def test_DIN_att():
model_name = "DIN_att"
x, y, feature_dim_dict, behavior_feature_list = get_xy_fd()
model = DIN(feature_dim_dict, behavior_feature_list, hist_len_max=4, embedding_size=8,
hidden_size=[4, 4, 4], keep_prob=0.6,)
model.compile('adam', 'binary_crossentropy',
metrics=['binary_crossentropy'])
model.fit(x, y, verbose=1, validation_split=0.5)
print(model_name+" test train valid pass!")
model.save_weights(model_name + '_weights.h5')
model.load_weights(model_name + '_weights.h5')
print(model_name+" test save load weight pass!")
# try:
# save_model(model, name + '.h5')
# model = load_model(name + '.h5', custom_objects)
# print(name + " test save load model pass!")
# except:
# print("【Error】There is a bug when save model use Dice---------------------------------------------------")
print(model_name + " test pass!")
def test_DIN_att():
model_name = "DIN_att"
x, y, feature_dim_dict, behavior_feature_list = get_xy_fd()
model = DIN(feature_dim_dict, behavior_feature_list, hist_len_max=4, embedding_size=8,
hidden_size=[4, 4, 4], keep_prob=0.6,)
model.compile('adam', 'binary_crossentropy',
metrics=['binary_crossentropy'])
model.fit(x, y, verbose=1, validation_split=0.5)
print(model_name+" test train valid pass!")
model.save_weights(model_name + '_weights.h5')
model.load_weights(model_name + '_weights.h5')
print(model_name+" test save load weight pass!")
print(model_name + " test pass!")