| - history (dict): Dictionary containing evaluation metrics for each run. | - history (dict): Dictionary containing evaluation metrics for each run. | ||||
| """ | """ | ||||
| device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") | device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") | ||||
| print(torch.cuda.is_available()) | |||||
| torch.zeros(1).cuda() | |||||
| # Step 1: Initialize a dictionary to store evaluation metrics | # Step 1: Initialize a dictionary to store evaluation metrics | ||||
| history = {'AUC': [], 'AUPRC': [], "Accuracy": [], "Precision": [], "Recall": [], "F1 score": []} | history = {'AUC': [], 'AUPRC': [], "Accuracy": [], "Precision": [], "Recall": [], "F1 score": []} | ||||
| torch.manual_seed(RANDOM_SEED) | torch.manual_seed(RANDOM_SEED) | ||||
| random.seed(RANDOM_SEED) | random.seed(RANDOM_SEED) | ||||
| np.random.seed(RANDOM_SEED) | np.random.seed(RANDOM_SEED) | ||||
| run(10, is_test=True) | |||||
| run(10, is_test=False) |