import tensorflow as tf

               stddev=1e-2,
               strides=[1, 1, 1, 1],
               padding="SAME",
               nonlinearity=None,
               bias=False,
               weight_norm=False,
               scale=False):
    """Convolutional layer."""
    with tf.variable_scope(name) as scope:
        weights = variable_on_cpu(
            "weights",
            filter_size + [dim_in, dim_out],
            tf.random_uniform_initializer(
                minval=-stddev, maxval=stddev))
        # weight normalization
        if weight_norm:
