import tensorflow as tf

            channel_axis = 3 if data_format == 'channels_last' else 1
            in_channel = in_shape[channel_axis]
            assert in_channel is not None, "[Deconv2D] Input cannot have unknown channel!"

            padding = padding.upper()

            if w_init is None:
                w_init = tf.contrib.layers.variance_scaling_initializer()
            if b_init is None:
                b_init = tf.constant_initializer()

            ret = tf.layers.conv2d_transpose(inputs=inputdata, filters=out_channel,
                                             kernel_size=kernel_size,
                                             strides=stride, padding=padding,
                                             data_format=data_format,
                                             activation=activation, use_bias=use_bias,
                                             kernel_initializer=w_init,
                                             bias_initializer=b_init, trainable=trainable,
