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[tune] Refactoring: Deduplicate (#7918)
* refactoring: Deduplication * refactoring: Deduplication * refactoring: Deduplication * refactoring: Deduplication * lint fix: Variable naming case * fix: Remove White Space * fix_lint Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
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@@ -109,12 +109,13 @@ class GeneticSearch(AutoMLSearcher):
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for i in range(top_num, num_population):
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flip_coin = np.random.uniform()
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if flip_coin < self._selection_bound:
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next_generation.append(GeneticSearch._selection(candidate))
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next_gen = GeneticSearch._selection(candidate)
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else:
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if flip_coin < self._selection_bound + self._crossover_bound:
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next_generation.append(GeneticSearch._crossover(candidate))
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next_gen = GeneticSearch._crossover(candidate)
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else:
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next_generation.append(GeneticSearch._mutation(candidate))
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next_gen = GeneticSearch._mutation(candidate)
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next_generation.append(next_gen)
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return next_generation
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def _next_population_size(self, last_population_size):
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@@ -167,10 +168,8 @@ class GeneticSearch(AutoMLSearcher):
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next_gen = []
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for i in range(len(sample_1)):
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if i is select_index:
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next_gen.append(sample_2[i])
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else:
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next_gen.append(sample_1[i])
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sample = sample_2[i] if i is select_index else sample_1[i]
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next_gen.append(sample)
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return next_gen
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@staticmethod
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@@ -209,10 +208,8 @@ class GeneticSearch(AutoMLSearcher):
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next_gen = []
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for i in range(len(sample_1)):
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if i > cross_index:
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next_gen.append(sample_2[i])
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else:
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next_gen.append(sample_1[i])
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sample = sample_2[i] if i > cross_index else sample_1[i]
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next_gen.append(sample)
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return next_gen
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@staticmethod
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@@ -858,10 +858,7 @@ class LocalIterator(Generic[T]):
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"other must be of type LocalIterator, got {}".format(
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type(it)))
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if deterministic:
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timeout = None
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else:
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timeout = 0
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timeout = None if deterministic else 0
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active = []
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parent_iters = [self] + list(others)
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