activation functions added for bounded outputs #14
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Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## develop #14 +/- ##
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Coverage 99.83% 99.84%
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Files 22 23 +1
Lines 1216 1277 +61
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+ Hits 1214 1275 +61
Misses 2 2 ☔ View full report in Codecov by Sentry. |
mchantry
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Sep 10, 2024
mchantry
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Great work on this, thanks. |
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mchantry
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Sep 23, 2024
JesperDramsch
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Sep 23, 2024
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* activation functions added for bounded outputs * generalised fraction normalisation * precommit changes * precommit changes * chore: mv bounding to post-processors * feat: make bounding strategies torch Module * refactor: pre-build indices during init * refactor: nn.module in place modification * refactor: mv bounding to layers * refactor: implement bounding ModuleList * docs: add changelog * refactor: mv bounding config to models * feat: enable 1-1 variable remapping in preprocessors * test: create tests and fix code * test: add a test for hydra instantiating of bounding * fix: naming * refactor: reduce verboseness * docs: add comments * fix: inject name_to_index on initiation * fixed reading of statistics remapping * revert * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update test_preprocessor_normalizer.py * Update encoder_processor_decoder.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * docs: added a comment on special keys * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * docs: add docstrings * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix: changelog --------- Co-authored-by: Jesper Dramsch <[email protected]>
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This PR is related to the open issue #13 and the aifs-mono PR https://github.com/ecmwf-lab/aifs-mono/pull/224.
The basic idea behind this PR is to implement bounding strategies for specific variables, chosen by the user, via the usage of activation functions. One evident example the total precipitation accumulation variable, which is not currently bounded, therefore prone to negative value predictions.
Closes #13