Add a notebook demonstrating how to evolve objects #102
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This commit adds an example notebook which demonstrates how one can declare and solve an optimization problem that has its `dtype` set as `object`, and therefore has a custom solution structure. While working on the example notebook, one bug, and one genetic algorithm-related shortcoming have been identified and fixed. The bug was preventing one from instantiating a new `ObjectArray` with the help of `evotorch.tools.as_tensor(..., dtype=object)`. This commit fixes this bug. The shortcoming was as follows: when the user defined a custom mutation operator using a regular function, `GeneticAlgorithm` assumed that the regular function would return a new batch of solutions whose length is equal to the number of solutions it received. This was an unnecessary restriction, and therefore, got fixed with this commit.
engintoklu
requested review from
Higgcz,
pliskowski,
flukeskywalker and
NaturalGradient
Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## master #102 +/- ##
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- Coverage 76.74% 76.73% -0.01%
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Files 49 49
Lines 7509 7519 +10
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+ Hits 5763 5770 +7
- Misses 1746 1749 +3 ☔ View full report in Codecov by Sentry. |
flukeskywalker
approved these changes
Jun 6, 2024
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This pull request adds an example notebook which demonstrates how one can declare and solve an optimization problem that has its
dtypeset asobject, and therefore has a custom solution structure.While working on the example notebook, one bug, and one genetic algorithm-related shortcoming have been identified and fixed.
The bug was preventing one from instantiating a new
ObjectArraywith the help ofevotorch.tools.as_tensor(..., dtype=object). This bug is fixed by this pull request.The shortcoming was as follows: when the user defined a custom mutation operator using a regular function,
GeneticAlgorithmassumed that the regular function would return a new batch of solutions whose length is equal to the number of solutions it received. This was an unnecessary restriction, and therefore, gets fixed with this pull request.