(self, loss, neighbor, neigh_embeddings)
| 378 | return tf.group(*update_ops) |
| 379 | |
| 380 | def _update_gradient(self, loss, neighbor, neigh_embeddings): |
| 381 | update_ops = [] |
| 382 | for gradient_store, neigh_embedding in zip( |
| 383 | self.gradient_stores, neigh_embeddings): |
| 384 | embedding_gradient = tf.gradients(loss, neigh_embedding)[0] |
| 385 | update_ops.append( |
| 386 | utils_embedding.embedding_add(gradient_store, |
| 387 | neighbor, embedding_gradient)) |
| 388 | return tf.group(*update_ops) |
| 389 | |
| 390 | def _optimize_store(self, node, node_embeddings): |
| 391 | if not self.gradient_stores: |