unpooling.py

def unpool(pool, ind, ksize=[1, 2, 2, 1], scope='unpool'):
    """
       Unpooling layer after max_pool_with_argmax.
       Args:
           pool:   max pooled output tensor
           ind:      argmax indices (produced by tf.nn.max_pool_with_argmax)
           ksize:     ksize is the same as for the pool
       Return:
           unpool:    unpooling tensor
    """
    with tf.variable_scope(scope):
        input_shape = pool.get_shape().as_list()
        output_shape = (input_shape[0], input_shape[1] * ksize[1], input_shape[2] * ksize[2], input_shape[3])

        flat_input_size = np.prod(input_shape)
        flat_output_shape = [output_shape[0], output_shape[1] * output_shape[2] * output_shape[3]]

        pool_ = tf.reshape(pool, [flat_input_size])
        batch_range = tf.reshape(tf.range(output_shape[0], dtype=ind.dtype), shape=[input_shape[0], 1, 1, 1])
        b = tf.ones_like(ind) * batch_range
        b = tf.reshape(b, [flat_input_size, 1])
        ind_ = tf.reshape(ind, [flat_input_size, 1])
        ind_ = tf.concat([b, ind_], 1)

        ret = tf.scatter_nd(ind_, pool_, shape=flat_output_shape)
        ret = tf.reshape(ret, output_shape)
        return ret