diff --git a/lib/Dialect/Torch/Transforms/DecomposeComplexOps.cpp b/lib/Dialect/Torch/Transforms/DecomposeComplexOps.cpp
index 2f276b1a2..6207e753e 100644
--- a/lib/Dialect/Torch/Transforms/DecomposeComplexOps.cpp
+++ b/lib/Dialect/Torch/Transforms/DecomposeComplexOps.cpp
@@ -2593,16 +2593,22 @@ public:
     // first the input tensor is flattened to 1d tensor and then the reduction
     // happens on the 0th dimension.
     if (isa<Torch::NoneType>(dim.getType())) {
-      BaseTensorType flattenType =
-          cast<BaseTensorType>(inputType.getWithSizesAndDtype(
-              {kUnknownSize}, inputType.getOptionalDtype()));
-      Value zero =
-          rewriter.create<ConstantIntOp>(loc, rewriter.getI64IntegerAttr(0));
-      Value end = rewriter.create<ConstantIntOp>(
-          loc, rewriter.getI64IntegerAttr(inputRank - 1));
+      Value zero = rewriter.create<ConstantIntOp>(loc, 0);
       Value falseValue = rewriter.create<ConstantBoolOp>(loc, false);
-      input = rewriter.create<AtenFlattenUsingIntsOp>(loc, flattenType, input,
-                                                      zero, end);
+      if (inputType.getSizes().size() > 1) {
+        int64_t flattenSize = Torch::kUnknownSize;
+        if (inputType.areAllSizesKnown()) {
+          flattenSize = 1;
+          for (int64_t sze : inputType.getSizes())
+            flattenSize *= sze;
+        }
+        auto flattenType = cast<BaseTensorType>(inputType.getWithSizesAndDtype(
+            {flattenSize}, inputType.getOptionalDtype()));
+        Value end = rewriter.create<ConstantIntOp>(
+            loc, rewriter.getI64IntegerAttr(inputRank - 1));
+        input = rewriter.create<AtenFlattenUsingIntsOp>(loc, flattenType, input,
+                                                        zero, end);
+      }
       Value resultIndices =
           rewriter
               .create<DecompOpTy>(
diff --git a/projects/pt1/e2e_testing/xfail_sets.py b/projects/pt1/e2e_testing/xfail_sets.py
index e0011b9a3..e8bdda1e6 100644
--- a/projects/pt1/e2e_testing/xfail_sets.py
+++ b/projects/pt1/e2e_testing/xfail_sets.py
@@ -545,10 +545,6 @@ FX_IMPORTER_CRASHING_SET = LINALG_CRASHING_SET | {
 
 FX_IMPORTER_STABLEHLO_XFAIL_SET = {
     "AddFloatIntModule_basic",
-    "ArgmaxIntModule_basic",
-    "ArgmaxIntModule_multiple_maxs",
-    "ArgmaxKeepdimModule_basic",
-    "ArgmaxModule_basic",
     "AtenKthvalueDynamicDimsModule_basic",
     "AtenKthvalueFloat64DynamicDimsModule_basic",
     "AtenKthvalueFloat64Module_basic",
@@ -618,9 +614,6 @@ FX_IMPORTER_STABLEHLO_XFAIL_SET = {
     "AnyBoolFalseModule_basic",
     "AnyBoolTrueModule_basic",
     "ArangeStartOutViewModule_basic",
-    "ArgminIntModule_basic",
-    "ArgminIntModule_multiple_mins",
-    "ArgminModule_basic",
     "AtenComplexImagModule_basic",
     "AtenComplexRealModule_basic",
     "AtenComplexViewModule_basic",
diff --git a/test/Dialect/Torch/decompose-complex-ops.mlir b/test/Dialect/Torch/decompose-complex-ops.mlir
index 4da482af0..c29635de6 100644
--- a/test/Dialect/Torch/decompose-complex-ops.mlir
+++ b/test/Dialect/Torch/decompose-complex-ops.mlir
@@ -25,6 +25,19 @@ func.func @matmul_decompose_3d(%arg0: !torch.vtensor<[?,?,?],f32>, %arg1: !torch
   return %0 : !torch.tensor
 }
 
+// -----
+// CHECK-LABEL: func.func @argmax_rank_1
+// CHECK:         %[[I0:.*]] = torch.constant.int 0
+// CHECK:         %[[FALSE:.*]] = torch.constant.bool false
+// CHECK:         %[[VALUES:.*]], %[[INDICES:.*]] = torch.aten.max.dim %arg0, %[[I0]], %[[FALSE]] : !torch.vtensor<[20],si32>, !torch.int, !torch.bool -> !torch.vtensor<[],si32>, !torch.vtensor<[],si64>
+// CHECK:         return %[[INDICES]] : !torch.vtensor<[],si64>
+func.func @argmax_rank_1(%arg0: !torch.vtensor<[20],si32>) -> !torch.vtensor<[],si64> {
+    %none = torch.constant.none
+    %false = torch.constant.bool false
+    %7 = torch.aten.argmax %arg0, %none, %false : !torch.vtensor<[20],si32>, !torch.none, !torch.bool -> !torch.vtensor<[],si64>
+    return %7 : !torch.vtensor<[],si64>
+}
+
 // -----
 // CHECK-LABEL:  func.func @torch.aten.type_as$basic(
 // CHECK-SAME:                                %[[ARG_0:.*]]: !torch.tensor, %[[ARG_1:.*]]: !torch.tensor) -> !torch.tensor {