code: def _concat_labels_column(dataset, target_column, classes):
      """Concatenate labels column for multilabel models.
  
      :param dataset: The dataset including the label column.
      :type dataset: pandas.DataFrame
      :param target_column: The list of label columns in multilabel task.
      :type target_column: list[str]
      :param classes: The list of labels in multilabel task.
      :type classes: list
      :return: The labels column concatenated.
      :rtype: list
      """
      labels = []
      for _, row in dataset[target_column].iterrows():
          row_idxs = range(len(row))
          pred_classes = [classes[i] for i in row_idxs if row[i]]
          labels.append(",".join(pred_classes))
      return labels
  
imports: import json
  import numbers
  from typing import Any, List, Optional, Union
  import jsonschema
  import numpy
  import pandas
  from ml_wrappers import wrap_model
  from erroranalysis._internal.error_analyzer import ModelAnalyzer
  from erroranalysis._internal.error_report import as_error_report
  from responsibleai._tools.shared.state_directory_management import DirectoryManager
  from responsibleai.exceptions import UserErrorException
  from responsibleai.managers.error_analysis_manager import ErrorAnalysisManager
  from responsibleai.managers.error_analysis_manager import as_error_config
  from responsibleai_text.common.constants import ModelTask
  from responsibleai_text.utils.feature_extractors import get_text_columns
label_desc: Use image node_id 1 for calling a global function with example usage: _concat_labels_column(dataset, target_column, classes) and returns: labels