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Changes to the test function #737

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HarshSharma12
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Before submitting

  • Was this discussed/approved via a Github issue? (no need for typos, doc improvements)
  • Did you read the contributor guideline?
  • Did you make sure to update the docs?
  • Did you write any new necessary tests?

What does this PR do?

Fixes #657. Overrides PR #726

Updates as per the comments (#723) and changes to the test function

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Anyone in the community is free to review the PR once the tests have passed.
If we didn't discuss your PR in Github issues there's a high chance it will not be merged.

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Make sure you had fun coding 🙃

@HarshSharma12 HarshSharma12 mentioned this pull request Jan 23, 2020
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@Borda Borda added feature Is an improvement or enhancement good first issue Good for newcomers labels Jan 31, 2020
@Borda Borda added this to the 0.6.1 milestone Jan 31, 2020
@williamFalcon
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@HarshSharma12 @Borda is this still active?

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there is no need to close the progress bar?

@@ -65,6 +65,10 @@ def run_model_test(trainer_options, model, on_gpu=True):
# correct result and ok accuracy
assert result == 1, 'amp + ddp model failed to complete'

if early_stop:
assert trainer.current_epoch >= trainer.min_epochs, 'amp + ddp model failed to complete'
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rather make is raise an error

@Borda Borda changed the title #657 - Updates as per the comments and changes to the test function Changes to the test function Feb 14, 2020
@Borda Borda requested review from neggert and a team February 17, 2020 20:01
@Borda
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Borda commented Feb 19, 2020

@HarshSharma12 may you rebase, pls?

@ethanwharris
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ethanwharris commented Feb 25, 2020

@Borda @williamFalcon @HarshSharma12 I had a look at rebasing this - the issue seems to have been fixed by #856 - see here

I vote for closing this PR and the associated issue

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Borda commented Feb 25, 2020

Ok, closing this... anyway very thanks @HarshSharma12 for your help and looking forward to your future help 🤖

@Borda Borda closed this Feb 25, 2020
@HarshSharma12 HarshSharma12 deleted the issue657 branch March 11, 2020 20:04
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on_train_end callback is not called if training is stopped early
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