code: def set_regularization(
      model,
      kernel_regularizer=None,
      bias_regularizer=None,
      activity_regularizer=None,
      beta_regularizer=None,
      gamma_regularizer=None,
      **kwargs,
  ):
      """Set regularizers to all layers
  
      Note:
         Returned model's config is updated correctly
  
      Args:
          model (``keras.models.Model``): instance of keras model
          kernel_regularizer(``regularizer`): regularizer of kernels
          bias_regularizer(``regularizer``): regularizer of bias
          activity_regularizer(``regularizer``): regularizer of activity
          gamma_regularizer(``regularizer``): regularizer of gamma of BatchNormalization
          beta_regularizer(``regularizer``): regularizer of beta of BatchNormalization
  
      Return:
          out (``Model``): config updated model
      """
      _, _, models, _ = get_submodules_from_kwargs(kwargs)
  
      for layer in model.layers:
          # set kernel_regularizer
          if kernel_regularizer is not None and hasattr(
              layer, "kernel_regularizer"
          ):
              layer.kernel_regularizer = kernel_regularizer
          # set bias_regularizer
          if bias_regularizer is not None and hasattr(
              layer, "bias_regularizer"
          ):
              layer.bias_regularizer = bias_regularizer
          # set activity_regularizer
          if activity_regularizer is not None and hasattr(
              layer, "activity_regularizer"
          ):
              layer.activity_regularizer = activity_regularizer
  
          # set beta and gamma of BN layer
          if beta_regularizer is not None and hasattr(
              layer, "beta_regularizer"
          ):
              layer.beta_regularizer = beta_regularizer
  
          if gamma_regularizer is not None and hasattr(
              layer, "gamma_regularizer"
          ):
              layer.gamma_regularizer = gamma_regularizer
  
      out = models.model_from_json(model.to_json())
      out.set_weights(model.get_weights())
  
      return out
  
label_desc: Use image node_id 2 for calling a global function with example usage: set_regularization(model, kernel_regularizer, bias_regularizer, activity_regularizer, beta_regularizer, gamma_regularizer) and returns: out