[mlir] Fix memref_cast + subview folder when reducing rank

[ThomasRaoux]

Summary

When the destination of the subview has a lower rank than its source we need to fix the result type of the new subview op.

[ThomasRaoux]

Fix test failure.

mlir/lib/Dialect/StandardOps/IR/Ops.cpp

isRankReducedType(Type originalType, Type candidateReducedType,
   llvm::SmallDenseSet<unsigned> unusedDims = optionalUnusedDimsMask.getValue();
   auto inferredType =
       getProjectedMap(getStridedLinearLayoutMap(original), unusedDims);
   AffineMap candidateLayout;
   if (candidateReduced.getAffineMaps().empty())
     candidateLayout = getStridedLinearLayoutMap(candidateReduced);
   else
     candidateLayout = candidateReduced.getAffineMaps().front();
-  if (inferredType != candidateLayout) {
+  assert(inferredType.getNumResults() == 1 &&
+         candidateLayout.getNumResults() == 1);
+  if (inferredType.getNumSymbols() != candidateLayout.getNumSymbols() ||
+      inferredType.getNumDims() != candidateLayout.getNumDims())
+    return SubViewVerificationResult::AffineMapMismatch;
+  // Check that the difference of the affine maps simplifies to 0.
+  AffineExpr diffExpr =
+      inferredType.getResult(0) - candidateLayout.getResult(0);
+  diffExpr = simplifyAffineExpr(diffExpr, inferredType.getNumDims(),
+                                inferredType.getNumSymbols());
+  auto cst = diffExpr.dyn_cast<AffineConstantExpr>();
+  if (!(cst && cst.getValue() == 0)) {
     if (errMsg) {
       llvm::raw_string_ostream os(*errMsg);
       os << "inferred type: " << inferredType;
     }
     return SubViewVerificationResult::AffineMapMismatch;
   }
   return SubViewVerificationResult::Success;
 }
if (!castOp)
       return failure();
 
     if (!canFoldIntoConsumerOp(castOp))
       return failure();
 
     /// Deduce the resultType of the SubViewOp using `inferSubViewResultType` on
     /// the cast source operand type and the SubViewOp static information. This
     /// is the resulting type if the MemRefCastOp were folded.
-    Type resultType = SubViewOp::inferResultType(
+    auto resultType = SubViewOp::inferResultType(
                           castOp.source().getType().cast<MemRefType>(),
                           extractFromI64ArrayAttr(subViewOp.static_offsets()),
                           extractFromI64ArrayAttr(subViewOp.static_sizes()),
-        extractFromI64ArrayAttr(subViewOp.static_strides()));
+                          extractFromI64ArrayAttr(subViewOp.static_strides()))
+                          .cast<MemRefType>();
+    uint32_t rankDiff =
+        subViewOp.getSourceType().getRank() - subViewOp.getType().getRank();
+    if (rankDiff > 0) {
+      auto shape = resultType.getShape();
+      auto projectedShape = shape.drop_front(rankDiff);
+      AffineMap map;
+      auto maps = resultType.getAffineMaps();
+      if (!maps.empty() && maps.front()) {
+        auto optionalUnusedDimsMask =
+            computeRankReductionMask(shape, projectedShape);
+        llvm::SmallDenseSet<unsigned> dimsToProject =
+            optionalUnusedDimsMask.getValue();
+        map = getProjectedMap(maps.front(), dimsToProject);
+      }
+      resultType = MemRefType::get(projectedShape, resultType.getElementType(),
+                                   map, resultType.getMemorySpace());
+    }
     Value newSubView = rewriter.create<SubViewOp>(
         subViewOp.getLoc(), resultType, castOp.source(), subViewOp.offsets(),
         subViewOp.sizes(), subViewOp.strides(), subViewOp.static_offsets(),
         subViewOp.static_sizes(), subViewOp.static_strides());
     rewriter.replaceOpWithNewOp<MemRefCastOp>(subViewOp, subViewOp.getType(),
                                               newSubView);
     return success();
   }

mlir/test/Dialect/Standard/canonicalize.mlir

 //       CHECK:   %[[M1:.+]] = memref_cast %[[M]] : memref<4x6x16x32xi8> to memref<?x?x16x32xi8>
 //       CHECK:   return %[[M1]] : memref<?x?x16x32xi8>
 func @tensor_cast_to_memref(%arg0 : tensor<4x6x16x32xi8>) ->
   memref<?x?x16x32xi8> {
   %0 = tensor.cast %arg0 : tensor<4x6x16x32xi8> to tensor<?x?x16x32xi8>
   %1 = tensor_to_memref %0 : memref<?x?x16x32xi8>
   return %1 : memref<?x?x16x32xi8>
 }
+
+// CHECK-LABEL: func @subview_of_memcast
+//  CHECK-SAME:   %[[ARG0:.[a-z0-9A-Z_]+]]: memref<4x6x16x32xi8>
+//       CHECK:   %[[S:.+]] = subview %arg0[0, 1, 0, 0] [1, 1, 16, 32] [1, 1, 1, 1] : memref<4x6x16x32xi8> to memref<16x32xi8, #{{.*}}>
+//       CHECK:   %[[M:.+]] = memref_cast %[[S]] : memref<16x32xi8, #{{.*}}> to memref<16x32xi8, #{{.*}}>
+//       CHECK:   return %[[M]] : memref<16x32xi8, #{{.*}}>
+func @subview_of_memcast(%arg : memref<4x6x16x32xi8>) ->
+  memref<16x32xi8, affine_map<(d0, d1)[s0] -> (d0 * 32 + d1 + s0)>>{
+  %0 = memref_cast %arg : memref<4x6x16x32xi8> to memref<?x?x16x32xi8>
+  %1 = subview %0[0, 1, 0, 0] [1, 1, 16, 32] [1, 1, 1, 1] :
+    memref<?x?x16x32xi8> to
+    memref<16x32xi8, affine_map<(d0, d1)[s0] -> (d0 * 32 + d1 + s0)>>
+  return %1 : memref<16x32xi8, affine_map<(d0, d1)[s0] -> (d0 * 32 + d1 + s0)>>
+}