Merge branch 'main' into detectron_model_health

.github/workflows/docs.yml

@@ -39,7 +39,7 @@ jobs:
           fi
 
       - name: Set up Node.js
-        uses: actions/[email protected].2
+        uses: actions/[email protected].3
         with:
           node-version: 18
           cache: yarn

cyclops/data/clean.py

@@ -131,7 +131,7 @@ def normalize_events(
     data = data.infer_objects()
     data[event_name_col] = normalize_names(data[event_name_col])
 
-    if event_value_col and data[event_value_col].dtypes == object:
+    if event_value_col and data[event_value_col].dtypes == object:  # noqa: E721
         data[event_value_col] = normalize_values(data[event_value_col])
         log_df_counts(data, event_name_col, "Normalized values...", columns=True)
 

cyclops/data/slicer.py

@@ -923,7 +923,7 @@ def is_datetime(
             return False
     if isinstance(value, (list, np.ndarray)):
         return all((is_datetime(v) for v in value))
-    if isinstance(value, (datetime.datetime, np.datetime64)):
+    if isinstance(value, (datetime.datetime, np.datetime64)):  # noqa: SIM103
         return True
 
     return False

cyclops/evaluate/metrics/average_precision.py

@@ -131,9 +131,13 @@ def __new__(  # type: ignore # mypy expects a subclass of AveragePrecision
                 pos_label=pos_label,
             )
         if task == "multiclass":
-            NotImplementedError("Multiclass average precision is not implemented.")
+            raise NotImplementedError(
+                "Multiclass average precision is not implemented."
+            )
         if task == "multilabel":
-            NotImplementedError("Multilabel average precision is not implemented.")
+            raise NotImplementedError(
+                "Multilabel average precision is not implemented."
+            )
 
         raise ValueError(
             "Expected argument `task` to be either 'binary', 'multiclass' or "

cyclops/evaluate/metrics/functional/average_precision.py

@@ -159,9 +159,9 @@ def average_precision(
     if task == "binary":
         return binary_average_precision(target, preds, thresholds, pos_label)
     if task == "multiclass":
-        NotImplementedError("Multiclass average precision is not implemented.")
+        raise NotImplementedError("Multiclass average precision is not implemented.")
     if task == "multilabel":
-        NotImplementedError("Multilabel average precision is not implemented.")
+        raise NotImplementedError("Multilabel average precision is not implemented.")
 
     raise ValueError(
         "Expected argument `task` to be either 'binary', 'multiclass' or "

cyclops/report/model_card/base.py

@@ -118,7 +118,7 @@ def update_field(self, name: str, value: Any) -> None:
             raise ValueError(f"Field {name} does not exist.")
 
         field = self.__fields__[name]
-        if field.default_factory == list or isinstance(getattr(self, name), list):
+        if field.default_factory == list or isinstance(getattr(self, name), list):  # noqa: E721
             # NOTE: pydantic does not trigger validation when appending to a list,
             # but if `validate_assignment` is set to `True`, then validation will
             # be triggered when the list is assigned to the field.
@@ -173,6 +173,6 @@ def add_field(self, name: str, value: Any) -> None:
             model_config=BaseModelCardField.Config,
             default_factory=default_factory,
             field_info=FieldInfo(unique_items=True)
-            if default_factory == list
+            if default_factory == list  # noqa: E721
             else None,
         )

tests/cyclops/evaluate/metrics/experimental/test_metric.py

@@ -53,7 +53,7 @@ def test_add_state_factory():
     # default_factory is 'list'
     metric.add_state_default_factory("b", list)  # type: ignore
     assert (
-        metric._default_factories.get("b") == list
+        metric._default_factories.get("b") == list  # noqa: E721
     ), "Default factory should be 'list'."
 
     # dist_reduce_fn is "sum"