class_docstr: A speaker model with ResNet layers. 
class_docstr_tok: ["A","speaker","model","with","ResNet","layers","."]
code: def prelu_layer(self, x, name, num_parameters=1, init=0.25):
      if num_parameters == 1:
          shape = 1
      else:
          shape = x.get_shape()[-1]
      alpha = tf.get_variable(
          name,
          shape=shape,
          dtype=x.dtype,
          initializer=tf.constant_initializer(init),
      )
      return tf.maximum(0.0, x) + alpha * tf.minimum(0.0, x)
  
imports: import math
  from absl import logging
  import delta.compat
  import tensorflow.keras.layers
  from delta import utils
  from delta.layers import common_layers
  from delta.models.base_model import RawModel
  from delta.utils.register import registers
  from delta.utils.loss.loss_utils import arcface_loss
  from delta.utils.hparam import HParams
label_desc: Use image node_id 4 for calling the SpeakerResNetRawModel obj's underlying member method code with example usage: obj.prelu_layer(x, name, num_parameters, init) and returns: unknown