(self)
| 81 | return total_cost |
| 82 | |
| 83 | def optimizer(self): |
| 84 | lr = tf.train.exponential_decay( |
| 85 | learning_rate=1e-3, |
| 86 | global_step=get_global_step_var(), |
| 87 | decay_steps=468 * 10, |
| 88 | decay_rate=0.3, staircase=True, name='learning_rate') |
| 89 | # This will also put the summary in tensorboard, stat.json and print in terminal, |
| 90 | # but this time without moving average |
| 91 | tf.summary.scalar('lr', lr) |
| 92 | return tf.train.AdamOptimizer(lr) |
| 93 | |
| 94 | |
| 95 | def get_data(): |
nothing calls this directly
no test coverage detected