class_docstr: Original reference (MIT Licensed): https://github.com/gpleiss/temperature_scaling
  NB: Output of the neural network should be the classification logits, NOT the softmax (or log softmax)! TODO
code: def softmax(self, logits):
      return self._softmax(self.temperature_scale(logits))
  
file_path: lightwood/lightwood/analysis/nn_conf/temp_scale.py
imports: from copy import deepcopy
  from typing import Dict, Tuple
  from types import SimpleNamespace
  import torch
  import pandas
  from torch import nn, optim
  from sklearn.preprocessing import OrdinalEncoder
  from lightwood.helpers.log import log
  from lightwood.analysis.base import BaseAnalysisBlock
label_desc: Use image node_id 3 for calling the TempScaler obj's underlying member method code with example usage: obj.softmax(logits) and returns: self