Fix nit

compiler/src/iree/compiler/Dialect/LinalgExt/IR/LinalgExtOps.td

@@ -542,7 +542,7 @@ def IREELinalgExt_AttentionOp : IREELinalgExt_PureOp<"attention",
     statistics while processing the current tile.
 
     With indexing_maps we can also infer when variables are transposed.
-    for example, if V has indexing_map of (m, k1, k2, n) -> (n, k2) insted
+    for example, if V has indexing_map of (m, k1, k2, n) -> (n, k2) instead
     of (m, k1, k2, n) -> (k2, n), then we'd know that V is transposed (V.T),
     and we can expect computation to look like:
 
@@ -669,8 +669,9 @@ def IREELinalgExt_AttentionOp : IREELinalgExt_PureOp<"attention",
       return sumType->getRank();
     }
 
-    // Use indexing_map to infer if V is transposed.
-    bool getTransposeV() {
+    // Since we expect map_V to be (b, m, k1, k2, n) -> (b, k2, n), this function
+    // returns true if n is not the fastest dim.
+    bool isTransposeV() {
       AffineMap vMap = getValueMap();
       auto vFastDim = llvm::cast<AffineDimExpr>(vMap.getResults().back());
       int64_t nDim = vMap.getNumInputs() - 1;

compiler/src/iree/compiler/Dialect/LinalgExt/Transforms/DecomposeAttention.cpp

@@ -331,7 +331,7 @@ void decomposeTiledAttention(IREE::LinalgExt::AttentionOp tiledAttnOp,
   auto [result, newMax, newSum] = createAttentionBody(
       keySlice, valueSlice, querySlice, tiledResult, max, sum,
       sequenceTileLength, keyValueTileLength, headDimension, elementType, ops,
-      tiledAttnOp.getTransposeV(), loc, rewriter);
+      tiledAttnOp.isTransposeV(), loc, rewriter);
 
   rewriter.replaceOp(tiledAttnOp, ValueRange{result, newMax, newSum});
 }

compiler/src/iree/compiler/Dialect/LinalgExt/Transforms/TileAttention.cpp

@@ -297,15 +297,15 @@ IREE::LinalgExt::AttentionOp tileAttention(IREE::LinalgExt::AttentionOp attnOp,
                                 headDimension, elementType, loc, rewriter);
   Value valueSlice =
       extractSlice(value, keyShape, ivs, keyValueTileLength, headDimension,
-                   elementType, loc, rewriter, attnOp.getTransposeV());
+                   elementType, loc, rewriter, attnOp.isTransposeV());
   Value querySlice = extractSlice(query, queryShape, {}, sequenceTileLength,
                                   headDimension, elementType, loc, rewriter);
 
   Value scale = attnOp.getScale();
 
   int64_t tiledInputRank = cast<ShapedType>(querySlice.getType()).getRank();
   SmallVector<AffineMap> tiledIndexingMaps = getTileAttentionIndexingMaps(
-      rewriter, tiledInputRank, attnOp.getTransposeV());
+      rewriter, tiledInputRank, attnOp.isTransposeV());
 
   auto tiledAttentionOp = rewriter.create<IREE::LinalgExt::AttentionOp>(
       attnOp.getLoc(),