[MLIR][Linalg] Fix linalg crash during elementwise op fusion

mlir/include/mlir/Dialect/Linalg/IR/LinalgInterfaces.td

@@ -741,7 +741,7 @@ def LinalgStructuredInterface
       /*methodBody=*/"",
       /*defaultImplementation=*/[{
         auto maps =  $_op.getIndexingMapsArray();
-        return concatAffineMaps(maps);
+        return concatAffineMaps(maps, $_op.getContext());
       }]
     >,
     InterfaceMethod<

mlir/include/mlir/IR/AffineMap.h

@@ -613,7 +613,7 @@ AffineMap inverseAndBroadcastProjectedPermutation(AffineMap map);
 /// ```mlir
 ///     (i, j, k) -> (i, k, k, j, i, j)
 /// ```
-AffineMap concatAffineMaps(ArrayRef<AffineMap> maps);
+AffineMap concatAffineMaps(ArrayRef<AffineMap> maps, MLIRContext *context);
 
 /// Returns the map that results from projecting out the dimensions specified in
 /// `projectedDimensions`. The projected dimensions are set to 0.

mlir/lib/Dialect/Linalg/IR/LinalgInterfaces.cpp

@@ -54,7 +54,8 @@ bool linalg::detail::canOpOperandsBeDroppedImpl(
     // if the op has no loops.
     return linalgOp.getNumLoops() == 0;
   }
-  return inversePermutation(concatAffineMaps(indexingMaps)) != AffineMap();
+  return inversePermutation(concatAffineMaps(
+             indexingMaps, linalgOp.getContext())) != AffineMap();
 }
 
 //===----------------------------------------------------------------------===//

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

@@ -392,7 +392,8 @@ linalg::dropUnitDims(RewriterBase &rewriter, GenericOp genericOp,
   // 1. Check if any of the iteration dimensions are unit-trip count. They will
   //    end up being unit-trip count if they are used to index into a unit-dim
   //    tensor/memref.
-  AffineMap invertedMap = inversePermutation(concatAffineMaps(indexingMaps));
+  AffineMap invertedMap =
+      inversePermutation(concatAffineMaps(indexingMaps, rewriter.getContext()));
   if (!invertedMap) {
     return rewriter.notifyMatchFailure(genericOp,
                                        "invalid indexing maps for operation");
@@ -486,7 +487,8 @@ linalg::dropUnitDims(RewriterBase &rewriter, GenericOp genericOp,
   // Abort if the indexing maps of the result operation are not invertible
   // (i.e. not legal) or if no dimension was reduced.
   if (newIndexingMaps == indexingMaps ||
-      !inversePermutation(concatAffineMaps(newIndexingMaps)))
+      !inversePermutation(
+          concatAffineMaps(newIndexingMaps, rewriter.getContext())))
     return failure();
 
   Location loc = genericOp.getLoc();

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

@@ -88,12 +88,18 @@ static bool isOpOperandCanBeDroppedAfterFusedLinalgs(
       indexingMaps.push_back(op.getMatchingIndexingMap(&opOperand));
     }
   }
+  if (indexingMaps.empty()) {
+    // If there are no indexing maps, the operand can only be dropped
+    // if neither op has loops.
+    return producer.getNumLoops() == 0 && consumer.getNumLoops() == 0;
+  }
 
   // The concatanation of the remained indexing maps must be invertible, so
   // the bounds of the op can be still computed after dropping the selected
   // operand. inversePermutation returns an empty AffineMap in case the
   // concatanated indexing maps are not invertible.
-  return inversePermutation(concatAffineMaps(indexingMaps)) != AffineMap();
+  return inversePermutation(concatAffineMaps(
+             indexingMaps, producer.getContext())) != AffineMap();
 }
 
 /// Returns a set of indices of the producer's results which would
@@ -1995,7 +2001,8 @@ class FoldScalarOrSplatConstant : public OpRewritePattern<GenericOp> {
             genericOp.getMatchingIndexingMap(&outputOperand));
 
       // Check if the operation shapes to loops map is computable.
-      if (!inversePermutation(concatAffineMaps(fusedIndexMaps))) {
+      if (!inversePermutation(
+              concatAffineMaps(fusedIndexMaps, rewriter.getContext()))) {
         return rewriter.notifyMatchFailure(
             genericOp, "fused op loop bound computation failed");
       }

mlir/lib/IR/AffineMap.cpp

@@ -833,7 +833,10 @@ AffineMap mlir::inverseAndBroadcastProjectedPermutation(AffineMap map) {
   return AffineMap::get(map.getNumResults(), /*symbolCount=*/0, exprs, context);
 }
 
-AffineMap mlir::concatAffineMaps(ArrayRef<AffineMap> maps) {
+AffineMap mlir::concatAffineMaps(ArrayRef<AffineMap> maps,
+                                 MLIRContext *context) {
+  if (maps.empty())
+    return AffineMap::get(context);
   unsigned numResults = 0, numDims = 0, numSymbols = 0;
   for (auto m : maps)
     numResults += m.getNumResults();
@@ -846,8 +849,7 @@ AffineMap mlir::concatAffineMaps(ArrayRef<AffineMap> maps) {
     numSymbols += m.getNumSymbols();
     numDims = std::max(m.getNumDims(), numDims);
   }
-  return AffineMap::get(numDims, numSymbols, results,
-                        maps.front().getContext());
+  return AffineMap::get(numDims, numSymbols, results, context);
 }
 
 /// Common implementation to project out dimensions or symbols from an affine

mlir/test/Dialect/Linalg/fusion-elementwise.mlir

@@ -28,3 +28,34 @@ func.func @drop_unused_producer_result(%arg0 : tensor<?x?xf32>,
 //       CHECK:   %[[FUSED_OP:.+]] = linalg.generic
 //  CHECK-SAME:       ins(%[[ARG0]], %[[ARG1]] :
 //       CHECK:   return %[[FUSED_OP]]
+
+// -----
+
+#map = affine_map<(d0) -> (d0)>
+func.func @handle_unused_operands(%arg0: tensor<8xf32>, %arg1: tensor<8xf32>) -> tensor<8xf32> {
+  %cst_0 = arith.constant 0.000000e+00 : f32
+  %cst_1 = arith.constant 1.000000e+00 : f32
+  %0:2 = linalg.generic {indexing_maps = [#map, #map], iterator_types = ["parallel"]} outs(%arg0, %arg1 : tensor<8xf32>, tensor<8xf32>) {
+  ^bb0(%out: f32, %out_2: f32):
+    %1 = linalg.index 0 : index
+    %2 = arith.index_cast %1 : index to i64
+    %3 = arith.sitofp %2 : i64 to f32
+    %4 = arith.divf %3, %cst_0 : f32
+    linalg.yield %3, %4 : f32, f32
+  } -> (tensor<8xf32>, tensor<8xf32>)
+  linalg.generic {indexing_maps = [#map], iterator_types = ["parallel"]} ins(%0#1 : tensor<8xf32>) {
+  ^bb0(%in: f32):
+    %2 = arith.cmpf one, %in, %cst_1 : f32
+    cf.assert %2, "Side effect op"
+    linalg.yield
+  }
+  func.return %arg1 : tensor<8xf32>
+}
+
+// CHECK-LABEL: func @handle_unused_operands
+//  CHECK-SAME:   %[[ARG0:[a-zA-Z0-9]+]]: tensor<8xf32>
+//  CHECK-SAME:   %[[ARG1:[a-zA-Z0-9]+]]: tensor<8xf32>
+//       CHECK:   %[[EMPTY:.+]] = tensor.empty() : tensor<8xf32>
+//       CHECK:   %[[FUSED_OP:.+]] = linalg.generic
+//  CHECK-SAME:       outs(%[[EMPTY]] :
+//   CHECK-NOT:   linalg.generic