class_docstr: _id, batch normalization, activation, dropout, ready
class_docstr_tok: ["_id",",","batch","normalization",",","activation",",","dropout",",","ready"]
docstr: beta: mean scale
  gamma: variance scale
  y = gamma * (x - moving_mean) / sqrt(epsilon + moving_variance) + beta
docstr_tok: ["beta",":","mean","scale","gamma",":","variance","scale","y","=","gamma","*","(","x","-","moving_mean",")","\/","sqrt","(","epsilon","+","moving_variance",")","+","beta"]
code: def variable_list(self):
      """
      beta: mean scale
      gamma: variance scale
      y = gamma * (x - moving_mean) / sqrt(epsilon + moving_variance) + beta
      """
      if self.use_bn:
          return {
              "moving_mean": "BatchNorm/moving_mean:0",
              "moving_variance": "BatchNorm/moving_variance:0",
              "beta": "BatchNorm/beta:0",
              "gamma": "BatchNorm/gamma:0",
          }
      else:
          return {}
  
imports: from models.basic_model import BasicModel
  import tensorflow
  import numpy
  import copy
label_desc: Use image node_id 9 for calling the BaseLayer obj's underlying member method code with example usage: obj.variable_list() and returns: dict, dict