[ruff] INP rule, extend install tests (#3245)

#3244

### Changes

- Enabled INP rule for ruff
https://docs.astral.sh/ruff/rules/#flake8-no-pep420-inp
- Added missed `__init__.py` files
- Extended install tests for torch and tf to load modules
- Moved fx quantizers to fx directory 
- Removed import openvino in torch backend files

### Reason for changes

Some files are not added to package

### Tests

https://github.com/openvinotoolkit/nncf/actions/runs/13142880275

nncf/experimental/quantization/algorithms/__init__.py

@@ -0,0 +1,10 @@
+# Copyright (c) 2025 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.

nncf/experimental/quantization/algorithms/post_training/algorithm.py

@@ -17,7 +17,7 @@
 from nncf.common.tensor_statistics.statistic_point import StatisticPointsContainer
 from nncf.common.utils.backend import BackendType
 from nncf.experimental.quantization.algorithms.post_training.pipeline import experimental_create_ptq_pipeline
-from nncf.experimental.quantization.quantizers.quantizer import Quantizer
+from nncf.experimental.quantization.quantizer import Quantizer
 from nncf.quantization.advanced_parameters import AdvancedBiasCorrectionParameters
 from nncf.quantization.advanced_parameters import AdvancedSmoothQuantParameters
 from nncf.quantization.advanced_parameters import RangeEstimatorParameters

nncf/experimental/quantization/algorithms/post_training/pipeline.py

@@ -12,7 +12,7 @@
 from typing import Optional, TypeVar
 
 from nncf.experimental.quantization.algorithms.range_estimator.algorithm import MinMaxRangeEstimator
-from nncf.experimental.quantization.quantizers.quantizer import Quantizer
+from nncf.experimental.quantization.quantizer import Quantizer
 from nncf.quantization.advanced_parameters import AdvancedBiasCorrectionParameters
 from nncf.quantization.advanced_parameters import AdvancedSmoothQuantParameters
 from nncf.quantization.advanced_parameters import RangeEstimatorParameters

nncf/experimental/quantization/algorithms/range_estimator/__init__.py

@@ -0,0 +1,10 @@
+# Copyright (c) 2025 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.

nncf/experimental/quantization/algorithms/range_estimator/algorithm.py

@@ -15,7 +15,7 @@
 from nncf.common.graph.graph import NNCFGraph
 from nncf.common.tensor_statistics.statistic_point import StatisticPointsContainer
 from nncf.common.utils.backend import BackendType
-from nncf.experimental.quantization.quantizers.quantizer import Quantizer
+from nncf.experimental.quantization.quantizer import Quantizer
 from nncf.quantization.algorithms.algorithm import Algorithm
 from nncf.quantization.algorithms.min_max.algorithm import MinMaxQuantization
 from nncf.quantization.range_estimator import RangeEstimatorParameters

nncf/experimental/torch/fx/quantization/quantize_pt2e.py

@@ -27,10 +27,10 @@
 from nncf.common.logging import nncf_logger
 from nncf.data import Dataset
 from nncf.experimental.quantization.algorithms.post_training.algorithm import ExperimentalPostTrainingQuantization
-from nncf.experimental.quantization.quantizers.openvino_adapter import OpenVINOQuantizerAdapter
-from nncf.experimental.quantization.quantizers.openvino_quantizer import OpenVINOQuantizer
-from nncf.experimental.quantization.quantizers.torch_ao_adapter import TorchAOQuantizerAdapter
 from nncf.experimental.torch.fx.constant_folding import constant_fold
+from nncf.experimental.torch.fx.quantization.quantizer.openvino_adapter import OpenVINOQuantizerAdapter
+from nncf.experimental.torch.fx.quantization.quantizer.openvino_quantizer import OpenVINOQuantizer
+from nncf.experimental.torch.fx.quantization.quantizer.torch_ao_adapter import TorchAOQuantizerAdapter
 from nncf.experimental.torch.fx.transformations import QUANTIZE_NODE_TARGETS
 from nncf.experimental.torch.fx.transformations import compress_post_quantize_transformation
 from nncf.quantization.advanced_parameters import AdvancedBiasCorrectionParameters

nncf/experimental/torch/fx/quantization/quantizer/__init__.py

@@ -0,0 +1,10 @@
+# Copyright (c) 2025 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.

nncf/experimental/quantization/quantizers/openvino_adapter.py → nncf/experimental/torch/fx/quantization/quantizer/openvino_adapter.py

@@ -13,8 +13,8 @@
 
 from nncf.common.graph.graph import NNCFGraph
 from nncf.common.quantization.quantizer_setup import SingleConfigQuantizerSetup
-from nncf.experimental.quantization.quantizers.openvino_quantizer import OpenVINOQuantizer
-from nncf.experimental.quantization.quantizers.quantizer import Quantizer
+from nncf.experimental.quantization.quantizer import Quantizer
+from nncf.experimental.torch.fx.quantization.quantizer.openvino_quantizer import OpenVINOQuantizer
 
 
 class OpenVINOQuantizerAdapter(Quantizer):

nncf/experimental/quantization/quantizers/torch_ao_adapter.py → nncf/experimental/torch/fx/quantization/quantizer/torch_ao_adapter.py

@@ -30,7 +30,7 @@
 from nncf.common.quantization.quantizer_setup import WeightQuantizationInsertionPoint
 from nncf.common.quantization.structs import QuantizationScheme as QuantizationMode
 from nncf.common.quantization.structs import QuantizerConfig
-from nncf.experimental.quantization.quantizers.quantizer import Quantizer
+from nncf.experimental.quantization.quantizer import Quantizer
 from nncf.experimental.torch.fx.nncf_graph_builder import GraphConverter
 
 EdgeOrNode = Union[Tuple[torch.fx.Node, torch.fx.Node]]

nncf/experimental/torch2/quantization/__init__.py

@@ -0,0 +1,10 @@
+# Copyright (c) 2025 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.

nncf/experimental/torch2/statistics/__init__.py

@@ -0,0 +1,10 @@
+# Copyright (c) 2025 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.

nncf/quantization/algorithms/smooth_quant/torch_backend.py

@@ -24,13 +24,12 @@
 from nncf.experimental.common.tensor_statistics.collectors import AbsMaxReducer
 from nncf.experimental.common.tensor_statistics.collectors import MaxAggregator
 from nncf.experimental.common.tensor_statistics.collectors import TensorCollector
-from nncf.openvino.graph.transformations.commands import OVMultiplyInsertionCommand
-from nncf.openvino.graph.transformations.commands import OVWeightUpdateCommand
 from nncf.quantization.algorithms.smooth_quant.backend import SmoothQuantAlgoBackend
 from nncf.tensor import Tensor
 from nncf.torch.graph.transformations.command_creation import create_command_to_update_weight
 from nncf.torch.graph.transformations.commands import PTSharedFnInsertionCommand
 from nncf.torch.graph.transformations.commands import PTTargetPoint
+from nncf.torch.graph.transformations.commands import PTWeightUpdateCommand
 from nncf.torch.layer_utils import COMPRESSION_MODULES
 from nncf.torch.layer_utils import CompressionParameter
 from nncf.torch.layer_utils import StatefullModuleInterface
@@ -127,7 +126,7 @@ def get_weight_value(node_with_weight: NNCFNode, model: NNCFNetwork, nncf_graph:
         return Tensor(weight_data)
 
     @staticmethod
-    def weight_update_command(node_with_weight: NNCFNode, weight_value: np.ndarray) -> OVWeightUpdateCommand:
+    def weight_update_command(node_with_weight: NNCFNode, weight_value: np.ndarray) -> PTWeightUpdateCommand:
         return create_command_to_update_weight(node_with_weight, weight_value)
 
     @staticmethod
@@ -137,7 +136,7 @@ def scale_insertion_command(
         source_output_port_id: int,
         nodes: List[NNCFNode],
         scale_node_name: str,
-    ) -> OVMultiplyInsertionCommand:
+    ) -> PTSharedFnInsertionCommand:
         input_port_id = 0
         target_points = []
         for node in nodes:

nncf/quantization/algorithms/smooth_quant/torch_fx_backend.py

@@ -28,8 +28,6 @@
 from nncf.experimental.torch.fx.transformations import constant_update_transformation_builder
 from nncf.experimental.torch.fx.transformations import get_graph_node_by_name
 from nncf.experimental.torch.fx.transformations import module_insertion_transformation_builder
-from nncf.openvino.graph.transformations.commands import OVMultiplyInsertionCommand
-from nncf.openvino.graph.transformations.commands import OVWeightUpdateCommand
 from nncf.quantization.algorithms.smooth_quant.backend import SmoothQuantAlgoBackend
 from nncf.tensor import Tensor
 from nncf.torch.graph.transformations.commands import PTTargetPoint
@@ -104,7 +102,7 @@ def get_weight_value(node_with_weight: NNCFNode, model: torch.fx.GraphModule, nn
         return Tensor(weight_data.data)
 
     @staticmethod
-    def weight_update_command(node_with_weight: NNCFNode, weight_value: torch.Tensor) -> OVWeightUpdateCommand:
+    def weight_update_command(node_with_weight: NNCFNode, weight_value: torch.Tensor) -> FXApplyTransformationCommand:
         # TODO(dlyakhov): Use input port id depending on the node metatype/attributes.
         return FXApplyTransformationCommand(
             constant_update_transformation_builder(node_with_weight, weight_value.data, input_port_id=1)
@@ -117,7 +115,7 @@ def scale_insertion_command(
         source_output_port_id: int,
         nodes: List[NNCFNode],
         scale_node_name: str,
-    ) -> OVMultiplyInsertionCommand:
+    ) -> FXApplyTransformationCommand:
         input_port_id = 0
         target_points = []
         for node in nodes:

pyproject.toml

@@ -138,6 +138,7 @@ select = [
     "F", # pyflakes rules
     "CPY001", # copyright check
     "NPY", # numpy rules
+    "INP", # flake8-no-pep420
 ]
 extend-select = [
     "SIM", # https://pypi.org/project/flake8-simplify
@@ -149,6 +150,7 @@ extend-select = [
 "tests/**/*.py" = ["F403"]
 "tests/**/__init__.py" = ["F401"]
 "examples/**/*.py" = ["F403"]
+"!nncf/**.py" = ["INP"]
 
 [tool.ruff.lint.flake8-copyright]
 notice-rgx = """\

tests/cross_fw/install/common.py

@@ -32,10 +32,14 @@ def onerror(name, excluded_modules_patterns):
 def load_nncf_modules(excluded_modules_patterns, verbose=False):
     onerror_partial = partial(onerror, excluded_modules_patterns=excluded_modules_patterns)
     for loader, module_name, _ in pkgutil.walk_packages(nncf.__path__, nncf.__name__ + ".", onerror_partial):
-        if module_name in sys.modules or excluded_module(module_name, excluded_modules_patterns):
+        if excluded_module(module_name, excluded_modules_patterns):
             if verbose:
                 print(f"Module {module_name} ------ SKIPPED")
             continue
+        if module_name in sys.modules:
+            if verbose:
+                print(f"Module {module_name} ------ LOADED")
+            continue
         loader.find_module(module_name).load_module(module_name)
         if verbose:
             print(f"Module {module_name} ------ LOADED")

tests/cross_fw/install/install_checks_onnx.py

@@ -18,9 +18,9 @@
     "nncf\\.experimental\\.tensorflow.*",
     "nncf\\.experimental\\.torch.*",
     "nncf\\.experimental\\.openvino.*",
-    ".*?openvino_[^\\.]*",
-    ".*?torch_[^\\.]*",
-    ".*?tf_[^\\.]*",
+    "^(?!nncf(?:\\.experimental)*\\.onnx.*?\\.).*?openvino_[^\\.]*",
+    "^(?!nncf(?:\\.experimental)*\\.onnx.*?\\.).*?torch_[^\\.]*",
+    "^(?!nncf(?:\\.experimental)*\\.onnx.*?\\.).*?tf_[^\\.]*",
 )
 
 load_nncf_modules(EXCLUDED_MODULES_PATTERNS)

tests/cross_fw/install/install_checks_openvino.py

@@ -18,10 +18,9 @@
     "nncf\\.experimental\\.onnx.*",
     "nncf\\.experimental\\.tensorflow.*",
     "nncf\\.experimental\\.torch.*",
-    ".*?onnx_[^\\.]*",
-    ".*?torch_[^\\.]*",
-    ".*?tf_[^\\.]*",
-    "nncf\\.openvino\\.pot.*",
+    "^(?!nncf(?:\\.experimental)*\\.openvino.*?\\.).*?onnx_[^\\.]*",
+    "^(?!nncf(?:\\.experimental)*\\.openvino.*?\\.).*?torch_[^\\.]*",
+    "^(?!nncf(?:\\.experimental)*\\.openvino.*?\\.).*?tf_[^\\.]*",
 )
 
 load_nncf_modules(EXCLUDED_MODULES_PATTERNS)

tests/cross_fw/install/install_checks_tf.py

@@ -14,6 +14,7 @@
 import nncf  # noqa: F401
 from nncf.common.compression import BaseCompressionAlgorithmController
 from nncf.tensorflow.helpers.model_creation import create_compressed_model
+from tests.cross_fw.install.common import load_nncf_modules
 from tests.tensorflow.quantization.utils import get_basic_quantization_config
 
 # Do not remove - these imports are for testing purposes.
@@ -26,3 +27,17 @@
 config = get_basic_quantization_config()
 compression_state_to_skip_init = {BaseCompressionAlgorithmController.BUILDER_STATE: {}}
 compression_model, compression_ctrl = create_compressed_model(model, config, compression_state_to_skip_init)
+
+EXCLUDED_MODULES_PATTERNS = (
+    "nncf\\.openvino.*",
+    "nncf\\.torch.*",
+    "nncf\\.onnx.*",
+    "nncf\\.experimental\\.torch.*",
+    "nncf\\.experimental\\.openvino.*",
+    "nncf\\.experimental\\.onnx.*",
+    "^(?!nncf(?:\\.experimental)*\\.tensorflow.*?\\.).*?openvino_[^\\.]*",
+    "^(?!nncf(?:\\.experimental)*\\.tensorflow.*?\\.).*?onnx_[^\\.]*",
+    "^(?!nncf(?:\\.experimental)*\\.tensorflow.*?\\.).*?torch_[^\\.]*",
+)
+
+load_nncf_modules(EXCLUDED_MODULES_PATTERNS)

tests/cross_fw/install/install_checks_torch.py

@@ -14,6 +14,7 @@
 import torch
 
 import nncf
+from tests.cross_fw.install.common import load_nncf_modules
 
 if len(sys.argv) != 3:
     raise nncf.ValidationError(
@@ -54,3 +55,17 @@
     )
 else:
     raise nncf.ValidationError(f"Invalid execution type {execution_type} (expected 'cpu' or 'gpu')!")
+
+EXCLUDED_MODULES_PATTERNS = (
+    "nncf\\.openvino.*",
+    "nncf\\.tensorflow.*",
+    "nncf\\.onnx.*",
+    "nncf\\.experimental\\.tensorflow.*",
+    "nncf\\.experimental\\.openvino.*",
+    "nncf\\.experimental\\.onnx.*",
+    "^(?!nncf(?:\\.experimental)*\\.torch.*?\\.).*?openvino_[^\\.]*",
+    "^(?!nncf(?:\\.experimental)*\\.torch.*?\\.).*?onnx_[^\\.]*",
+    "^(?!nncf(?:\\.experimental)*\\.torch.*?\\.).*?tf_[^\\.]*",
+)
+
+load_nncf_modules(EXCLUDED_MODULES_PATTERNS)

tests/cross_fw/shared/helpers.py

@@ -36,7 +36,7 @@ def get_cli_dict_args(args):
 
 
 MAP_BACKEND_PACKAGES = {
-    "torch": ["torch"],
+    "torch": ["torch", "torchvision"],
     "openvino": ["openvino"],
     "onnx": ["onnx", "onnxruntime"],
     "tf": ["tensorflow"],

tests/torch/fx/test_quantizer.py

@@ -31,10 +31,10 @@
 from torch.ao.quantization.quantizer.x86_inductor_quantizer import get_default_x86_inductor_quantization_config
 
 import nncf
-from nncf.experimental.quantization.quantizers.openvino_quantizer import OpenVINOQuantizer
-from nncf.experimental.quantization.quantizers.torch_ao_adapter import _get_edge_or_node_to_qspec
 from nncf.experimental.torch.fx.nncf_graph_builder import GraphConverter
 from nncf.experimental.torch.fx.quantization.quantize_pt2e import quantize_pt2e
+from nncf.experimental.torch.fx.quantization.quantizer.openvino_quantizer import OpenVINOQuantizer
+from nncf.experimental.torch.fx.quantization.quantizer.torch_ao_adapter import _get_edge_or_node_to_qspec
 from tests.torch import test_models
 from tests.torch.fx.helpers import get_torch_fx_model
 from tests.torch.test_compressed_graph import check_graph