[Py OV] Update .runtime in strings (#28479)

### Details:
 - Update docstrings
 - Update tests that rely on them
- Update `py::module_::import("openvino.runtime").attr("Model")` e.g.
[here](https://github.com/openvinotoolkit/openvino/blob/9d77a3da11f0dbdb72cbd412c06a1da5e0e47ef0/src/bindings/python/src/pyopenvino/graph/attribute_visitor.cpp#L38)

### Tickets:
 - *ticket-id*

---------

Signed-off-by: Alicja Miloszewska <alicja.miloszewska@intel.com>

src/bindings/python/src/openvino/_ov_api.py

@@ -63,13 +63,13 @@ def clone(self) -> "Model":
         return Model(self.__model.clone())
 
     def __copy__(self) -> "Model":
-        raise TypeError("Cannot copy 'openvino.runtime.Model'. Please, use deepcopy instead.")
+        raise TypeError("Cannot copy 'openvino.Model'. Please, use deepcopy instead.")
 
     def __deepcopy__(self, memo: Dict) -> "Model":
         """Returns a deepcopy of Model.
 
         :return: A copy of Model.
-        :rtype: openvino.runtime.Model
+        :rtype: openvino.Model
         """
         return Model(self.__model.clone())
 
@@ -108,14 +108,14 @@ def infer(
 
         (1) `int`
         (2) `str`
-        (3) `openvino.runtime.ConstOutput`
+        (3) `openvino.ConstOutput`
 
         The allowed types of values in the `inputs` are:
 
         (1) `numpy.ndarray` and all the types that are castable to it, e.g. `torch.Tensor`
-        (2) `openvino.runtime.Tensor`
+        (2) `openvino.Tensor`
 
-        Can be called with only one `openvino.runtime.Tensor` or `numpy.ndarray`,
+        Can be called with only one `openvino.Tensor` or `numpy.ndarray`,
         it will work only with one-input models. When model has more inputs,
         function throws error.
 
@@ -190,14 +190,14 @@ def start_async(
 
         (1) `int`
         (2) `str`
-        (3) `openvino.runtime.ConstOutput`
+        (3) `openvino.ConstOutput`
 
         The allowed types of values in the `inputs` are:
 
         (1) `numpy.ndarray` and all the types that are castable to it, e.g. `torch.Tensor`
-        (2) `openvino.runtime.Tensor`
+        (2) `openvino.Tensor`
 
-        Can be called with only one `openvino.runtime.Tensor` or `numpy.ndarray`,
+        Can be called with only one `openvino.Tensor` or `numpy.ndarray`,
         it will work only with one-input models. When model has more inputs,
         function throws error.
 
@@ -241,7 +241,7 @@ def get_compiled_model(self) -> "CompiledModel":
         """Gets the compiled model this InferRequest is using.
 
         :return: a CompiledModel object
-        :rtype: openvino.runtime.ie_api.CompiledModel
+        :rtype: openvino.CompiledModel
         """
         return CompiledModel(super().get_compiled_model())
 
@@ -250,7 +250,7 @@ def results(self) -> OVDict:
         """Gets all outputs tensors of this InferRequest.
 
         :return: Dictionary of results from output tensors with ports as keys.
-        :rtype: Dict[openvino.runtime.ConstOutput, numpy.array]
+        :rtype: Dict[openvino.ConstOutput, numpy.array]
         """
         return OVDict(super().results)
 
@@ -277,15 +277,15 @@ def create_infer_request(self) -> InferRequest:
         The created request has allocated input and output tensors.
 
         :return: New InferRequest object.
-        :rtype: openvino.runtime.InferRequest
+        :rtype: openvino.InferRequest
         """
         return InferRequest(super().create_infer_request())
 
     def query_state(self) -> None:
         """Gets state control interface for the underlaying infer request.
 
         :return: List of VariableState objects.
-        :rtype: List[openvino.runtime.VariableState]
+        :rtype: List[openvino.VariableState]
         """
         if self._infer_request is None:
             self._infer_request = self.create_infer_request()
@@ -316,14 +316,14 @@ def infer_new_request(self, inputs: Any = None) -> OVDict:
 
         (1) `int`
         (2) `str`
-        (3) `openvino.runtime.ConstOutput`
+        (3) `openvino.ConstOutput`
 
         The allowed types of values in the `inputs` are:
 
         (1) `numpy.ndarray` and all the types that are castable to it, e.g. `torch.Tensor`
-        (2) `openvino.runtime.Tensor`
+        (2) `openvino.Tensor`
 
-        Can be called with only one `openvino.runtime.Tensor` or `numpy.ndarray`,
+        Can be called with only one `openvino.Tensor` or `numpy.ndarray`,
         it will work only with one-input models. When model has more inputs,
         function throws error.
 
@@ -361,14 +361,14 @@ def __call__(
 
         (1) `int`
         (2) `str`
-        (3) `openvino.runtime.ConstOutput`
+        (3) `openvino.ConstOutput`
 
         The allowed types of values in the `inputs` are:
 
         (1) `numpy.ndarray` and all the types that are castable to it, e.g. `torch.Tensor`
-        (2) `openvino.runtime.Tensor`
+        (2) `openvino.Tensor`
 
-        Can be called with only one `openvino.runtime.Tensor` or `numpy.ndarray`,
+        Can be called with only one `openvino.Tensor` or `numpy.ndarray`,
         it will work only with one-input models. When model has more inputs,
         function throws error.
 
@@ -448,7 +448,7 @@ def __iter__(self) -> Iterable[InferRequest]:
         will put the parent AsyncInferQueue object in an invalid state.
 
         :return: a generator that yields InferRequests.
-        :rtype: Iterable[openvino.runtime.InferRequest]
+        :rtype: Iterable[openvino.InferRequest]
         """
         return (InferRequest(x) for x in super().__iter__())
 
@@ -462,7 +462,7 @@ def __getitem__(self, i: int) -> InferRequest:
         :param i:  InferRequest id.
         :type i: int
         :return: InferRequests from the pool with given id.
-        :rtype: openvino.runtime.InferRequest
+        :rtype: openvino.InferRequest
         """
         return InferRequest(super().__getitem__(i))
 
@@ -478,14 +478,14 @@ def start_async(
 
         (1) `int`
         (2) `str`
-        (3) `openvino.runtime.ConstOutput`
+        (3) `openvino.ConstOutput`
 
         The allowed types of values in the `inputs` are:
 
         (1) `numpy.ndarray` and all the types that are castable to it, e.g. `torch.Tensor`
-        (2) `openvino.runtime.Tensor`
+        (2) `openvino.Tensor`
 
-        Can be called with only one `openvino.runtime.Tensor` or `numpy.ndarray`,
+        Can be called with only one `openvino.Tensor` or `numpy.ndarray`,
         it will work only with one-input models. When model has more inputs,
         function throws error.
 
@@ -574,7 +574,7 @@ def compile_model(
 
         :param model: Model acquired from read_model function or a path to a model in IR / ONNX / PDPD /
                       TF and TFLite format.
-        :type model: Union[openvino.runtime.Model, str, pathlib.Path]
+        :type model: Union[openvino.Model, str, pathlib.Path]
         :param device_name: Optional. Name of the device to load the model to. If not specified,
                             the default OpenVINO device will be selected by AUTO plugin.
         :type device_name: str
@@ -584,7 +584,7 @@ def compile_model(
         :param weights: Optional. Weights of model in memory to be loaded to the model.
         :type weights: bytes, optional, keyword-only
         :return: A compiled model.
-        :rtype: openvino.runtime.CompiledModel
+        :rtype: openvino.CompiledModel
         """
         if isinstance(model, Model):
             model = model._Model__model
@@ -635,7 +635,7 @@ def import_model(
                        (property name, property value) relevant only for this load operation.
         :type config: dict, optional
         :return: A compiled model.
-        :rtype: openvino.runtime.CompiledModel
+        :rtype: openvino.CompiledModel
 
         :Example:
 
@@ -680,15 +680,15 @@ def compile_model(
 
     :param model: Model acquired from read_model function or a path to a model in IR / ONNX / PDPD /
                     TF and TFLite format.
-    :type model: Union[openvino.runtime.Model, str, pathlib.Path]
+    :type model: Union[openvino.Model, str, pathlib.Path]
     :param device_name: Optional. Name of the device to load the model to. If not specified,
                         the default OpenVINO device will be selected by AUTO plugin.
     :type device_name: str
     :param config: Optional dict of pairs:
                     (property name, property value) relevant only for this load operation.
     :type config: dict, optional
     :return: A compiled model.
-    :rtype: openvino.runtime.CompiledModel
+    :rtype: openvino.CompiledModel
 
     """
     core = Core()

src/bindings/python/src/openvino/helpers/packing.py

@@ -21,7 +21,7 @@ def pack_data(array: np.ndarray, type: Type) -> np.ndarray:
     :param array: numpy array with values to pack.
     :type array: numpy array
     :param type: Type to interpret the array values. Type must be u1, u4, i4, nf4 or f4e2m1.
-    :type type: openvino.runtime.Type
+    :type type: openvino.Type
     """
     assert type in [Type.u1, Type.u4, Type.i4, Type.nf4, Type.f4e2m1], "Packing algorithm for the" "data types stored in 1, 2 or 4 bits"
 
@@ -58,9 +58,9 @@ def unpack_data(array: np.ndarray, type: Type, shape: Union[list, Shape]) -> np.
     :param array: numpy array to unpack.
     :type array: numpy array
     :param type: Type to extract from array values. Type must be u1, u4, i4, nf4 or f4e2m1.
-    :type type: openvino.runtime.Type
+    :type type: openvino.Type
     :param shape: the new shape for the unpacked array.
-    :type shape: Union[list, openvino.runtime.Shape]
+    :type shape: Union[list, openvino.Shape]
     """
     assert type in [Type.u1, Type.u4, Type.i4, Type.nf4, Type.f4e2m1], "Unpacking algorithm for the" "data types stored in 1, 2 or 4 bits"
     unpacked = np.unpackbits(array.view(np.uint8))

src/bindings/python/src/openvino/utils/data_helpers/wrappers.py

@@ -36,7 +36,7 @@ class OVDict(Mapping):
     This class is a dict-like object. It provides possibility to
     address data tensors with three key types:
 
-    * `openvino.runtime.ConstOutput` - port of the output
+    * `openvino.ConstOutput` - port of the output
     * `int` - index of the output
     * `str` - names of the output
 

src/bindings/python/src/pyopenvino/core/async_infer_queue.cpp

@@ -166,7 +166,7 @@ class AsyncInferQueue {
 
 void regclass_AsyncInferQueue(py::module m) {
     py::class_<AsyncInferQueue, std::shared_ptr<AsyncInferQueue>> cls(m, "AsyncInferQueue");
-    cls.doc() = "openvino.runtime.AsyncInferQueue represents a helper that creates a pool of asynchronous"
+    cls.doc() = "openvino.AsyncInferQueue represents a helper that creates a pool of asynchronous"
                 "InferRequests and provides synchronization functions to control flow of a simple pipeline.";
 
     cls.def(py::init<ov::CompiledModel&, size_t>(),
@@ -176,11 +176,11 @@ void regclass_AsyncInferQueue(py::module m) {
                 Creates AsyncInferQueue.
 
                 :param model: Model to be used to create InferRequests in a pool.
-                :type model: openvino.runtime.CompiledModel
+                :type model: openvino.CompiledModel
                 :param jobs: Number of InferRequests objects in a pool. If 0, jobs number
                 will be set automatically to the optimal number. Default: 0
                 :type jobs: int
-                :rtype: openvino.runtime.AsyncInferQueue
+                :rtype: openvino.AsyncInferQueue
             )");
 
     // Overload for single input, it will throw error if a model has more than one input.
@@ -216,7 +216,7 @@ void regclass_AsyncInferQueue(py::module m) {
 
             :param inputs: Data to set on single input tensor of next available InferRequest from
             AsyncInferQueue's pool.
-            :type inputs: openvino.runtime.Tensor
+            :type inputs: openvino.Tensor
             :param userdata: Any data that will be passed to a callback
             :type userdata: Any
             :rtype: None
@@ -262,7 +262,7 @@ void regclass_AsyncInferQueue(py::module m) {
 
             :param inputs: Data to set on input tensors of next available InferRequest from
             AsyncInferQueue's pool.
-            :type inputs: dict[Union[int, str, openvino.runtime.ConstOutput] : openvino.runtime.Tensor]
+            :type inputs: dict[Union[int, str, openvino.ConstOutput] : openvino.Tensor]
             :param userdata: Any data that will be passed to a callback
             :rtype: None
 
@@ -348,7 +348,7 @@ void regclass_AsyncInferQueue(py::module m) {
         :param i: InferRequest id
         :type i: int
         :return: InferRequests from the pool with given id.
-        :rtype: openvino.runtime.InferRequest
+        :rtype: openvino.InferRequest
     )");
 
     cls.def_property_readonly(

src/bindings/python/src/pyopenvino/core/common.cpp

@@ -578,7 +578,7 @@ ov::PartialShape partial_shape_from_list(const py::list& shape) {
         } else {
             throw py::type_error("Incorrect type " + std::string(py::str(dim.get_type())) +
                                  " for dimension. Expected types are: "
-                                 "int, str, openvino.runtime.Dimension, list/tuple with lower and upper values for "
+                                 "int, str, openvino.Dimension, list/tuple with lower and upper values for "
                                  "dynamic dimension.");
         }
     }

src/bindings/python/src/pyopenvino/core/compiled_model.cpp

@@ -16,7 +16,7 @@ namespace py = pybind11;
 
 void regclass_CompiledModel(py::module m) {
     py::class_<ov::CompiledModel, std::shared_ptr<ov::CompiledModel>> cls(m, "CompiledModel");
-    cls.doc() = "openvino.runtime.CompiledModel represents Model that is compiled for a specific device by applying "
+    cls.doc() = "openvino.CompiledModel represents Model that is compiled for a specific device by applying "
                 "multiple optimization transformations, then mapping to compute kernels.";
 
     cls.def(py::init([](ov::CompiledModel& other) {
@@ -40,7 +40,7 @@ void regclass_CompiledModel(py::module m) {
             The created request has allocated input and output tensors.
 
             :return: New InferRequest object.
-            :rtype: openvino.runtime.InferRequest
+            :rtype: openvino.InferRequest
         )");
 
     cls.def(
@@ -174,7 +174,7 @@ void regclass_CompiledModel(py::module m) {
                 is optimized and which kernels, element types, and layouts are selected.
 
                 :return: Model, containing Executable Graph information.
-                :rtype: openvino.runtime.Model
+                :rtype: openvino.Model
             )");
 
     cls.def("release_memory",
@@ -193,7 +193,7 @@ void regclass_CompiledModel(py::module m) {
                                 Gets all inputs of a compiled model.
 
                                 :return: Inputs of a compiled model.
-                                :rtype: List[openvino.runtime.ConstOutput]
+                                :rtype: List[openvino.ConstOutput]
                               )");
 
     cls.def("input",
@@ -203,7 +203,7 @@ void regclass_CompiledModel(py::module m) {
                 If a model has more than one input, this method throws an exception.
 
                 :return: A compiled model input.
-                :rtype: openvino.runtime.ConstOutput
+                :rtype: openvino.ConstOutput
             )");
 
     cls.def("input",
@@ -216,7 +216,7 @@ void regclass_CompiledModel(py::module m) {
                 :param index: An input index.
                 :type index: int
                 :return: A compiled model input.
-                :rtype: openvino.runtime.ConstOutput
+                :rtype: openvino.ConstOutput
             )");
 
     cls.def(
@@ -230,7 +230,7 @@ void regclass_CompiledModel(py::module m) {
                 :param tensor_name: An input tensor name.
                 :type tensor_name: str
                 :return: A compiled model input.
-                :rtype: openvino.runtime.ConstOutput
+                :rtype: openvino.ConstOutput
             )");
 
     cls.def_property_readonly("outputs",
@@ -239,7 +239,7 @@ void regclass_CompiledModel(py::module m) {
                                 Gets all outputs of a compiled model.
 
                                 :return: Outputs of a compiled model.
-                                :rtype: List[openvino.runtime.ConstOutput]
+                                :rtype: List[openvino.ConstOutput]
                               )");
 
     cls.def("output",
@@ -249,7 +249,7 @@ void regclass_CompiledModel(py::module m) {
                 If the model has more than one output, this method throws an exception.
 
                 :return: A compiled model output.
-                :rtype: openvino.runtime.ConstOutput
+                :rtype: openvino.ConstOutput
             )");
 
     cls.def("output",
@@ -262,7 +262,7 @@ void regclass_CompiledModel(py::module m) {
                 :param index: An output index.
                 :type index: int
                 :return: A compiled model output.
-                :rtype: openvino.runtime.ConstOutput
+                :rtype: openvino.ConstOutput
             )");
 
     cls.def("output",
@@ -276,7 +276,7 @@ void regclass_CompiledModel(py::module m) {
                 :param tensor_name: An output tensor name.
                 :type tensor_name: str
                 :return: A compiled model output.
-                :rtype: openvino.runtime.ConstOutput
+                :rtype: openvino.ConstOutput
             )");
 
     cls.def("__repr__", [](const ov::CompiledModel& self) {