SimonBlanke /
Gradient-Free-Optimizers
| @@ 69-96 (lines=28) @@ | ||
| 66 | ) |
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| 67 | ||
| 68 | ||
| 69 | @pytest.mark.parametrize(*optimizers) |
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| 70 | def test_early_stop_3(Optimizer): |
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| 71 | def objective_function(para): |
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| 72 | score = -para["x1"] * para["x1"] |
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| 73 | return score |
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| 74 | ||
| 75 | search_space = { |
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| 76 | "x1": np.arange(0, 100, 0.1), |
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| 77 | } |
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| 78 | ||
| 79 | n_iter_no_change = 5 |
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| 80 | early_stopping = { |
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| 81 | "n_iter_no_change": n_iter_no_change, |
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| 82 | } |
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| 83 | ||
| 84 | opt = Optimizer(search_space, initialize={"warm_start": [{"x1": 0}]}) |
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| 85 | opt.search( |
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| 86 | objective_function, |
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| 87 | n_iter=100000, |
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| 88 | early_stopping=early_stopping, |
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| 89 | ) |
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| 90 | search_data = opt.results |
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| 91 | n_performed_iter = len(search_data) |
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| 92 | ||
| 93 | print("\n n_performed_iter \n", n_performed_iter) |
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| 94 | print("\n n_iter_no_change \n", n_iter_no_change) |
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| 95 | ||
| 96 | assert n_performed_iter == (n_iter_no_change + 1) |
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| 97 | ||
| 98 | ||
| 99 | @pytest.mark.parametrize(*optimizers) |
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| @@ 68-94 (lines=27) @@ | ||
| 65 | ) |
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| 66 | ||
| 67 | ||
| 68 | def test_early_stop_3(): |
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| 69 | def objective_function(para): |
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| 70 | score = -para["x1"] * para["x1"] |
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| 71 | return score |
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| 72 | ||
| 73 | search_space = { |
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| 74 | "x1": np.arange(0, 100, 0.1), |
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| 75 | } |
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| 76 | ||
| 77 | n_iter_no_change = 5 |
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| 78 | early_stopping = { |
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| 79 | "n_iter_no_change": n_iter_no_change, |
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| 80 | } |
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| 81 | ||
| 82 | opt = HillClimbingOptimizer(search_space, initialize={"warm_start": [{"x1": 0}]}) |
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| 83 | opt.search( |
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| 84 | objective_function, |
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| 85 | n_iter=100000, |
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| 86 | early_stopping=early_stopping, |
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| 87 | ) |
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| 88 | search_data = opt.results |
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| 89 | n_performed_iter = len(search_data) |
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| 90 | ||
| 91 | print("\n n_performed_iter \n", n_performed_iter) |
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| 92 | print("\n n_iter_no_change \n", n_iter_no_change) |
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| 93 | ||
| 94 | assert n_performed_iter == (n_iter_no_change + 1) |
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| 95 | ||
| 96 | ||
| 97 | def test_early_stop_4(): |
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