import tensorflow as tf

        :param kernel_size:
        :param name:
        :param depth_multiplier:
        :param padding:
        :param stride:
        :return:
        """
        with tf.variable_scope(name_or_scope=name):
            in_shape = input_tensor.get_shape().as_list()
            in_channel = in_shape[3]
            padding = padding.upper()

            depthwise_filter_shape = [kernel_size, kernel_size] + [in_channel, depth_multiplier]
            w_init = tf.contrib.layers.variance_scaling_initializer()
