Function resblock

train_code/network.py:16–26

(inputs, out_channel=32, name='resblock')

def resblock(inputs, out_channel=32, name='resblock'):
    
    with tf.variable_scope(name):
        
        x = slim.convolution2d(inputs, out_channel, [3, 3], 
                               activation_fn=None, scope='conv1')
        x = tf.nn.leaky_relu(x)
        x = slim.convolution2d(x, out_channel, [3, 3], 
                               activation_fn=None, scope='conv2')
        
        return x + inputs