class_docstr: Class to append newly compute training metrics to a csv file
  for data logging.
  Is used together with the LOGGER class.
class_docstr_tok: ["Class","to","append","newly","compute","training","metrics","to","a","csv","file","for","data","logging",".","Is","used","together","with","the","LOGGER","class","."]
docstr: Args:
      save_path: str, where to store the csv file
      columns:   list of str, name of csv columns under which the resp. metrics are stored.
  Returns:
      Nothing!
docstr_tok: ["Args",":","save_path",":","str",",","where","to","store","the","csv","file","columns",":","list","of","str",",","name","of","csv","columns","under","which","the","resp",".","metrics","are","stored",".","Returns",":","Nothing","!"]
code: def __init__(self, save_path, columns):
      """
      Args:
          save_path: str, where to store the csv file
          columns:   list of str, name of csv columns under which the resp. metrics are stored.
      Returns:
          Nothing!
      """
      self.save_path = save_path
      self.columns = columns
  
      with open(self.save_path, "a") as csv_file:
          writer = csv.writer(csv_file, delimiter=",")
          writer.writerow(self.columns)
  
imports: import warnings
  import csv
  import datetime
  import os
  import pickle
  import faiss
  import matplotlib.pyplot
  import numpy
  import torch
  from PIL import Image
  from sklearn import metrics
  from torch import nn
  from tqdm import tqdm
  import pdb
label_desc: Use image node_id 1 to create a new CSV_Writer object  with example: obj = CSV_Writer(save_path, columns)