Possible bug with is_training parameter
lucgiffon opened this issue · 0 comments
Hello,
Going through the code of your project, I think the parameter is_training
is not taken into account for the CNN model in file mnist_cnn_train.py
.
I've seen that the cnn_model.CNN
function takes "is_training" argument with default equals True which prevent the code to crash.
In mnist_cnn_train
, you define the is_training placeholder but you don't use it when calling the cnn_model.CNN
function. You use it in the training and testing loops of the same file so I assume this is not an intended behavior.
I've not tested it yet, but I think the is_training
entry of the feed_dict
is just ignored and this cause dropout to be applied during the testing loop (same goes for batch normalization). This bug could be the cause of the issue #1