if __name__ == '__main__': import Recommender_System.utility.gpu_memory_growth from Recommender_System.algorithm.KGCN.tool import construct_undirected_kg, get_adj_list from Recommender_System.algorithm.KGCN.model import KGCN_model from Recommender_System.algorithm.KGCN.train import train from Recommender_System.data import kg_loader, data_process import tensorflow as tf n_user, n_item, n_entity, n_relation, train_data, test_data, kg, topk_data = data_process.pack_kg( kg_loader.ml1m_kg1m, negative_sample_threshold=4) neighbor_size = 16 adj_entity, adj_relation = get_adj_list(construct_undirected_kg(kg), n_entity, neighbor_size) model = KGCN_model(n_user, n_entity, n_relation, adj_entity, adj_relation, neighbor_size, iter_size=1, dim=16, l2=1e-7, aggregator='sum') train(model, train_data, test_data, topk_data, optimizer=tf.keras.optimizers.Adam(0.01),
if __name__ == '__main__': import Recommender_System.utility.gpu_memory_growth from Recommender_System.algorithm.KGCN.tool import construct_undirected_kg, get_adj_list from Recommender_System.algorithm.KGCN.model import KGCN_model from Recommender_System.algorithm.KGCN.train import train from Recommender_System.algorithm.KGNNLS.tool import get_interaction_table from Recommender_System.algorithm.KGNNLS.model import KGNNLS_model from Recommender_System.data import kg_loader, data_process import tensorflow as tf n_user, n_item, n_entity, n_relation, train_data, test_data, kg, topk_data = data_process.pack_kg(kg_loader.ml1m_kg1m, negative_sample_threshold=4) neighbor_size, iter_size, dim, l2, ls, lr, epochs, batch = 16, 1, 16, 1e-7, 1., 0.01, 10, 512 ''' n_user, n_item, n_entity, n_relation, train_data, test_data, kg, topk_data = data_process.pack_kg(kg_loader.ml20m_kg500k, negative_sample_threshold=4) neighbor_size, iter_size, dim, l2, ls, lr, epochs, batch = 16, 1, 32, 1e-7, 1., 0.01, 10, 65536 n_user, n_item, n_entity, n_relation, train_data, test_data, kg, topk_data = data_process.pack_kg(kg_loader.lastfm_kg15k) neighbor_size, iter_size, dim, l2, ls, lr, epochs, batch = 8, 1, 16, 5e-5, 0.1, 0.001, 7, 128 n_user, n_item, n_entity, n_relation, train_data, test_data, kg, topk_data = data_process.pack_kg(kg_loader.bx_kg150k) neighbor_size, iter_size, dim, l2, ls, lr, epochs, batch = 8, 2, 64, 1e-5, 0.5, 2e-4, 10, 256 ''' interaction_table = get_interaction_table(train_data, n_entity) adj_entity, adj_relation = get_adj_list(construct_undirected_kg(kg), n_entity, neighbor_size) model = KGNNLS_model(n_user, n_entity, n_relation, adj_entity, adj_relation, interaction_table, neighbor_size, iter_size, dim, l2, ls) train(model, train_data, test_data, topk_data, tf.keras.optimizers.Adam(lr), epochs, batch) model = KGCN_model(n_user, n_entity, n_relation, adj_entity, adj_relation, neighbor_size, iter_size, dim, l2) train(model, train_data, test_data, topk_data, tf.keras.optimizers.Adam(lr), epochs, batch)