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import time |
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import pytest |
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import numpy as np |
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from hyperactive import Hyperactive |
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from hyperactive.optimizers.strategies import CustomOptimizationStrategy |
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from hyperactive.optimizers import GridSearchOptimizer |
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from ._parametrize import optimizers_non_smbo |
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def objective_function(opt): |
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time.sleep(0.01) |
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score = -(opt["x1"] * opt["x1"]) |
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return score |
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search_space = { |
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"x1": list(np.arange(0, 100, 1)), |
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} |
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def test_memory_Warm_start_0(): |
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optimizer1 = GridSearchOptimizer() |
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optimizer2 = GridSearchOptimizer() |
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opt_strat = CustomOptimizationStrategy() |
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opt_strat.add_optimizer(optimizer1, duration=0.2) |
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opt_strat.add_optimizer(optimizer2, duration=0.8) |
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n_iter = 1000 |
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c_time = time.time() |
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hyper = Hyperactive() |
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hyper.add_search( |
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objective_function, |
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search_space, |
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optimizer=opt_strat, |
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n_iter=n_iter, |
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memory=True, |
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) |
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hyper.run() |
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d_time = time.time() - c_time |
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48
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search_data = hyper.search_data(objective_function) |
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50
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optimizer1 = hyper.opt_pros[0].optimizer_setup_l[0]["optimizer"] |
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optimizer2 = hyper.opt_pros[0].optimizer_setup_l[1]["optimizer"] |
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assert len(search_data) == n_iter |
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assert len(optimizer1.search_data) == 200 |
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assert len(optimizer2.search_data) == 800 |
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assert optimizer1.best_score <= optimizer2.best_score |
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print("\n d_time", d_time) |
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assert d_time < 3 |
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64
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65
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View Code Duplication |
def test_memory_Warm_start_1(): |
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optimizer1 = GridSearchOptimizer() |
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optimizer2 = GridSearchOptimizer() |
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opt_strat = CustomOptimizationStrategy() |
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opt_strat.add_optimizer(optimizer1, duration=0.2) |
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opt_strat.add_optimizer(optimizer2, duration=0.8) |
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n_iter = 100 |
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75
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search_space = { |
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"x1": list(np.arange(0, 1, 1)), |
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} |
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c_time = time.time() |
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81
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hyper = Hyperactive() |
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hyper.add_search( |
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objective_function, |
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search_space, |
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optimizer=opt_strat, |
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n_iter=n_iter, |
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memory=False, |
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) |
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hyper.run() |
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91
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d_time = time.time() - c_time |
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93
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search_data = hyper.search_data(objective_function) |
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95
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optimizer1 = hyper.opt_pros[0].optimizer_setup_l[0]["optimizer"] |
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optimizer2 = hyper.opt_pros[0].optimizer_setup_l[1]["optimizer"] |
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assert len(search_data) == n_iter |
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100
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assert len(optimizer1.search_data) == 20 |
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assert len(optimizer2.search_data) == 80 |
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assert optimizer1.best_score <= optimizer2.best_score |
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print("\n d_time", d_time) |
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assert d_time > 0.95 |
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109
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110
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111
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View Code Duplication |
@pytest.mark.parametrize(*optimizers_non_smbo) |
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112
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def test_memory_Warm_start_2(Optimizer_non_smbo): |
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optimizer1 = GridSearchOptimizer() |
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optimizer2 = Optimizer_non_smbo() |
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115
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116
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opt_strat = CustomOptimizationStrategy() |
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opt_strat.add_optimizer(optimizer1, duration=0.5) |
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opt_strat.add_optimizer(optimizer2, duration=0.5) |
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119
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120
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search_space = { |
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"x1": list(np.arange(0, 50, 1)), |
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} |
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123
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124
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n_iter = 100 |
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125
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126
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c_time = time.time() |
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127
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128
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hyper = Hyperactive() |
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129
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hyper.add_search( |
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130
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objective_function, |
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131
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search_space, |
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optimizer=opt_strat, |
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133
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n_iter=n_iter, |
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memory=True, |
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135
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) |
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136
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hyper.run() |
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137
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138
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d_time = time.time() - c_time |
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139
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140
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search_data = hyper.search_data(objective_function) |
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141
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142
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optimizer1 = hyper.opt_pros[0].optimizer_setup_l[0]["optimizer"] |
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optimizer2 = hyper.opt_pros[0].optimizer_setup_l[1]["optimizer"] |
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144
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145
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assert len(search_data) == n_iter |
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146
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147
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assert len(optimizer1.search_data) == 50 |
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assert len(optimizer2.search_data) == 50 |
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149
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150
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assert optimizer1.best_score <= optimizer2.best_score |
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151
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152
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print("\n d_time", d_time) |
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153
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154
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assert d_time < 0.9 |
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155
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SimonBlanke /
Hyperactive
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