SimonBlanke /
Hyperactive
| @@ 168-221 (lines=54) @@ | ||
| 165 | assert n_performed_iter == n_iter |
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| 166 | ||
| 167 | ||
| 168 | def test_early_stop_5(): |
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| 169 | class Experiment(BaseExperiment): |
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| 170 | def objective_function(self, para): |
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| 171 | return para["x0"] |
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| 172 | ||
| 173 | experiment = Experiment() |
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| 174 | ||
| 175 | search_config = SearchConfig( |
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| 176 | x0=list(np.arange(0, 100, 0.01)), |
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| 177 | ) |
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| 178 | ||
| 179 | n_iter_no_change = 5 |
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| 180 | early_stopping = { |
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| 181 | "n_iter_no_change": n_iter_no_change, |
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| 182 | "tol_abs": 10, |
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| 183 | "tol_rel": None, |
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| 184 | } |
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| 185 | ||
| 186 | start1 = {"x0": 0} |
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| 187 | start2 = {"x0": 9} |
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| 188 | start3 = {"x0": 20} |
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| 189 | ||
| 190 | warm_start_l = [ |
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| 191 | start1, |
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| 192 | start1, |
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| 193 | start1, |
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| 194 | start1, |
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| 195 | start1, |
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| 196 | start2, |
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| 197 | start2, |
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| 198 | start2, |
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| 199 | start3, |
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| 200 | start3, |
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| 201 | start3, |
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| 202 | ] |
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| 203 | n_iter = len(warm_start_l) |
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| 204 | ||
| 205 | hyper = RandomSearchOptimizer() |
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| 206 | hyper.add_search( |
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| 207 | experiment, |
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| 208 | search_config, |
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| 209 | n_iter=n_iter, |
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| 210 | initialize={"warm_start": warm_start_l}, |
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| 211 | early_stopping=early_stopping, |
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| 212 | ) |
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| 213 | hyper.run() |
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| 214 | ||
| 215 | search_data = hyper.search_data(experiment) |
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| 216 | n_performed_iter = len(search_data) |
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| 217 | ||
| 218 | print("\n n_performed_iter \n", n_performed_iter) |
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| 219 | print("\n n_iter_no_change \n", n_iter_no_change) |
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| 220 | ||
| 221 | assert n_performed_iter == (n_iter_no_change + 1) |
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| 222 | ||
| 223 | ||
| 224 | def test_early_stop_6(): |
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| @@ 288-340 (lines=53) @@ | ||
| 285 | assert n_performed_iter == n_iter |
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| 286 | ||
| 287 | ||
| 288 | def test_early_stop_7(): |
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| 289 | def objective_function(para): |
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| 290 | return para["x0"] |
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| 291 | ||
| 292 | experiment = Experiment() |
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| 293 | ||
| 294 | search_config = SearchConfig( |
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| 295 | x0=list(np.arange(0, 100, 0.01)), |
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| 296 | ) |
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| 297 | ||
| 298 | n_iter_no_change = 5 |
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| 299 | early_stopping = { |
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| 300 | "n_iter_no_change": n_iter_no_change, |
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| 301 | "tol_abs": None, |
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| 302 | "tol_rel": 10, |
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| 303 | } |
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| 304 | ||
| 305 | start1 = {"x0": 1} |
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| 306 | start2 = {"x0": 1.09} |
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| 307 | start3 = {"x0": 1.20} |
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| 308 | ||
| 309 | warm_start_l = [ |
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| 310 | start1, |
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| 311 | start1, |
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| 312 | start1, |
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| 313 | start1, |
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| 314 | start1, |
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| 315 | start2, |
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| 316 | start2, |
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| 317 | start2, |
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| 318 | start3, |
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| 319 | start3, |
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| 320 | start3, |
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| 321 | ] |
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| 322 | n_iter = len(warm_start_l) |
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| 323 | ||
| 324 | hyper = RandomSearchOptimizer() |
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| 325 | hyper.add_search( |
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| 326 | experiment, |
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| 327 | search_config, |
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| 328 | n_iter=n_iter, |
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| 329 | initialize={"warm_start": warm_start_l}, |
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| 330 | early_stopping=early_stopping, |
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| 331 | ) |
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| 332 | hyper.run() |
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| 333 | ||
| 334 | search_data = hyper.search_data(experiment) |
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| 335 | n_performed_iter = len(search_data) |
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| 336 | ||
| 337 | print("\n n_performed_iter \n", n_performed_iter) |
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| 338 | print("\n n_iter_no_change \n", n_iter_no_change) |
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| 339 | ||
| 340 | assert n_performed_iter == (n_iter_no_change + 1) |
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| 341 | ||
