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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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import os |
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import json |
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import shutil |
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import hashlib |
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import inspect |
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import numpy as np |
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from .memory_load import MemoryLoad |
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from .memory_dump import MemoryDump |
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class Memory: |
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def __init__(self): |
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current_path = os.path.realpath(__file__) |
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self.meta_learn_path, _ = current_path.rsplit("/", 1) |
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self.meta_path = self.meta_learn_path + "/meta_data/" |
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def get_best_models(self, X, y): |
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# TODO: model_dict key:model value:score |
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return model_dict |
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def get_model_search_config(self, model): |
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# TODO |
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return search_config |
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def get_model_init_config(self, model): |
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# TODO |
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return init_config |
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def delete_model(self, model): |
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model_hash = self._get_model_hash(model) |
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shutil.rmtree(self.meta_path + str(model_hash)) |
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def delete_model_dataset(self, model, X, y): |
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self.func_path_ = self._get_model_hash(model) + "/" |
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self.func_path = self.meta_path + self.func_path_ |
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self.feature_hash = self._get_hash(X) |
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self.label_hash = self._get_hash(y) |
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csv_file = self._get_file_path() |
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os.remove(csv_file) |
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def merge_model_hashes(self, model1, model2): |
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# do checks if search space has same dim |
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with open(self.meta_path + 'model_connections.json') as f: |
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data = json.load(f) |
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model1_hash = self._get_model_hash(model1) |
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model2_hash = self._get_model_hash(model2) |
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models_dict = {str(model1_hash): str(model2_hash)} |
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data.update(models_dict) |
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with open(self.meta_path + 'model_connections.json', 'w') as f: |
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json.dump(data, f) |
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def split_model_hashes(self, model1, model2): |
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# TODO: do checks if search space has same dim |
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with open(self.meta_path + 'model_connections.json') as f: |
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data = json.load(f) |
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model1_hash = self._get_model_hash(model1) |
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model2_hash = self._get_model_hash(model2) |
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if model1_hash in data.keys(): |
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del data[model1_hash] |
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if model2_hash in data.keys(): |
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del data[model2_hash] |
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with open(self.meta_path + 'model_connections.json', 'w') as f: |
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json.dump(data, f) |
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def _get_model_hash(self, model): |
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return self._get_hash(self._get_func_str(model).encode("utf-8")) |
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def _get_file_path(self): |
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if not os.path.exists(self.date_path): |
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os.makedirs(self.date_path) |
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return self.func_path + (self.feature_hash + "_" + self.label_hash + "_.csv") |
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def _get_func_str(self, func): |
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return inspect.getsource(func) |
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def _get_hash(self, object): |
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return hashlib.sha1(object).hexdigest() |
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class BaseMemory: |
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def __init__(self, _space_, _main_args_, _cand_): |
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self._space_ = _space_ |
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self._main_args_ = _main_args_ |
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self.pos_best = None |
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self.score_best = -np.inf |
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self.memory_type = _main_args_.memory |
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self.memory_dict = {} |
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self.meta_data_found = False |
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self.n_dims = None |
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class ShortTermMemory(BaseMemory): |
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def __init__(self, _space_, _main_args_, _cand_): |
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super().__init__(_space_, _main_args_, _cand_) |
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class LongTermMemory(BaseMemory): |
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def __init__(self, _space_, _main_args_, _cand_): |
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super().__init__(_space_, _main_args_, _cand_) |
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self._load_ = MemoryLoad(_space_, _main_args_, _cand_) |
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self._dump_ = MemoryDump(_space_, _main_args_, _cand_) |
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def load_memory(self, _cand_, _verb_): |
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self.memory_dict = self._load_._load_memory(_cand_, _verb_, self.memory_dict) |
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def save_memory(self, _main_args_, _opt_args_, _cand_): |
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self._dump_._save_memory(_main_args_, _opt_args_, _cand_, self.memory_dict) |
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def _get_hash(self, object): |
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return hashlib.sha1(object).hexdigest() |
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def _get_func_str(self, func): |
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return inspect.getsource(func) |
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def _obj2hash(self): |
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obj2hash_dict = {} |
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para_hash_list = self._get_para_hash_list() |
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for para_hash in para_hash_list: |
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obj = self._read_dill(para_hash) |
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obj2hash_dict[para_hash] = obj |
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return obj2hash_dict |
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SimonBlanke /
Hyperactive
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