class_docstr: Reads in the STS dataset. Each line contains two sentences (s1_col_idx, s2_col_idx) and one label (score_col_idx)
  
  Default values expects a tab separated file with the first & second column the sentence pair and third column the score (0...1). Default config normalizes scores from 0...5 to 0...1
code: def __init__(
      self,
      dataset_folder,
      s1_col_idx=0,
      s2_col_idx=1,
      score_col_idx=2,
      delimiter="\t",
      quoting=csv.QUOTE_NONE,
      normalize_scores=True,
      min_score=0,
      max_score=5,
  ):
      self.dataset_folder = dataset_folder
      self.score_col_idx = score_col_idx
      self.s1_col_idx = s1_col_idx
      self.s2_col_idx = s2_col_idx
      self.delimiter = delimiter
      self.quoting = quoting
      self.normalize_scores = normalize_scores
      self.min_score = min_score
      self.max_score = max_score
  
file_path: sentence-transformers/sentence_transformers/readers/STSDataReader.py
imports: from .None import InputExample
  import csv
  import gzip
  import os
label_desc: Use image node_id 1 to create a new STSDataReader object  with example: obj = STSDataReader(dataset_folder, s1_col_idx, s2_col_idx, score_col_idx, delimiter, quoting, normalize_scores, min_score, max_score)