code: def run_procedure(args):
      do_training(args)
  
imports: import argparse
  import io
  import os
  import torch
  from torch.utils.data import DataLoader, RandomSampler, SequentialSampler
  from nlp_architect.data.sequential_tagging import TokenClsInputExample, TokenClsProcessor
  from nlp_architect.data.utils import write_column_tagged_file
  from nlp_architect.models.tagging import NeuralTagger
  from nlp_architect.nn.torch.modules.embedders import IDCNN, CNNLSTM
  from nlp_architect.nn.torch import setup_backend, set_seed
  from nlp_architect.nn.torch.distillation import TeacherStudentDistill
  from nlp_architect.procedures.procedure import Procedure
  from nlp_architect.procedures.registry import register_train_cmd, register_inference_cmd
  from nlp_architect.utils.embedding import get_embedding_matrix, load_embedding_file
  from nlp_architect.utils.io import prepare_output_path
  from nlp_architect.utils.text import SpacyInstance
  from nlp_architect.nn.torch.data.dataset import ParallelDataset, ConcatTensorDataset, CombinedTensorDataset
  from nlp_architect.models.transformers import TransformerTokenClassifier
label_desc: Use image node_id 2 for calling the TrainTagger obj's underlying member method code with example usage: obj.run_procedure(args) without return types