Add tensorboard to torch engine #1704
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albertz
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| # write losses/errors to tensorboard | ||
| for key, val in eval_info.items(): | ||
| self._tensorboard_writer.add_scalar( | ||
| f"{dataset_name}/{key}", val, global_step=self.global_train_step |
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global_train_step always stays the same here for one specific epoch. Isn't that a problem?
Maybe you want to do it for the accumulated_losses_dict instead below?
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Note: You can rebase to master now. That should fix the CI issues. (But despite that, see also my other comment.) |
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This adds tensorboard support to the torch engine. right now, it just uses the default directory name "runs" to dump the data to. also, it just dumps all scores from
eval_infointo the tensorbard. since we might want to discuss these two decisions, i marked this as a draft request.