import tensorflow as tf

        pool = tf.transpose(pool, [0,2,1])
    # Linear
    elif downsampling_type=='linear':
        pool = tf.layers.conv1d(inputs=inputs, filters=inputs.get_shape()[2], kernel_size=3,
                            strides=2, padding='same', use_bias=False)
    # Maxpooling
    else:
        pool = tf.layers.max_pooling1d(inputs=inputs, pool_size=3, strides=2, padding='same', name=name)
    if optional_shortcut:
        shortcut = tf.layers.conv1d(inputs=shortcut, filters=shortcut.get_shape()[2], kernel_size=1,
                            strides=2, padding='same', use_bias=False)
        print("-"*5)
        print("Optional Downsampling Shortcut:", shortcut.get_shape())
        print("-"*5)
