class_docstr: Generic processor for a single sentence classification data set.
class_docstr_tok: ["Generic","processor","for","a","single","sentence","classification","data","set","."]
code: def add_examples_from_csv(
      self,
      file_name,
      split_name="",
      column_label=0,
      column_text=1,
      column_id=None,
      skip_first_row=False,
      overwrite_labels=False,
      overwrite_examples=False,
  ):
      lines = self._read_tsv(file_name)
      if skip_first_row:
          lines = lines[1:]
      texts = []
      labels = []
      ids = []
      for i, line in enumerate(lines):
          texts.append(line[column_text])
          labels.append(line[column_label])
          if column_id is not None:
              ids.append(line[column_id])
          else:
              guid = f"{split_name}-{i}" if split_name else str(i)
              ids.append(guid)
  
      return self.add_examples(
          texts,
          labels,
          ids,
          overwrite_labels=overwrite_labels,
          overwrite_examples=overwrite_examples,
      )
  
imports: import csv
  import dataclasses
  import json
  from dataclasses import dataclass
  from typing import List, Optional, Union
  from ...utils import is_tf_available, is_torch_available, logging
label_desc: Use image node_id 6 for calling the SingleSentenceClassificationProcessor obj's underlying member method code with example usage: obj.add_examples_from_csv(file_name, split_name, column_label, column_text, column_id, skip_first_row, overwrite_labels, overwrite_examples) and returns: self