(self)
| 62 | self.flush_gradients() |
| 63 | |
| 64 | def flush_gradients(self): |
| 65 | assert self.trainable, "Layer is frozen" |
| 66 | |
| 67 | self.X = [] |
| 68 | self._dv = {} |
| 69 | for c in self.components: |
| 70 | for k, v in c.derived_variables.items(): |
| 71 | c.derived_variables[k] = None |
| 72 | |
| 73 | for k, v in c.gradients.items(): |
| 74 | c.gradients[k] = np.zeros_like(v) |
| 75 | |
| 76 | def set_params(self, summary_dict): |
| 77 | cids = self.hyperparameters["component_ids"] |