[PyOV] Update Python API stub files (openvinotoolkit#33031)

- Updated Python API stub (.pyi) files from the latest available nightly

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Author: sys-openvino-ci

src/bindings/python/src/openvino/_ov_api.pyi

@@ -93,13 +93,19 @@ class AsyncInferQueue(openvino._pyopenvino.AsyncInferQueue):
         
                                       If set to `True` the data dispatcher tries to provide "zero-copy"
                                       Tensors for every input in form of:
-                                      * `numpy.ndarray` and all the types that are castable to it, e.g. `torch.Tensor`
+        
+                                      * `numpy.ndarray` and all the types that are castable to it,
+                                        e.g. `torch.Tensor`
+        
                                       Data that is going to be copied:
-                                      * `numpy.ndarray` which are not C contiguous and/or not writable (WRITEABLE flag is set to False)
+        
+                                      * `numpy.ndarray` which are not C contiguous and/or not writable
+                                        (WRITEABLE flag is set to False)
                                       * inputs which data types are mismatched from Infer Request's inputs
                                       * inputs that should be in `BF16` data type
                                       * scalar inputs (i.e. `np.float_`/`str`/`bytes`/`int`/`float`)
                                       * lists of simple data types (i.e. `str`/`bytes`/`int`/`float`)
+        
                                       Keeps Tensor inputs "as-is".
         
                                       Note: Use with extra care, shared data can be modified during runtime!
@@ -157,13 +163,19 @@ class CompiledModel(openvino._pyopenvino.CompiledModel):
         
                                       If set to `True` the data dispatcher tries to provide "zero-copy"
                                       Tensors for every input in form of:
-                                      * `numpy.ndarray` and all the types that are castable to it, e.g. `torch.Tensor`
+        
+                                      * `numpy.ndarray` and all the types that are castable to it,
+                                        e.g. `torch.Tensor`
+        
                                       Data that is going to be copied:
-                                      * `numpy.ndarray` which are not C contiguous and/or not writable (WRITEABLE flag is set to False)
+        
+                                      * `numpy.ndarray` which are not C contiguous and/or not writable
+                                        (WRITEABLE flag is set to False)
                                       * inputs which data types are mismatched from Infer Request's inputs
                                       * inputs that should be in `BF16` data type
                                       * scalar inputs (i.e. `np.float_`/`str`/`bytes`/`int`/`float`)
                                       * lists of simple data types (i.e. `str`/`bytes`/`int`/`float`)
+        
                                       Keeps Tensor inputs "as-is".
         
                                       Note: Use with extra care, shared data can be modified during runtime!
@@ -386,13 +398,19 @@ class InferRequest(openvino.utils.data_helpers.wrappers._InferRequestWrapper):
         
                                       If set to `True` the data dispatcher tries to provide "zero-copy"
                                       Tensors for every input in form of:
-                                      * `numpy.ndarray` and all the types that are castable to it, e.g. `torch.Tensor`
+        
+                                      * `numpy.ndarray` and all the types that are castable to it,
+                                        e.g. `torch.Tensor`
+        
                                       Data that is going to be copied:
-                                      * `numpy.ndarray` which are not C contiguous and/or not writable (WRITEABLE flag is set to False)
+        
+                                      * `numpy.ndarray` which are not C contiguous and/or not writable
+                                        (WRITEABLE flag is set to False)
                                       * inputs which data types are mismatched from Infer Request's inputs
                                       * inputs that should be in `BF16` data type
                                       * scalar inputs (i.e. `np.float_`/`str`/`bytes`/`int`/`float`)
                                       * lists of simple data types (i.e. `str`/`bytes`/`int`/`float`)
+        
                                       Keeps Tensor inputs "as-is".
         
                                       Note: Use with extra care, shared data can be modified during runtime!
@@ -461,13 +479,19 @@ class InferRequest(openvino.utils.data_helpers.wrappers._InferRequestWrapper):
         
                                       If set to `True` the data dispatcher tries to provide "zero-copy"
                                       Tensors for every input in form of:
-                                      * `numpy.ndarray` and all the types that are castable to it, e.g. `torch.Tensor`
+        
+                                      * `numpy.ndarray` and all the types that are castable to it,
+                                        e.g. `torch.Tensor`
+        
                                       Data that is going to be copied:
-                                      * `numpy.ndarray` which are not C contiguous and/or not writable (WRITEABLE flag is set to False)
+        
+                                      * `numpy.ndarray` which are not C contiguous and/or not writable
+                                        (WRITEABLE flag is set to False)
                                       * inputs which data types are mismatched from Infer Request's inputs
                                       * inputs that should be in `BF16` data type
                                       * scalar inputs (i.e. `np.float_`/`str`/`bytes`/`int`/`float`)
                                       * lists of simple data types (i.e. `str`/`bytes`/`int`/`float`)
+        
                                       Keeps Tensor inputs "as-is".
         
                                       Note: Use with extra care, shared data can be modified during runtime!

src/bindings/python/src/openvino/frontend/tensorflow/__init__.pyi

@@ -1,6 +1,5 @@
 # type: ignore
 from . import py_tensorflow_frontend
-from . import utils
 from __future__ import annotations
 from openvino.frontend.tensorflow.py_tensorflow_frontend import ConversionExtensionTensorflow as ConversionExtension
 from openvino.frontend.tensorflow.py_tensorflow_frontend import OpExtensionTensorflow as OpExtension
@@ -10,4 +9,4 @@ from openvino.frontend.tensorflow.py_tensorflow_frontend import _FrontEndPyGraph
 Package: openvino
 Low level wrappers for the FrontEnd C++ API.
 """
-__all__: list[str] = ['ConversionExtension', 'GraphIterator', 'OpExtension', 'py_tensorflow_frontend', 'utils']
+__all__: list[str] = ['ConversionExtension', 'GraphIterator', 'OpExtension', 'py_tensorflow_frontend']

src/bindings/python/src/openvino/frontend/tensorflow/utils.pyi

@@ -35,7 +35,8 @@ def bitwise_and(left, right, *args, **kwargs) -> openvino._pyopenvino.Node:
     
         :param left_node: Tensor of integer or boolean datatype providing data.
         :param right_node: Tensor of integer or boolean datatype providing data.
-        :param auto_broadcast: The type of broadcasting specifies rules used for auto-broadcasting of input tensors. Defaults to “NUMPY”.
+        :param auto_broadcast: The type of broadcasting specifies rules used for
+                               auto-broadcasting of input tensors. Defaults to "NUMPY".
         :param name: The optional new name for output node.
         :return: The node performing bitwise AND operation on input nodes corresponding elements.
         
@@ -59,7 +60,8 @@ def bitwise_or(left, right, *args, **kwargs) -> openvino._pyopenvino.Node:
     
         :param left_node: Tensor of integer or boolean datatype providing data.
         :param right_node: Tensor of integer or boolean datatype providing data.
-        :param auto_broadcast: The type of broadcasting specifies rules used for auto-broadcasting of input tensors. Defaults to “NUMPY”.
+        :param auto_broadcast: The type of broadcasting specifies rules used for
+                               auto-broadcasting of input tensors. Defaults to "NUMPY".
         :param name: The optional new name for output node.
         :return: The node performing bitwise OR operation on input nodes corresponding elements.
         
@@ -72,7 +74,8 @@ def bitwise_xor(left, right, *args, **kwargs) -> openvino._pyopenvino.Node:
     
         :param left_node: Tensor of integer or boolean datatype providing data.
         :param right_node: Tensor of integer or boolean datatype providing data.
-        :param auto_broadcast: The type of broadcasting specifies rules used for auto-broadcasting of input tensors. Defaults to “NUMPY”.
+        :param auto_broadcast: The type of broadcasting specifies rules used for
+                               auto-broadcasting of input tensors. Defaults to "NUMPY".
         :param name: The optional new name for output node.
         :return: The node performing bitwise XOR operation on input nodes corresponding elements.
         
@@ -149,15 +152,19 @@ def nms_rotated(*args, **kwargs) -> openvino._pyopenvino.Node:
     """
     Return a node which performs NMSRotated.
     
-        :param boxes: Tensor with box coordinates of floating point type and shape [num_batches, num_boxes, 5],
-                      where the last dimension is defined as [x_ctr, y_ctr, width, height, angle_radians].
-        :param scores: Tensor with box scores of floating point type and shape [num_batches, num_classes, num_boxes].
-        :param max_output_boxes_per_class: Tensor (scalar or 1D) of integer type, specifying maximum number of boxes
-                                            to be selected per class.
-        :param iou_threshold: Tensor (scalar or 1D) of floating point type, specifying intersection over union threshold
-        :param score_threshold: Tensor (scalar or 1D) of floating point type, specifying minimum score to consider box for the processing.
-        :param sort_result_descending: Flag that specifies whenever it is necessary to sort selected
-                                       boxes across batches or not.
+        :param boxes: Tensor with box coordinates of floating point type and shape
+                      [num_batches, num_boxes, 5], where the last dimension is defined as
+                      [x_ctr, y_ctr, width, height, angle_radians].
+        :param scores: Tensor with box scores of floating point type and shape
+                       [num_batches, num_classes, num_boxes].
+        :param max_output_boxes_per_class: Tensor (scalar or 1D) of integer type, specifying
+                                            maximum number of boxes to be selected per class.
+        :param iou_threshold: Tensor (scalar or 1D) of floating point type, specifying
+                              intersection over union threshold
+        :param score_threshold: Tensor (scalar or 1D) of floating point type, specifying
+                                minimum score to consider box for the processing.
+        :param sort_result_descending: Flag that specifies whenever it is necessary to sort
+                                       selected boxes across batches or not.
         :param output_type: Output element type.
         :param clockwise: Flag that specifies direction of the box rotation.
         :return: The new node which performs NMSRotated

src/bindings/python/src/openvino/opset13/ops.pyi

@@ -40,9 +40,12 @@ def convert_promote_types(*args, **kwargs) -> openvino._pyopenvino.Node:
     
         :param left_node: input node with type to be promoted to common one.
         :param right_node: input node with type to be promoted to common one.
-        :param promote_unsafe: Bool attribute whether to allow promotions that might result in bit-widening, precision loss and undefined behaviors.
-        :param pytorch_scalar_promotion: Bool attribute whether to promote scalar input to type provided by non-scalar input when number format is matching.
-        :param u64_integer_promotion_target: Element type attribute to select promotion result when inputs are u64 and signed integer.
+        :param promote_unsafe: Bool attribute whether to allow promotions that might result
+                               in bit-widening, precision loss and undefined behaviors.
+        :param pytorch_scalar_promotion: Bool attribute whether to promote scalar input to type
+                                         provided by non-scalar input when number format is matching.
+        :param u64_integer_promotion_target: Element type attribute to select promotion result
+                                             when inputs are u64 and signed integer.
         :param name: Optional name for the new output node.
     
         :return: The new node performing ConvertPromoteTypes operation.

src/bindings/python/src/openvino/opset14/ops.pyi

@@ -85,8 +85,10 @@ def segment_max(*args, **kwargs) -> openvino._pyopenvino.Node:
     
         :param data: ND tensor of type T, the numerical data on which SegmentMax operation will be performed.
         :param segment_ids: 1D Tensor of sorted non-negative numbers, representing the segments.
-        :param num_segments: An optional scalar value representing the segments count. If not provided, it is inferred from segment_ids.
-        :param fill_mode: Responsible for the value assigned to segments which are empty. Can be "ZERO" or "LOWEST".
+        :param num_segments: An optional scalar value representing the segments count.
+                             If not provided, it is inferred from segment_ids.
+        :param fill_mode: Responsible for the value assigned to segments which are empty.
+                          Can be "ZERO" or "LOWEST".
         :param name: Optional name for the node.
     
         :return: The new node performing SegmentMax operation.

src/bindings/python/src/openvino/opset16/ops.pyi

@@ -40,9 +40,12 @@ def generate_proposals(*args, **kwargs) -> openvino._pyopenvino.Node:
         :param nms_threshold: Specifies threshold to be used in the NMS stage.
         :param pre_nms_count: Specifies number of top-n proposals before NMS.
         :param post_nms_count: Specifies number of top-n proposals after NMS.
-        :param normalized: Specifies whether proposal bboxes are normalized or not. Optional attribute, default value is `True`.
-        :param nms_eta: Specifies eta parameter for adaptive NMS., must be in range `[0.0, 1.0]`. Optional attribute, default value is `1.0`.
-        :param roi_num_type: Specifies the element type of the third output `rpnroisnum`. Optional attribute, range of values: `i64` (default) or `i32`.
+        :param normalized: Specifies whether proposal bboxes are normalized or not.
+                           Optional attribute, default value is `True`.
+        :param nms_eta: Specifies eta parameter for adaptive NMS., must be in range `[0.0, 1.0]`.
+                        Optional attribute, default value is `1.0`.
+        :param roi_num_type: Specifies the element type of the third output `rpnroisnum`.
+                             Optional attribute, range of values: `i64` (default) or `i32`.
         :param name: The optional name for the output node.
         :return: New node performing GenerateProposals operation.
         

src/bindings/python/src/openvino/opset9/ops.pyi

@@ -35,7 +35,9 @@ def classproperty(func: typing.Any) -> _ClassPropertyDescriptor:
     ...
 def deprecated(name: typing.Any = None, version: str = '', message: str = '', stacklevel: int = 2) -> collections.abc.Callable[..., typing.Any]:
     """
-    Prints deprecation warning "{function_name} is deprecated and will be removed in version {version}. {message}" and runs the function.
+    Prints deprecation warning and runs the function.
+    
+        "{function_name} is deprecated and will be removed in version {version}. {message}"
     
         :param version: The version in which the code will be removed.
         :param message: A message explaining why the function is deprecated and/or what to use instead.