Clean up

Author: josel-amd

mlir/include/mlir/Dialect/Linalg/Utils/Utils.h

@@ -12,7 +12,6 @@
 #include "mlir/Dialect/Linalg/IR/Linalg.h"
 #include "mlir/Dialect/SCF/IR/SCF.h"
 #include "mlir/Dialect/Utils/StructuredOpsUtils.h"
-#include "llvm/ADT/ArrayRef.h"
 #include "llvm/ADT/StringSet.h"
 #include <optional>
 
@@ -177,8 +176,7 @@ Operation *makeTiledShape(OpBuilder &builder, Location loc, Value valueToTile,
                           ArrayRef<OpFoldResult> lbs,
                           ArrayRef<OpFoldResult> ubs,
                           ArrayRef<OpFoldResult> subShapeSizes,
-                          bool omitPartialTileCheck,
-                          ArrayRef<OpFoldResult> sizeBounds = {});
+                          bool omitPartialTileCheck);
 
 /// Creates extract_slice/subview ops for all `valuesToTile` of the given
 /// `linalgOp` with `builder`, assuming `linalgOp` is being fused into a loop

mlir/lib/Dialect/Linalg/Utils/Utils.cpp

@@ -90,7 +90,6 @@ static bool isTiled(AffineExpr expr, ArrayRef<OpFoldResult> tileSizes,
                     ArrayRef<int64_t> domainSizes) {
   if (!expr)
     return false;
-
   TileCheck t(tileSizes, domainSizes);
   t.visit(expr);
   return t.isTiled;
@@ -612,7 +611,6 @@ SliceParameters computeSliceParameters(
 
     // Tiling creates a new slice at the proper index, the slice step is 1
     // (i.e. the op does not subsample, stepping occurs in the loop).
-    auto m = map.getSubMap({r});
     LLVM_DEBUG(llvm::dbgs() << "computeSliceParameters: submap: " << m << "\n");
     IRRewriter rewriter(builder);
     // The offset of the slice is map(lbs) - map(0).

mlir/test/Dialect/Linalg/tile-tensors.mlir

@@ -167,3 +167,31 @@ module attributes {transform.with_named_sequence} {
     transform.yield
   }
 }
+
+// -----
+
+func.func @non_monotonic_affine_expr(%arg0 : tensor<7xf32>) -> tensor<7xf32> {
+  %c0 = arith.constant 0 : index
+  %0 = tensor.dim %arg0, %c0 : tensor<7xf32>
+  %empty = tensor.empty() : tensor<7xf32>
+  // FIXME: Do proper testing
+  // CHECK: tensor.extract_slice %arg2[0] [7] [1] : tensor<7xf32> to tensor<7xf32>
+  %generic = linalg.generic
+    {indexing_maps = [affine_map<(d0) -> (d0 mod 4)>,
+                      affine_map<(d0) -> (d0)>],
+     iterator_types = ["parallel"]}
+    ins(%arg0: tensor<7xf32>)
+    outs(%empty : tensor<7xf32>) {
+    ^bb0(%in : f32, %out: f32):
+      linalg.yield %in : f32
+    } -> tensor<7xf32>
+  return %generic : tensor<7xf32>
+}
+
+module attributes {transform.with_named_sequence} {
+  transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
+    %0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+    %1, %loop = transform.structured.tile_using_for %0 tile_sizes [7] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
+    transform.yield
+  }
+}