(self)
| 68 | return cost |
| 69 | |
| 70 | def optimizer(self): |
| 71 | lr = tf.get_variable('learning_rate', initializer=5e-3, trainable=False) |
| 72 | opt = tf.train.AdamOptimizer(lr, epsilon=1e-3) |
| 73 | return optimizer.apply_grad_processors( |
| 74 | opt, [GlobalNormClip(5), SummaryGradient()]) |
| 75 | |
| 76 | |
| 77 | def get_data(path, isTrain, stat_file): |
nothing calls this directly
no test coverage detected