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Improve precision recall metric issue 2571 #2573
Improve precision recall metric issue 2571 #2573
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@sadra-barikbin thanks a lot for the PR !
I left few comments to clear out the API. I haven't checked yet the details but the feature looks cool !
Please check also docs build failure.
…github.com/sadra-barikbin/ignite into improve-precision-recall-metric-issue-2571
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…github.com/sadra-barikbin/ignite into improve-precision-recall-metric-issue-2571
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_test(average=True) | ||
_test(average=False) | ||
assert pr._updated is False | ||
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def _test_distrib_integration_multiclass(device): |
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Is there any reason that this test has not been parametrized?
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This test and other similar ones are used in test_distrib_hvd, test_distrib_gloo_cpu_or_gpu, test_distrib_nccl_gpu tests. IMO, it is not obvious how to properly parametrize them. However, there was a task to rewrite distributed tests such that we do not need to write all: test_distrib_hvd, test_distrib_gloo_cpu_or_gpu, test_distrib_nccl_gpu
but only _test_distrib_integration_multiclass
and they could be executed with hvd, gloo, nccl confs...
Scikit-Learn has another data type called |
undo calling item() on result when data is binary and average=True due to resulting Fbeta failure
…github.com/sadra-barikbin/ignite into improve-precision-recall-metric-issue-2571
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Thanks a lot for this great PR @sadra-barikbin !
I'm checking it on GPU and if CI is green let's merge it.
In a follow-up PR, let's clean-up docstring about
- torch.Tensor(...)
+ torch.tensor(...)
Fixes #2571
Check list: