def test_psl_rule_7_run_model(self):
rule_weights = (1.0, )
rule_names = ('rule_7', )
psl_constraints = model.PSLModelMultiWoZ(rule_weights,
rule_names,
config=self.config)
constrained_model = test_util.build_constrained_model([
self.config['max_dialog_size'], self.config['max_utterance_size']
])
constrained_model.fit(self.train_ds,
epochs=self.config['train_epochs'])
logits = eval_model.evaluate_constrained_model(constrained_model,
self.test_ds,
psl_constraints)
predictions = tf.math.argmax(logits[0], axis=-1)
self.assertEqual(predictions[1][2], self.config['class_map']['end'])
self.assertEqual(predictions[2][3], self.config['class_map']['end'])
def test_psl_rule_1_run_model(self):
rule_weights = (1.0, )
rule_names = ('rule_1', )
psl_constraints = model.PSLModelMultiWoZ(rule_weights,
rule_names,
config=self.config)
constrained_model = test_util.build_constrained_model([
self.config['max_dialog_size'], self.config['max_utterance_size']
])
constrained_model.fit(self.train_ds,
epochs=self.config['train_epochs'])
logits = eval_model.evaluate_constrained_model(constrained_model,
self.test_ds,
psl_constraints)
predictions = tf.math.argmax(logits[0], axis=-1)
result = self.check_greet(predictions, self.test_labels[1],
self.config['class_map'])
self.assertTrue(result)