[PYTHON API] Check new config (openvinotoolkit#11402)

Improve code-style in Python API and reduce number of ignored hints.

Co-authored-by: Anastasia Kuporosova <[email protected]>

src/bindings/python/pyproject.toml

@@ -0,0 +1,3 @@
+[tool.black]
+line-length = 160
+include = '\.pyi?$'

src/bindings/python/setup.cfg

@@ -33,16 +33,29 @@ deps = -rrequirements.txt
 
 [flake8]
 # ignore:
+# A001 variable "var_name" is shadowing a python builtin
+# A002 argument "..." is shadowing a python builtin
+# CCE001 ClassName.method1 should be after ClassName.method2
 # D100 - Missing docstring in public module
+# D101 - Missing docstring in public class
 # D102 - Missing docstring in public method
 # D103 - Missing docstring in public function
 # D104 - Missing docstring in public package
 # D105 - Missing docstring in magic method
 # D107 - Missing docstring in __init__
 # D412 - No blank lines allowed between a section header and its content
 # F401 - module imported but unused
+# N803 - argument name '...' should be lowercase
+# T001 - print found
 # W503 - line break before binary operator (prefer line breaks before op, not after)
-ignore=D100,D102,D103,D104,D105,D107,D412,F401,W503
+# RST301 - Unexpected indentation
+# TAE002 - too complex annotation
+# PT007 - wrong values type @pytest.mark.parametrize, expected list of tuples
+# PT012 -  pytest.raises() block should contain a single simple statement
+# VNE001 - single letter variable names like 'X' are not allowed
+# VNE003 - variable names that shadow builtins are not allowed
+
+ignore=A001,A002,CCE001,D100,D101,D102,D103,D104,D105,D107,D412,E402,F401,N803,RST301,TAE002,T001,W503,PT007,PT012
 inline-quotes = double
 filename = *.py
 max-line-length = 160
@@ -51,12 +64,9 @@ show_source = True
 docstring-convention = google
 enable-extensions = G
 per-file-ignores =
-    # todo: will be fixed as part of 81803
-    tests/*: A001,C101,C812,C815,C816,C819,CCE001,D100,D101,D102,D103,D104,D105,D107,D212,E800,ECE001,N400,N802,N806,P101,P103,PT001,PT005,PT006,PT007,PT011,PT012,PT019,PT023,RST201,RST301,S001,T001,VNE001,VNE002,VNE003,W503
-    tests_compatibility/test_ngraph/*: A001,C101,C812,C815,C816,C819,CCE001,D100,D101,D102,D103,D104,D105,D107,D212,E800,ECE001,N400,N802,N806,P101,P103,PT001,PT005,PT006,PT007,PT011,PT012,PT019,PT023,RST201,RST301,S001,T001,VNE001,VNE002,VNE003,W503
-    src/compatibility/ngraph/*: A001,A002,C101,C812,C819,CCE001,E800,N803,N806,P101,RST201,RST202,RST203,RST206,RST301,T001,TAE002,VNE001,VNE003
-    # todo: will be fixed as part of 81803
-    src/openvino/*: A001,A002,C101,C812,C819,CCE001,E402,E800,N803,N806,P101,RST201,RST202,RST203,RST205,RST206,RST299,RST301,T001,TAE002,VNE001,VNE002,VNE003
+    src/openvino/runtime/*/ops.py: VNE001,VNE003
+    tests_compatibility/test_ngraph/*: C101,C812,C815,C816,C819,CCE001,D212,E800,ECE001,N400,N802,N806,P101,P103,PT001,PT005,PT006,PT011,PT019,PT023,RST201,S001,VNE002
+    src/compatibility/ngraph/*: C101,C812,C819,CCE001,E800,N806,P101,RST201,RST202,RST203,RST206,VNE001,VNE003
 
 [pydocstyle]
 convention = google

src/bindings/python/src/openvino/runtime/__init__.py

@@ -1,3 +1,4 @@
+# -*- coding: utf-8 -*-
 # Copyright (C) 2018-2022 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
@@ -7,6 +8,7 @@
 from openvino.utils import add_openvino_libs_to_path
 from pkg_resources import get_distribution, DistributionNotFound
 
+
 try:
     __version__ = get_distribution("openvino-core").version
 except DistributionNotFound:
@@ -65,6 +67,7 @@
 from openvino.runtime.ie_api import tensor_from_file
 from openvino.runtime.ie_api import compile_model
 
+
 # Extend Node class to support binary operators
 Node.__add__ = opset9.add
 Node.__sub__ = opset9.subtract

src/bindings/python/src/openvino/runtime/exceptions.py

@@ -1,3 +1,4 @@
+# -*- coding: utf-8 -*-
 # Copyright (C) 2018-2022 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 

src/bindings/python/src/openvino/runtime/ie_api.py

@@ -1,3 +1,4 @@
+# -*- coding: utf-8 -*-
 # Copyright (C) 2018-2022 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
@@ -22,19 +23,15 @@ def tensor_from_file(path: str) -> Tensor:
     return Tensor(np.fromfile(path, dtype=np.uint8))
 
 
-def set_scalar_tensor(
-    request: InferRequestBase, tensor: Tensor, key: Union[str, int, ConstOutput] = None
-) -> None:
+def set_scalar_tensor(request: InferRequestBase, tensor: Tensor, key: Union[str, int, ConstOutput] = None) -> None:
     if key is None:
         request.set_input_tensor(tensor)
     elif isinstance(key, int):
         request.set_input_tensor(key, tensor)
     elif isinstance(key, (str, ConstOutput)):
         request.set_tensor(key, tensor)
     else:
-        raise TypeError(
-            "Unsupported key type: {} for Tensor under key: {}".format(type(key), key)
-        )
+        raise TypeError(f"Unsupported key type: {type(key)} for Tensor under key: {key}")
 
 
 @singledispatch
@@ -43,9 +40,7 @@ def update_tensor(
     request: InferRequestBase,
     key: Union[str, int, ConstOutput] = None,
 ) -> None:
-    raise TypeError(
-        "Incompatible input data of type {} under {} key!".format(type(inputs), key)
-    )
+    raise TypeError(f"Incompatible input data of type {type(inputs)} under {key} key!")
 
 
 @update_tensor.register(np.ndarray)
@@ -65,11 +60,7 @@ def _(
         elif isinstance(key, (str, ConstOutput)):
             tensor = request.get_tensor(key)
         else:
-            raise TypeError(
-                "Unsupported key type: {} for Tensor under key: {}".format(
-                    type(key), key
-                )
-            )
+            raise TypeError(f"Unsupported key type: {type(key)} for Tensor under key: {key}")
         # Update shape if there is a mismatch
         if tensor.shape != inputs.shape:
             tensor.shape = inputs.shape
@@ -86,7 +77,7 @@ def _(
     key: Union[str, int, ConstOutput] = None,
 ) -> None:
     set_scalar_tensor(
-        request, Tensor(np.ndarray([], type(inputs), np.array(inputs))), key
+        request, Tensor(np.ndarray([], type(inputs), np.array(inputs))), key,
     )
 
 
@@ -100,29 +91,25 @@ def normalize_inputs(request: InferRequestBase, inputs: dict) -> dict:
     # new_inputs will be used to transfer data to inference calls,
     # ensuring that original inputs are not overwritten with Tensors.
     new_inputs: Dict[Union[str, int, ConstOutput], Tensor] = {}
-    for k, val in inputs.items():
-        if not isinstance(k, (str, int, ConstOutput)):
-            raise TypeError("Incompatible key type for input: {}".format(k))
+    for key, value in inputs.items():
+        if not isinstance(key, (str, int, ConstOutput)):
+            raise TypeError(f"Incompatible key type for input: {key}")
         # Copy numpy arrays to already allocated Tensors.
-        if isinstance(val, (np.ndarray, np.number, int, float)):
-            update_tensor(val, request, k)
+        if isinstance(value, (np.ndarray, np.number, int, float)):
+            update_tensor(value, request, key)
         # If value is of Tensor type, put it into temporary dictionary.
-        elif isinstance(val, Tensor):
-            new_inputs[k] = val
+        elif isinstance(value, Tensor):
+            new_inputs[key] = value
         # Throw error otherwise.
         else:
-            raise TypeError(
-                "Incompatible input data of type {} under {} key!".format(type(val), k)
-            )
+            raise TypeError(f"Incompatible input data of type {type(value)} under {key} key!")
     return new_inputs
 
 
 class InferRequest(InferRequestBase):
     """InferRequest class represents infer request which can be run in asynchronous or synchronous manners."""
 
-    def infer(
-        self, inputs: Union[dict, list, tuple, Tensor, np.ndarray] = None
-    ) -> dict:
+    def infer(self, inputs: Union[dict, list, tuple, Tensor, np.ndarray] = None) -> dict:
         """Infers specified input(s) in synchronous mode.
 
         Blocks all methods of InferRequest while request is running.
@@ -158,10 +145,7 @@ def infer(
         # It is an extension of above branch with dict inputs.
         elif isinstance(inputs, (list, tuple)):
             return super().infer(
-                normalize_inputs(
-                    self, {index: input for index, input in enumerate(inputs)}
-                )
-            )
+                normalize_inputs(self, {index: input for index, input in enumerate(inputs)}))
         # If inputs are Tensor, call infer method directly.
         elif isinstance(inputs, Tensor):
             return super().infer(inputs)
@@ -211,11 +195,7 @@ def start_async(
             super().start_async(normalize_inputs(self, inputs), userdata)
         elif isinstance(inputs, (list, tuple)):
             super().start_async(
-                normalize_inputs(
-                    self, {index: input for index, input in enumerate(inputs)}
-                ),
-                userdata,
-            )
+                normalize_inputs(self, {index: input for index, input in enumerate(inputs)}), userdata)
         elif isinstance(inputs, Tensor):
             super().start_async(inputs, userdata)
         elif isinstance(inputs, (np.ndarray, np.number, int, float)):
@@ -242,9 +222,7 @@ def create_infer_request(self) -> InferRequest:
         """
         return InferRequest(super().create_infer_request())
 
-    def infer_new_request(
-        self, inputs: Union[dict, list, tuple, Tensor, np.ndarray] = None
-    ) -> dict:
+    def infer_new_request(self, inputs: Union[dict, list, tuple, Tensor, np.ndarray] = None) -> dict:
         """Infers specified input(s) in synchronous mode.
 
         Blocks all methods of CompiledModel while request is running.
@@ -292,7 +270,6 @@ class AsyncInferQueue(AsyncInferQueueBase):
     InferRequests and provides synchronization functions to control flow of
     a simple pipeline.
     """
-
     def __getitem__(self, i: int) -> InferRequest:
         """Gets InferRequest from the pool with given i id.
 
@@ -334,7 +311,7 @@ def start_async(
             super().start_async({}, userdata)
         elif isinstance(inputs, dict):
             super().start_async(
-                normalize_inputs(self[self.get_idle_request_id()], inputs), userdata
+                normalize_inputs(self[self.get_idle_request_id()], inputs), userdata,
             )
         elif isinstance(inputs, (list, tuple)):
             super().start_async
@@ -364,7 +341,7 @@ class Core(CoreBase):
     """
 
     def compile_model(
-        self, model: Union[Model, str], device_name: str = None, config: dict = None
+        self, model: Union[Model, str], device_name: str = None, config: dict = None,
     ) -> CompiledModel:
         """Creates a compiled model.
 
@@ -389,15 +366,15 @@ def compile_model(
         """
         if device_name is None:
             return CompiledModel(
-                super().compile_model(model, {} if config is None else config)
+                super().compile_model(model, {} if config is None else config),
             )
 
         return CompiledModel(
-            super().compile_model(model, device_name, {} if config is None else config)
+            super().compile_model(model, device_name, {} if config is None else config),
         )
 
     def import_model(
-        self, model_stream: bytes, device_name: str, config: dict = None
+        self, model_stream: bytes, device_name: str, config: dict = None,
     ) -> CompiledModel:
         """Imports a compiled model from a previously exported one.
 
@@ -414,6 +391,7 @@ def import_model(
         :rtype: openvino.runtime.CompiledModel
 
         :Example:
+
         .. code-block:: python
 
             user_stream = compiled.export_model()
@@ -439,8 +417,8 @@ def import_model(
         """
         return CompiledModel(
             super().import_model(
-                model_stream, device_name, {} if config is None else config
-            )
+                model_stream, device_name, {} if config is None else config,
+            ),
         )
 
 

src/bindings/python/src/openvino/runtime/opset1/__init__.py

@@ -1,3 +1,4 @@
+# -*- coding: utf-8 -*-
 # Copyright (C) 2018-2022 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0