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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 time |
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from importlib import import_module |
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import multiprocessing |
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from .checks import check_args |
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from .verbosity import ProgressBar |
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search_process_dict = { |
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False: "SearchProcessNoMem", |
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"short": "SearchProcessShortMem", |
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"long": "SearchProcessLongMem", |
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} |
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search_dict = { |
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False: "Search", |
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"short": "Search", |
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"long": "SearchLongTermMemory", |
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} |
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def set_n_jobs(n_jobs): |
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"""Sets the number of jobs to run in parallel""" |
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num_cores = multiprocessing.cpu_count() |
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if n_jobs == -1 or n_jobs > num_cores: |
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return num_cores |
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else: |
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return n_jobs |
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def get_class(file_path, class_name): |
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module = import_module(file_path, "hyperactive") |
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return getattr(module, class_name) |
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class Hyperactive: |
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def __init__( |
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self, X, y, random_state=None, verbosity=3, warnings=False, ext_warnings=False, |
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): |
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self.training_data = { |
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"features": X, |
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"target": y, |
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} |
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self.verbosity = verbosity |
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self.random_state = random_state |
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self.search_processes = [] |
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def _add_process( |
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self, |
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nth_process, |
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model, |
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search_space, |
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name, |
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n_iter, |
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optimizer, |
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n_jobs, |
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init_para, |
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memory, |
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): |
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search_process_kwargs = { |
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"nth_process": nth_process, |
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"p_bar": ProgressBar(), |
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"model": model, |
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"search_space": search_space, |
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"search_name": name, |
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"n_iter": n_iter, |
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"training_data": self.training_data, |
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"optimizer": optimizer, |
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"n_jobs": n_jobs, |
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"init_para": init_para, |
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"memory": memory, |
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"random_state": self.random_state, |
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} |
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SearchProcess = get_class(".search_process", search_process_dict[memory]) |
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new_search_process = SearchProcess(**search_process_kwargs) |
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self.search_processes.append(new_search_process) |
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def add_search( |
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self, |
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model, |
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search_space, |
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name=None, |
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n_iter=10, |
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optimizer="RandomSearch", |
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n_jobs=1, |
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init_para=[], |
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memory="short", |
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): |
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check_args( |
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model, search_space, n_iter, optimizer, n_jobs, init_para, memory, |
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) |
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n_jobs = set_n_jobs(n_jobs) |
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for nth_job in range(n_jobs): |
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nth_process = len(self.search_processes) |
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self._add_process( |
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nth_process, |
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model, |
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search_space, |
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name, |
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n_iter, |
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optimizer, |
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n_jobs, |
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init_para, |
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memory, |
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) |
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Search = get_class(".search", search_dict[memory]) |
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self.search = Search(self.training_data, self.search_processes) |
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def run(self, max_time=None, distribution=None): |
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if max_time is not None: |
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max_time = max_time * 60 |
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start_time = time.time() |
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self.search.run(start_time, max_time) |
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# self.position_results = self.search.position_results |
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self.eval_times = self.search.eval_times_dict |
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self.iter_times = self.search.iter_times_dict |
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self.best_para = self.search.para_best_dict |
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self.best_score = self.search.score_best_dict |
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SimonBlanke /
Hyperactive
