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Mish inplace question

See original GitHub issue

Hi, thanks for the great repo! What’s the reason that the x.mul_(inner) line is commented out? Does the commented line return different results? Thanks!

https://github.com/rwightman/gen-efficientnet-pytorch/blob/d2eadab6eb4427014c3b80eeaff1ff82d2d1f3f4/geffnet/activations/activations.py#L20-L25

Issue Analytics

  • State:closed
  • Created 4 years ago
  • Comments:5 (3 by maintainers)

github_iconTop GitHub Comments

1reaction
rwightmancommented, Nov 20, 2019

It’s dead code now, I should get rid of it… when I first implemented mish I though I’d be smart and make it a little more efficient with the inplace variation… however it triggered an inplace gradient error (during training)

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rwightmancommented, Nov 23, 2019

I believe you put your training loop, or call to it under a detect_anomaly context manager… been a while since I’ve used it, has a performance impact but this sort of error should be detected quickly.

with autograd.detect_anomaly():
    training_loop()
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