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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 collections |
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import numpy as np |
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def check_hyperactive_para(X, y, memory, random_state, verbosity): |
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memory_list = ["short", "long", True, False] |
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if not isinstance(X, np.ndarray): |
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raise ValueError(r'Positional argument X must be of type numpy.ndarray') |
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if not isinstance(y, np.ndarray): |
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raise ValueError(r'Positional argument X must be of type numpy.ndarray') |
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if memory not in memory_list: |
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raise ValueError(r'Keyword argument memory must be "short", "long", True or False') |
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if not isinstance(random_state, int) and not random_state == False: |
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raise ValueError(r'Keyword argument random_state must be of type int or False') |
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if not isinstance(verbosity, int): |
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raise ValueError(r'Keyword argument verbosity must be of type int') |
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def check_search_para(search_config, max_time, n_iter, optimizer, n_jobs, init_config): |
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if not isinstance(search_config, dict): |
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raise ValueError(r'Positional argument search_config must be of type dict') |
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elif isinstance(search_config, dict): |
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_check_search_config(search_config) |
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if not isinstance(max_time, (int, float)) and not max_time == None: |
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raise ValueError(r'Keyword argument max_time must be of type int, float or None') |
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if not isinstance(n_iter, int): |
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raise ValueError(r'Keyword argument n_iter must be of type int') |
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if not isinstance(optimizer, dict) and not isinstance(optimizer, str): |
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raise ValueError(r'Keyword argument optimizer must be of type str or dict') |
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if not isinstance(n_jobs, int): |
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raise ValueError(r'Keyword argument n_jobs must be of type int') |
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if not isinstance(init_config, dict) and not init_config == None: |
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raise ValueError(r'Keyword argument init_config must be of type dict or None') |
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elif isinstance(init_config, dict): |
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_check_init_config(init_config) |
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def _check_search_config(search_config): |
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for key in search_config.keys(): |
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if not isinstance(key, collections.Callable): |
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raise ValueError(r'Key in search_config must be callable') |
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if not isinstance(search_config[key], dict): |
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raise ValueError(r'Value in search_config must be of type dict') |
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def _check_init_config(init_config): |
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for key in init_config.keys(): |
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if not isinstance(key, collections.Callable): |
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raise ValueError(r'Key in init_config must be callable') |
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if not isinstance(init_config[key], dict): |
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raise ValueError(r'Value in init_config must be of type dict') |
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SimonBlanke /
Hyperactive
