(self, loss, neighbor, neigh_embeddings)
| 718 | return tf.group(*update_ops) |
| 719 | |
| 720 | def _update_gradient(self, loss, neighbor, neigh_embeddings): |
| 721 | update_ops = [] |
| 722 | for gradient_store, neigh_embedding in zip(self.gradient_stores, |
| 723 | neigh_embeddings): |
| 724 | embedding_gradient = tf.gradients(loss, neigh_embedding)[0] |
| 725 | update_ops.append( |
| 726 | utils_embedding.embedding_add(gradient_store, |
| 727 | neighbor, embedding_gradient)) |
| 728 | return tf.group(*update_ops) |
| 729 | |
| 730 | def _optimize_store(self, node, node_embeddings): |
| 731 | if not self.gradient_stores: |