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, aggregator, lr, epochs, batch = 16, 1, 16, 1e-7, 1., 'neighbor', 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, aggregator, lr, epochs, batch = 16, 1, 32, 1e-7, 1., 'sum', 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, aggregator, lr, epochs, batch = 8, 1, 16, 4e-5, 0.1, 'sum', 0.001, 10, 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, aggregator, lr, epochs, batch = 8, 2, 64, 1e-5, 0.5, 'sum', 1e-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, aggregator)
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, aggregator)
train(model, train_data, test_data, topk_data,
tf.keras.optimizers.Adam(lr), epochs, batch)
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),
epochs=10,
batch=512)
adj_relation,
interaction_table,
neighbor_size,
iter_size=1,
dim=32,
l2=1e-7)
train(model,
train_data,
test_data,
topk_data,
optimizer=tf.keras.optimizers.Adam(0.01),
epochs=10,
batch=512)
model = KGCN_model(n_user,
n_entity,
n_relation,
adj_entity,
adj_relation,
neighbor_size,
iter_size=1,
dim=32,
l2=1e-7)
train2(model,
train_data,
test_data,
topk_data,
optimizer=tf.keras.optimizers.Adam(0.01),
epochs=10,
batch=512)