Total Complexity | 6 |
Total Lines | 35 |
Duplicated Lines | 0 % |
Changes | 0 |
1 | # Author: Simon Blanke |
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2 | # Email: [email protected] |
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3 | # License: MIT License |
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4 | |||
5 | import time |
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6 | import numpy as np |
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7 | |||
8 | |||
9 | class Model: |
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10 | def __init__(self, func_, nth_process, _main_args_): |
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11 | self.func_ = func_ |
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12 | self.nth_process = nth_process |
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13 | self.X = _main_args_.X |
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14 | self.y = _main_args_.y |
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15 | |||
16 | def train_model(self, para_dict): |
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17 | start_time = time.time() |
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18 | results = self.func_(para_dict, self.X, self.y) |
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19 | eval_time = time.time() - start_time |
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20 | |||
21 | if isinstance(results, tuple): |
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22 | score = results[0] |
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23 | model = results[1] |
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24 | elif ( |
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25 | isinstance(results, float) |
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26 | or isinstance(results, np.float64) |
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27 | or isinstance(results, np.float32) |
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28 | ): |
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29 | score = results |
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30 | model = None |
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31 | else: |
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32 | print("Error: model function must return float or tuple") |
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33 | |||
34 | return score, eval_time, model |
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35 |