[PYTHON API] Tensor.data property for low precisions + packing (#11131)

* rebase old branch with master

* Fix doc style

* fix test

* update tests

* Add missed param

* Rewrite docstring for tensor and refactor set_input_tensors test

* update python exclusives

* keep compatibility

* remove notes about slices

* fix code style

* Fix code style

docs/snippets/ov_python_exclusives.py

@@ -50,17 +50,6 @@ shared_tensor.data[0][2] = 0.6
 assert data_to_share[0][2] == 0.6
 #! [tensor_shared_mode]
 
-#! [tensor_slice_mode]
-data_to_share = np.ones(shape=(2,8))
-
-# Specify slice of memory and the shape
-shared_tensor = ov.Tensor(data_to_share[1][:] , shape=ov.Shape([8]))
-
-# Editing of the numpy array affects Tensor's data
-data_to_share[1][:] = 2
-assert np.array_equal(shared_tensor.data, data_to_share[1][:])
-#! [tensor_slice_mode]
-
 infer_request = compiled.create_infer_request()
 data = np.random.randint(-5, 3 + 1, size=(8))
 
@@ -132,6 +121,23 @@ infer_queue.wait_all()
 assert all(data_done)
 #! [asyncinferqueue_set_callback]
 
+unt8_data = np.ones([100])
+
+#! [packing_data]
+from openvino.helpers import pack_data
+
+packed_buffer = pack_data(unt8_data, ov.Type.u4)
+# Create tensor with shape in element types
+t = ov.Tensor(packed_buffer, [1, 128], ov.Type.u4)
+#! [packing_data]
+
+#! [unpacking]
+from openvino.helpers import unpack_data
+
+unpacked_data = unpack_data(t.data, t.element_type, t.shape)
+assert np.array_equal(unpacked_data , unt8_data)
+#! [unpacking]
+
 #! [releasing_gil]
 import openvino.runtime as ov
 import cv2 as cv