def create_simple_cnn_ln(input_shape, kernel_regularizer=None):
    common_params = dict(filters=32, kernel_size=3, kernel_regularizer=kernel_regularizer)
    return Sequential([Conv2D(input_shape=input_shape, **common_params), LayerNormalization(), Activation('relu'), Conv2D(**common_params), LayerNormalization(), Activation('relu'), Conv2D(**common_params), LayerNormalization(), Activation('relu'), Conv2D(**common_params), LayerNormalization(), Activation('relu'), Conv2D(**common_params), LayerNormalization()])
def create_simple_cnn_ln(input_shape, kernel_regularizer=None):
    common_params = dict(filters=32, kernel_size=3, kernel_regularizer=kernel_regularizer)
    return Sequential([Conv2D(input_shape=input_shape, **common_params), LayerNormalization(), Activation('relu'), Conv2D(**common_params), LayerNormalization(), Activation('relu'), Conv2D(**common_params), LayerNormalization(), Activation('relu'), Conv2D(**common_params), LayerNormalization(), Activation('relu'), Conv2D(**common_params), LayerNormalization()])