/
algorithm_factory.py
77 lines (70 loc) · 4.24 KB
/
algorithm_factory.py
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import os, sys
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__))))
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".." )))
from algorithm.base import DepressionDetectionAlgorithmBase
from algorithm.ml_saeb import DepressionDetectionAlgorithm_ML_saeb
from algorithm.ml_canzian import DepressionDetectionAlgorithm_ML_canzian
from algorithm.ml_wahle import DepressionDetectionAlgorithm_ML_wahle
from algorithm.ml_farhan import DepressionDetectionAlgorithm_ML_farhan
from algorithm.ml_lu import DepressionDetectionAlgorithm_ML_lu
from algorithm.ml_wang import DepressionDetectionAlgorithm_ML_wang
from algorithm.ml_chikersal import DepressionDetectionAlgorithm_ML_chikersal
from algorithm.ml_xu_interpretable import DepressionDetectionAlgorithm_ML_xu_interpretable
from algorithm.ml_xu_personalized import DepressionDetectionAlgorithm_ML_xu_personalized
from algorithm.dl_erm import DepressionDetectionAlgorithm_DL_erm
from algorithm.dl_siamese import DepressionDetectionAlgorithm_DL_siamese
from algorithm.dl_reorder import DepressionDetectionAlgorithm_DL_reorder
from algorithm.dl_mldg import DepressionDetectionAlgorithm_DL_mldg
from algorithm.dl_masf import DepressionDetectionAlgorithm_DL_masf
from algorithm.dl_csd import DepressionDetectionAlgorithm_DL_csd
from algorithm.dl_dann import DepressionDetectionAlgorithm_DL_dann
from algorithm.dl_irm import DepressionDetectionAlgorithm_DL_irm
from algorithm.dl_clustering import DepressionDetectionAlgorithm_DL_clustering
def load_algorithm(config_name:str) -> DepressionDetectionAlgorithmBase:
"""Load an algorithm given a config name
Args:
config_name (str): config name
Raises:
ValueError: Unsupported algorithm
Returns:
DepressionDetectionAlgorithmBase: algorithm object
"""
if (config_name.startswith("ml_saeb")):
algorithm = DepressionDetectionAlgorithm_ML_saeb(config_name = config_name)
elif (config_name.startswith("ml_canzian")):
algorithm = DepressionDetectionAlgorithm_ML_canzian(config_name = config_name)
elif (config_name.startswith("ml_wahle")):
algorithm = DepressionDetectionAlgorithm_ML_wahle(config_name = config_name)
elif (config_name.startswith("ml_farhan")):
algorithm = DepressionDetectionAlgorithm_ML_farhan(config_name = config_name)
elif (config_name.startswith("ml_lu")):
algorithm = DepressionDetectionAlgorithm_ML_lu(config_name = config_name)
elif (config_name.startswith("ml_wang")):
algorithm = DepressionDetectionAlgorithm_ML_wang(config_name = config_name)
elif (config_name.startswith("ml_chikersal")):
algorithm = DepressionDetectionAlgorithm_ML_chikersal(config_name = config_name)
elif (config_name.startswith("ml_xu_interpretable")):
algorithm = DepressionDetectionAlgorithm_ML_xu_interpretable(config_name = config_name)
elif (config_name.startswith("ml_xu_personalized")):
algorithm = DepressionDetectionAlgorithm_ML_xu_personalized(config_name = config_name)
elif (config_name.startswith("dl_erm")):
algorithm = DepressionDetectionAlgorithm_DL_erm(config_name = config_name)
elif (config_name.startswith("dl_irm")):
algorithm = DepressionDetectionAlgorithm_DL_irm(config_name = config_name)
elif (config_name.startswith("dl_mldg")):
algorithm = DepressionDetectionAlgorithm_DL_mldg(config_name = config_name)
elif (config_name.startswith("dl_masf")):
algorithm = DepressionDetectionAlgorithm_DL_masf(config_name = config_name)
elif (config_name.startswith("dl_dann")):
algorithm = DepressionDetectionAlgorithm_DL_dann(config_name = config_name)
elif (config_name.startswith("dl_csd")):
algorithm = DepressionDetectionAlgorithm_DL_csd(config_name = config_name)
elif (config_name.startswith("dl_siamese")):
algorithm = DepressionDetectionAlgorithm_DL_siamese(config_name = config_name)
elif ("dl_reorder" in config_name):
algorithm = DepressionDetectionAlgorithm_DL_reorder(config_name = config_name)
elif ("dl_clustering" in config_name):
algorithm = DepressionDetectionAlgorithm_DL_clustering(config_name = config_name)
else:
raise ValueError(f"config_name: {config_name} is not supported")
return algorithm