Various minor fixes for typos and types #105
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brentyi
commented
Jul 8, 2022
| # TODO(ethan): add loss weightings here from a config | ||
| # e.g. weighted_losses = map(lambda k: some_weight_dict[k] * loss_dict[k], loss_dict.keys()) | ||
| weighted_losses = loss_dict.values() | ||
| return functools.reduce(torch.add, weighted_losses) |
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this is mostly because the loss_sum = 0.0 + for loop pattern makes being strict about typing a bit tough, since I wanted to annotate the output as torch.Tensor but 0.0 isn't one
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This is logic we intend to refactor - #90 (comment)
brentyi
commented
Jul 8, 2022
| @@ -56,8 +56,7 @@ class TrainerConfig: | |||
| steps_per_save: int = MISSING | |||
| steps_per_test: int = MISSING | |||
| max_num_iterations: int = MISSING | |||
| # additional optional parameters here | |||
| resume_train: Optional[ResumeTrainConfig] = None | |||
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the code pretty regularly accesses resume_train.* without any checks for resume_train is not None, so if this were actually None here I think we'd just get a bunch of runtime errors?
brentyi
commented
Jul 8, 2022
| self.profiler_dict.keys(), | ||
| key=lambda k: self.profiler_dict[k]["val"], | ||
| reverse=True, | ||
| ) |
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(this is the same, just seemed a little bit clearer)
|
LGTM |
tancik
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Jul 8, 2022
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…_masking Move masking abstraction
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* minor fixes for typos and types * run isort
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Just some minor things I noticed while making the fix in #104 🙂