def latent_code_discriminator_two_layers(in_signal, layer_sizes=[256, 512], b_norm=False, non_linearity=tf.nn.relu, reuse=False, scope=None):
    ' Used in ICML submission.\n    '
    layer_sizes = (layer_sizes + [1])
    d_logit = decoder_with_fc_only(in_signal, layer_sizes=layer_sizes, non_linearity=non_linearity, b_norm=b_norm, reuse=reuse, scope=scope)
    d_prob = tf.nn.sigmoid(d_logit)
    return (d_prob, d_logit)
Used in ICML submission.
def latent_code_discriminator_two_layers(in_signal, layer_sizes=[256, 512], b_norm=False, non_linearity=tf.nn.relu, reuse=False, scope=None):
    ' \n    '
    layer_sizes = (layer_sizes + [1])
    d_logit = decoder_with_fc_only(in_signal, layer_sizes=layer_sizes, non_linearity=non_linearity, b_norm=b_norm, reuse=reuse, scope=scope)
    d_prob = tf.nn.sigmoid(d_logit)
    return (d_prob, d_logit)