(discriminator, real, fake, scale=1,channel=32, patch=False, name='discriminator')
| 147 | |
| 148 | |
| 149 | def gan_loss(discriminator, real, fake, scale=1,channel=32, patch=False, name='discriminator'): |
| 150 | |
| 151 | real_logit = discriminator(real, scale, channel, name=name, patch=patch, reuse=False) |
| 152 | fake_logit = discriminator(fake, scale, channel, name=name, patch=patch, reuse=True) |
| 153 | |
| 154 | real_logit = tf.nn.sigmoid(real_logit) |
| 155 | fake_logit = tf.nn.sigmoid(fake_logit) |
| 156 | |
| 157 | g_loss_blur = -tf.reduce_mean(tf.log(fake_logit)) |
| 158 | d_loss_blur = -tf.reduce_mean(tf.log(real_logit) + tf.log(1. - fake_logit)) |
| 159 | |
| 160 | return d_loss_blur, g_loss_blur |
| 161 | |
| 162 | |
| 163 |
nothing calls this directly
no outgoing calls
no test coverage detected