Robust segvit compatibility + new dataset. #1183
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…es for 10 train samples for 1 epoch
… update segmenter_test to test different classifiers
…baselines into load_check merging ub which now includes segmenter
merge changes in ub
…terministic and sngp weights
dusenberrymw
requested changes
Nov 4, 2022
| # pytype: enable=wrong-arg-types | ||
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| # free memory | ||
| del restored_params |
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This will be deleted anyway when the function returns on the next line, so I don't think we need to explicitly delete it here.
| from uncertainty_metrics import SegmentationUncertaintyMetrics # local file import from experimental.robust_segvit | ||
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| class UncertaintyMetricsTest(parameterized.TestCase): |
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What do you think about updating these tests instead of deleting them?
dusenberrymw
requested changes
Nov 7, 2022
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| # TODO(kellybuchanan): add masking to ece metric in rm. | ||
| # updates on each host separately | ||
| ece_metric.update_state(e_batch['label'], probs, sample_weight=e_batch['batch_mask']) |
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Based on the comment in google-research/robustness_metrics#77, can we move the binary masking logic here such that we pass in a masked subset of labels and probs as needed without changing the ECE metric API?
…of corruption_level
… eval toy config file
… not support negative values
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This commit makes the code in robust_segvit compatible externally and adds config files to experiment with a benchmark for open set recognition in image segmentation, namely the street hazards dataset from https://arxiv.org/abs/1911.11132.