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[mlir][tensor] Fold padding expand_shape into insert_slice (#93018)
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+133
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‎mlir/lib/Dialect/Tensor/Transforms/ReshapePatterns.cpp‎

Lines changed: 31 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -79,12 +79,42 @@ struct FoldInsertOfRankReducingInsert : public OpRewritePattern<OpTy> {
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return success();
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}
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};
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/// Fold expand_shape which only adds static dimensions of size `1`
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/// into insert_slice.
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template <typename OpTy>
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struct FoldPaddingExpandIntoInsert : public OpRewritePattern<OpTy> {
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using OpRewritePattern<OpTy>::OpRewritePattern;
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LogicalResult matchAndRewrite(OpTy insertSliceOp,
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PatternRewriter &rewriter) const override {
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auto expandShapeOp = insertSliceOp.getSource()
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.template getDefiningOp<tensor::ExpandShapeOp>();
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if (!expandShapeOp)
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return failure();
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// Only fold away simple expansion where all added dimensions have static
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// size `1`.
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SliceVerificationResult res = isRankReducedType(
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expandShapeOp.getResultType(), expandShapeOp.getSrcType());
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if (res != SliceVerificationResult::Success)
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return rewriter.notifyMatchFailure(insertSliceOp,
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"expected rank increasing expansion");
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rewriter.modifyOpInPlace(insertSliceOp, [&]() {
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insertSliceOp.getSourceMutable().assign(expandShapeOp.getSrc());
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});
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return success();
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}
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};
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} // namespace
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void mlir::tensor::populateReassociativeReshapeFoldingPatterns(
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RewritePatternSet &patterns) {
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patterns.add<FoldExpandOfRankReducingExtract,
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FoldInsertOfRankReducingInsert<tensor::InsertSliceOp>,
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FoldInsertOfRankReducingInsert<tensor::ParallelInsertSliceOp>>(
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FoldInsertOfRankReducingInsert<tensor::ParallelInsertSliceOp>,
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FoldPaddingExpandIntoInsert<tensor::InsertSliceOp>,
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FoldPaddingExpandIntoInsert<tensor::ParallelInsertSliceOp>>(
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patterns.getContext());
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}

‎mlir/test/Dialect/Tensor/fold-reassociative-reshapes.mlir‎

Lines changed: 102 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -54,3 +54,105 @@ func.func @rank_reducing_parallel_insert_of_collapse_shape(
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}
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return %1 : tensor<?x?x?x?xf32>
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}
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// -----
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// CHECK-LABEL: func @insert_of_padding_expand_shape(
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// CHECK-SAME: %[[t:.*]]: tensor<?x?xf32>
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// CHECK-SAME: %[[d:.*]]: tensor<?x?x?x?xf32>
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// CHECK-SAME: %[[x:[a-zA-Z0-9_]+]]: index
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// CHECK-SAME: %[[y:[a-zA-Z0-9_]+]]: index
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// 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>
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// CHECK: return %[[insert]]
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func.func @insert_of_padding_expand_shape(
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%t: tensor<?x?xf32>, %d: tensor<?x?x?x?xf32>, %x: index, %y: index)
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-> tensor<?x?x?x?xf32> {
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%c0 = arith.constant 0 : index
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%c1 = arith.constant 1 : index
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%sz0 = tensor.dim %t, %c0 : tensor<?x?xf32>
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%sz1 = tensor.dim %t, %c1 : tensor<?x?xf32>
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%0 = tensor.expand_shape %t [[0, 1], [2, 3]] output_shape [1, %sz0, 1, %sz1]
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: tensor<?x?xf32> into tensor<1x?x1x?xf32>
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%1 = tensor.insert_slice %0 into %d[%x, %y, 0, 0][1, %sz0, 1, %sz1][1, 1, 1, 1]
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: tensor<1x?x1x?xf32> into tensor<?x?x?x?xf32>
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return %1 : tensor<?x?x?x?xf32>
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}
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// -----
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// CHECK-LABEL: func @insert_of_non_padding_expand_shape(
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// CHECK-SAME: %[[t:.*]]: tensor<?x?xf32>
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// CHECK-SAME: %[[d:.*]]: tensor<?x?x?x?xf32>
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// CHECK-SAME: %[[x:[a-zA-Z0-9_]+]]: index
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// CHECK-SAME: %[[y:[a-zA-Z0-9_]+]]: index
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// CHECK-SAME: %[[sz:[a-zA-Z0-9_]+]]: index
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// CHECK: %[[expand:.*]] = tensor.expand_shape %[[t]] {{\[}}[0, 1], [2]] output_shape [%[[sz]], %{{.*}}, %{{.*}}] : tensor<?x?xf32> into tensor<?x?x?xf32>
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// 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>
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// CHECK: return %[[insert]]
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func.func @insert_of_non_padding_expand_shape(
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%t: tensor<?x?xf32>, %d: tensor<?x?x?x?xf32>, %x: index, %y: index, %sz: index)
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-> tensor<?x?x?x?xf32> {
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%c0 = arith.constant 0 : index
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%c1 = arith.constant 1 : index
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%sz0 = tensor.dim %t, %c0 : tensor<?x?xf32>
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%sz1 = tensor.dim %t, %c1 : tensor<?x?xf32>
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%0 = tensor.expand_shape %t [[0, 1], [2]] output_shape [%sz, %sz0, %sz1]
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: tensor<?x?xf32> into tensor<?x?x?xf32>
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%1 = tensor.insert_slice %0 into %d[%x, %y, 0, 0][%sz, 1, %sz0, %sz1][1, 1, 1, 1]
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: tensor<?x?x?xf32> into tensor<?x?x?x?xf32>
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return %1 : tensor<?x?x?x?xf32>
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}
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// -----
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// CHECK-LABEL: func @parallel_insert_of_padding_expand_shape(
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// CHECK-SAME: %[[t:.*]]: tensor<?x?xf32>
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// CHECK-SAME: %[[d:.*]]: tensor<?x?x?x?xf32>
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// CHECK-SAME: %[[x:[a-zA-Z0-9_]+]]: index
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// CHECK-SAME: %[[y:[a-zA-Z0-9_]+]]: index
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// CHECK: tensor.parallel_insert_slice %[[t]] into %{{.*}}[%{{.*}}, %{{.*}}, 0, 0] [1, %{{.*}}, 1, %{{.*}}] [1, 1, 1, 1] : tensor<?x?xf32> into tensor<?x?x?x?xf32>
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func.func @parallel_insert_of_padding_expand_shape(
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%t: tensor<?x?xf32>, %d: tensor<?x?x?x?xf32>, %x: index, %y: index)
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-> tensor<?x?x?x?xf32> {
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%c0 = arith.constant 0 : index
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%c1 = arith.constant 1 : index
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%sz0 = tensor.dim %t, %c0 : tensor<?x?xf32>
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%sz1 = tensor.dim %t, %c1 : tensor<?x?xf32>
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%0 = tensor.expand_shape %t [[0, 1], [2, 3]] output_shape [1, %sz0, 1, %sz1]
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: tensor<?x?xf32> into tensor<1x?x1x?xf32>
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%1 = scf.forall (%i, %j) in (%x, %y) shared_outs(%o = %d) -> (tensor<?x?x?x?xf32>) {
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scf.forall.in_parallel {
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tensor.parallel_insert_slice %0 into %o[%i, %j, 0, 0][1, %sz0, 1, %sz1][1, 1, 1, 1]
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: tensor<1x?x1x?xf32> into tensor<?x?x?x?xf32>
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}
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}
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return %1 : tensor<?x?x?x?xf32>
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}
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// -----
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// CHECK-LABEL: func @parallel_insert_of_non_padding_expand_shape(
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// CHECK-SAME: %[[t:.*]]: tensor<?x?xf32>
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// CHECK-SAME: %[[d:.*]]: tensor<?x?x?x?xf32>
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// CHECK-SAME: %[[x:[a-zA-Z0-9_]+]]: index
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// CHECK-SAME: %[[y:[a-zA-Z0-9_]+]]: index
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// CHECK-SAME: %[[sz:[a-zA-Z0-9_]+]]: index
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// CHECK: %[[expand:.*]] = tensor.expand_shape %[[t]] {{\[}}[0, 1], [2]] output_shape [%[[sz]], %{{.*}}, %{{.*}}] : tensor<?x?xf32> into tensor<?x?x?xf32>
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// 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>
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func.func @parallel_insert_of_non_padding_expand_shape(
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%t: tensor<?x?xf32>, %d: tensor<?x?x?x?xf32>, %x: index, %y: index, %sz: index)
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-> tensor<?x?x?x?xf32> {
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%c0 = arith.constant 0 : index
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%c1 = arith.constant 1 : index
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%sz0 = tensor.dim %t, %c0 : tensor<?x?xf32>
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%sz1 = tensor.dim %t, %c1 : tensor<?x?xf32>
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%0 = tensor.expand_shape %t [[0, 1], [2]] output_shape [%sz, %sz0, %sz1]
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: tensor<?x?xf32> into tensor<?x?x?xf32>
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%1 = scf.forall (%i, %j) in (%x, %y) shared_outs(%o = %d) -> (tensor<?x?x?x?xf32>) {
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scf.forall.in_parallel {
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tensor.parallel_insert_slice %0 into %o[%i, %j, 0, 0][%sz, 1, %sz0, %sz1][1, 1, 1, 1]
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: tensor<?x?x?xf32> into tensor<?x?x?x?xf32>
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}
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}
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return %1 : tensor<?x?x?x?xf32>
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}

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