Classification of MNIST_data using CNN or batch normalized CNN
Train CNN with TF-slim which can batch normalization
python main.py cnn_normal
or python main.py cnn_batch_norm
Required
select_net
: select cnn_norm or cnn_batch_norm
Optional
--activation_func
: choice(sigmoid, relu, lrelu). Default :relu
--feature_map1
: Number of feature map1. Default :64
--feature_map2
: Number of feature map2. Default :128
--feature_map3
: Number of feature map3. Default :256
--filter_size
: size of filter. Default :3
--pool_size
: size of max_pooling. Default :2
--epoch
: Number of epochs to run. Default :10
--batch_size
: Number of batch_size to run. Default :100
--learning_rate
: Learning rate for Adam optimizer. Default :0.001
--drop_rate
: Prob of dropout. Default :0.7
python main.py cnn_batch_norm