Statefarm kaggle comp

Part 1 (2017)
48

So this is my batch_norm fn:

def bn_get_layers(p=0.):
    layers = [MaxPooling2D(input_shape=conv_layers[-1].output_shape[1:]),
             Flatten(),
             Dense(4096,activation='relu'),
             Dropout(p),
             BatchNormalization(mode=2),
             Dense(4096,activation='relu'),
             Dropout(p),
             BatchNormalization(mode=2),
             Dense(10,activation='softmax')]
    
    return layers

Reading your state farm sample notebook, I noticed axis=1 is only present in the convolution part and not the dense layer. BatchNormalization(axis = 1) when used on convolutional layers