build: update llvm tag to d2613d5b (#1343)

Summary of changes:
 - Update the dataflow analysis in RefineTypes.cpp
 - Add tosa-to-arith pass after tosa-to-linalg pass, since
   tosa-to-linalg (and canonicalizations) can produce tosa.const() ops
 - Fixed warning about not making `matchAndRewrite` as override

externals/llvm-project

@@ -1 +1 @@
-Subproject commit 00d648bdb5a8b71785269b4851b651c883de2cd9
+Subproject commit d2613d5bb5dca0624833e4747f67db6fe3236ce8

externals/mlir-hlo

@@ -1 +1 @@
-Subproject commit 305a2f25229660ea789bf70ed8e7336227f6228a
+Subproject commit 3bfb91e4ee44352f6620603078e2e2fc587d9a1e

lib/Conversion/TorchToMhlo/Linear.cpp

@@ -609,8 +609,9 @@ public:
     return mhloConvOp.getResult();
   }
 
-  LogicalResult matchAndRewrite(AtenConvolutionOp op, OpAdaptor adaptor,
-                                ConversionPatternRewriter &rewriter) const {
+  LogicalResult
+  matchAndRewrite(AtenConvolutionOp op, OpAdaptor adaptor,
+                  ConversionPatternRewriter &rewriter) const override {
     Value input = adaptor.input();
     Value weight = adaptor.weight();
 

lib/Dialect/Torch/Transforms/RefineTypes.cpp

@@ -383,6 +383,12 @@ public:
   void visitOperation(Operation *op, ArrayRef<const ValueState *> operands,
                       ArrayRef<ValueState *> results) final;
 
+  void setToEntryState(ValueState *lattice) override {
+    auto refType = lattice->getPoint().getType();
+    auto knowledge = ValueKnowledge::getKnowledgeFromType(refType);
+    propagateIfChanged(lattice, lattice->join(knowledge));
+  }
+
 private:
   // Get the MLIR type of the tensor dtype given the dtype integer value and the
   // input dtype. When DType is None the type is inferred from the input dtype.
@@ -1106,9 +1112,8 @@ void TypeAnalysis::visitOperation(Operation *op,
     return;
   }
 
-  // Otherwise, this is an unknown operation. Just mark all results as
-  // having reached a pessimistic fixpoint.
-  markAllPessimisticFixpoint(results);
+  // Otherwise, this is an unknown operation, so reset the state.
+  setAllToEntryStates(results);
   return;
 }
 

python/torch_mlir_e2e_test/tosa_backends/linalg_on_tensors.py

@@ -52,10 +52,13 @@ class LinalgOnTensorsTosaBackend(TosaBackend):
             "func.func(tosa-to-linalg-named)",
             "Lowering TOSA to Linalg-on-Tensors for Named Ops")
 
+        # TOSA-to-LinAlg may generate tosa.const() ops, so we want to lower them
+        # to arith.constants here before proceeding further.
         run_pipeline_with_repro_report(
             imported_module,
-            "func.func(tosa-to-linalg)",
+            "func.func(tosa-to-linalg),func.func(tosa-to-arith)",
             "Lowering TOSA to Linalg-on-Tensors")
+
         return self.refbackend.compile(imported_module)
 
     def load(self, module):