code: def __call__(self, y_true, y_pred):
      raise NotImplementedError(
          "Custom Metrics must implement this function"
      )
  
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 for calling the Metric obj's underlying member method code with example usage: obj.__call__(y_true, y_pred) without return types