Update Space (evaluate main: c447fc8e)

requirements.txt

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

seqeval.py

@@ -14,7 +14,6 @@
 """ seqeval metric. """
 
 import importlib
-from dataclasses import dataclass
 from typing import List, Optional, Union
 
 import datasets
@@ -100,31 +99,14 @@ Examples:
 """
 
 
-@dataclass
-class SeqevalConfig(evaluate.info.Config):
-
-    name: str = "default"
-
-    suffix: bool = False
-    scheme: Optional[str] = None
-    mode: Optional[str] = None
-    sample_weight: Optional[List[int]] = None
-    zero_division: Union[str, int] = "warn"
-
-
 @evaluate.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION)
 class Seqeval(evaluate.Metric):
-
-    CONFIG_CLASS = SeqevalConfig
-    ALLOWED_CONFIG_NAMES = ["default"]
-
-    def _info(self, config):
+    def _info(self):
         return evaluate.MetricInfo(
             description=_DESCRIPTION,
             citation=_CITATION,
             homepage="https://github.com/chakki-works/seqeval",
             inputs_description=_KWARGS_DESCRIPTION,
-            config=config,
             features=datasets.Features(
                 {
                     "predictions": datasets.Sequence(datasets.Value("string", id="label"), id="sequence"),
@@ -139,26 +121,27 @@ class Seqeval(evaluate.Metric):
         self,
         predictions,
         references,
+        suffix: bool = False,
+        scheme: Optional[str] = None,
+        mode: Optional[str] = None,
+        sample_weight: Optional[List[int]] = None,
+        zero_division: Union[str, int] = "warn",
     ):
-        if self.config.scheme is not None:
+        if scheme is not None:
             try:
                 scheme_module = importlib.import_module("seqeval.scheme")
-                scheme = getattr(scheme_module, self.config.scheme)
+                scheme = getattr(scheme_module, scheme)
             except AttributeError:
-                raise ValueError(
-                    f"Scheme should be one of [IOB1, IOB2, IOE1, IOE2, IOBES, BILOU], got {self.config.scheme}"
-                )
-        else:
-            scheme = self.config.scheme
+                raise ValueError(f"Scheme should be one of [IOB1, IOB2, IOE1, IOE2, IOBES, BILOU], got {scheme}")
         report = classification_report(
             y_true=references,
             y_pred=predictions,
-            suffix=self.config.suffix,
+            suffix=suffix,
             output_dict=True,
             scheme=scheme,
-            mode=self.config.mode,
-            sample_weight=self.config.sample_weight,
-            zero_division=self.config.zero_division,
+            mode=mode,
+            sample_weight=sample_weight,
+            zero_division=zero_division,
         )
         report.pop("macro avg")
         report.pop("weighted avg")