[mlir] Add bubbling patterns for non intersecting reshapes

mlir/include/mlir/Dialect/Tensor/Transforms/Transforms.h

@@ -67,6 +67,10 @@ void populateDropRedundantInsertSliceRankExpansionPatterns(
 /// `tensor.collapse_shape` into other ops.
 void populateReassociativeReshapeFoldingPatterns(RewritePatternSet &patterns);
 
+/// Populates `patterns` with patterns that bubble up `tensor.expand_shape`
+/// through `tensor.collapse_shape` ops.
+void populateBubbleUpExpandShapePatterns(RewritePatternSet &patterns);
+
 /// Populates `patterns` with patterns that fold tensor.empty with its
 /// consumers.
 ///

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

@@ -17,6 +17,7 @@
 #include "mlir/Dialect/Linalg/IR/Linalg.h"
 #include "mlir/Dialect/Linalg/Transforms/Transforms.h"
 #include "mlir/Dialect/SparseTensor/IR/SparseTensor.h"
+#include "mlir/Dialect/Tensor/Transforms/Transforms.h"
 #include "mlir/IR/AffineExpr.h"
 #include "mlir/IR/AffineMap.h"
 #include "mlir/IR/Matchers.h"
@@ -2144,6 +2145,7 @@ struct LinalgElementwiseOpFusionPass
     // Add elementwise op fusion patterns.
     populateElementwiseOpsFusionPatterns(patterns, defaultControlFn);
     populateFoldReshapeOpsByExpansionPatterns(patterns, defaultControlFn);
+    tensor::populateBubbleUpExpandShapePatterns(patterns);
 
     // General canonicalization patterns.
     affine::AffineApplyOp::getCanonicalizationPatterns(patterns, context);

mlir/lib/Dialect/Tensor/Transforms/ReshapePatterns.cpp

@@ -140,6 +140,76 @@ struct FoldPaddingExpandIntoInsert : public OpRewritePattern<OpTy> {
     return success();
   }
 };
+
+/// Pattern to bubble up a tensor.expand_shape op through a producer
+/// tensor.collapse_shape op that has non intersecting reassociations.
+struct BubbleUpExpandThroughParallelCollapse
+    : public OpRewritePattern<tensor::ExpandShapeOp> {
+  using OpRewritePattern<tensor::ExpandShapeOp>::OpRewritePattern;
+
+  LogicalResult matchAndRewrite(tensor::ExpandShapeOp expandOp,
+                                PatternRewriter &rewriter) const override {
+    auto collapseOp =
+        expandOp.getSrc().getDefiningOp<tensor::CollapseShapeOp>();
+    if (!collapseOp)
+      return failure();
+    auto expandReInds = expandOp.getReassociationIndices();
+    auto collapseReInds = collapseOp.getReassociationIndices();
+
+    // Reshapes are parallel to each other if none of the reassociation indices
+    // have greater than 1 index for both reshapes.
+    for (auto [expandReassociation, collapseReassociation] :
+         llvm::zip_equal(expandReInds, collapseReInds)) {
+      if (collapseReassociation.size() != 1 && expandReassociation.size() != 1)
+        return failure();
+    }
+
+    // Compute new reassociation indices and expanded/collaped shapes.
+    SmallVector<ReassociationIndices> newExpandReInds, newCollapseReInds;
+    Location loc = expandOp->getLoc();
+    SmallVector<OpFoldResult> collapseSizes =
+        tensor::getMixedSizes(rewriter, loc, collapseOp.getSrc());
+    SmallVector<OpFoldResult> expandSizes(getMixedValues(
+        expandOp.getStaticOutputShape(), expandOp.getOutputShape(), rewriter));
+    SmallVector<OpFoldResult> newExpandSizes;
+    int64_t index = 0, expandIndex = 0, collapseIndex = 0;
+    for (auto [idx, collapseReassociation] : llvm::enumerate(collapseReInds)) {
+      if (collapseReassociation.size() != 1) {
+        ReassociationIndices newCollapseReassociation;
+        for (size_t i = 0; i < collapseReassociation.size(); ++i) {
+          newCollapseReassociation.push_back(index);
+          newExpandReInds.push_back({index++});
+          newExpandSizes.push_back(collapseSizes[collapseIndex++]);
+        }
+        newCollapseReInds.push_back(newCollapseReassociation);
+        expandIndex++;
+        continue;
+      }
+      ReassociationIndices newExpandReassociation;
+      auto expandReassociation = expandReInds[idx];
+      for (size_t i = 0; i < expandReassociation.size(); ++i) {
+        newExpandReassociation.push_back(index);
+        newCollapseReInds.push_back({index++});
+        newExpandSizes.push_back(expandSizes[expandIndex++]);
+      }
+      newExpandReInds.push_back(newExpandReassociation);
+      collapseIndex++;
+    }
+
+    // Swap reshape order.
+    SmallVector<Value> dynamicSizes;
+    SmallVector<int64_t> staticSizes;
+    dispatchIndexOpFoldResults(newExpandSizes, dynamicSizes, staticSizes);
+    auto expandResultType = expandOp.getResultType().clone(staticSizes);
+    auto newExpand = rewriter.create<tensor::ExpandShapeOp>(
+        loc, expandResultType, collapseOp.getSrc(), newExpandReInds,
+        newExpandSizes);
+    rewriter.replaceOpWithNewOp<tensor::CollapseShapeOp>(
+        expandOp, newExpand.getResult(), newCollapseReInds);
+    return success();
+  }
+};
+
 } // namespace
 
 void mlir::tensor::populateReassociativeReshapeFoldingPatterns(
@@ -152,3 +222,8 @@ void mlir::tensor::populateReassociativeReshapeFoldingPatterns(
            FoldPaddingExpandIntoInsert<tensor::ParallelInsertSliceOp>>(
           patterns.getContext());
 }
+
+void mlir::tensor::populateBubbleUpExpandShapePatterns(
+    RewritePatternSet &patterns) {
+  patterns.add<BubbleUpExpandThroughParallelCollapse>(patterns.getContext());
+}

mlir/test/Dialect/Tensor/bubble-reshapes.mlir

@@ -0,0 +1,47 @@
+// RUN: mlir-opt -split-input-file -test-tensor-transform-patterns=test-expand-shape-bubbling %s | FileCheck %s
+
+func.func @bubble_parallel_reshapes(%arg0: tensor<?x?x?x?xf32>, %s0: index, %s1: index, %s2: index, %s3: index) -> tensor<?x?x?x?xf32> {
+  %collapse = tensor.collapse_shape %arg0 [[0], [1, 2], [3]] : tensor<?x?x?x?xf32> into tensor<?x?x?xf32>
+  %expand = tensor.expand_shape %collapse [[0], [1], [2, 3]]
+              output_shape [%s0, %s1, %s2, %s3] : tensor<?x?x?xf32> into tensor<?x?x?x?xf32>
+  return %expand : tensor<?x?x?x?xf32>
+}
+//      CHECK: func @bubble_parallel_reshapes
+// CHECK-SAME:   %[[ARG0:.+]]: tensor<?x?x?x?xf32>
+// CHECK-SAME:   %[[S0:.+]]: index, %[[S1:.+]]: index, %[[S2:.+]]: index, %[[S3:.+]]: index
+//  CHECK-DAG:   %[[C1:.+]] = arith.constant 1 : index
+//  CHECK-DAG:   %[[C2:.+]] = arith.constant 2 : index
+//  CHECK-DAG:   %[[DIM1:.+]] = tensor.dim %[[ARG0]], %[[C1]] : tensor<?x?x?x?xf32>
+//  CHECK-DAG:   %[[DIM2:.+]] = tensor.dim %[[ARG0]], %[[C2]] : tensor<?x?x?x?xf32>
+//      CHECK:   %[[EXPAND:.+]] = tensor.expand_shape %[[ARG0]] {{\[}}[0], [1], [2], [3, 4]]
+// CHECK-SAME:       output_shape [%[[S0]], %[[DIM1]], %[[DIM2]], %[[S2]], %[[S3]]] : tensor<?x?x?x?xf32> into tensor<?x?x?x?x?xf32>
+//      CHECK:   %[[COLLAPSE:.+]] = tensor.collapse_shape %[[EXPAND]] {{\[}}[0], [1, 2], [3], [4]] : tensor<?x?x?x?x?xf32> into tensor<?x?x?x?xf32>
+//      CHECK:   return %[[COLLAPSE]]
+
+// -----
+
+func.func @no_bubble_full_intersecting_reshapes(%arg0: tensor<?x?x?x?xf32>, %s0: index, %s1: index, %s2: index, %s3: index) -> tensor<?x?x?x?xf32> {
+  %collapse = tensor.collapse_shape %arg0 [[0], [1, 2], [3]] : tensor<?x?x?x?xf32> into tensor<?x?x?xf32>
+  %expand = tensor.expand_shape %collapse [[0], [1, 2], [3]]
+              output_shape [%s0, %s1, %s2, %s3] : tensor<?x?x?xf32> into tensor<?x?x?x?xf32>
+  return %expand : tensor<?x?x?x?xf32>
+}
+//      CHECK: func @no_bubble_full_intersecting_reshapes
+// CHECK-SAME:   %[[ARG0:.+]]: tensor<?x?x?x?xf32>
+//      CHECK:   %[[COLLAPSE:.+]] = tensor.collapse_shape %[[ARG0]] {{\[}}[0], [1, 2], [3]]
+//      CHECK:   %[[EXPAND:.+]] = tensor.expand_shape %[[COLLAPSE]] {{\[}}[0], [1, 2], [3]]
+//      CHECK:   return %[[EXPAND]]
+
+// -----
+
+func.func @no_bubble_partial_intersecting_reshapes(%arg0: tensor<?x?x?x?xf32>, %s0: index, %s1: index, %s2: index, %s3: index) -> tensor<?x?x?x?xf32> {
+  %collapse = tensor.collapse_shape %arg0 [[0, 1, 2], [3]] : tensor<?x?x?x?xf32> into tensor<?x?xf32>
+  %expand = tensor.expand_shape %collapse [[0, 1], [2, 3]]
+              output_shape [%s0, %s1, %s2, %s3] : tensor<?x?xf32> into tensor<?x?x?x?xf32>
+  return %expand : tensor<?x?x?x?xf32>
+}
+//      CHECK: func @no_bubble_partial_intersecting_reshapes
+// CHECK-SAME:   %[[ARG0:.+]]: tensor<?x?x?x?xf32>
+//      CHECK:   %[[COLLAPSE:.+]] = tensor.collapse_shape %[[ARG0]] {{\[}}[0, 1, 2], [3]]
+//      CHECK:   %[[EXPAND:.+]] = tensor.expand_shape %[[COLLAPSE]] {{\[}}[0, 1], [2, 3]]
+//      CHECK:   return %[[EXPAND]]

mlir/test/lib/Dialect/Tensor/TestTensorTransforms.cpp

@@ -72,6 +72,11 @@ struct TestTensorTransforms
       llvm::cl::desc("Test folding of expand_shape/collapse_shape"),
       llvm::cl::init(false)};
 
+  Option<bool> testBubbleUpExpandShapePatterns{
+      *this, "test-expand-shape-bubbling",
+      llvm::cl::desc("Test folding of expand_shape/collapse_shape"),
+      llvm::cl::init(false)};
+
   Option<bool> testFoldIntoPackAndUnpack{
       *this, "test-fold-into-pack-and-unpack",
       llvm::cl::desc("Test folding ops into tensor.pack and tensor.unpack"),
@@ -102,6 +107,12 @@ static void applyReassociativeReshapeFoldingPatterns(Operation *rootOp) {
   (void)applyPatternsAndFoldGreedily(rootOp, std::move(patterns));
 }
 
+static void applyBubbleUpExpandShapePatterns(Operation *rootOp) {
+  RewritePatternSet patterns(rootOp->getContext());
+  tensor::populateBubbleUpExpandShapePatterns(patterns);
+  (void)applyPatternsAndFoldGreedily(rootOp, std::move(patterns));
+}
+
 static void applyFoldIntoPackAndUnpackPatterns(Operation *rootOp) {
   RewritePatternSet patterns(rootOp->getContext());
   tensor::populateFoldIntoPackAndUnpackPatterns(patterns);
@@ -386,6 +397,8 @@ void TestTensorTransforms::runOnOperation() {
     applyDropRedundantInsertSliceRankExpansionPatterns(rootOp);
   if (testReassociativeReshapeFolding)
     applyReassociativeReshapeFoldingPatterns(rootOp);
+  if (testBubbleUpExpandShapePatterns)
+    applyBubbleUpExpandShapePatterns(rootOp);
   if (testFoldIntoPackAndUnpack)
     applyFoldIntoPackAndUnpackPatterns(rootOp);
   if (testRewriteExtractSliceWithTiledCollapseShape) {