models.py 文件源码

def uppool(value, name='uppool'):  # TODO TBD??
    """N-dimensional version of the unpooling operation from
    https://www.robots.ox.ac.uk/~vgg/rg/papers/Dosovitskiy_Learning_to_Generate_2015_CVPR_paper.pdf
    Note that the only dimension that can be unspecified is the first one (b)

    :param name:
    :param value: A Tensor of shape [b, d0, d1, ..., dn, ch]
    :return: A Tensor of shape [b, 2*d0, 2*d1, ..., 2*dn, ch]

    """
    with tf.name_scope(name) as scope:
        sh = value.get_shape().as_list()
        dim = len(sh[1:-1])
        print(value)
        out = (tf.reshape(value, [-1] + sh[-dim:]))
        for i in range(dim, 0, -1):
            # out = tf.concat(i, [out, tf.zeros_like(out)])  #original implementation added zeros
            out = tf.concat([out, tf.identity(out)], i)  # copies values
        out_size = [-1] + [s * 2 for s in sh[1:-1]] + [sh[-1]]
        out = tf.reshape(out, out_size, name=scope)
    return out