SimonBlanke /
Hyperactive
| @@ 96-115 (lines=20) @@ | ||
| 93 | hyper1.run() |
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| 94 | ||
| 95 | ||
| 96 | @pytest.mark.parametrize("smbo_opt", smbo_opts) |
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| 97 | def test_warm_start_smbo_1(smbo_opt): |
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| 98 | hyper0 = Hyperactive(distribution="pathos") |
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| 99 | hyper0.add_search( |
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| 100 | objective_function, |
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| 101 | search_space, |
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| 102 | n_iter=n_iter, |
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| 103 | n_jobs=2, |
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| 104 | initialize=initialize, |
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| 105 | ) |
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| 106 | hyper0.run() |
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| 107 | ||
| 108 | search_data0 = hyper0.search_data(objective_function) |
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| 109 | smbo_opt_ = smbo_opt(warm_start_smbo=search_data0) |
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| 110 | ||
| 111 | hyper1 = Hyperactive() |
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| 112 | hyper1.add_search( |
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| 113 | objective_function, search_space, n_iter=n_iter, optimizer=smbo_opt_ |
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| 114 | ) |
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| 115 | hyper1.run() |
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| 116 | ||
| 117 | ||
| 118 | @pytest.mark.parametrize("smbo_opt", smbo_opts) |
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| @@ 139-157 (lines=19) @@ | ||
| 136 | hyper1.run() |
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| 137 | ||
| 138 | ||
| 139 | @pytest.mark.parametrize("smbo_opt", smbo_opts) |
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| 140 | def test_warm_start_smbo_3(smbo_opt): |
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| 141 | hyper0 = Hyperactive(distribution="pathos") |
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| 142 | hyper0.add_search(objective_function, search_space, n_iter=n_iter, n_jobs=2) |
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| 143 | hyper0.run() |
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| 144 | ||
| 145 | search_data0 = hyper0.search_data(objective_function) |
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| 146 | smbo_opt_ = smbo_opt(warm_start_smbo=search_data0) |
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| 147 | ||
| 148 | hyper1 = Hyperactive(distribution="joblib") |
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| 149 | hyper1.add_search( |
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| 150 | objective_function, |
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| 151 | search_space, |
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| 152 | n_iter=n_iter, |
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| 153 | n_jobs=2, |
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| 154 | optimizer=smbo_opt_, |
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| 155 | initialize=initialize, |
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| 156 | ) |
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| 157 | hyper1.run() |
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| 158 | ||
| @@ 118-136 (lines=19) @@ | ||
| 115 | hyper1.run() |
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| 116 | ||
| 117 | ||
| 118 | @pytest.mark.parametrize("smbo_opt", smbo_opts) |
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| 119 | def test_warm_start_smbo_2(smbo_opt): |
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| 120 | hyper0 = Hyperactive() |
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| 121 | hyper0.add_search(objective_function, search_space, n_iter=n_iter) |
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| 122 | hyper0.run() |
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| 123 | ||
| 124 | search_data0 = hyper0.search_data(objective_function) |
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| 125 | smbo_opt_ = smbo_opt(warm_start_smbo=search_data0) |
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| 126 | ||
| 127 | hyper1 = Hyperactive(distribution="joblib") |
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| 128 | hyper1.add_search( |
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| 129 | objective_function, |
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| 130 | search_space, |
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| 131 | n_iter=n_iter, |
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| 132 | n_jobs=2, |
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| 133 | optimizer=smbo_opt_, |
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| 134 | initialize=initialize, |
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| 135 | ) |
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| 136 | hyper1.run() |
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| 137 | ||
| 138 | ||
| 139 | @pytest.mark.parametrize("smbo_opt", smbo_opts) |
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