[ruff] Enable ISC rule

examples/tensorflow/common/object_detection/architecture/fpn.py

@@ -108,10 +108,11 @@ def __call__(self, multilevel_features, is_training=None):
 
         input_levels = list(multilevel_features.keys())
         if min(input_levels) > self._min_level:
-            raise ValueError(
+            msg = (
                 f"The minimum backbone level {min(input_levels)} should be "
-                + f"less or equal to FPN minimum level {self._min_level}."
+                f"less or equal to FPN minimum level {self._min_level}."
             )
+            raise ValueError(msg)
 
         backbone_max_level = min(max(input_levels), self._max_level)
         with tf.name_scope("fpn"):

nncf/common/quantization/quantizer_setup.py

@@ -220,7 +220,7 @@ def select_qconfig(self, qconfig: QuantizerConfig) -> SingleConfigQuantizationPo
             qconfig_any = deepcopy(qconfig)
             qconfig_any.signedness_to_force = None
             if qconfig_any not in self.possible_qconfigs:
-                msg = "Invalid selection for a quantizer config - " "tried to select {} among [{}]".format(
+                msg = "Invalid selection for a quantizer config - tried to select {} among [{}]".format(
                     qconfig, ",".join([str(q) for q in self.possible_qconfigs])
                 )
                 raise ValueError(msg)

nncf/quantization/algorithms/bias_correction/torch_fx_backend.py

@@ -105,7 +105,7 @@ def get_output_name(model: torch.fx.GraphModule, node_name: str, output_port_id:
             elif node.op == "output":
                 return node.all_input_nodes.index(graph_node)
 
-        msg = f"Node with name {node_name} expected to have an output," " no outputs were found."
+        msg = f"Node with name {node_name} expected to have an output, no outputs were found."
         raise nncf.InternalError(msg)
 
     @staticmethod

nncf/tensorflow/quantization/init_range.py

@@ -75,7 +75,7 @@ def get_init_config_for_scope_and_group(self, node_name: str, group: QuantizerGr
                     )
                 )
         if len(matches) > 1:
-            msg = f"Location {str(node_name)} matches more than one per-layer initialization parameter " "definition!"
+            msg = f"Location {str(node_name)} matches more than one per-layer initialization parameter definition!"
             raise ValueError(msg)
         if len(matches) == 1:
             return matches[0]

nncf/torch/model_creation.py

@@ -180,7 +180,7 @@ def get_input_info_from_config(config: NNCFConfig) -> ModelInputInfo:
         return FillerInputInfo.from_nncf_config(config)
 
     nncf_logger.debug(
-        "Config has no 'input_info' section, trying to use dataloader output as model inputs " "for graph building."
+        "Config has no 'input_info' section, trying to use dataloader output as model inputs for graph building."
     )
     exact_info = LoaderInputInfo.from_nncf_config_dataloaders(config)
     if exact_info is not None:

pyproject.toml

@@ -142,6 +142,7 @@ select = [
     "UP", # pyupgrade
     "EM",  # flake8-errmsg
     "INP", # flake8-no-pep420
+    "ISC", # flake8-implicit-str-concat
 ]
 extend-select = [
     "SIM", # https://pypi.org/project/flake8-simplify

tests/openvino/tools/calibrate.py

@@ -355,7 +355,7 @@ def map_ignored_scope(ignored):
     if operations is not None:
         for op in operations:
             if op.get("attributes") is not None:
-                msg = '"attributes" in the ignored operations ' "are not supported"
+                msg = '"attributes" in the ignored operations are not supported'
                 raise ValueError(msg)
             ignored_operations.append(op["type"])
     return {"ignored_scope": IgnoredScope(names=ignored.get("scope", []), types=ignored_operations)}