code: def log_norms(self):
      lines = ["NORMS FOR MODEL PARAMTERS"]
      for name, param in self.named_parameters():
          if param.requires_grad and name.split(".")[0] not in (
              "charmodel_forward",
              "charmodel_backward",
          ):
              lines.append(
                  "  %s %.6g" % (name, torch.norm(param).item())
              )
      logger.info("\n".join(lines))
  
file_path: stanza/stanza/models/pos/model.py
imports: import logging
  import os
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn.utils.rnn import pad_packed_sequence, pack_padded_sequence, pack_sequence, pad_sequence, PackedSequence
  from stanza.models.common.bert_embedding import extract_bert_embeddings
  from stanza.models.common.biaffine import BiaffineScorer
  from stanza.models.common.foundation_cache import load_bert, load_charlm
  from stanza.models.common.hlstm import HighwayLSTM
  from stanza.models.common.dropout import WordDropout
  from stanza.models.common.vocab import CompositeVocab
  from stanza.models.common.char_model import CharacterModel
label_desc: Use image node_id 2 for calling the Tagger obj's underlying member method code with example usage: obj.log_norms() without return types