[PT FE] aten::to extend op support for device tracing case (#15712)

src/frontends/pytorch/src/op/to.cpp

@@ -30,6 +30,13 @@ OutputVector translate_to(NodeContext& context) {
         // Input with index 1 is device we skip that input.
         dtype_idx = 2;
         memory_format_idx = 5;
+    } else if (context.get_input_size() == 8) {
+        // aten::to(Tensor(a) self, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool?
+        // pin_memory=None,
+        // bool non_blocking=False, bool copy=False, MemoryFormat? memory_format=None)
+        dtype_idx = 1;
+        memory_format_idx = 7;
+
     } else {
         FRONT_END_OP_CONVERSION_CHECK(false, "Unknown aten::to format");
     }

tests/layer_tests/pytorch_tests/test_to.py

@@ -91,3 +91,25 @@ class TestAtenTo(PytorchLayerTest):
         self.input_type = input_type
         with pytest.raises(OpConversionFailure) as e:
             self._test(*self.create_model(output_type, memory_format=memory_format), ie_device, precision, ir_version)
+
+
+class TestAtenToDevice(PytorchLayerTest):
+    def _prepare_input(self):
+        return (np.random.uniform(low=0.0, high=50.0, size=(3,)), np.random.uniform(low=0.0, high=50.0, size=(3,)))
+
+    def create_model(self):
+        import torch
+
+        class aten_to(torch.nn.Module):
+
+            def forward(self, x, y):
+                return x.to(y.device)
+
+        ref_net = None
+
+        return aten_to(), ref_net, "aten::to"
+
+    @pytest.mark.nightly
+    @pytest.mark.precommit
+    def test_aten_to_device(self, ie_device, precision, ir_version):
+        self._test(*self.create_model(), ie_device, precision, ir_version, trace_model=True)