Remove None at outputs of the model, improve types handling in frontend (#15258)

* Remove None at outputs of the model, improve types handling in frontend

* Fix py code style

* Add torch dependency in pybind tests

* Fix tests if fe is disabled and add backward type cpnversion

* Move decoder tests to layer tests

* Fix codestyle

* Add comment

* Move tests to separate folder

* Update .ci/azure/linux.yml

tests/layer_tests/pytorch_tests/test_tuple_construct.py

@@ -0,0 +1,45 @@
+# Copyright (C) 2018-2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+import pytest
+import numpy as np
+from pytorch_layer_test_class import PytorchLayerTest
+
+
+class TestTupleConstruct(PytorchLayerTest):
+    def _prepare_input(self):
+        return (np.random.uniform(0, 50, (1, 10)).astype(np.float32),)
+
+    def create_model(self, case):
+        import torch
+
+        class prim_tuple_construct_single_value(torch.nn.Module):
+
+            def forward(self, x):
+                return (x,)
+
+        class prim_tuple_construct(torch.nn.Module):
+
+            def forward(self, x):
+                return (x, x + x)
+
+        class prim_tuple_construct_with_none(torch.nn.Module):
+
+            def forward(self, x):
+                return (x, None, x + x, None)
+
+        cases = {
+            "single": prim_tuple_construct_single_value,
+            "multiple": prim_tuple_construct,
+            "none": prim_tuple_construct_with_none
+        }
+
+        ref_net = None
+        model = cases[case]
+
+        return model(), ref_net, "prim::TupleConstruct"
+
+    @pytest.mark.parametrize("case", ["single", "multiple", "none"])
+    @pytest.mark.nightly
+    def test_tuple_construct(self, case, ie_device, precision, ir_version):
+        self._test(*self.create_model(case), ie_device, precision, ir_version)