Update Space (evaluate main: c447fc8e)

requirements.txt

@@ -1,2 +1,2 @@
-git+https://github.com/huggingface/evaluate.git@e4a2724377909fe2aeb4357e3971e5a569673b39
+git+https://github.com/huggingface/evaluate.git@c447fc8eda9c62af501bfdc6988919571050d950
 nltk~=3.7

word_length.py

@@ -12,9 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from dataclasses import dataclass
 from statistics import mean
-from typing import Callable, Optional
 
 import datasets
 from nltk import word_tokenize
@@ -54,22 +52,11 @@ year={2020}
 """
 
 
-@dataclass
-class WordLengthConfig(evaluate.info.Config):
-
-    name: str = "default"
-
-    tokenizer: Optional[Callable] = None
-
-
 @evaluate.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION)
 class WordLength(evaluate.Measurement):
     """This measurement returns the average number of words in the input string(s)."""
 
-    CONFIG_CLASS = WordLengthConfig
-    ALLOWED_CONFIG_NAMES = ["default"]
-
-    def _info(self, config):
+    def _info(self):
         # TODO: Specifies the evaluate.MeasurementInfo object
         return evaluate.MeasurementInfo(
             # This is the description that will appear on the modules page.
@@ -77,7 +64,6 @@ class WordLength(evaluate.Measurement):
             description=_DESCRIPTION,
             citation=_CITATION,
             inputs_description=_KWARGS_DESCRIPTION,
-            config=config,
             # This defines the format of each prediction and reference
             features=datasets.Features(
                 {
@@ -91,12 +77,8 @@ class WordLength(evaluate.Measurement):
 
         nltk.download("punkt")
 
-    def _compute(self, data):
+    def _compute(self, data, tokenizer=word_tokenize):
         """Returns the average word length of the input data"""
-        if self.config.tokenizer is None:
-            tokenizer = word_tokenize
-        else:
-            tokenizer = self.config.tokenizer
         lengths = [len(tokenizer(d)) for d in data]
         average_length = mean(lengths)
         return {"average_word_length": average_length}