def test_validation_evaluate_and_classification_report(self, *mocks):
model = CharLoadTFModel(self.model_path, self.label_mapping)
model._construct_model() # must make model to do priv validate func
# validation data
val_gen = [[
np.ones((2, 20)), # x_data
np.zeros((2, 20, model.num_labels)), # y_data
]]
val_gen[0][1][0, :11, self.label_mapping["ADDRESS"]] = 1
f1, f1_report = model._validate_training(val_gen, 32, True, True)
self.assertIsNotNone(f1)
self.assertIsNotNone(f1_report)
self.assertEqual(11, f1_report["ADDRESS"]["support"])
def test_param_validation(self, *mocks):
# Make sure all parameters can be altered. Make sure non-valid params
# are caught
parameters = {
"default_label": "UNKNOWN",
}
invalid_parameters = {
"fake_extra_param": "fails",
}
model = CharLoadTFModel(self.model_path,
label_mapping=self.label_mapping,
parameters=parameters)
model._construct_model()
self.assertDictEqual(parameters, model._parameters)
with self.assertRaises(ValueError):
CharLoadTFModel(
self.model_path,
label_mapping=self.label_mapping,
parameters=invalid_parameters,
)