Introduce functional genetic algorithm operators #109
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Alternative implementations for genetic algorithm operators are introduced. These alternative implementations conform to the paradigm of functional programming, and they are batchable (via simply adding a leftmost dimension to the population, or via `torch.func.vmap`). A custom genetic algorithm can be implemented by combining these operators.
engintoklu
requested review from
Higgcz,
pliskowski,
flukeskywalker and
NaturalGradient
for more information, see https://pre-commit.ci
This commit adds a new example notebook which demonstrates how one can use the functional operators API to solve problems where a solution is expressed via objects. A bugfix is also introduced for the method `make_callable_evaluator` for problems where the dtype is set as object.
for more information, see https://pre-commit.ci
Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## master #109 +/- ##
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+ Coverage 76.74% 76.80% +0.05%
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Files 49 58 +9
Lines 7509 9000 +1491
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+ Hits 5763 6912 +1149
- Misses 1746 2088 +342 ☔ View full report in Codecov by Sentry. |
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Alternative implementations for genetic algorithm operators are introduced. These alternative implementations conform to the paradigm of functional programming, and they are batchable (via simply adding a leftmost dimension to the population, or via
torch.func.vmap).A custom genetic algorithm can be implemented by combining these operators.