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Respect the passed dtype with self.log
#10076
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pytorch_lightning/trainer/connectors/logger_connector/result.py
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@carmocca Any updates on this PR ? |
value Out[35]: tensor(3211., device='cuda:0') value.mean() * batch_size / batch_size Out[36]: tensor(3210.9998, device='cuda:0') value.type(torch.float64).mean() * batch_size / batch_size Out[37]: tensor(3211., device='cuda:0', dtype=torch.float64)
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@tchaton I finished it.
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nit
pytorch_lightning/trainer/connectors/logger_connector/result.py
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LGTM ! Great work !
pytorch_lightning/trainer/connectors/logger_connector/result.py
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Co-authored-by: Rohit Gupta <[email protected]>
for more information, see https://pre-commit.ci
Co-authored-by: Carlos Mocholi <[email protected]> Co-authored-by: Rohit Gupta <[email protected]>
Co-authored-by: Carlos Mocholi <[email protected]> Co-authored-by: Rohit Gupta <[email protected]>
Co-authored-by: Carlos Mocholi <[email protected]> Co-authored-by: Rohit Gupta <[email protected]>
Co-authored-by: Carlos Mocholi <[email protected]> Co-authored-by: Rohit Gupta <[email protected]>
What does this PR do?
Author: @carmocca
Fixes #9713
Fixes #8930
Does your PR introduce any breaking changes? If yes, please list them.
Batch size must be fixed point. This would only be breaking if somebody was importing and using
ResultMetric
s directly (please don't)Before submitting
PR review