(inputs, out_channel=32, name='resblock')
| 5 | |
| 6 | |
| 7 | def resblock(inputs, out_channel=32, name='resblock'): |
| 8 | |
| 9 | with tf.variable_scope(name): |
| 10 | |
| 11 | x = slim.convolution2d(inputs, out_channel, [3, 3], |
| 12 | activation_fn=None, scope='conv1') |
| 13 | x = tf.nn.leaky_relu(x) |
| 14 | x = slim.convolution2d(x, out_channel, [3, 3], |
| 15 | activation_fn=None, scope='conv2') |
| 16 | |
| 17 | return x + inputs |
| 18 | |
| 19 | |
| 20 |