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# Author: Simon Blanke |
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# Email: [email protected] |
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# License: MIT License |
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from tqdm.auto import tqdm |
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class Verbosity: |
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def init_p_bar(self, _cand_, _core_): |
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pass |
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def update_p_bar(self, n, _cand_): |
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pass |
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def close_p_bar(self): |
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pass |
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def warm_start(self): |
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pass |
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def scatter_start(self): |
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pass |
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def random_start(self): |
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pass |
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def load_meta_data(self): |
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pass |
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def no_meta_data(self): |
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pass |
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def load_samples(self, para): |
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pass |
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class VerbosityLVL0(Verbosity): |
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def __init__(self): |
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pass |
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def print_start_point(self, _cand_): |
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return _cand_._get_warm_start() |
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class VerbosityLVL1(VerbosityLVL0): |
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def __init__(self): |
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pass |
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def print_start_point(self, _cand_): |
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start_point = _cand_._get_warm_start() |
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print("best para =", start_point) |
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print("score =", _cand_.score_best, "\n") |
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return start_point |
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def warm_start(self): |
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print("Set warm start") |
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def scatter_start(self): |
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print("Set scatter init") |
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def random_start(self): |
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print("Set random start position") |
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def load_meta_data(self): |
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print("Loading meta data successful", end="\r") |
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def no_meta_data(self, model_func): |
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print("No meta data found for", model_func.__name__, "function") |
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def load_samples(self, para): |
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print("Loading meta data successful:", len(para), "samples found") |
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class VerbosityLVL2(VerbosityLVL1): |
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def __init__(self): |
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self.best_since_iter = 0 |
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def init_p_bar(self, _cand_, _core_): |
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self.p_bar = tqdm(**self._tqdm_dict(_cand_, _core_)) |
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def update_p_bar(self, n, _cand_): |
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self.p_bar.update(n) |
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def close_p_bar(self): |
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self.p_bar.close() |
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def _tqdm_dict(self, _cand_, _core_): |
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"""Generates the parameter dict for tqdm in the iteration-loop of each optimizer""" |
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return { |
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"total": _core_.n_iter, |
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"desc": "Thread " |
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+ str(_cand_.nth_process) |
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+ " -> " |
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+ _cand_._model_.func_.__name__, |
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"position": _cand_.nth_process, |
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"leave": True, |
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} |
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class VerbosityLVL3(VerbosityLVL2): |
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def __init__(self): |
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self.best_since_iter = 0 |
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def update_p_bar(self, n, _cand_): |
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self.p_bar.update(n) |
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self.p_bar.set_postfix( |
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best_score=str(_cand_.score_best), best_since_iter=self.best_since_iter |
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) |
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