def test_model13b(self):
    model = Sequential(self.s, model_table='simple_cnn')
    model.add(layer=InputLayer(n_channels=1, height=10, width=10))
    model.add(layer=OutputLayer(n=10, full_connect=False))
    self.assertTrue((model.summary.loc[(1, 'Number of Parameters')] == (0, 0)))
    model1 = Sequential(self.s, model_table='simple_cnn')
    model1.add(layer=InputLayer(n_channels=1, height=10, width=10))
    model1.add(layer=OutputLayer(n=10, full_connect=True))
    self.assertTrue((model1.summary.loc[(1, 'Number of Parameters')] == (1000, 10)))
    model2 = Sequential(self.s, model_table='Simple_CNN')
    model2.add(layer=InputLayer(n_channels=1, height=10, width=10))
    model2.add(layer=OutputLayer(n=10, full_connect=True, include_bias=False))
    self.assertTrue((model2.summary.loc[(1, 'Number of Parameters')] == (1000, 0)))
    model3 = Sequential(self.s, model_table='Simple_CNN')
    model3.add(layer=InputLayer(n_channels=1, height=10, width=10))
    model3.add(layer=Conv2d(4, 3))
    model3.add(layer=OutputLayer(n=10))
    self.assertTrue((model3.summary.loc[(2, 'Number of Parameters')] == (4000, 10)))
    model4 = Sequential(self.s, model_table='Simple_CNN')
    model4.add(layer=InputLayer(n_channels=1, height=10, width=10))
    model4.add(layer=Conv2d(4, 3))
    model4.add(layer=OutputLayer(n=10, full_connect=False))
    self.assertTrue((model4.summary.loc[(2, 'Number of Parameters')] == (0, 0)))
def test_model13b(self):
    model = Sequential(self.s, model_table='simple_cnn')
    model.add(layer=InputLayer(n_channels=1, height=10, width=10))
    model.add(layer=OutputLayer(n=10, full_connect=False))
    self.assertTrue((model.summary.loc[(1, 'Number of Parameters')] == (0, 0)))
    model1 = Sequential(self.s, model_table='simple_cnn')
    model1.add(layer=InputLayer(n_channels=1, height=10, width=10))
    model1.add(layer=OutputLayer(n=10, full_connect=True))
    self.assertTrue((model1.summary.loc[(1, 'Number of Parameters')] == (1000, 10)))
    model2 = Sequential(self.s, model_table='Simple_CNN')
    model2.add(layer=InputLayer(n_channels=1, height=10, width=10))
    model2.add(layer=OutputLayer(n=10, full_connect=True, include_bias=False))
    self.assertTrue((model2.summary.loc[(1, 'Number of Parameters')] == (1000, 0)))
    model3 = Sequential(self.s, model_table='Simple_CNN')
    model3.add(layer=InputLayer(n_channels=1, height=10, width=10))
    model3.add(layer=Conv2d(4, 3))
    model3.add(layer=OutputLayer(n=10))
    self.assertTrue((model3.summary.loc[(2, 'Number of Parameters')] == (4000, 10)))
    model4 = Sequential(self.s, model_table='Simple_CNN')
    model4.add(layer=InputLayer(n_channels=1, height=10, width=10))
    model4.add(layer=Conv2d(4, 3))
    model4.add(layer=OutputLayer(n=10, full_connect=False))
    self.assertTrue((model4.summary.loc[(2, 'Number of Parameters')] == (0, 0)))