diff --git a/lib/Conversion/TorchToTosa/TorchToTosa.cpp b/lib/Conversion/TorchToTosa/TorchToTosa.cpp
index ed2726fa1b42..779bd6249283 100644
--- a/lib/Conversion/TorchToTosa/TorchToTosa.cpp
+++ b/lib/Conversion/TorchToTosa/TorchToTosa.cpp
@@ -2766,21 +2766,23 @@ LogicalResult ConvertAtenOp<AtenPermuteOp>::matchAndRewrite(
         op,
         "Only ranked tensor types with static shapes are currently supported");
 
-  SmallVector<int64_t> dimListInt;
-  if (!matchPattern(adaptor.getDims(), m_TorchListOfConstantInts(dimListInt)))
+  SmallVector<int64_t> dimListInt64;
+  if (!matchPattern(adaptor.getDims(), m_TorchListOfConstantInts(dimListInt64)))
     return rewriter.notifyMatchFailure(
         op, "Only constant dimensions are currently supported");
+  SmallVector<int32_t> dimListInt32;
+  copy(dimListInt64, std::back_inserter(dimListInt32));
 
   int64_t selfRank = selfType.getRank();
   // TODO: If this is already verified on the op then we can drop checking here.
-  for (auto &d : dimListInt) {
+  for (auto &d : dimListInt32) {
     d = toPositiveDim(d, selfRank);
     if (!isValidDim(d, selfRank))
       return rewriter.notifyMatchFailure(op, "Not all dims are valid");
   }
 
-  auto transposeDimsConst = mlir::tosa::getConstTensor<int64_t>(
-      rewriter, op.getOperation(), dimListInt, {selfRank});
+  auto transposeDimsConst = mlir::tosa::getConstTensor<int32_t>(
+      rewriter, op.getOperation(), dimListInt32, {selfRank});
 
   rewriter.replaceOpWithNewOp<tosa::TransposeOp>(
       op, getTypeConverter()->convertType(op.getType()), adaptor.getSelf(),
diff --git a/test/Conversion/TorchToTosa/basic.mlir b/test/Conversion/TorchToTosa/basic.mlir
index eb852f6c76b2..7d046177fc14 100644
--- a/test/Conversion/TorchToTosa/basic.mlir
+++ b/test/Conversion/TorchToTosa/basic.mlir
@@ -797,8 +797,8 @@ func.func @torch.aten.ne.Tensor$basic(%arg0: !torch.vtensor<[?,?],f32>, %arg1: !
 // CHECK:           %[[VAL_3:.*]] = torch.constant.int 2
 // CHECK:           %[[VAL_4:.*]] = torch.constant.int 0
 // CHECK:           %[[VAL_5:.*]] = torch.prim.ListConstruct %[[VAL_4]], %[[VAL_3]], %[[VAL_2]] : (!torch.int, !torch.int, !torch.int) -> !torch.list<int>
-// CHECK:           %[[VAL_6:.*]] = "tosa.const"() <{value = dense<[0, 2, 1]> : tensor<3xi64>}> : () -> tensor<3xi64>
-// CHECK:           %[[VAL_7:.*]] = tosa.transpose %[[VAL_1]], %[[VAL_6]] : (tensor<3x4x2xf32>, tensor<3xi64>) -> tensor<3x2x4xf32>
+// CHECK:           %[[VAL_6:.*]] = "tosa.const"() <{value = dense<[0, 2, 1]> : tensor<3xi32>}> : () -> tensor<3xi32>
+// CHECK:           %[[VAL_7:.*]] = tosa.transpose %[[VAL_1]], %[[VAL_6]] : (tensor<3x4x2xf32>, tensor<3xi32>) -> tensor<3x2x4xf32>
 // CHECK:           %[[VAL_8:.*]] = torch_c.from_builtin_tensor %[[VAL_7]] : tensor<3x2x4xf32> -> !torch.vtensor<[3,2,4],f32>
 // CHECK:           return %[[VAL_8]] : !torch.vtensor<[3,2,4],f32>
 // CHECK:         }