chained residual pooling

[dkatsios]

Thanks for sharing
I think that at the chained residual pooling block there is a mistake.
Based on Fig. 3 of the paper, the input to the second, third etc. Pool layer is the output of the previous one, not the output of the ReLU layer:

def ChainedResidualPooling(inputs,features=256):
    net_relu=tf.nn.relu(inputs)
    net=slim.max_pool2d(net_relu, [5, 5],stride=1,padding='SAME')
    net=slim.conv2d(net,features,3)
    net_sum_1=tf.add(net,net_relu)

    # net = slim.max_pool2d(net_relu, [5, 5], stride=1, padding='SAME')
    net = slim.max_pool2d(net, [5, 5], stride=1, padding='SAME')

    net = slim.conv2d(net, features, 3)
    net_sum_2=tf.add(net,net_sum_1)

    return net_sum_2