import tensorflow as tf


        x = tf.nn.conv2d(input, filters, strides=[1, stride, stride, 1], padding=padding, name='zero-conv_' + id,
                        dilations=(1, dilation, dilation, 1))
        if use_bias:
            bias = tf.get_variable("bias", [channels], initializer=tf.constant_initializer(0.0))
            x = tf.nn.bias_add(x, bias)
        return x
        
    def t_conv(self, id, input, channels, size=3, stride=1, use_bias=True, padding="SAME", init_stddev=-1.0):
            # good old t-conv. I love it!
