[OV20] InputTensorInfo::set_shape (#9059)

* InputTensorInfo::set_shape

* Fix clang-format

src/bindings/python/tests/test_ngraph/test_preprocess.py

@@ -201,6 +201,37 @@ def test_ngraph_preprocess_spatial_static_shape():
     assert np.equal(output, expected_output).all()
 
 
+def test_ngraph_preprocess_set_shape():
+    shape = [1, 1, 1]
+    parameter_a = ops.parameter(shape, dtype=np.int32, name="A")
+    model = parameter_a
+    function = Function(model, [parameter_a], "TestFunction")
+
+    @custom_preprocess_function
+    def custom_crop(out_node: Output):
+        start = ops.constant(np.array([1, 1, 1]), dtype=np.int32)
+        stop = ops.constant(np.array([2, 2, 2]), dtype=np.int32)
+        step = ops.constant(np.array([1, 1, 1]), dtype=np.int32)
+        axis = ops.constant(np.array([0, 1, 2]), dtype=np.int32)
+        return ops.slice(out_node, start, stop, step, axis)
+
+    p = PrePostProcessor(function)
+    inp = p.input()
+    inp.tensor().set_shape([3, 3, 3])
+    inp.preprocess().custom(custom_crop)
+    function = p.build()
+
+    input_data = np.array([[[0, 1, 2], [3, 4, 5], [6, 7, 8]],
+                           [[9, 10, 11], [12, 13, 14], [15, 16, 17]],
+                           [[18, 19, 20], [21, 22, 23], [24, 25, 26]]]).astype(np.int32)
+    expected_output = np.array([[[13]]]).astype(np.float32)
+
+    runtime = get_runtime()
+    computation = runtime.computation(function)
+    output = computation(input_data)
+    assert np.equal(output, expected_output).all()
+
+
 @pytest.mark.parametrize(
     "algorithm, color_format1, color_format2, is_failing",
     [(ResizeAlgorithm.RESIZE_LINEAR, ColorFormat.UNDEFINED, ColorFormat.BGR, True),