class_docstr: Any iterable of (label, text_input) pairs qualifies as a ``Dataset``.
class_docstr_tok: ["Any","iterable","of","(","label",",","text_input",")","pairs","qualifies","as","a","``","Dataset","``","."]
docstr: Loads csv file, one line correspond one sample.
  
  :param csv_path: file path
  :param encoding: file's encoding, default: utf-8
  :param headers: file's headers, if None, make file's first line
      as headers. default: None
  :param sep: separator for each column. default: ','
  :param dropna: weather to ignore and drop invalid data,
      :if False, raise ValueError when reading invalid data. default: True
  :return:
docstr_tok: ["Loads","csv","file",",","one","line","correspond","one","sample",".",":","param","csv_path",":","file","path",":","param","encoding",":","file","'s","encoding",",","default",":","utf-8",":","param","headers",":","file","'s","headers",",","if","None",",","make","file","'s","first","line","as","headers",".","default",":","None",":","param","sep",":","separator","for","each","column",".","default",":","'",",","'",":","param","dropna",":","weather","to","ignore","and","drop","invalid","data",",",":","if","False",",","raise","ValueError","when","reading","invalid","data",".","default",":","True",":","return",":"]
code: def load_csv(
      self,
      csv_path,
      encoding="utf-8",
      headers=None,
      sep=",",
      dropna=True,
  ):
      r"""
      Loads csv file, one line correspond one sample.
  
      :param csv_path: file path
      :param encoding: file's encoding, default: utf-8
      :param headers: file's headers, if None, make file's first line
          as headers. default: None
      :param sep: separator for each column. default: ','
      :param dropna: weather to ignore and drop invalid data,
          :if False, raise ValueError when reading invalid data. default: True
      :return:
  
      """
      json_dics = []
      for line, json_dic in read_csv(
          csv_path,
          encoding=encoding,
          headers=headers,
          sep=sep,
          dropna=dropna,
      ):
          json_dics.append(json_dic)
  
      self.load(json_dics)
  
imports: from tqdm import tqdm
  from ...common.utils import logger
  from ..component.sample import Sample, CnSample
  from ...common.utils.load import task_class_load
  from ...common.settings import SAMPLE_PATH, NLP_TASK_MAP
  from ...common.utils.file_io import read_csv, read_json, save_csv, save_json
label_desc: Use image node_id 12 for calling the Dataset obj's underlying member method code with example usage: obj.load_csv(csv_path, encoding, headers, sep, dropna) without return types