[Torch Dialect] add fold pattern for aten.clone

include/torch-mlir/Dialect/Torch/IR/GeneratedTorchOps.td

@@ -9101,6 +9101,7 @@ def Torch_AtenCloneOp : Torch_Op<"aten.clone", [
       printDefaultTorchOp(printer, *this, 2, 1);
     }
   }];
+  let hasFolder = 1;
 }
 
 def Torch_AtenLiftFreshCopyOp : Torch_Op<"aten.lift_fresh_copy", [

lib/Conversion/TorchToStablehlo/Basic.cpp

@@ -1763,7 +1763,6 @@ void mlir::torch::torch_to_stablehlo::populateBasicOpPatternsAndLegality(
 #define INSERT_UNARY_PATTERN(AtenOp, StablehloOp)                              \
   target.addIllegalOp<AtenOp>();                                               \
   patterns.add<ConvertAtenUnaryOp<AtenOp, StablehloOp>>(typeConverter, context)
-  INSERT_UNARY_PATTERN(AtenCloneOp, stablehlo::ConvertOp);
   INSERT_UNARY_PATTERN(AtenNegOp, stablehlo::NegOp);
   INSERT_UNARY_PATTERN(AtenLogicalNotOp, stablehlo::NotOp);
   INSERT_UNARY_PATTERN(AtenBitwiseNotOp, stablehlo::NotOp);

lib/Dialect/Torch/IR/TorchOps.cpp

@@ -1658,6 +1658,19 @@ void AtenMaskedFillTensorOp::getCanonicalizationPatterns(
   });
 }
 
+//===----------------------------------------------------------------------===//
+// AtenCloneOp
+//===----------------------------------------------------------------------===//
+
+OpFoldResult AtenCloneOp::fold(FoldAdaptor adaptor) {
+  // note: memory_format would be ignored
+  if (llvm::dyn_cast<ValueTensorType>(getSelf().getType())) {
+    // self should have value semantics
+    return getSelf();
+  }
+  return {};
+}
+
 //===----------------------------------------------------------------------===//
 // AtenSortIntOp
 //===----------------------------------------------------------------------===//

projects/pt1/e2e_testing/xfail_sets.py

@@ -1020,6 +1020,7 @@
     "BroadcastZeroRankInputStaticModule_basic",
     "BucketizeTensorStaticFloatModule_basic",
     "BucketizeTensorStaticModule_basic",
+    "CloneModule_basic",
     "ChunkListUnpackUneven_Module_basic",
     "ChunkListUnpack_Module_basic",
     "ConstantBoolParameterModule_basic",

projects/pt1/python/torch_mlir/jit_ir_importer/build_tools/torch_ods_gen.py

@@ -592,7 +592,7 @@ def emit_with_mutating_variants(key, **kwargs):
     emit("aten::one_hot : (Tensor, int) -> (Tensor)")
     emit("aten::einsum : (str, Tensor[], int[]?) -> (Tensor)")
     emit("aten::bucketize.Tensor : (Tensor, Tensor, bool, bool) -> (Tensor)")
-    emit("aten::clone : (Tensor, int?) -> (Tensor)")
+    emit("aten::clone : (Tensor, int?) -> (Tensor)", has_folder=True)
     emit("aten::lift_fresh_copy : (Tensor) -> (Tensor)")
     emit("aten::contiguous : (Tensor, int) -> (Tensor)")
     emit_with_mutating_variants("aten::copy : (Tensor, Tensor, bool) -> (Tensor)")

projects/pt1/python/torch_mlir_e2e_test/test_suite/basic.py

@@ -4994,3 +4994,23 @@ def forward(self, x):
 @register_test_case(module_factory=lambda: IscloseStaticModuleTrue())
 def IscloseStaticModuleTrue_basic(module, tu: TestUtils):
     module.forward(torch.ones(5, 5))
+
+
+# ==============================================================================
+
+class CloneModule(torch.nn.Module):
+
+    def __init__(self):
+        super().__init__()
+
+    @export
+    @annotate_args([
+        None,
+        ([5, 5], torch.float32, True),
+    ])
+    def forward(self, x):
+        return torch.ops.aten.clone(x)
+
+@register_test_case(module_factory=lambda: CloneModule())
+def CloneModule_basic(module, tu: TestUtils):
+    module.forward(tu.rand(5, 5))

test/Conversion/TorchToStablehlo/basic.mlir

@@ -1,21 +1,6 @@
 // RUN: torch-mlir-opt <%s -convert-torch-to-stablehlo -split-input-file -verify-diagnostics | FileCheck %s
 
 
-// -----
-
-// CHECK-LABEL:  func.func @torch.aten.clone$basic(
-// CHECK-SAME:         %[[ARG0:.*]]: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[?,?],f32> {
-// CHECK:         %[[T0:.*]] = torch_c.to_builtin_tensor %[[ARG0]] : !torch.vtensor<[?,?],f32> -> tensor<?x?xf32>
-// CHECK:         %[[NONE:.*]] = torch.constant.none
-// CHECK:         %[[T1:.*]] = stablehlo.convert %[[T0]] : tensor<?x?xf32>
-// CHECK:         %[[T2:.*]] = torch_c.from_builtin_tensor %[[T1]] : tensor<?x?xf32> -> !torch.vtensor<[?,?],f32>
-// CHECK:         return %[[T2]] : !torch.vtensor<[?,?],f32>
-func.func @torch.aten.clone$basic(%arg0: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[?,?],f32> {
-  %none = torch.constant.none
-  %0 = torch.aten.clone %arg0, %none : !torch.vtensor<[?,?],f32>, !torch.none -> !torch.vtensor<[?,?],f32>
-  return %0 : !torch.vtensor<[?,?],f32>
-}
-
 // -----
 
 // CHECK-LABEL:   func.func @torch.vtensor.literal$basic() -> !torch.vtensor<[],f32> {