| @@ -111,8 +111,6 @@ def run(k, is_test=False): | |||
| - history (dict): Dictionary containing evaluation metrics for each run. | |||
| """ | |||
| 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 | |||
| history = {'AUC': [], 'AUPRC': [], "Accuracy": [], "Precision": [], "Recall": [], "F1 score": []} | |||
| @@ -176,4 +174,4 @@ if __name__ == '__main__': | |||
| torch.manual_seed(RANDOM_SEED) | |||
| random.seed(RANDOM_SEED) | |||
| np.random.seed(RANDOM_SEED) | |||
| run(10, is_test=True) | |||
| run(10, is_test=False) | |||