Add save_every_iter option#173
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rikonaka
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Dec 14, 2023
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There seems to be a logical problem with some of the code ❤️
| return inputs | ||
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| @staticmethod | ||
| def _save_adv_examples( |
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Perhaps adding a type constraint or default parameters value for each parameter here would help other maintainers have a clear definition of parameter types.
| save_dict = { | ||
| "adv_inputs": adv_input_list_cat, | ||
| "labels": label_list_cat, | ||
| } # nopep8 |
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Here # nopep8 can be removed.
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| save_dict["save_type"] = save_type | ||
| torch.save(save_dict, save_path) | ||
| if save_path is not None and save_every_iter: |
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The input parameters of these two self._save_adv_examples functions seem to be the same, so why are two placed here?
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PR Type and Checklist
What kind of change does this PR introduce?
When saving a large number of samples, saving each batch repeatedly will consume a lot of time.
I added an option to control whether generated samples are saved every epoch.
model.supported_modewhether the attack supports targeted mode.