[Mlir-commits] [mlir] [mlir][tensor] Fold unpadding collapse_shape into extract_slice (PR #93554)

llvmlistbot at llvm.org llvmlistbot at llvm.org
Tue May 28 07:27:37 PDT 2024


llvmbot wrote:


<!--LLVM PR SUMMARY COMMENT-->

@llvm/pr-subscribers-mlir

Author: Adam Siemieniuk (adam-smnk)

<details>
<summary>Changes</summary>



---
Full diff: https://github.com/llvm/llvm-project/pull/93554.diff


2 Files Affected:

- (modified) mlir/lib/Dialect/Tensor/Transforms/ReshapePatterns.cpp (+40-6) 
- (modified) mlir/test/Dialect/Tensor/fold-reassociative-reshapes.mlir (+69) 


``````````diff
diff --git a/mlir/lib/Dialect/Tensor/Transforms/ReshapePatterns.cpp b/mlir/lib/Dialect/Tensor/Transforms/ReshapePatterns.cpp
index 6cf0f845f59db..d7c608a773bb7 100644
--- a/mlir/lib/Dialect/Tensor/Transforms/ReshapePatterns.cpp
+++ b/mlir/lib/Dialect/Tensor/Transforms/ReshapePatterns.cpp
@@ -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.getResult().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());
 }
diff --git a/mlir/test/Dialect/Tensor/fold-reassociative-reshapes.mlir b/mlir/test/Dialect/Tensor/fold-reassociative-reshapes.mlir
index 644d9a918f6ca..c2368c4bf2c91 100644
--- a/mlir/test/Dialect/Tensor/fold-reassociative-reshapes.mlir
+++ b/mlir/test/Dialect/Tensor/fold-reassociative-reshapes.mlir
@@ -22,6 +22,75 @@ 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] [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] [%{{.*}}, %{{.*}}, %[[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] [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>

``````````

</details>


https://github.com/llvm/llvm-project/pull/93554


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