Multiline refactor #195
Multiline refactor #195
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Hello @YamLyubov! Thanks for updating this PR. We checked the lines you've touched for PEP 8 issues, and found: There are currently no PEP 8 issues detected in this Pull Request. Cheers! 🍻 Comment last updated at 2023-10-02 13:26:23 UTC |
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Hello @YamLyubov! Thanks for updating this PR. We checked the lines you've touched for PEP 8 issues, and found: There are currently no PEP 8 issues detected in this Pull Request. Cheers! 🍻 Comment last updated at 2023-10-05 12:02:12 UTC |
Codecov Report
@@ Coverage Diff @@
## main #195 +/- ##
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- Coverage 74.35% 73.76% -0.59%
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Files 130 131 +1
Lines 7760 7826 +66
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+ Hits 5770 5773 +3
- Misses 1990 2053 +63
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… find_best_running_fitness)
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| node_types = ['X'] | ||
| for graph_name, num_nodes in product(graph_names, graph_sizes): | ||
| experiment_id = f'Experiment [graph={graph_name} graph_size={num_nodes}]' | ||
| file_name = f'{optimizer_cls.__name__[:-9]}_{graph_name}_n{num_nodes}_iter{trial_iterations}' |
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это так слово Optimizer вырезается? или почему именно 9
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Абсолютно точно)))
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| def generate_dag(n): | ||
| g = nx.gnp_random_graph(n, p=0.5, directed=True) |
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там чел в комментах к этому решению писал, что на супер больших графах оно ломается. нам-то не принципиально, но пометку я бы оставила
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| class RandomMutationSearchOptimizer(RandomSearchOptimizer): | ||
| class PopulationalRandomMutationOptimizer(PopulationalOptimizer): | ||
| """ |
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я на написала побольше текста про то зачем такой оптимизатор и, например, где он был использован
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| def __init__(self, | ||
| historical_fitnesses: Dict[str, Sequence[Sequence[Union[float, Sequence[float]]]]], | ||
| metric_names, |
| self.log = default_log(self) | ||
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| @staticmethod | ||
| def from_saved_histories(experiment_folders: List[str], root_path: os.PathLike): |
| # Required | ||
| version: 2 | ||
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| build: |
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бтв кажется, оно уже заработало и без этого
Adds:
PopulationalRandomMutationOptimizerFixes: