code: def _sklearn_accuracy(target, preds):
      score = sk_accuracy(target, preds)
      return score if not np.isnan(score) else 0.0
  
imports: from functools import partial
  import numpy
  import pytest
  import torch
  from scipy.special import expit
  from sklearn.metrics import accuracy_score
  from sklearn.metrics import confusion_matrix
  from torchmetrics.classification.accuracy import Accuracy, BinaryAccuracy, MulticlassAccuracy, MultilabelAccuracy
  from torchmetrics.functional.classification.accuracy import accuracy, binary_accuracy, multiclass_accuracy, multilabel_accuracy
  from torchmetrics.metric import Metric
  from unittests import NUM_CLASSES, THRESHOLD
  from unittests.classification.inputs import _binary_cases, _input_binary, _multiclass_cases, _multilabel_cases
  from unittests.helpers import seed_all
  from unittests.helpers.testers import MetricTester, inject_ignore_index, remove_ignore_index
label_desc: Use image node_id 1 for calling a global function with example usage: _sklearn_accuracy(target, preds) and returns: unknown