How to use the mtcnn.layer_factory.LayerFactory function in mtcnn

def _config(self):
        layer_factory = LayerFactory(self)

        layer_factory.new_feed(name='data', layer_shape=(None, 48, 48, 3))
        layer_factory.new_conv(name='conv1', kernel_size=(3, 3), channels_output=32, stride_size=(1, 1),
                               padding='VALID', relu=False)
        layer_factory.new_prelu(name='prelu1')
        layer_factory.new_max_pool(name='pool1', kernel_size=(3, 3), stride_size=(2, 2))
        layer_factory.new_conv(name='conv2', kernel_size=(3, 3), channels_output=64, stride_size=(1, 1),
                               padding='VALID', relu=False)
        layer_factory.new_prelu(name='prelu2')
        layer_factory.new_max_pool(name='pool2', kernel_size=(3, 3), stride_size=(2, 2), padding='VALID')
        layer_factory.new_conv(name='conv3', kernel_size=(3, 3), channels_output=64, stride_size=(1, 1),
                               padding='VALID', relu=False)
        layer_factory.new_prelu(name='prelu3')
        layer_factory.new_max_pool(name='pool3', kernel_size=(2, 2), stride_size=(2, 2))
        layer_factory.new_conv(name='conv4', kernel_size=(2, 2), channels_output=128, stride_size=(1, 1),
                               padding='VALID', relu=False)

def _config(self):

        layer_factory = LayerFactory(self)

        layer_factory.new_feed(name='data', layer_shape=(None, 24, 24, 3))
        layer_factory.new_conv(name='conv1', kernel_size=(3, 3), channels_output=28, stride_size=(1, 1),
                               padding='VALID', relu=False)
        layer_factory.new_prelu(name='prelu1')
        layer_factory.new_max_pool(name='pool1', kernel_size=(3, 3), stride_size=(2, 2))
        layer_factory.new_conv(name='conv2', kernel_size=(3, 3), channels_output=48, stride_size=(1, 1),
                               padding='VALID', relu=False)
        layer_factory.new_prelu(name='prelu2')
        layer_factory.new_max_pool(name='pool2', kernel_size=(3, 3), stride_size=(2, 2), padding='VALID')
        layer_factory.new_conv(name='conv3', kernel_size=(2, 2), channels_output=64, stride_size=(1, 1),
                               padding='VALID', relu=False)
        layer_factory.new_prelu(name='prelu3')
        layer_factory.new_fully_connected(name="fc1", output_count=128, relu=False)  # shouldn't the name be "fc1"?
        layer_factory.new_prelu(name='prelu4')
        layer_factory.new_fully_connected(name='fc2-1', output_count=2, relu=False)   # shouldn't the name be "fc2-1"?

def _config(self):
        layer_factory = LayerFactory(self)

        layer_factory.new_feed(name='data', layer_shape=(None, None, None, 3))
        layer_factory.new_conv(name='conv1', kernel_size=(3, 3), channels_output=10, stride_size=(1, 1),
                               padding='VALID', relu=False)
        layer_factory.new_prelu(name='prelu1')
        layer_factory.new_max_pool(name='pool1', kernel_size=(2, 2), stride_size=(2, 2))
        layer_factory.new_conv(name='conv2', kernel_size=(3, 3), channels_output=16, stride_size=(1, 1),
                               padding='VALID', relu=False)
        layer_factory.new_prelu(name='prelu2')
        layer_factory.new_conv(name='conv3', kernel_size=(3, 3), channels_output=32, stride_size=(1, 1),
                               padding='VALID', relu=False)
        layer_factory.new_prelu(name='prelu3')
        layer_factory.new_conv(name='conv4-1', kernel_size=(1, 1), channels_output=2, stride_size=(1, 1), relu=False)
        layer_factory.new_softmax(name='prob1', axis=3)

        layer_factory.new_conv(name='conv4-2', kernel_size=(1, 1), channels_output=4, stride_size=(1, 1),

def __validate_padding(padding):
        if padding not in LayerFactory.AVAILABLE_PADDINGS:
            raise Exception("Padding {} not valid".format(padding))