class_docstr: Layer scale module.
  
  References:
  
  - https://arxiv.org/abs/2103.17239
  
  Args:
      init_values (float): Initial value for layer scale. Should be within
          [0, 1].
      projection_dim (int): Projection dimensionality.
  
  Returns:
      Tensor multiplied to the scale.
class_docstr_tok: ["Layer","scale","module",".","References",":","-","https",":","\/\/arxiv.org\/abs\/2103.17239","Args",":","init_values","(","float",")",":","Initial","value","for","layer","scale",".","Should","be","within","[","0",",","1","]",".","projection_dim","(","int",")",":","Projection","dimensionality",".","Returns",":","Tensor","multiplied","to","the","scale","."]
code: def get_config(self):
      config = super().get_config()
      config.update(
          {
              "init_values": self.init_values,
              "projection_dim": self.projection_dim,
          }
      )
      return config
  
imports: import numpy
  from keras import backend
  from keras import initializers
  from keras import layers
  from keras import ops
  from keras import random
  from keras.api_export import keras_export
  from keras.applications import imagenet_utils
  from keras.layers.layer import Layer
  from keras.models import Functional
  from keras.models import Sequential
  from keras.ops import operation_utils
  from keras.utils import file_utils
label_desc: Use image node_id 4 for calling the LayerScale obj's underlying member method code with example usage: obj.get_config() and returns: config