[MLIR][Vector] Generalize DropUnitDimFromElementwiseOps to non leading / trailing dimensions.

mlir/lib/Dialect/Vector/Transforms/VectorTransforms.cpp

@@ -1607,7 +1607,27 @@ struct ChainedReduction final : OpRewritePattern<vector::ReductionOp> {
   }
 };
 
-/// For vectors with either leading or trailing unit dim, replaces:
+// Scalable unit dimensions are not supported. Folding such dimensions would
+// require "shifting" the scalable flag onto some other fixed-width dim (e.g.
+// vector<[1]x4xf32> -> vector<[4]xf32>). This could be implemented in the
+// future.
+static VectorType dropNonScalableUnitDimFromType(VectorType inVecTy) {
+  auto inVecShape = inVecTy.getShape();
+  SmallVector<int64_t> newShape;
+  SmallVector<bool> newScalableDims;
+  for (auto [dim, isScalable] :
+       llvm::zip_equal(inVecShape, inVecTy.getScalableDims())) {
+    if (dim == 1 && !isScalable)
+      continue;
+
+    newShape.push_back(dim);
+    newScalableDims.push_back(isScalable);
+  }
+
+  return VectorType::get(newShape, inVecTy.getElementType(), newScalableDims);
+}
+
+/// For vectors with at least an unit dim, replaces:
 ///   elementwise(a, b)
 /// with:
 ///   sc_a = shape_cast(a)
@@ -1619,20 +1639,16 @@ struct ChainedReduction final : OpRewritePattern<vector::ReductionOp> {
 /// required to be rank > 1.
 ///
 /// Ex:
-/// ```
 ///  %mul = arith.mulf %B_row, %A_row : vector<1x[4]xf32>
 ///  %cast = vector.shape_cast %mul : vector<1x[4]xf32> to vector<[4]xf32>
-/// ```
 ///
 /// gets converted to:
 ///
-/// ```
 ///  %B_row_sc = vector.shape_cast %B_row : vector<1x[4]xf32> to vector<[4]xf32>
 ///  %A_row_sc = vector.shape_cast %A_row : vector<1x[4]xf32> to vector<[4]xf32>
 ///  %mul = arith.mulf %B_row_sc, %A_row_sc : vector<[4]xf32>
 ///  %cast_new = vector.shape_cast %mul : vector<[4]xf32> to vector<1x[4]xf32>
 ///  %cast = vector.shape_cast %cast_new : vector<1x[4]xf32> to vector<[4]xf32>
-/// ```
 ///
 /// Patterns for folding shape_casts should instantly eliminate `%cast_new` and
 /// `%cast`.
@@ -1652,42 +1668,29 @@ struct DropUnitDimFromElementwiseOps final
     // guaranteed to have identical shapes (with some exceptions such as
     // `arith.select`) and it suffices to only check one of them.
     auto sourceVectorType = dyn_cast<VectorType>(op->getOperand(0).getType());
-    if (!sourceVectorType)
-      return failure();
-    if (sourceVectorType.getRank() < 2)
-      return failure();
-
-    bool hasTrailingDimUnitFixed =
-        ((sourceVectorType.getShape().back() == 1) &&
-         (!sourceVectorType.getScalableDims().back()));
-    bool hasLeadingDimUnitFixed =
-        ((sourceVectorType.getShape().front() == 1) &&
-         (!sourceVectorType.getScalableDims().front()));
-    if (!hasLeadingDimUnitFixed && !hasTrailingDimUnitFixed)
+    if (!sourceVectorType || sourceVectorType.getRank() < 2)
       return failure();
 
-    // Drop leading/trailing unit dim by applying vector.shape_cast to all
-    // operands
-    int64_t dim = hasLeadingDimUnitFixed ? 0 : sourceVectorType.getRank() - 1;
-
     SmallVector<Value> newOperands;
     auto loc = op->getLoc();
     for (auto operand : op->getOperands()) {
       auto opVectorType = cast<VectorType>(operand.getType());
-      VectorType newVType = VectorType::Builder(opVectorType).dropDim(dim);
+      auto newVType = dropNonScalableUnitDimFromType(opVectorType);
+      if (newVType == opVectorType)
+        return rewriter.notifyMatchFailure(op, "No unit dimension to remove.");
+
       auto opSC = rewriter.create<vector::ShapeCastOp>(loc, newVType, operand);
       newOperands.push_back(opSC);
     }
 
     VectorType newResultVectorType =
-        VectorType::Builder(resultVectorType).dropDim(dim);
-    // Create an updated elementwise Op without leading/trailing unit dim
+        dropNonScalableUnitDimFromType(resultVectorType);
+    // Create an updated elementwise Op without unit dim.
     Operation *elementwiseOp =
         rewriter.create(loc, op->getName().getIdentifier(), newOperands,
                         newResultVectorType, op->getAttrs());
 
-    // Restore the leading/trailing unit dim by applying vector.shape_cast
-    // to the result
+    // Restore the unit dim by applying vector.shape_cast to the result.
     rewriter.replaceOpWithNewOp<ShapeCastOp>(op, resultVectorType,
                                              elementwiseOp->getResult(0));
 

mlir/test/Dialect/Vector/vector-transfer-flatten.mlir

@@ -499,6 +499,42 @@ func.func @fold_unit_dims_entirely(%arg0 : vector<8xi32>,
 
 // -----
 
+func.func @fold_inner_unit_dim(%arg0 : vector<8x1x3xf128>,
+                              %arg1 : vector<1x8x3xf128>) -> vector<8x3xf128> {
+   %sc_arg1 = vector.shape_cast %arg1 : vector<1x8x3xf128> to vector<8x1x3xf128>
+   %mul = arith.mulf %arg0, %sc_arg1 : vector<8x1x3xf128>
+   %res = vector.shape_cast %mul : vector<8x1x3xf128> to vector<8x3xf128>
+   return %res : vector<8x3xf128>
+}
+
+// CHECK-LABEL: func.func @fold_inner_unit_dim(
+// CHECK-SAME:    %[[VAL_0:.*]]: vector<8x1x3xf128>,
+// CHECK-SAME:    %[[VAL_1:.*]]: vector<1x8x3xf128>) -> vector<8x3xf128> {
+// CHECK:         %[[VAL_2:.*]] = vector.shape_cast %[[VAL_0]] : vector<8x1x3xf128> to vector<8x3xf128>
+// CHECK:         %[[VAL_3:.*]] = vector.shape_cast %[[VAL_1]] : vector<1x8x3xf128> to vector<8x3xf128>
+// CHECK:         %[[VAL_4:.*]] = arith.mulf %[[VAL_2]], %[[VAL_3]] : vector<8x3xf128>
+// CHECK:         return %[[VAL_4]] : vector<8x3xf128>
+
+// -----
+
+func.func @fold_inner_unit_dim_scalable(%arg0 : vector<8x1x[1]x3xf128>,
+                              %arg1 : vector<1x8x[1]x3xf128>) -> vector<8x[1]x3xf128> {
+   %sc_arg1 = vector.shape_cast %arg1 : vector<1x8x[1]x3xf128> to vector<8x1x[1]x3xf128>
+   %mul = arith.mulf %arg0, %sc_arg1 : vector<8x1x[1]x3xf128>
+   %res = vector.shape_cast %mul : vector<8x1x[1]x3xf128> to vector<8x[1]x3xf128>
+   return %res : vector<8x[1]x3xf128>
+}
+
+// CHECK-LABEL: func.func @fold_inner_unit_dim_scalable(
+// CHECK-SAME:    %[[VAL_0:.*]]: vector<8x1x[1]x3xf128>,
+// CHECK-SAME:    %[[VAL_1:.*]]: vector<1x8x[1]x3xf128>) -> vector<8x[1]x3xf128> {
+// CHECK:         %[[VAL_2:.*]] = vector.shape_cast %[[VAL_0]] : vector<8x1x[1]x3xf128> to vector<8x[1]x3xf128>
+// CHECK:         %[[VAL_3:.*]] = vector.shape_cast %[[VAL_1]] : vector<1x8x[1]x3xf128> to vector<8x[1]x3xf128>
+// CHECK:         %[[VAL_4:.*]] = arith.mulf %[[VAL_2]], %[[VAL_3]] : vector<8x[1]x3xf128>
+// CHECK:         return %[[VAL_4]] : vector<8x[1]x3xf128>
+
+// -----
+
 func.func @negative_out_of_bound_transfer_read(
     %arg : memref<?x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>>) -> vector<5x4x3x2xi8> {
   %c0 = arith.constant 0 : index