Pylint fixes

.pylintrc

@@ -22,7 +22,8 @@ disable = arguments-differ,
           duplicate-code,
           consider-using-f-string,
           logging-fstring-interpolation,
-          cyclic-import
+          cyclic-import,
+          useless-import-alias
 
 max-line-length = 120
 ignore-docstrings = yes

nncf/__init__.py

@@ -31,7 +31,7 @@
 
 _SUPPORTED_FRAMEWORKS = ["torch", "tensorflow", "onnx", "openvino"]
 
-
+#pylint:disable=wrong-import-position
 from importlib.util import find_spec as _find_spec  # noqa: E402
 
 _AVAILABLE_FRAMEWORKS = {name: _find_spec(name) is not None for name in _SUPPORTED_FRAMEWORKS}

nncf/config/config.py

@@ -37,7 +37,7 @@ class NNCFConfig(dict):
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
-        self.__nncf_extra_structs: dict[str, NNCFExtraConfigStruct] = {}
+        self.__nncf_extra_structs: Dict[str, NNCFExtraConfigStruct] = {}
 
     @classmethod
     def from_dict(cls, nncf_dict: Dict) -> "NNCFConfig":

nncf/tensorflow/__init__.py

@@ -11,6 +11,7 @@
 """
 Base subpackage for NNCF TensorFlow functionality.
 """
+# pylint:skip-file
 import tensorflow
 from packaging import version
 

nncf/torch/dynamic_graph/graph_tracer.py

@@ -98,8 +98,6 @@ def trace_graph(
     ) -> DynamicGraph:
         sd = deepcopy(model.state_dict())
 
-        from nncf.torch.dynamic_graph.context import TracingContext  # pylint: disable=cyclic-import
-
         if context_to_use is None:
             context_to_use = TracingContext()
 

nncf/torch/graph/graph_builder.py

@@ -31,7 +31,7 @@ def __init__(self, custom_forward_fn: Callable[[torch.nn.Module], Any]):
     def build_graph(
         self,
         model: torch.nn.Module,
-        context_to_use: Optional["TracingContext"] = None,
+        context_to_use: Optional[TracingContext] = None,
         as_eval: bool = False,
         input_infos: List[ModelInputInfo] = None,
     ) -> PTNNCFGraph:

nncf/torch/quantization/base_ctrl.py

@@ -1,13 +1,13 @@
-#  Copyright (c) 2023 Intel Corporation
-#  Licensed under the Apache License, Version 2.0 (the "License");
-#  you may not use this file except in compliance with the License.
-#  You may obtain a copy of the License at
+# Copyright (c) 2023 Intel Corporation
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
 #      http://www.apache.org/licenses/LICENSE-2.0
-#  Unless required by applicable law or agreed to in writing, software
-#  distributed under the License is distributed on an "AS IS" BASIS,
-#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-#  See the License for the specific language governing permissions and
-#  limitations under the License.
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
 from nncf.torch.compression_method_api import PTCompressionAlgorithmController
 
 

nncf/torch/quantization/precision_init/definitions.py

@@ -1,13 +1,13 @@
-#  Copyright (c) 2023 Intel Corporation
-#  Licensed under the Apache License, Version 2.0 (the "License");
-#  you may not use this file except in compliance with the License.
-#  You may obtain a copy of the License at
+# Copyright (c) 2023 Intel Corporation
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
 #      http://www.apache.org/licenses/LICENSE-2.0
-#  Unless required by applicable law or agreed to in writing, software
-#  distributed under the License is distributed on an "AS IS" BASIS,
-#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-#  See the License for the specific language governing permissions and
-#  limitations under the License.
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
 from typing import List
 
 from nncf.common.quantization.structs import QuantizerConfig

nncf/torch/quantization/precision_init/hawq_debug.py

@@ -25,6 +25,8 @@
 from nncf.torch.quantization.adjust_padding import add_adjust_padding_nodes
 from nncf.torch.quantization.layers import QUANTIZATION_MODULES
 from nncf.torch.quantization.precision_init.adjacent_quantizers import GroupsOfAdjacentQuantizers
+
+# pylint:disable=unused-import
 from nncf.torch.quantization.precision_init.definitions import QConfigSequenceForHAWQToEvaluate
 from nncf.torch.quantization.precision_init.perturbations import PerturbationObserver
 from nncf.torch.quantization.precision_init.perturbations import Perturbations

nncf/torch/utils.py

@@ -25,6 +25,7 @@
 from nncf.common.logging import nncf_logger
 from nncf.common.scopes import matches_any
 from nncf.torch.dynamic_graph.scope import Scope
+from nncf.torch.dynamic_graph.scope import ScopeElement
 from nncf.torch.dynamic_graph.trace_tensor import TracedTensor
 from nncf.torch.layer_utils import _NNCFModuleMixin
 from nncf.torch.structures import ExecutionParameters
@@ -55,8 +56,6 @@ def get_all_modules_by_type(
     if isinstance(module_types, str):
         module_types = [module_types]
     found = OrderedDict()
-    from nncf.torch.dynamic_graph.scope import Scope  # pylint: disable=cyclic-import
-    from nncf.torch.dynamic_graph.scope import ScopeElement  # pylint: disable=cyclic-import
 
     if current_scope is None:
         current_scope = Scope()

tests/common/conftest.py

@@ -9,4 +9,5 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+#pylint:disable=unused-import
 from tests.shared.logging import nncf_caplog  # noqa: F401

tests/torch/quantization/test_logarithm_scale.py

@@ -53,10 +53,10 @@ def __len__(self):
     data_loader = torch.utils.data.DataLoader(RandDatasetMock(), batch_size=1, shuffle=False, drop_last=True)
 
     class SquadInitializingDataloader(nncf.torch.initialization.PTInitializingDataLoader):
-        def get_inputs(self, batch):
-            return batch, {}
+        def get_inputs(self, dataloader_output):
+            return dataloader_output, {}
 
-        def get_target(self, batch):
+        def get_target(self, dataloader_output):
             return None
 
     initializing_data_loader = SquadInitializingDataloader(data_loader)