class_docstr: A Table Dataset, load data from a give csv path, or transform FATE DTable
  
  Parameters
  ----------
  label_col str, name of label column in csv, if None, will automatically take 'y' or 'label' or 'target' as label
  match_id_col str, name of match id column in csv, if None, will automatically take 'id' or 'sid' as match id
  sample_id_col str, name of sample id column in csv, if None, will automatically generate sample id
  feature_dtype str, dtype of features, available: 'long', 'int', 'float', 'double'
  label_dtype str, dtype of label, available: 'long', 'int', 'float', 'double'
  label_shape tuple or list, shape of label, if None, will automatically infer from data
  flatten_label bool, whether to flatten label, if True, will flatten label to 1-d array
  to_tensor bool, whether to transform data to pytorch tensor, if True, will transform data to tensor
  return_dict bool, whether to return a dict in the format of {'x': xxx, 'label': xxx} if True, will return a dict, else will return a tuple
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code: def get_match_id_name(self) -> str:
      if self.match_ids is not None and isinstance(
          self.match_ids, pd.DataFrame
      ):
          return self.match_ids.columns[0]
      else:
          raise ValueError("Cannot get match id name")
  
file_path: FATE/python/fate/ml/nn/dataset/table.py
imports: import numpy
  import pandas
  from fate.arch.dataframe import DataFrame
  from fate.ml.nn.dataset.base import Dataset
  import logging
  import torch
label_desc: Use image node_id 10 for calling the TableDataset obj's underlying member method code with example usage: obj.get_match_id_name() and returns: self