Drop torch attributes at the end of backend conversion. (#2876)

Fixes https://github.com/llvm/torch-mlir/issues/2866

Some backends / downstream projects expect that a "fully converted"
program has no remaining ops or attributes from the original dialect(s).

lib/Dialect/TorchConversion/Transforms/BackendTypeConversionPasses.cpp

@@ -115,6 +115,21 @@ static void setupFinalization(ConversionTarget &target,
   setupFinalization<OpTy2, OpTys...>(target, patterns, typeConverter);
 }
 
+static void stripTorchAttrs(func::FuncOp func) {
+  bool modified = false;
+  SmallVector<NamedAttribute> newAttrs;
+  for (auto attr : func->getDialectAttrs()) {
+    if (attr.getName().getValue().starts_with("torch."))
+      modified = true;
+    else
+      newAttrs.push_back(attr);
+  }
+  if (modified)
+    func->setDialectAttrs(newAttrs);
+
+  // Note: this could also strip "arg" and "result" attrs if they were used.
+}
+
 namespace {
 struct FinalizingBackendTypeConversionPass
     : public FinalizingBackendTypeConversionBase<
@@ -151,6 +166,9 @@ struct FinalizingBackendTypeConversionPass
 
     if (failed(applyFullConversion(func, target, std::move(patterns))))
       signalPassFailure();
+
+    // Drop attributes that are no longer used after conversion out of Torch.
+    stripTorchAttrs(func);
   }
 };
 } // namespace

test/Conversion/TorchToLinalg/basic.mlir

@@ -30,7 +30,7 @@ func.func @torch.aten.mm$basic(%arg0: !torch.vtensor<[?,?],f32>, %arg1: !torch.v
 // -----
 
 // CHECK-LABEL: func.func @torch.aten.matmul.2d
-func.func @torch.aten.matmul.2d(%arg0: !torch.vtensor<[8,16],f32>, %arg1: !torch.vtensor<[16,8],f32>) -> !torch.vtensor<[8,8],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+func.func @torch.aten.matmul.2d(%arg0: !torch.vtensor<[8,16],f32>, %arg1: !torch.vtensor<[16,8],f32>) -> !torch.vtensor<[8,8],f32> {
   // CHECK-DAG:  %[[LHS:.+]] = torch_c.to_builtin_tensor %arg0 : !torch.vtensor<[8,16],f32> -> tensor<8x16xf32>
   // CHECK-DAG:  %[[RHS:.+]] = torch_c.to_builtin_tensor %arg1 : !torch.vtensor<[16,8],f32> -> tensor<16x8xf32>
   // CHECK-DAG:  %[[ZERO:.+]] = arith.constant 0.000000e+00 : f32

test/Dialect/TorchConversion/finalizing-backend-type-conversion.mlir

@@ -54,6 +54,20 @@ func.func @eliminate_materializations$torch.Generator(%arg0: i64) -> i64 {
 
 // -----
 
+// CHECK-LABEL:   func.func @eliminate_attributes()
+// CHECK-NOT: attributes
+// CHECK-NOT: torch.onnx_meta
+func.func @eliminate_attributes() attributes {
+  torch.onnx_meta.ir_version = 8 : si64,
+  torch.onnx_meta.opset_version = 17 : si64,
+  torch.onnx_meta.producer_name = "pytorch",
+  torch.onnx_meta.producer_version = "2.1.0"
+} {
+  return
+}
+
+// -----
+
 func.func @unable_to_convert_lone_buffer_cast() -> tensor<f32> {
   // expected-error @+1 {{failed to legalize operation 'test.source'}}
   %0 = "test.source"() : () -> !torch.vtensor<[],f32>