Why disable dropout during validation and testing? : <p>I've seen in multiple places that you should disable dropout during validation and testing stages and only keep it during the training phase. Is there a reason why that should happen? I haven't been able to find a good reason for that and was just wondering.</p>

<p>One reason I'm asking is because I trained a model with dropout, and the results turned out well - about 80% accuracy. Then, I went on to validate the model but forgot to set the prob to 1 and the model's accuracy went down to about 70%. Is it supposed to be that drastic? And is it as simple as setting the prob to 1 in each dropout layer?</p>

<p>Thanks in advance!</p>
