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d934656 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 | import config
import argparse
from utils import *
from pipelines import PipelineManager
import warnings
warnings.filterwarnings("ignore")
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--dataset_name', type=str, default=config.Constants.dataset_name)
parser.add_argument('--evaluation_mode', type=str, default=config.Constants.evaluation_mode)
parser.add_argument('--run_preparatory_phase', type=bool, default=config.TrainingPhase.run_preparatory_phase)
parser.add_argument('--blocking_method', type=str, default=config.Blocking.blocking_method)
parser.add_argument('--seeds_num', type=int, default=config.Constants.seeds_num)
parser.add_argument('--dataset_size_version', type=str, default=config.Constants.dataset_size_version)
parser.add_argument('--vector_normalization', type=str2bool, default=True)
parser.add_argument('--sdr_factor', type=str2bool, default=False)
parser.add_argument('--neg_samples_num', type=int, default=config.Constants.neg_samples_num)
parser.add_argument('--bkafi_criterion', type=str, default=config.Blocking.bkafi_criterion)
parser.add_argument('--run_blocker_train', type=str2bool, default=False)
parser.add_argument('--matching_cands_generation', type=str,
default=config.Constants.matching_cands_generation)
parser.add_argument('--contamination_mode', type=str2bool, default=False)
args = parser.parse_args()
logger = define_logger()
print_config(logger, args)
result_dict = {}
for seed in range(1, args.seeds_num+1):
logger.info(f"Seed: {seed}")
logger.info(3*'--------------------------')
pipeline_manager_obj = PipelineManager(seed, logger, args)
result_dict[seed] = pipeline_manager_obj.result_dict
if not args.run_blocker_train:
generate_final_result_csv(result_dict, args)
logger.info("Done!")
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