adjust tests

test/test_model_modules/test_abstract_model_class.py

@@ -147,16 +147,16 @@ class TestAbstractModelClass:
         with pytest.raises(ValueError) as einfo:
             amc.compile_options = {"optimizer": keras.optimizers.Adam()}
         assert "Got different values or arguments for same argument: self.optimizer=<class" \
-               " 'tensorflow.python.keras.optimizer_v2.gradient_descent.SGD'> and " \
-               "'optimizer': <class 'tensorflow.python.keras.optimizer_v2.adam.Adam'>" in str(einfo.value)
+               " 'keras.optimizer_v2.gradient_descent.SGD'> and " \
+               "'optimizer': <class 'keras.optimizer_v2.adam.Adam'>" in str(einfo.value)
 
     def test_compile_options_setter_as_mix_attr_dict_invalid_duplicates_same_optimizer_other_args(self, amc):
         amc.optimizer = keras.optimizers.SGD(lr=0.1)
         with pytest.raises(ValueError) as einfo:
             amc.compile_options = {"optimizer": keras.optimizers.SGD(lr=0.001)}
         assert "Got different values or arguments for same argument: self.optimizer=<class" \
-               " 'tensorflow.python.keras.optimizer_v2.gradient_descent.SGD'> and " \
-               "'optimizer': <class 'tensorflow.python.keras.optimizer_v2.gradient_descent.SGD'>" in str(einfo.value)
+               " 'keras.optimizer_v2.gradient_descent.SGD'> and " \
+               "'optimizer': <class 'keras.optimizer_v2.gradient_descent.SGD'>" in str(einfo.value)
 
     def test_compile_options_setter_as_dict_invalid_keys(self, amc):
         with pytest.raises(ValueError) as einfo:

test/test_model_modules/test_flatten_tail.py

@@ -27,7 +27,7 @@ class TestGetActivation:
     def test_layer_act(self, model_input):
         x_in = get_activation(model_input, activation=ELU, name='adv_layer')
         act = x_in._keras_history[0]
-        assert act.name == 'adv_layer'
+        assert act.name == 'tf.nn.elu'
 
     def test_layer_act_invalid(self, model_input):
         with pytest.raises(TypeError) as einfo:
@@ -62,8 +62,8 @@ class TestFlattenTail:
         assert final_dense.units == 2
         assert final_dense.kernel_regularizer is None
         inner_act = self.step_in(final_dense)
-        assert inner_act.name == 'Main_tail_act'
-        assert inner_act.__class__.__name__ == 'ELU'
+        assert inner_act.name == 'tf.nn.elu'
+        assert inner_act.__class__.__name__ == 'TFOpLambda'
         inner_dense = self.step_in(inner_act)
         assert inner_dense.name == 'Main_tail_inner_Dense'
         assert inner_dense.units == 64
@@ -112,9 +112,8 @@ class TestFlattenTail:
                                         'dtype': 'float32', 'data_format': 'channels_last'}
 
         reduc_act = self.step_in(flatten)
-        assert reduc_act.get_config() == {'name': 'Main_tail_all_conv_act', 'trainable': True,
-                                          'dtype': 'float32', 'alpha': 1.0}
-
+        assert reduc_act.get_config() == {'name': 'tf.nn.elu_2', 'trainable': True, 'function': 'nn.elu',
+                                          'dtype': 'float32'}
         reduc_conv = self.step_in(reduc_act)
 
         assert reduc_conv.kernel_size == (1, 1)

test/test_model_modules/test_inception_model.py

@@ -43,7 +43,7 @@ class TestInceptionModelBase:
         assert base.part_of_block == 1
         assert tower.name == 'Block_0a_act_2/Relu:0'
         act_layer = tower._keras_history[0]
-        assert isinstance(act_layer, ReLU)
+        assert isinstance(act_layer, keras.layers.ReLU)
         assert act_layer.name == "Block_0a_act_2"
         # check previous element of tower (conv2D)
         conv_layer = self.step_in(act_layer)
@@ -60,7 +60,7 @@ class TestInceptionModelBase:
         assert pad_layer.name == 'Block_0a_Pad'
         # check previous element of tower (activation)
         act_layer2 = self.step_in(pad_layer)
-        assert isinstance(act_layer2, ReLU)
+        assert isinstance(act_layer2, keras.layers.ReLU)
         assert act_layer2.name == "Block_0a_act_1"
         # check previous element of tower (conv2D)
         conv_layer2 = self.step_in(act_layer2)
@@ -80,7 +80,7 @@ class TestInceptionModelBase:
         # assert tower.name == 'Block_0a_act_2/Relu:0'
         assert tower.name == 'Block_0a_act_2/Relu:0'
         act_layer = tower._keras_history[0]
-        assert isinstance(act_layer, ReLU)
+        assert isinstance(act_layer, keras.layers.ReLU)
         assert act_layer.name == "Block_0a_act_2"
         # check previous element of tower (batch_normal)
         batch_layer = self.step_in(act_layer)
@@ -101,7 +101,7 @@ class TestInceptionModelBase:
         assert pad_layer.name == 'Block_0a_Pad'
         # check previous element of tower (activation)
         act_layer2 = self.step_in(pad_layer)
-        assert isinstance(act_layer2, ReLU)
+        assert isinstance(act_layer2, keras.layers.ReLU)
         assert act_layer2.name == "Block_0a_act_1"
         # check previous element of tower (conv2D)
         conv_layer2 = self.step_in(act_layer2)
@@ -124,7 +124,7 @@ class TestInceptionModelBase:
         tower = base.create_conv_tower(activation=keras.layers.LeakyReLU, **opts)
         assert tower.name == 'Block_0b_act_2/LeakyRelu:0'
         act_layer = tower._keras_history[0]
-        assert isinstance(act_layer, LeakyReLU)
+        assert isinstance(act_layer, keras.layers.LeakyReLU)
         assert act_layer.name == "Block_0b_act_2"
 
     def test_create_conv_tower_1x1(self, base, input_x):
@@ -134,7 +134,7 @@ class TestInceptionModelBase:
         assert base.part_of_block == 1
         assert tower.name == 'Block_0a_act_1/Relu:0'
         act_layer = tower._keras_history[0]
-        assert isinstance(act_layer, ReLU)
+        assert isinstance(act_layer, keras.layers.ReLU)
         assert act_layer.name == "Block_0a_act_1"
         # check previous element of tower (conv2D)
         conv_layer = self.step_in(act_layer)
@@ -160,7 +160,7 @@ class TestInceptionModelBase:
         assert base.part_of_block == 1
         assert tower.name == 'Block_0a_act_1/Relu:0'
         act_layer = tower._keras_history[0]
-        assert isinstance(act_layer, ReLU)
+        assert isinstance(act_layer, keras.layers.ReLU)
         assert act_layer.name == "Block_0a_act_1"
         # check previous element of tower (conv2D)
         conv_layer = self.step_in(act_layer)