SimonBlanke /
Hyperactive
| @@ 287-337 (lines=51) @@ | ||
| 284 | assert n_performed_iter == n_iter |
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| 285 | ||
| 286 | ||
| 287 | def test_early_stop_7(): |
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| 288 | def objective_function(para): |
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| 289 | return para["x1"] |
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| 290 | ||
| 291 | search_space = { |
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| 292 | "x1": list(np.arange(0, 100, 0.01)), |
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| 293 | } |
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| 294 | ||
| 295 | n_iter_no_change = 5 |
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| 296 | early_stopping = { |
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| 297 | "n_iter_no_change": n_iter_no_change, |
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| 298 | "tol_abs": None, |
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| 299 | "tol_rel": 10, |
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| 300 | } |
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| 301 | ||
| 302 | start1 = {"x1": 1} |
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| 303 | start2 = {"x1": 1.09} |
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| 304 | start3 = {"x1": 1.20} |
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| 305 | ||
| 306 | warm_start_l = [ |
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| 307 | start1, |
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| 308 | start1, |
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| 309 | start1, |
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| 310 | start1, |
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| 311 | start1, |
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| 312 | start2, |
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| 313 | start2, |
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| 314 | start2, |
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| 315 | start3, |
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| 316 | start3, |
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| 317 | start3, |
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| 318 | ] |
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| 319 | n_iter = len(warm_start_l) |
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| 320 | ||
| 321 | hyper = Hyperactive() |
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| 322 | hyper.add_search( |
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| 323 | objective_function, |
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| 324 | search_space, |
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| 325 | n_iter=n_iter, |
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| 326 | initialize={"warm_start": warm_start_l}, |
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| 327 | early_stopping=early_stopping, |
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| 328 | ) |
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| 329 | hyper.run() |
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| 330 | ||
| 331 | search_data = hyper.search_data(objective_function) |
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| 332 | n_performed_iter = len(search_data) |
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| 333 | ||
| 334 | print("\n n_performed_iter \n", n_performed_iter) |
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| 335 | print("\n n_iter_no_change \n", n_iter_no_change) |
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| 336 | ||
| 337 | assert n_performed_iter == (n_iter_no_change + 1) |
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| 338 | ||
| @@ 173-223 (lines=51) @@ | ||
| 170 | assert n_performed_iter == n_iter |
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| 171 | ||
| 172 | ||
| 173 | def test_early_stop_5(): |
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| 174 | def objective_function(para): |
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| 175 | return para["x1"] |
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| 176 | ||
| 177 | search_space = { |
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| 178 | "x1": list(np.arange(0, 100, 0.01)), |
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| 179 | } |
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| 180 | ||
| 181 | n_iter_no_change = 5 |
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| 182 | early_stopping = { |
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| 183 | "n_iter_no_change": n_iter_no_change, |
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| 184 | "tol_abs": 0.1, |
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| 185 | "tol_rel": None, |
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| 186 | } |
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| 187 | ||
| 188 | start1 = {"x1": 0} |
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| 189 | start2 = {"x1": 0.09} |
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| 190 | start3 = {"x1": 0.20} |
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| 191 | ||
| 192 | warm_start_l = [ |
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| 193 | start1, |
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| 194 | start1, |
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| 195 | start1, |
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| 196 | start1, |
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| 197 | start1, |
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| 198 | start2, |
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| 199 | start2, |
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| 200 | start2, |
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| 201 | start3, |
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| 202 | start3, |
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| 203 | start3, |
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| 204 | ] |
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| 205 | n_iter = len(warm_start_l) |
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| 206 | ||
| 207 | hyper = Hyperactive() |
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| 208 | hyper.add_search( |
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| 209 | objective_function, |
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| 210 | search_space, |
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| 211 | n_iter=n_iter, |
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| 212 | initialize={"warm_start": warm_start_l}, |
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| 213 | early_stopping=early_stopping, |
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| 214 | ) |
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| 215 | hyper.run() |
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| 216 | ||
| 217 | search_data = hyper.search_data(objective_function) |
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| 218 | n_performed_iter = len(search_data) |
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| 219 | ||
| 220 | print("\n n_performed_iter \n", n_performed_iter) |
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| 221 | print("\n n_iter_no_change \n", n_iter_no_change) |
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| 222 | ||
| 223 | assert n_performed_iter == (n_iter_no_change + 1) |
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| 224 | ||
| 225 | ||
| 226 | def test_early_stop_6(): |
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| @@ 279-329 (lines=51) @@ | ||
| 276 | assert n_performed_iter == n_iter |
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| 277 | ||
| 278 | ||
| 279 | def test_early_stop_7(): |
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| 280 | def objective_function(para): |
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| 281 | return para["x0"] |
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| 282 | ||
| 283 | search_space = { |
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| 284 | "x0": list(np.arange(0, 100, 0.01)), |
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| 285 | } |
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| 286 | ||
| 287 | n_iter_no_change = 5 |
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| 288 | early_stopping = { |
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| 289 | "n_iter_no_change": n_iter_no_change, |
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| 290 | "tol_abs": None, |
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| 291 | "tol_rel": 10, |
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| 292 | } |
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| 293 | ||
| 294 | start1 = {"x0": 1} |
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| 295 | start2 = {"x0": 1.09} |
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| 296 | start3 = {"x0": 1.20} |
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| 297 | ||
| 298 | warm_start_l = [ |
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| 299 | start1, |
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| 300 | start1, |
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| 301 | start1, |
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| 302 | start1, |
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| 303 | start1, |
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| 304 | start2, |
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| 305 | start2, |
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| 306 | start2, |
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| 307 | start3, |
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| 308 | start3, |
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| 309 | start3, |
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| 310 | ] |
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| 311 | n_iter = len(warm_start_l) |
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| 312 | ||
| 313 | hyper = RandomSearchOptimizer() |
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| 314 | hyper.add_search( |
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| 315 | experiment, |
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| 316 | search_config, |
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| 317 | n_iter=n_iter, |
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| 318 | initialize={"warm_start": warm_start_l}, |
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| 319 | early_stopping=early_stopping, |
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| 320 | ) |
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| 321 | hyper.run() |
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| 322 | ||
| 323 | search_data = hyper.search_data(experiment) |
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| 324 | n_performed_iter = len(search_data) |
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| 325 | ||
| 326 | print("\n n_performed_iter \n", n_performed_iter) |
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| 327 | print("\n n_iter_no_change \n", n_iter_no_change) |
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| 328 | ||
| 329 | assert n_performed_iter == (n_iter_no_change + 1) |
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| 330 | ||
| @@ 165-215 (lines=51) @@ | ||
| 162 | assert n_performed_iter == n_iter |
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| 163 | ||
| 164 | ||
| 165 | def test_early_stop_5(): |
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| 166 | def objective_function(para): |
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| 167 | return para["x0"] |
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| 168 | ||
| 169 | search_space = { |
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| 170 | "x0": list(np.arange(0, 100, 0.01)), |
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| 171 | } |
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| 172 | ||
| 173 | n_iter_no_change = 5 |
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| 174 | early_stopping = { |
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| 175 | "n_iter_no_change": n_iter_no_change, |
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| 176 | "tol_abs": 0.1, |
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| 177 | "tol_rel": None, |
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| 178 | } |
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| 179 | ||
| 180 | start1 = {"x0": 0} |
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| 181 | start2 = {"x0": 0.09} |
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| 182 | start3 = {"x0": 0.20} |
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| 183 | ||
| 184 | warm_start_l = [ |
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| 185 | start1, |
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| 186 | start1, |
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| 187 | start1, |
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| 188 | start1, |
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| 189 | start1, |
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| 190 | start2, |
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| 191 | start2, |
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| 192 | start2, |
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| 193 | start3, |
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| 194 | start3, |
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| 195 | start3, |
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| 196 | ] |
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| 197 | n_iter = len(warm_start_l) |
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| 198 | ||
| 199 | hyper = RandomSearchOptimizer() |
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| 200 | hyper.add_search( |
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| 201 | experiment, |
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| 202 | search_config, |
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| 203 | n_iter=n_iter, |
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| 204 | initialize={"warm_start": warm_start_l}, |
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| 205 | early_stopping=early_stopping, |
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| 206 | ) |
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| 207 | hyper.run() |
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| 208 | ||
| 209 | search_data = hyper.search_data(experiment) |
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| 210 | n_performed_iter = len(search_data) |
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| 211 | ||
| 212 | print("\n n_performed_iter \n", n_performed_iter) |
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| 213 | print("\n n_iter_no_change \n", n_iter_no_change) |
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| 214 | ||
| 215 | assert n_performed_iter == (n_iter_no_change + 1) |
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| 216 | ||
| 217 | ||
| 218 | def test_early_stop_6(): |
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