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)