def test_save_and_load_model(self):
model = TensorRec(n_components=10)
model.fit(self.interactions,
self.user_features,
self.item_features,
epochs=10)
predictions = model.predict(user_features=self.user_features,
item_features=self.item_features)
ranks = model.predict_rank(user_features=self.user_features,
item_features=self.item_features)
model.save_model(directory_path=self.test_dir)
# Check that, after saving, the same predictions come back
predictions_after_save = model.predict(
user_features=self.user_features, item_features=self.item_features)
ranks_after_save = model.predict_rank(user_features=self.user_features,
item_features=self.item_features)
self.assertTrue((predictions == predictions_after_save).all())
self.assertTrue((ranks == ranks_after_save).all())
# Blow away the session
set_session(None)
tf.reset_default_graph()
# Reload the model, predict, and check for equal predictions
new_model = TensorRec.load_model(directory_path=self.test_dir)
new_predictions = new_model.predict(user_features=self.user_features,
item_features=self.item_features)
new_ranks = new_model.predict_rank(user_features=self.user_features,
item_features=self.item_features)
self.assertTrue((predictions == new_predictions).all())
self.assertTrue((ranks == new_ranks).all())
def test_save_and_load_model(self):
model = TensorRec(n_components=10)
model.fit(self.interactions, self.user_features, self.item_features, epochs=10)
predictions = model.predict(user_features=self.user_features, item_features=self.item_features)
ranks = model.predict_rank(user_features=self.user_features, item_features=self.item_features)
model.save_model(directory_path=self.test_dir)
# Check that, after saving, the same predictions come back
predictions_after_save = model.predict(user_features=self.user_features, item_features=self.item_features)
ranks_after_save = model.predict_rank(user_features=self.user_features, item_features=self.item_features)
self.assertTrue((predictions == predictions_after_save).all())
self.assertTrue((ranks == ranks_after_save).all())
# Blow away the session
set_session(None)
tf.reset_default_graph()
# Reload the model, predict, and check for equal predictions
new_model = TensorRec.load_model(directory_path=self.test_dir)
new_predictions = new_model.predict(user_features=self.user_features, item_features=self.item_features)
new_ranks = new_model.predict_rank(user_features=self.user_features, item_features=self.item_features)
self.assertTrue((predictions == new_predictions).all())
self.assertTrue((ranks == new_ranks).all())
def test_save_and_load_model_same_session(self): model = TensorRec(n_components=10) model.fit(self.interactions, self.user_features, self.item_features, epochs=10) predictions = model.predict(user_features=self.user_features, item_features=self.item_features) ranks = model.predict_rank(user_features=self.user_features, item_features=self.item_features) model.save_model(directory_path=self.test_dir) # Reload the model, predict, and check for equal predictions new_model = TensorRec.load_model(directory_path=self.test_dir) new_predictions = new_model.predict(user_features=self.user_features, item_features=self.item_features) new_ranks = new_model.predict_rank(user_features=self.user_features, item_features=self.item_features) self.assertEqual(predictions.all(), new_predictions.all()) self.assertEqual(ranks.all(), new_ranks.all())
def test_save_and_load_model_same_session(self):
model = TensorRec(n_components=10)
model.fit(self.interactions, self.user_features, self.item_features, epochs=10)
predictions = model.predict(user_features=self.user_features, item_features=self.item_features)
ranks = model.predict_rank(user_features=self.user_features, item_features=self.item_features)
model.save_model(directory_path=self.test_dir)
# Reload the model, predict, and check for equal predictions
new_model = TensorRec.load_model(directory_path=self.test_dir)
new_predictions = new_model.predict(user_features=self.user_features, item_features=self.item_features)
new_ranks = new_model.predict_rank(user_features=self.user_features, item_features=self.item_features)
self.assertTrue((predictions == new_predictions).all())
self.assertTrue((ranks == new_ranks).all())
ks.layers.Dense(n_components * 16, activation='relu'),
ks.layers.Dense(n_components * 4, activation='relu'),
ks.layers.Dense(n_components, activation='linear'),
]
model = TensorRec(n_components=10,
item_repr_graph=ExampleKerasRepresentationGraph(),
user_repr_graph=ExampleKerasRepresentationGraph(),
loss_graph=BalancedWMRBLossGraph())
fit_kwargs = {
'epochs': 100,
'learning_rate': .01,
'n_sampled_items': 100,
'verbose': True
}
result = fit_and_eval(model,
user_features,
item_features,
train_interactions,
test_interactions,
fit_kwargs,
recall_k=100,
precision_k=100,
ndcg_k=100)
model.save_model('/tmp/tensorrec/keras_example/linear_graph')
logging.info(result)