test_recurrent_stress_tests.py 文件源码

def test_SimpleLSTM(self):
        params = dict(
            input_dims=[1, 3, 5], go_backwards=True, activation='linear',
            stateful=False, unroll=False, return_sequences=False, output_dim=3,
            inner_activation='linear'
        ),
        model = Sequential()
        if keras.__version__[:2] == '2.':
            model.add(LSTM(units=params[0]['output_dim'],
                           input_shape=(params[0]['input_dims'][1],params[0]['input_dims'][2]),
                           activation=params[0]['activation'],
                           return_sequences=params[0]['return_sequences'],
                           go_backwards=params[0]['go_backwards'],
                           unroll=True,
                           recurrent_activation='linear'
                           ))
        else:
            model.add(LSTM(output_dim=params[0]['output_dim'],
                           input_length=params[0]['input_dims'][1],
                           input_dim=params[0]['input_dims'][2],
                           activation=params[0]['activation'],
                           return_sequences=params[0]['return_sequences'],
                           go_backwards=params[0]['go_backwards'],
                           unroll=True,
                           inner_activation='linear'
                           ))
        relative_error, keras_preds, coreml_preds = simple_model_eval(params, model)
        for i in range(len(relative_error)):
            self.assertLessEqual(relative_error[i], 0.01)