]
evaluator = AdLTREvaluator(cuda=cuda)
if config_with_json: # specify configuration with json files
# the directory of json files
#dir_json = '/home/dl-box/WorkBench/ExperimentBench/ALTR/ecir2021/irgan/mq2008_json/'
dir_json = '/home/dl-box/WorkBench/ExperimentBench/ALTR/ecir2021/irgan/ms30k_json/'
#dir_json = '/home/dl-box/WorkBench/ExperimentBench/ALTR/ecir2021/irfgan/mq2008_json/'
dir_json = '/home/dl-box/WorkBench/ExperimentBench/ALTR/ecir2021/irfgan/ms30k_json/'
#dir_json = '/Users/dryuhaitao/WorkBench/Dropbox/CodeBench/GitPool/irgan_ptranking/testing/ltr_adversarial/json/'
for model_id in models_to_run:
evaluator.run(debug=debug, model_id=model_id, config_with_json=config_with_json, dir_json=dir_json)
else: # specify configuration manually
data_id = 'MQ2008_Super'
''' Location of the adopted data '''
dir_data = '/Users/dryuhaitao/WorkBench/Corpus/' + 'LETOR4.0/MQ2008/'
#dir_data = '/home/dl-box/WorkBench/Datasets/L2R/LETOR4.0/MQ2008/'
#dir_data = '/Users/solar/WorkBench/Datasets/L2R/LETOR4.0/MQ2008/'
''' Output directory '''
dir_output = '/Users/dryuhaitao/WorkBench/CodeBench/Bench_Output/NeuralLTR/ALTR/'
#dir_output = '/home/dl-box/WorkBench/CodeBench/PyCharmProject/Project_output/Out_L2R/Listwise/'
#dir_output = '/Users/solar/WorkBench/CodeBench/PyCharmProject/Project_output/Out_L2R/'
grid_search = False # with grid_search, we can explore the effects of different hyper-parameters of a model
| IRGAN_MQ2008_Semi |
-----------------------------------------------------------------------------------------
"""
''' selected dataset '''
data_id = 'MQ2007_Super'
''' location of the adopted data '''
dir_data = os.path.join(DATASET_DIR, 'MQ2007/')
#dir_data = '/home/dl-box/WorkBench/Datasets/L2R/LETOR4.0/MQ2008/'
#dir_data = '/Users/solar/WorkBench/Datasets/L2R/LETOR4.0/MQ2008/'
''' output directory '''
dir_output = os.path.join(PROJECT_OUTPUT_DIR, 'NeuralLTR/Listwise/')
#dir_output = '/home/dl-box/WorkBench/CodeBench/PyCharmProject/Project_output/Out_L2R/Listwise/'
#dir_output = '/Users/solar/WorkBench/CodeBench/PyCharmProject/Project_output/Out_L2R/'
debug = True # with a debug mode, we can make a quick test, e.g., check whether the model can operate or not
grid_search = False # with grid_search, we can explore the effects of different hyper-parameters of a model
evaluator = AdLTREvaluator()
to_run_models = ['IRGAN_Pair']
for model_id in to_run_models:
evaluator.run(debug=debug,
model_id=model_id,
data_id=data_id,
dir_data=dir_data,
dir_output=dir_output,
grid_search=grid_search)