Helper function for init_opt
(self)
| 188 | self.log_vars.append(("d_learning_rate", self.discriminator_lr)) |
| 189 | |
| 190 | def define_summaries(self): |
| 191 | '''Helper function for init_opt''' |
| 192 | all_sum = {'g': [], 'd': [], 'hist': []} |
| 193 | for k, v in self.log_vars: |
| 194 | if k.startswith('g'): |
| 195 | all_sum['g'].append(tf.scalar_summary(k, v)) |
| 196 | elif k.startswith('d'): |
| 197 | all_sum['d'].append(tf.scalar_summary(k, v)) |
| 198 | elif k.startswith('hist'): |
| 199 | all_sum['hist'].append(tf.histogram_summary(k, v)) |
| 200 | |
| 201 | self.g_sum = tf.merge_summary(all_sum['g']) |
| 202 | self.d_sum = tf.merge_summary(all_sum['d']) |
| 203 | self.hist_sum = tf.merge_summary(all_sum['hist']) |
| 204 | |
| 205 | def visualize_one_superimage(self, img_var, images, rows, filename): |
| 206 | stacked_img = [] |