class_docstr: DEPRECATED.
class_docstr_tok: ["DEPRECATED","."]
code: def call(self, inputs, training=False):
      if training and self.rate > 0:
          alpha = 1.6732632423543772848170429916717
          scale = 1.0507009873554804934193349852946
          alpha_p = -alpha * scale
  
          if self.noise_shape is None:
              noise_shape = tf.shape(inputs)
          else:
              noise_shape = self.noise_shape
          kept_idx = tf.greater_equal(
              backend.random.uniform(noise_shape),
              self.rate,
              seed=self.seed_generator,
          )
          kept_idx = tf.cast(kept_idx, inputs.dtype)
  
          # Get affine transformation params
          a = ((1 - self.rate) * (1 + self.rate * alpha_p**2)) ** -0.5
          b = -a * alpha_p * self.rate
  
          # Apply mask
          x = inputs * kept_idx + alpha_p * (1 - kept_idx)
  
          # Do affine transformation
          return a * x + b
      return inputs
  
imports: from keras import backend
  from keras.api_export import keras_export
  from keras.layers.layer import Layer
  from keras.utils.module_utils import tensorflow
label_desc: Use image node_id 2 for calling the AlphaDropout obj's underlying member method code with example usage: obj.call(inputs, training) and returns: inputs, unknown