class_docstr: Layer that applies an update to the cost function based input activity.
  
  Args:
      l1: L1 regularization factor (positive float).
      l2: L2 regularization factor (positive float).
  
  Input shape:
      Arbitrary. Use the keyword argument `input_shape`
      (tuple of integers, does not include the samples axis)
      when using this layer as the first layer in a model.
  
  Output shape:
      Same shape as input.
code: def get_config(self):
      base_config = super().get_config()
      config = {"l1": self.l1, "l2": self.l2}
      return {**base_config, **config}
  
file_path: keras/keras/layers/regularization/activity_regularization.py
imports: from keras import regularizers
  from keras.api_export import keras_export
  from keras.layers.layer import Layer
label_desc: Use image node_id 4 for calling the ActivityRegularization obj's underlying member method code with example usage: obj.get_config() and returns: dict