Logs the metric dict passed in. :param metrics: :param grad_norm_dic:
(self, metrics, grad_norm_dic, step=None)
| 915 | return root_node |
| 916 | |
| 917 | def log_metrics(self, metrics, grad_norm_dic, step=None): |
| 918 | """Logs the metric dict passed in. |
| 919 | |
| 920 | :param metrics: |
| 921 | :param grad_norm_dic: |
| 922 | """ |
| 923 | # added metrics by Lightning for convenience |
| 924 | metrics['epoch'] = self.current_epoch |
| 925 | |
| 926 | # add norms |
| 927 | metrics.update(grad_norm_dic) |
| 928 | |
| 929 | # turn all tensors to scalars |
| 930 | scalar_metrics = self.metrics_to_scalars(metrics) |
| 931 | |
| 932 | step = step if step is not None else self.global_step |
| 933 | # log actual metrics |
| 934 | if self.proc_rank == 0 and self.logger is not None: |
| 935 | self.logger.log_metrics(scalar_metrics, step=step) |
| 936 | self.logger.save() |
| 937 | |
| 938 | def add_tqdm_metrics(self, metrics): |
| 939 | for k, v in metrics.items(): |
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