main.py

import numpy as np
import torch
from torch.utils.data import TensorDataset, DataLoader
from initial_dataSet import DataSet
from model import CICDM


def save_param(save_dir, name, param):
    np.savetxt(save_dir + name, param.cpu().detach().numpy(), fmt='%.6f', delimiter=',')


if __name__ == '__main__':

    # ----------基本参数--------------
    basedir = './'
    dataSet_list = ('ASSIST_0910', 'ASSIST_2017', 'JUNYI', 'MathEC')
    epochs_list = (8, 10, 1, 2)

    dataSet_idx = 3
    test_ratio = 0.2
    batch_size = 64
    potential_num = 32
    learn_rate = 3e-2
    n_splits = 2

    data_set_name = dataSet_list[dataSet_idx]
    epochs = epochs_list[dataSet_idx]
    device = 'cuda'
    # ----------基本参数--------------

    dataSet = DataSet(basedir, data_set_name)
    train_data, test_data = dataSet.get_train_test(dataSet.record, test_ratio=test_ratio)
    exer_conc_adj = dataSet.get_exer_conc_adj()
    conc_conc_adj = dataSet.get_conc_conc_adj()

    total_stu_list = dataSet.total_stu_list

    model = CICDM(student_num=dataSet.student_num,
                  concept_num=dataSet.concept_num,
                  exercise_num=dataSet.exercise_num,
                  exer_conc_adj=exer_conc_adj,
                  conc_conc_adj=conc_conc_adj,
                  potential_num=potential_num,
                  lr=learn_rate,
                  device=device)

    index_loader = DataLoader(TensorDataset(torch.tensor(list(total_stu_list)).float()),
                              batch_size=batch_size, shuffle=True)

    model.fit(index_loader, train_data, epochs=epochs, n_splits=n_splits, test_df=test_data)
    # acc, auc, rmse, mae = model.test(index_loader, train_data, test_data)
    cognitive_state, score_pred = model.get_A_and_Y(index_loader, dataSet.record)

    # 存储参数
    save_param_dir = dataSet.save_parameter_dir
    save_param(save_param_dir, 'H.csv', torch.softmax(model.cd_net.conc_conc_w, dim=0))
    save_param(save_param_dir, 'lambda.csv', torch.sigmoid(model.cd_net.lambd))

    save_result_dir = dataSet.save_result_dir
    save_param(save_result_dir, 'cognitive_state.csv', cognitive_state)