title: Weights/cost after 'Unsupervised Pre-Training' of DBN with/without Dropout
body: <p>Do weights/cost of each layer obtained after 'Unsupervised Pre-Training' of a Deep Belief Network differ when dropout is applied and when it isn't ?</p>
  
  <p>I have obtained different sets of weights and different value of cost after pre training a DBN with and without applying Dropout.
  According to me, Dropping out units should affect only the fine tuning stage and not the Unsupervised pre training where all units are required and none is dropped. Am I getting the concept wrong or the code wrong?</p>