(self, input_shape)
| 655 | self.store_init_maxval = store_init_maxval |
| 656 | |
| 657 | def build(self, input_shape): |
| 658 | self.stores = [ |
| 659 | tf.get_variable('store_layer_{}'.format(i), |
| 660 | [self.max_id + 2, dim], |
| 661 | initializer=tf.random_uniform_initializer( |
| 662 | maxval=self.store_init_maxval, seed=1), |
| 663 | trainable=False, |
| 664 | collections=[tf.GraphKeys.LOCAL_VARIABLES]) |
| 665 | for i, dim in enumerate(self.dims[1: -1], 1)] |
| 666 | self.gradient_stores = [ |
| 667 | tf.get_variable('gradient_store_layer_{}'.format(i), |
| 668 | [self.max_id + 2, dim], |
| 669 | initializer=tf.zeros_initializer(), |
| 670 | trainable=False, |
| 671 | collections=[tf.GraphKeys.LOCAL_VARIABLES]) |
| 672 | for i, dim in enumerate(self.dims[1: -1], 1)] |
| 673 | self.store_optimizer = tf.train.AdamOptimizer(self.store_learning_rate) |
| 674 | |
| 675 | def call(self, inputs, training=None): |
| 676 | if not training: |
nothing calls this directly
no outgoing calls
no test coverage detected