class_docstr: Args:
      dim (int): Number of input channels.
      drop_rate (float): Stochastic depth rate. Default: 0.0
      layer_scale_init_value (float): Init value for Layer Scale. Default: 1e-6.
code: def build(self, input_shape):
      if self.layer_scale_init_value > 0:
          self.gamma = self.add_weight(
              shape=[input_shape[-1]],
              initializer=initializers.Constant(
                  self.layer_scale_init_value
              ),
              trainable=True,
              dtype=tf.float32,
              name="gamma",
          )
      else:
          self.gamma = None
  
imports: import numpy
  import tensorflow
  from tensorflow.keras import layers, initializers, Model
label_desc: Use image node_id 2 for calling the Block obj's underlying member method code with example usage: obj.build(input_shape) without return types