class_docstr: Class to abstract the normalization that is used.
code: def __init__(self, norm_name, norm_params):
      if norm_name == "batchnorm":
          self.norm = tf.keras.layers.BatchNormalization
      else:
          raise ValueError(f"Norm type {norm_name} not recognized.")
  
      # To finetune without modifying the BN 'trainable': False
      self.params = {
          **norm_params,
          **{"name": "batchnorm", "epsilon": 1e-5, "momentum": 0.1},
      }
  
imports: import tensorflow
label_desc: Use image node_id 1 to create a new NormType object  with example: obj = NormType(norm_name, norm_params)