Bump LLVM to llvm/llvm-project@6c64c8a6f3f7 (#3818)

- bumps llvm-project to
llvm/llvm-project@6c64c8a
- bumps stablehlo to
openxla/stablehlo@6e403b1
- Updates type conversion materialization functions to return Value
after API change in llvm-project.

---------

Signed-off-by: Max Dawkins <max.dawkins@gmail.com>

lib/Dialect/TorchConversion/Transforms/BackendTypeConversion.cpp

@@ -57,16 +57,16 @@ static void setupTorchBoolToI1Conversion(ConversionTarget &target,
   typeConverter.addConversion([](Torch::BoolType type) -> std::optional<Type> {
     return IntegerType::get(type.getContext(), 1);
   });
-  typeConverter.addTargetMaterialization(
-      [](OpBuilder &builder, IntegerType type, ValueRange inputs,
-         Location loc) -> std::optional<Value> {
-        // Other builtin integer types could be handled by other materializers.
-        if (!(type.getWidth() == 1 && type.isSignless()))
-          return std::nullopt;
-        assert(inputs.size() == 1);
-        assert(isa<Torch::BoolType>(inputs[0].getType()));
-        return builder.create<ToI1Op>(loc, inputs[0]).getResult();
-      });
+  typeConverter.addTargetMaterialization([](OpBuilder &builder,
+                                            IntegerType type, ValueRange inputs,
+                                            Location loc) -> Value {
+    // Other builtin integer types could be handled by other materializers.
+    if (!(type.getWidth() == 1 && type.isSignless()))
+      return Value();
+    assert(inputs.size() == 1);
+    assert(isa<Torch::BoolType>(inputs[0].getType()));
+    return builder.create<ToI1Op>(loc, inputs[0]).getResult();
+  });
   auto sourceMaterialization = [](OpBuilder &builder, Torch::BoolType type,
                                   ValueRange inputs, Location loc) -> Value {
     assert(inputs.size() == 1);
@@ -83,19 +83,19 @@ static void setupTorchIntToI64Conversion(ConversionTarget &target,
   typeConverter.addConversion([](Torch::IntType type) -> std::optional<Type> {
     return IntegerType::get(type.getContext(), 64);
   });
-  typeConverter.addTargetMaterialization(
-      [](OpBuilder &builder, IntegerType type, ValueRange inputs,
-         Location loc) -> std::optional<Value> {
-        // Other builtin integer types could be handled by other materializers.
-        if (!(type.getWidth() == 64 && type.isSignless()))
-          return std::nullopt;
-        // Other input type to be converted to i64 are handled by other
-        // materializers.
-        if (!isa<Torch::IntType>(inputs[0].getType()))
-          return std::nullopt;
-        assert(inputs.size() == 1);
-        return builder.createOrFold<ToI64Op>(loc, inputs[0]);
-      });
+  typeConverter.addTargetMaterialization([](OpBuilder &builder,
+                                            IntegerType type, ValueRange inputs,
+                                            Location loc) -> Value {
+    // Other builtin integer types could be handled by other materializers.
+    if (!(type.getWidth() == 64 && type.isSignless()))
+      return Value();
+    // Other input type to be converted to i64 are handled by other
+    // materializers.
+    if (!isa<Torch::IntType>(inputs[0].getType()))
+      return Value();
+    assert(inputs.size() == 1);
+    return builder.createOrFold<ToI64Op>(loc, inputs[0]);
+  });
   auto sourceMaterialization = [](OpBuilder &builder, Torch::IntType type,
                                   ValueRange inputs, Location loc) -> Value {
     assert(inputs.size() == 1);
@@ -112,13 +112,13 @@ static void setupTorchFloatToF64Conversion(ConversionTarget &target,
   typeConverter.addConversion([](Torch::FloatType type) -> std::optional<Type> {
     return Float64Type::get(type.getContext());
   });
-  typeConverter.addTargetMaterialization(
-      [](OpBuilder &builder, Float64Type type, ValueRange inputs,
-         Location loc) -> std::optional<Value> {
-        assert(inputs.size() == 1);
-        assert(isa<Torch::FloatType>(inputs[0].getType()));
-        return builder.create<ToF64Op>(loc, inputs[0]).getResult();
-      });
+  typeConverter.addTargetMaterialization([](OpBuilder &builder,
+                                            Float64Type type, ValueRange inputs,
+                                            Location loc) -> Value {
+    assert(inputs.size() == 1);
+    assert(isa<Torch::FloatType>(inputs[0].getType()));
+    return builder.create<ToF64Op>(loc, inputs[0]).getResult();
+  });
   auto sourceMaterialization = [](OpBuilder &builder, Torch::FloatType type,
                                   ValueRange inputs, Location loc) -> Value {
     assert(inputs.size() == 1);
@@ -137,19 +137,19 @@ static void setupTorchGeneratorToI64Conversion(ConversionTarget &target,
       [](Torch::GeneratorType type) -> std::optional<Type> {
         return IntegerType::get(type.getContext(), 64);
       });
-  typeConverter.addTargetMaterialization(
-      [](OpBuilder &builder, IntegerType type, ValueRange inputs,
-         Location loc) -> std::optional<Value> {
-        // Other builtin integer types could be handled by other materializers.
-        if (!(type.getWidth() == 64 && type.isSignless()))
-          return std::nullopt;
-        // Other input type to be converted to i64 are handled by other
-        // materializers.
-        if (!isa<Torch::GeneratorType>(inputs[0].getType()))
-          return std::nullopt;
-        assert(inputs.size() == 1);
-        return builder.create<GeneratorToI64Op>(loc, inputs[0]).getResult();
-      });
+  typeConverter.addTargetMaterialization([](OpBuilder &builder,
+                                            IntegerType type, ValueRange inputs,
+                                            Location loc) -> Value {
+    // Other builtin integer types could be handled by other materializers.
+    if (!(type.getWidth() == 64 && type.isSignless()))
+      return Value();
+    // Other input type to be converted to i64 are handled by other
+    // materializers.
+    if (!isa<Torch::GeneratorType>(inputs[0].getType()))
+      return Value();
+    assert(inputs.size() == 1);
+    return builder.create<GeneratorToI64Op>(loc, inputs[0]).getResult();
+  });
   auto sourceMaterialization = [](OpBuilder &builder, Torch::GeneratorType type,
                                   ValueRange inputs, Location loc) -> Value {
     assert(inputs.size() == 1);