class_docstr: Unsupervised metric
class_docstr_tok: ["Unsupervised","metric"]
code: def __init__(self):
      self._name = "unsup_loss"
      self._maximize = False
  
imports: from dataclasses import dataclass
  from typing import List
  import numpy
  from sklearn.metrics import roc_auc_score, mean_squared_error, mean_absolute_error, accuracy_score, log_loss, balanced_accuracy_score, mean_squared_log_error
  import torch
label_desc: Use image node_id 1 to create a new UnsupervisedMetric object from inherited base classes: Metric with example: obj = UnsupervisedMetric()