code style update

ece.py

@@ -17,7 +17,10 @@ from typing import Dict
 import evaluate
 import datasets
 from torch import from_numpy, amax
-from torchmetrics.functional.classification.calibration_error import binary_calibration_error, multiclass_calibration_error
+from torchmetrics.functional.classification.calibration_error import (
+    binary_calibration_error,
+    multiclass_calibration_error,
+)
 from numpy import ndarray
 
 
@@ -75,15 +78,21 @@ class ECE(evaluate.Metric):
             citation=_CITATION,
             inputs_description=_KWARGS_DESCRIPTION,
             # This defines the format of each prediction and reference
-            features=datasets.Features({
-                'predictions': datasets.Sequence(datasets.Value('float32')),
-                'references': datasets.Value('int64'),
-            }),
+            features=datasets.Features(
+                {
+                    "predictions": datasets.Sequence(datasets.Value("float32")),
+                    "references": datasets.Value("int64"),
+                }
+            ),
             # Homepage of the module for documentation
             homepage="https://huggingface.co/spaces/Natooz/ece",
             # Additional links to the codebase or references
-            codebase_urls=["https://github.com/Lightning-AI/torchmetrics/blob/v0.11.4/src/torchmetrics/classification/calibration_error.py"],
-            reference_urls=["https://torchmetrics.readthedocs.io/en/stable/classification/calibration_error.html"]
+            codebase_urls=[
+                "https://github.com/Lightning-AI/torchmetrics/blob/v0.11.4/src/torchmetrics/classification/calibration_error.py"
+            ],
+            reference_urls=[
+                "https://torchmetrics.readthedocs.io/en/stable/classification/calibration_error.html"
+            ],
         )
 
     def _compute(self, predictions=None, references=None, **kwargs) -> Dict[str, float]: