class_docstr: Default configuration class to define some static types (based on configs/train_classifier.yaml)
code: def init(self):
      self.auto_balance_dataset = False
      self.exp_id = str(int(time.time() * 1000))
      self.mean_std = [
          [0.485, 0.456, 0.406],
          [0.229, 0.224, 0.225],
      ]  # imagenet default
      self.random_seed = 1337
      self.train_val_ratio = 0.8
      self.use_gpu = False
  
      self.keys_to_verify = [
          "batch_size",
          "dataroots",
          "input_size",
          "model_spec",
          "num_epochs",
          "optimizer",
          "output_root",
          "scheduler",
          "use_gpu",
          "workers",
      ]
  
imports: import time
  from typing import List
  from prodict import Prodict
label_desc: Use image node_id 1 for calling the ExpConfig obj's underlying member method code with example usage: obj.init() without return types