Update Space (evaluate main: c447fc8e)

accuracy.py

@@ -13,9 +13,6 @@
 # limitations under the License.
 """Accuracy metric."""
 
-from dataclasses import dataclass
-from typing import List, Optional
-
 import datasets
 from sklearn.metrics import accuracy_score
 
@@ -80,26 +77,13 @@ _CITATION = """
 """
 
 
-@dataclass
-class AccuracyConfig(evaluate.info.Config):
-
-    name: str = "default"
-
-    normalize: bool = True
-    sample_weight: Optional[List[float]] = None
-
-
 @evaluate.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION)
 class Accuracy(evaluate.Metric):
-    CONFIG_CLASS = AccuracyConfig
-    ALLOWED_CONFIG_NAMES = ["default", "multilabel"]
-
-    def _info(self, config):
+    def _info(self):
         return evaluate.MetricInfo(
             description=_DESCRIPTION,
             citation=_CITATION,
             inputs_description=_KWARGS_DESCRIPTION,
-            config=config,
             features=datasets.Features(
                 {
                     "predictions": datasets.Sequence(datasets.Value("int32")),
@@ -114,11 +98,9 @@ class Accuracy(evaluate.Metric):
             reference_urls=["https://scikit-learn.org/stable/modules/generated/sklearn.metrics.accuracy_score.html"],
         )
 
-    def _compute(self, predictions, references):
+    def _compute(self, predictions, references, normalize=True, sample_weight=None):
         return {
             "accuracy": float(
-                accuracy_score(
-                    references, predictions, normalize=self.config.normalize, sample_weight=self.config.sample_weight
-                )
+                accuracy_score(references, predictions, normalize=normalize, sample_weight=sample_weight)
             )
         }

requirements.txt

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