Add support for concating lists in aten::add (#15587)

src/frontends/pytorch/src/op/add.cpp

@@ -5,6 +5,7 @@
 #include "openvino/op/add.hpp"
 
 #include "openvino/frontend/pytorch/node_context.hpp"
+#include "openvino/op/concat.hpp"
 #include "openvino/op/convert_like.hpp"
 #include "openvino/op/multiply.hpp"
 #include "utils.hpp"
@@ -17,6 +18,13 @@ namespace op {
 OutputVector translate_add(NodeContext& context) {
     auto lhs = context.get_input(0);
     auto rhs = context.get_input(1);
+    auto dtype0 = context.get_input_type(0);
+    auto dtype1 = context.get_input_type(1);
+    if (dtype0.is<type::List>() && dtype1.is<type::List>()) {
+        // aten::add.t(t[] a, t[] b) -> t[]
+        // Case when two lists gets concatenated
+        return {context.mark_node(std::make_shared<ov::op::v0::Concat>(OutputVector{lhs, rhs}, 0))};
+    }
     align_eltwise_input_types(context, lhs, rhs);
     if (!context.input_is_none(2)) {
         auto converted_alpha = context.mark_node(std::make_shared<ov::op::v1::ConvertLike>(context.get_input(2), rhs));

tests/layer_tests/pytorch_tests/test_add.py

@@ -100,3 +100,20 @@ class TestAddTypes(PytorchLayerTest):
         self.rhs_shape = rhs_shape
         self._test(*self.create_model(lhs_type, lhs_shape, rhs_type, rhs_shape),
                    ie_device, precision, ir_version)
+
+class TestAddLists(PytorchLayerTest):
+
+    def _prepare_input(self):
+        return (np.random.randn(2, 5, 3, 4).astype(np.float32),)
+
+    def create_model(self):
+        class aten_add(torch.nn.Module):
+            def forward(self, x):
+                return x.reshape(x.shape[:-1] + (-1,))
+
+        return aten_add(), None, "aten::add"
+
+    @pytest.mark.nightly
+    @pytest.mark.precommit
+    def test_add(self, ie_device, precision, ir_version):
+        self._test(*self.create_model(), ie_device, precision, ir_version)