?x?x?xf32>
// CHECK: %[[insert:.*]] = tensor.insert_slice %[[expand]] into %[[d]][%[[x]], %[[y]], 0, 0] [%[[sz]], 1, %{{.*}}, %{{.*}}] [1, 1, 1, 1] : tensor<?x?x?xf32> into tensor<?x?x?x?xf32>
// CHECK: %[[expand:.*]] = tensor.expand_shape %[[t]] {{\[}}[0, 1], [2]]
// CHECK-SAME: output_shape [%[[sz]], %{{.*}}, %{{.*}}] : tensor<?x?xf32> into tensor<?x?x?xf32>
// CHECK: %[[insert:.*]] = tensor.insert_slice %[[expand]] into %[[d]][%[[x]], %[[y]], 0, 0]
// CHECK-SAME: [%[[sz]], 1, %{{.*}}, %{{.*}}] [1, 1, 1, 1] : tensor<?x?x?xf32> into tensor<?x?x?x?xf32>
// CHECK: return %[[insert]]
func.func @insert_of_non_padding_expand_shape(
%t: tensor<?x?xf32>, %d: tensor<?x?x?x?xf32>, %x: index, %y: index, %sz: index)
@ -110,7 +189,8 @@ func.func @insert_of_non_padding_expand_shape(
// CHECK-SAME: %[[d:.*]]: tensor<?x?x?x?xf32>
// CHECK-SAME: %[[x:[a-zA-Z0-9_]+]]: index
// CHECK-SAME: %[[y:[a-zA-Z0-9_]+]]: index
// CHECK: tensor.parallel_insert_slice %[[t]] into %{{.*}}[%{{.*}}, %{{.*}}, 0, 0] [1, %{{.*}}, 1, %{{.*}}] [1, 1, 1, 1] : tensor<?x?xf32> into tensor<?x?x?x?xf32>
// CHECK: tensor.parallel_insert_slice %[[t]] into %{{.*}}[%{{.*}}, %{{.*}}, 0, 0]
// CHECK-SAME: [1, %{{.*}}, 1, %{{.*}}] [1, 1, 1, 1] : tensor<?x?xf32> into tensor<?x?x?x?xf32>
func.func @parallel_insert_of_padding_expand_shape(
%t: tensor<?x?xf32>, %d: tensor<?x?x?x?xf32>, %x: index, %y: index)
-> tensor<?x?x?x?xf32> {
@ -137,8 +217,10 @@ func.func @parallel_insert_of_padding_expand_shape(
// CHECK-SAME: %[[x:[a-zA-Z0-9_]+]]: index
// CHECK-SAME: %[[y:[a-zA-Z0-9_]+]]: index
// CHECK-SAME: %[[sz:[a-zA-Z0-9_]+]]: index
// CHECK: %[[expand:.*]] = tensor.expand_shape %[[t]] {{\[}}[0, 1], [2]] output_shape [%[[sz]], %{{.*}}, %{{.*}}] : tensor<?x?xf32> into tensor<?x?x?xf32>
// CHECK: tensor.parallel_insert_slice %[[expand]] into %{{.*}}[%{{.*}}, %{{.*}}, 0, 0] [%[[sz]], 1, %{{.*}}, %{{.*}}] [1, 1, 1, 1] : tensor<?x?x?xf32> into tensor<?x?x?x?xf32>
// CHECK: %[[expand:.*]] = tensor.expand_shape %[[t]] {{\[}}[0, 1], [2]]
// CHECK-SAME: output_shape [%[[sz]], %{{.*}}, %{{.*}}] : tensor<?x?xf32> into tensor<?x?x?xf32>
// CHECK: tensor.parallel_insert_slice %[[expand]] into %{{.*}}[%{{.*}}, %{{.*}}, 0, 0]
// CHECK-SAME: [%[[sz]], 1, %{{.*}}, %{{.*}}] [1, 1, 1, 1] : tensor<?x?x?xf32> into tensor<?x?x?x?xf32>
func.func @parallel_insert_of_non_padding_expand_shape(
%t: tensor<?x?xf32>, %d: tensor<?x?x?x?xf32>, %x: index, %y: index, %sz: index)
-> tensor<?x?x?x?xf32> {