Helper function for init_opt
(self)
| 259 | self.log_vars.append(("hr_g_learning_rate", self.generator_lr)) |
| 260 | |
| 261 | def define_summaries(self): |
| 262 | '''Helper function for init_opt''' |
| 263 | all_sum = {'g': [], 'd': [], 'hr_g': [], 'hr_d': [], 'hist': []} |
| 264 | for k, v in self.log_vars: |
| 265 | if k.startswith('g'): |
| 266 | all_sum['g'].append(tf.scalar_summary(k, v)) |
| 267 | elif k.startswith('d'): |
| 268 | all_sum['d'].append(tf.scalar_summary(k, v)) |
| 269 | elif k.startswith('hr_g'): |
| 270 | all_sum['hr_g'].append(tf.scalar_summary(k, v)) |
| 271 | elif k.startswith('hr_d'): |
| 272 | all_sum['hr_d'].append(tf.scalar_summary(k, v)) |
| 273 | elif k.startswith('hist'): |
| 274 | all_sum['hist'].append(tf.histogram_summary(k, v)) |
| 275 | |
| 276 | self.g_sum = tf.merge_summary(all_sum['g']) |
| 277 | self.d_sum = tf.merge_summary(all_sum['d']) |
| 278 | self.hr_g_sum = tf.merge_summary(all_sum['hr_g']) |
| 279 | self.hr_d_sum = tf.merge_summary(all_sum['hr_d']) |
| 280 | self.hist_sum = tf.merge_summary(all_sum['hist']) |
| 281 | |
| 282 | def visualize_one_superimage(self, img_var, images, rows, filename): |
| 283 | stacked_img = [] |