Bump llvm/llvm-project@b6603e1bf1 (#3697)

Bump forward and refactor inline global slots to no longer track via
symlinks. This appears to make the tests past until we manage to remove
torchscript work.

externals/llvm-project

@@ -1 +1 @@
-Subproject commit f9031f00f2c90bc0af274b45ec3e169b5250a688
+Subproject commit b6603e1bf11dee4761e49af6581c8b8f074b705d

lib/Dialect/Torch/Transforms/InlineGlobalSlots.cpp

@@ -49,16 +49,15 @@ using namespace mlir::torch::Torch;
 /// a single module. If we had to support complex nested symbol references, we
 /// would probably want to go through the effort to indirect through the symbol
 /// tables to make things clearer.
-class FlatSymbolRefProgramPoint
+class FlatSymbolRefLatticeAnchor
-    : public GenericProgramPointBase<FlatSymbolRefProgramPoint,
+    : public GenericLatticeAnchorBase<FlatSymbolRefLatticeAnchor, Operation *> {
-                                     FlatSymbolRefAttr> {
 public:
   using Base::Base;
   void print(raw_ostream &os) const override {
-    os << "FlatSymbolRefProgramPoint(" << getValue() << ")";
+    os << "FlatSymbolRefLatticeAnchor(" << getValue() << ")";
   }
   Location getLoc() const override {
-    return UnknownLoc::get(getValue().getContext());
+    return UnknownLoc::get(getValue()->getContext());
   }
 };
 
@@ -84,7 +83,7 @@ static bool isUseTreatedWithValueSemantics(OpOperand &use) {
 /// State tracking if an IR construct is "safe".
 ///
 /// This state is tracked on Value's and also on global slots (via a
-/// FlatSymbolRefProgramPoint).
+/// FlatSymbolRefLatticeAnchor).
 ///
 /// In this context, "safe" means that the object is safe to inline.
 /// This covers a few concepts
@@ -93,7 +92,7 @@ static bool isUseTreatedWithValueSemantics(OpOperand &use) {
 ///   unsafe
 class InlineGlobalSlotsAnalysisState : public AnalysisState {
 public:
-  InlineGlobalSlotsAnalysisState(ProgramPoint point) : AnalysisState(point) {
+  InlineGlobalSlotsAnalysisState(LatticeAnchor point) : AnalysisState(point) {
     (void)setSafe();
   }
 
@@ -147,33 +146,33 @@ private:
 
 InlineGlobalSlotsAnalysis::InlineGlobalSlotsAnalysis(DataFlowSolver &solver)
     : DataFlowAnalysis(solver) {
-  registerPointKind<FlatSymbolRefProgramPoint>();
+  registerAnchorKind<FlatSymbolRefLatticeAnchor>();
 }
 
 LogicalResult InlineGlobalSlotsAnalysis::initialize(Operation *top) {
   auto walkResult = top->walk([this](Operation *op) {
     if (auto globalSlot = dyn_cast<Torch::GlobalSlotOp>(op)) {
       auto *state = getOrCreate<InlineGlobalSlotsAnalysisState>(
-          getProgramPoint<FlatSymbolRefProgramPoint>(
+          getLatticeAnchor<FlatSymbolRefLatticeAnchor>(globalSlot));
-              FlatSymbolRefAttr::get(globalSlot.getSymNameAttr())));
       propagateIfChanged(state,
                          state->setSafe(globalSlot.getVisibility() !=
                                         SymbolTable::Visibility::Public));
     }
     if (auto globalSlotSet = dyn_cast<Torch::GlobalSlotSetOp>(op)) {
+      auto globalSlot = SymbolTable::lookupNearestSymbolFrom<GlobalSlotOp>(
+          globalSlotSet, globalSlotSet.getSlotAttr());
+
       auto *state = getOrCreate<InlineGlobalSlotsAnalysisState>(
-          getProgramPoint<FlatSymbolRefProgramPoint>(
+          getLatticeAnchor<FlatSymbolRefLatticeAnchor>(globalSlot));
-              globalSlotSet.getSlotAttr()));
       propagateIfChanged(state, state->setSafe(false));
     }
     // Save the InitializeGlobalSlotsOp for later referencee
     if (auto initialize = dyn_cast<Torch::InitializeGlobalSlotsOp>(op)) {
       initializeGlobalSlotsOp = initialize;
     }
-    for (Value result : op->getResults()) {
+    if (failed(visit(op)))
-      if (failed(visit(result)))
+      return WalkResult::interrupt();
-        return WalkResult::interrupt();
+
-    }
     return WalkResult::advance();
   });
   if (walkResult.wasInterrupted())
@@ -182,50 +181,32 @@ LogicalResult InlineGlobalSlotsAnalysis::initialize(Operation *top) {
 }
 
 LogicalResult InlineGlobalSlotsAnalysis::visit(ProgramPoint point) {
-  if (Value value = dyn_cast<Value>(point)) {
+  if (auto op = dyn_cast<Operation *>(point)) {
-    bool isSafe = isValueSafeTransferFunction(value);
+    for (auto value : op->getResults()) {
-    auto *state = getOrCreate<InlineGlobalSlotsAnalysisState>(value);
+      bool isSafe = isValueSafeTransferFunction(value);
-    propagateIfChanged(state, state->setSafe(isSafe));
+      auto *state = getOrCreate<InlineGlobalSlotsAnalysisState>(value);
+      propagateIfChanged(state, state->setSafe(isSafe));
 
-    // Handle GlobalSlotGetOp's.
+      // Handle GlobalSlotGetOp's.
-    if (auto opResult = dyn_cast<OpResult>(value)) {
+      if (auto opResult = dyn_cast<OpResult>(value)) {
-      if (auto globalSlotGet =
+        if (auto globalSlotGet =
-              dyn_cast<Torch::GlobalSlotGetOp>(opResult.getOwner())) {
+                dyn_cast<Torch::GlobalSlotGetOp>(opResult.getOwner())) {
-        auto *flatSymbolRefPoint = getProgramPoint<FlatSymbolRefProgramPoint>(
+          auto globalSlot = SymbolTable::lookupNearestSymbolFrom<GlobalSlotOp>(
-            globalSlotGet.getSlotAttr());
+              globalSlotGet, globalSlotGet.getSlotAttr());
-        auto *valueState = getOrCreateFor<InlineGlobalSlotsAnalysisState>(
+          auto *flatSymbolRefPoint =
-            flatSymbolRefPoint, globalSlotGet.getResult());
+              getLatticeAnchor<FlatSymbolRefLatticeAnchor>(globalSlot);
-        auto *globalState =
+          auto *valueState = getOrCreateFor<InlineGlobalSlotsAnalysisState>(
-            getOrCreate<InlineGlobalSlotsAnalysisState>(flatSymbolRefPoint);
+              globalSlot, globalSlotGet.getResult());
-        propagateIfChanged(globalState,
+          auto *globalState =
-                           globalState->incorporateSafetyOfUse(valueState));
+              getOrCreate<InlineGlobalSlotsAnalysisState>(flatSymbolRefPoint);
+          propagateIfChanged(globalState,
+                             globalState->incorporateSafetyOfUse(valueState));
+        }
       }
     }
+  }
 
-    return success();
+  return success();
-  }
-  if (auto *genericProgramPoint = dyn_cast<GenericProgramPoint *>(point)) {
-    if (auto *flatSymbolRefPoint =
-            dyn_cast<FlatSymbolRefProgramPoint>(genericProgramPoint)) {
-      if (initializeGlobalSlotsOp) {
-        auto it =
-            llvm::find(initializeGlobalSlotsOp.getSlotSymNames(),
-                       static_cast<Attribute>(flatSymbolRefPoint->getValue()));
-        Value value = initializeGlobalSlotsOp->getOperand(std::distance(
-            initializeGlobalSlotsOp.getSlotSymNames().begin(), it));
-        auto *flatSymbolRefState =
-            getOrCreateFor<InlineGlobalSlotsAnalysisState>(value,
-                                                           flatSymbolRefPoint);
-        auto *valueState = getOrCreate<InlineGlobalSlotsAnalysisState>(value);
-        propagateIfChanged(valueState,
-                           valueState->setSafe(flatSymbolRefState->isSafe));
-      }
-      return success();
-    }
-  }
-  LLVM_DEBUG(
-      { llvm::dbgs() << "visit failing because of: " << point << "\n"; });
-  return failure();
 }
 
 // This is only a member function to access protected get* functions.
@@ -241,16 +222,20 @@ bool InlineGlobalSlotsAnalysis::isValueSafeTransferFunction(Value value) {
     // safe. This covers, for example, view-like ops that create aliases.
     if ((op->hasTrait<Torch::OpTrait::ReadOnly>() || isMemoryEffectFree(op)) &&
         llvm::all_of(op->getResults(), [&](Value result) {
-          auto *state =
+          auto *state = getOrCreateFor<InlineGlobalSlotsAnalysisState>(
-              getOrCreateFor<InlineGlobalSlotsAnalysisState>(value, result);
+              value.getDefiningOp(), result);
           return state->isSafe;
         }))
       continue;
     if (auto initialize = dyn_cast<Torch::InitializeGlobalSlotsOp>(op)) {
       auto symName = cast<FlatSymbolRefAttr>(
           initialize.getSlotSymNames()[use.getOperandNumber()]);
+      auto globalSlot =
+          SymbolTable::lookupNearestSymbolFrom<GlobalSlotOp>(op, symName);
+
       auto *state = getOrCreateFor<InlineGlobalSlotsAnalysisState>(
-          value, getProgramPoint<FlatSymbolRefProgramPoint>(symName));
+          value.getDefiningOp(),
+          getLatticeAnchor<FlatSymbolRefLatticeAnchor>(globalSlot));
       if (state->isSafe)
         continue;
     }
@@ -299,8 +284,7 @@ class InlineGlobalSlotsPass
       module->walk([&](Operation *op) {
         if (auto globalSlot = dyn_cast<Torch::GlobalSlotOp>(op)) {
           auto *state = solver.lookupState<InlineGlobalSlotsAnalysisState>(
-              solver.getProgramPoint<FlatSymbolRefProgramPoint>(
+              solver.getLatticeAnchor<FlatSymbolRefLatticeAnchor>(globalSlot));
-                  FlatSymbolRefAttr::get(globalSlot.getSymNameAttr())));
           state->print(llvm::dbgs());
           llvm::dbgs() << ": "
                        << FlatSymbolRefAttr::get(globalSlot.getSymNameAttr())
@@ -334,13 +318,16 @@ class InlineGlobalSlotsPass
       auto slotSymName =
           cast<FlatSymbolRefAttr>(initialize.getSlotSymNames()[i]);
       Value operand = initialize.getOperand(i);
-      auto symbolRefPoint = solver.getProgramPoint<FlatSymbolRefProgramPoint>(
+      auto globalSlot = SymbolTable::lookupNearestSymbolFrom<GlobalSlotOp>(
-          cast<FlatSymbolRefAttr>(initialize.getSlotSymNames()[i]));
+          initialize, slotSymName);
+
+      auto symbolRefPoint =
+          solver.getLatticeAnchor<FlatSymbolRefLatticeAnchor>(globalSlot);
       auto *state =
           solver.lookupState<InlineGlobalSlotsAnalysisState>(symbolRefPoint);
       // We roll the analysis of whether a slot is set or public into the
       // main dataflow analysis, so we need to check the slot's
-      // FlatSymbolRefProgramPoint itself to see if it is safe to inline.
+      // FlatSymbolRefLatticeAnchor itself to see if it is safe to inline.
       // For example, a public !torch.int is not safe to inline, even though
       // it is a value-semantic type and so the actual initializer value
       // itself is conceptually safe to inline.

test/Conversion/TorchToStablehlo/linear.mlir

@@ -259,7 +259,6 @@ func.func @torch.aten.mm$proj(%arg0: !torch.vtensor<[?,256],f32>) -> !torch.vten
 // CHECK:           %[[T_5:.*]] = torch.constant.int 1
 // CHECK:           %[[T_6:.*]] = torch.constant.int 4
 // CHECK:           %[[T_7:.*]] = torch.constant.int 3
-// CHECK:           %[[T_8:.*]] = arith.constant 3 : i64
 // CHECK:           %[[T_9:.*]] = torch.prim.ListConstruct %[[T_4]], %[[T_5]] : (!torch.int, !torch.int) -> !torch.list<int>
 // CHECK:           %[[T_10:.*]] = torch.prim.ListConstruct %[[T_6]], %[[T_4]] : (!torch.int, !torch.int) -> !torch.list<int>
 // CHECK:           %[[T_11:.*]] = torch.prim.ListConstruct %[[T_7]], %[[T_5]] : (!torch.int, !torch.int) -> !torch.list<int>
@@ -295,7 +294,6 @@ func.func @torch.aten.convolution(%arg0: !torch.vtensor<[?,?,?,?],f32>, %arg1: !
 // CHECK:           %int2 = torch.constant.int 2
 // CHECK:           %int1 = torch.constant.int 1
 // CHECK:           %int4 = torch.constant.int 4
-// CHECK:           %[[T_3:.*]] = arith.constant 3 : i64
 // CHECK:           %[[T_4:.*]] = torch.prim.ListConstruct %int2, %int1 : (!torch.int, !torch.int) -> !torch.list<int>
 // CHECK:           %[[T_5:.*]] = torch.prim.ListConstruct %int4, %int2 : (!torch.int, !torch.int) -> !torch.list<int>
 // CHECK:           %[[T_6:.*]] = torch.prim.ListConstruct %int3, %int1 : (!torch.int, !torch.int) -> !torch.list<int>
@@ -336,7 +334,6 @@ func.func @torch.aten.convolution$bias(%arg0: !torch.vtensor<[?,?,?,?],f32>, %ar
 // CHECK:           %none = torch.constant.none
 // CHECK:           %int0 = torch.constant.int 0
 // CHECK:           %int1 = torch.constant.int 1
-// CHECK:           %[[T_2:.*]] = arith.constant 1 : i64
 // CHECK:           %[[T_3:.*]] = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<int>
 // CHECK:           %[[T_4:.*]] = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<int>
 // CHECK:           %[[T_5:.*]] = stablehlo.transpose %[[T_1]], dims = [2, 3, 1, 0] : (tensor<2x4x3x3xf32>) -> tensor<3x3x4x2xf32>
@@ -367,7 +364,6 @@ func.func @torch.aten.convolution$transposed_basic(%arg0: !torch.vtensor<[1,2,7,
 // CHECK:           %none = torch.constant.none
 // CHECK:           %int0 = torch.constant.int 0
 // CHECK:           %int1 = torch.constant.int 1
-// CHECK:           %[[T_2:.*]] = arith.constant 1 : i64
 // CHECK:           %int2 = torch.constant.int 2
 // CHECK:           %[[T_3:.*]] = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<int>
 // CHECK:           %[[T_4:.*]] = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<int>
@@ -402,7 +398,6 @@ func.func @torch.aten.convolution$transposed_stride(%arg0: !torch.vtensor<[1,2,7
 // CHECK:           %none = torch.constant.none
 // CHECK:           %int0 = torch.constant.int 0
 // CHECK:           %int1 = torch.constant.int 1
-// CHECK:           %[[T_2:.*]] = arith.constant 1 : i64
 // CHECK:           %int2 = torch.constant.int 2
 // CHECK:           %[[T_3:.*]] = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<int>
 // CHECK:           %[[T_4:.*]] = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<int>
@@ -438,10 +433,6 @@ func.func @torch.aten.convolution$transposed_outputpadding(%arg0: !torch.vtensor
 // CHECK:           %int0 = torch.constant.int 0
 // CHECK:           %int1 = torch.constant.int 1
 // CHECK:           %int2 = torch.constant.int 2
-// CHECK:           %[[T_2:.*]] = arith.constant 2 : i64
-// CHECK:           %[[T_3:.*]] = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<int>
-// CHECK:           %[[T_4:.*]] = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<int>
-// CHECK:           %[[T_5:.*]] = torch.prim.ListConstruct %int2, %int2 : (!torch.int, !torch.int) -> !torch.list<int>
 // CHECK:           %[[T_6:.*]] = stablehlo.transpose %[[T_1]], dims = [2, 3, 1, 0] : (tensor<2x2x3x3xf32>) -> tensor<3x3x2x2xf32>
 // CHECK:           %[[T_7:.*]] = stablehlo.reverse %[[T_6]], dims = [0, 1] : tensor<3x3x2x2xf32>
 // CHECK:           %c0 = arith.constant 0 : index