def test_train_save_load_hybrid_self_attention(datasets):
model_save_path = "self_att_hybrid_model.pth"
model = MatchingModel(attr_summarizer=attr_summarizers.Hybrid(
word_contextualizer="self-attention"))
model.run_train(
datasets.train,
datasets.valid,
epochs=1,
batch_size=8,
best_save_path=model_save_path,
pos_neg_ratio=3,
)
s1 = model.run_eval(datasets.test)
model2 = MatchingModel(attr_summarizer=attr_summarizers.Hybrid(
word_contextualizer="self-attention"))
model2.load_state(model_save_path)
s2 = model2.run_eval(datasets.test)
assert s1 == s2
if os.path.exists(model_save_path):
os.remove(model_save_path)
def test_rnn(self):
model_save_path = 'rnn_model.pth'
model = MatchingModel(attr_summarizer='rnn')
model.run_train(self.train,
self.valid,
epochs=1,
batch_size=8,
best_save_path=model_save_path,
pos_neg_ratio=3)
s1 = model.run_eval(self.test)
model2 = MatchingModel(attr_summarizer='rnn')
model2.load_state(model_save_path)
s2 = model2.run_eval(self.test)
self.assertEqual(s1, s2)
if os.path.exists(model_save_path):
os.remove(model_save_path)
def test_train_save_load_rnn(datasets):
model_save_path = "rnn_model.pth"
model = MatchingModel(attr_summarizer="rnn")
model.run_train(
datasets.train,
datasets.valid,
epochs=1,
batch_size=8,
best_save_path=model_save_path,
pos_neg_ratio=3,
)
s1 = model.run_eval(datasets.test)
model2 = MatchingModel(attr_summarizer="rnn")
model2.load_state(model_save_path)
s2 = model2.run_eval(datasets.test)
assert s1 == s2
if os.path.exists(model_save_path):
os.remove(model_save_path)
def test_hybrid_self_attention(self):
model_save_path = 'self_att_hybrid_model.pth'
model = MatchingModel(attr_summarizer=attr_summarizers.Hybrid(
word_contextualizer='self-attention'))
model.run_train(self.train,
self.valid,
epochs=1,
batch_size=8,
best_save_path=model_save_path,
pos_neg_ratio=3)
s1 = model.run_eval(self.test)
model2 = MatchingModel(attr_summarizer=attr_summarizers.Hybrid(
word_contextualizer='self-attention'))
model2.load_state(model_save_path)
s2 = model2.run_eval(self.test)
self.assertEqual(s1, s2)
if os.path.exists(model_save_path):
os.remove(model_save_path)