code: def get_neural_net_reg_doc(doc):
      doc = neural_net_reg_doc_start + " " + doc.split("\n ", 4)[-1]
      pattern = re.compile(r"(\n\s+)(criterion .*\n)(\s.+){1,99}")
      start, end = pattern.search(doc).span()
      doc = doc[:start] + neural_net_reg_criterion_text + doc[end:]
      return doc
  
file_path: skorch/skorch/regressor.py
imports: import re
  from sklearn.base import RegressorMixin
  import torch
  from torch.utils.data import DataLoader
  from skorch import NeuralNet
  from skorch.utils import get_dim
  from skorch.utils import is_dataset
label_desc: Use image node_id 1 for calling a global function with example usage: get_neural_net_reg_doc(doc) and returns: doc