class_docstr: The AUC Metric measures the area under the receiver-operating characteristic
  (ROC) curve for binary classification problems.
class_docstr_tok: ["The","AUC","Metric","measures","the","area","under","the","receiver-operating","characteristic","(","ROC",")","curve","for","binary","classification","problems","."]
code: def __init__(self, positive_label=1):
      super().__init__()
      self._positive_label = positive_label
      self._all_predictions = torch.FloatTensor()
      self._all_gold_labels = torch.LongTensor()
  
file_path: allennlp/allennlp/training/metrics/auc.py
imports: from typing import Optional
  import torch
  import torch.distributed
  from sklearn import metrics
  from allennlp.common.util import is_distributed
  from allennlp.common.checks import ConfigurationError
  from allennlp.training.metrics.metric import Metric
label_desc: Use image node_id 1 to create a new Auc object from inherited base classes: Metric with example: obj = Auc(positive_label)