Update Space (evaluate main: c447fc8e)

mae.py

@@ -13,9 +13,6 @@
 # limitations under the License.
 """MAE - Mean Absolute Error Metric"""
 
-from dataclasses import dataclass
-from typing import List, Optional, Union
-
 import datasets
 from sklearn.metrics import mean_absolute_error
 
@@ -84,26 +81,13 @@ Examples:
 """
 
 
-@dataclass
-class MaeConfig(evaluate.info.Config):
-
-    name: str = "default"
-
-    multioutput: str = "uniform_average"
-    sample_weight: Optional[List[float]] = None
-
-
 @evaluate.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION)
 class Mae(evaluate.Metric):
-    CONFIG_CLASS = MaeConfig
-    ALLOWED_CONFIG_NAMES = ["default", "multilist"]
-
-    def _info(self, config):
+    def _info(self):
         return evaluate.MetricInfo(
             description=_DESCRIPTION,
             citation=_CITATION,
             inputs_description=_KWARGS_DESCRIPTION,
-            config=config,
             features=datasets.Features(self._get_feature_types()),
             reference_urls=[
                 "https://scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_absolute_error.html"
@@ -122,10 +106,8 @@ class Mae(evaluate.Metric):
                 "references": datasets.Value("float"),
             }
 
-    def _compute(self, predictions, references):
+    def _compute(self, predictions, references, sample_weight=None, multioutput="uniform_average"):
 
-        mae_score = mean_absolute_error(
-            references, predictions, sample_weight=self.config.sample_weight, multioutput=self.config.multioutput
-        )
+        mae_score = mean_absolute_error(references, predictions, sample_weight=sample_weight, multioutput=multioutput)
 
         return {"mae": mae_score}

requirements.txt

@@ -1,2 +1,2 @@
-git+https://github.com/huggingface/evaluate@e4a2724377909fe2aeb4357e3971e5a569673b39
+git+https://github.com/huggingface/evaluate@c447fc8eda9c62af501bfdc6988919571050d950
 sklearn