Code Duplication    Length = 35-35 lines in 2 locations

hyperactive/memory.py 1 location

@@ 182-216 (lines=35) @@
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            _verb_.no_meta_data(model_func)
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            return None, None
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    def _get_opt_meta_data(self):
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        results_dict = {}
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        para_list = []
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        score_list = []
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        for key in self.memory_dict.keys():
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            pos = np.fromstring(key, dtype=int)
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            para = self._space_.pos2para(pos)
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            score = self.memory_dict[key]
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            for key in para.keys():
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                if (
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                    not isinstance(para[key], int)
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                    and not isinstance(para[key], float)
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                    and not isinstance(para[key], str)
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                ):
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                    para_dill = dill.dumps(para[key])
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                    para_hash = self._get_hash(para_dill)
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                    with open(
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                        self.func_path + str(para_hash) + ".pkl", "wb"
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                    ) as pickle_file:
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                        dill.dump(para_dill, pickle_file)
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                    para[key] = para_hash
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            if score != 0:
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                para_list.append(para)
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                score_list.append(score)
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        results_dict["params"] = para_list
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        results_dict["mean_test_score"] = score_list
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        return results_dict
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    def _load_data_into_memory(self, paras, scores):
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hyperactive/extensions/memory/memory.py 1 location

@@ 180-214 (lines=35) @@
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            _verb_.no_meta_data(model_func)
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            return None, None
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    def _get_opt_meta_data(self):
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        results_dict = {}
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        para_list = []
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        score_list = []
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        for key in self.memory_dict.keys():
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            pos = np.fromstring(key, dtype=int)
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            para = self._space_.pos2para(pos)
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            score = self.memory_dict[key]
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            for key in para.keys():
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                if (
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                    not isinstance(para[key], int)
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                    and not isinstance(para[key], float)
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                    and not isinstance(para[key], str)
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                ):
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                    para_dill = dill.dumps(para[key])
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                    para_hash = self._get_hash(para_dill)
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                    with open(
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                        self.func_path + str(para_hash) + ".pkl", "wb"
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                    ) as pickle_file:
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                        dill.dump(para_dill, pickle_file)
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                    para[key] = para_hash
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            if score != 0:
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                para_list.append(para)
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                score_list.append(score)
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        results_dict["params"] = para_list
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        results_dict["mean_test_score"] = score_list
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        return results_dict
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    def _load_data_into_memory(self, paras, scores):
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