code: def forward(self, x):
      out = self.network(x)
      out = torch.squeeze(out, 1)
      return out
  
imports: from copy import deepcopy
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  from sklearn.metrics import roc_auc_score
  from sklearn.model_selection import train_test_split
  from sklearn.neighbors import NearestNeighbors
  from sklearn.preprocessing import MinMaxScaler
  from sklearn.utils.validation import check_is_fitted
  from .base import BaseDetector
label_desc: Use image node_id 2 for calling the SCORE_MODEL obj's underlying member method code with example usage: obj.forward(x) and returns: out