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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def weight_decay_and_noise(loss, hparams, learning_rate, var_list=None):
 """Apply weight decay and weight noise."""

  if var_list is None:
    var_list = tf.trainable_variables()

  decay_vars = [v for v in var_list]
  noise_vars = [v for v in var_list if "/body/" in v.name]

  weight_decay_loss = weight_decay(hparams.weight_decay, decay_vars)
  if hparams.weight_decay and common_layers.should_generate_summaries():
    tf.summary.scalar("losses/weight_decay", weight_decay_loss)
  weight_noise_ops = weight_noise(hparams.weight_noise, learning_rate,
                                  noise_vars)

  with tf.control_dependencies(weight_noise_ops):
    loss = tf.identity(loss)

  loss += weight_decay_loss
  return loss