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 build(self, _):
      self.gamma = self.add_weight(
          shape=(self.projection_dim,),
          initializer=initializers.Constant(self.init_values),
          trainable=True,
      )
  
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 2 for calling the LayerScale obj's underlying member method code with example usage: obj.build(_) without return types