fix tests

Author: irenab

tests/keras_tests/feature_networks_tests/feature_networks/network_editor/node_filter_test.py

@@ -44,9 +44,10 @@ class ScopeFilterTest(BaseKerasFeatureNetworkTest):
     - Check attribute changes
     '''
 
-    def __init__(self, unit_test, activation_n_bits: int = 3, weights_n_bits: int = 3):
-        self.activation_n_bits = activation_n_bits
-        self.weights_n_bits = weights_n_bits
+    def __init__(self, unit_test):
+        self.activation_n_bits = 5
+        self.weights_n_bits = 3
+        self.weights_n_bits2 = 2
         self.kernel = 3
         self.num_conv_channels = 4
         self.scope = 'scope'
@@ -73,12 +74,9 @@ def get_debug_config(self):
                           EditRule(filter=NodeNameScopeFilter(self.scope),
                                    action=ChangeCandidatesWeightsQuantConfigAttr(attr_name=KERNEL,
                                                                                  weights_n_bits=self.weights_n_bits)),
-                          EditRule(filter=NodeNameScopeFilter('change_2'),
-                                   action=ChangeCandidatesWeightsQuantConfigAttr(attr_name=KERNEL,
-                                                                                 enable_weights_quantization=True)),
                           EditRule(filter=NodeNameScopeFilter('change_2') or NodeNameScopeFilter('does_not_exist'),
                                    action=ChangeCandidatesWeightsQuantConfigAttr(attr_name=KERNEL,
-                                                                                 enable_weights_quantization=False))
+                                                                                 weights_n_bits=self.weights_n_bits2))
                           ]
         return mct.core.DebugConfig(network_editor=network_editor)
 
@@ -107,10 +105,12 @@ def compare(self, quantized_model, float_model, input_x=None, quantization_info=
         self.unit_test.assertTrue(
             len(np.unique(conv_layers[1].get_quantized_weights()['kernel'].numpy())) in [2 ** (self.weights_n_bits) - 1,
                                                                              2 ** (self.weights_n_bits)])
+        self.unit_test.assertTrue(
+            len(np.unique(conv_layers[2].get_quantized_weights()['kernel'].numpy())) in [2 ** (self.weights_n_bits2) - 1,
+                                                                                         2 ** (self.weights_n_bits2)])
+
         # check that this conv's weights did not change
         self.unit_test.assertTrue(np.all(conv_layers[0].get_quantized_weights()['kernel'].numpy() == self.conv_w))
-        # check that this conv's weights did not change
-        self.unit_test.assertTrue(np.all(conv_layers[2].kernel == self.conv_w))
         holder_layers = get_layers_from_model_by_type(quantized_model, KerasActivationQuantizationHolder)
         self.unit_test.assertTrue(holder_layers[1].activation_holder_quantizer.get_config()['num_bits'] == 16)
         self.unit_test.assertTrue(holder_layers[2].activation_holder_quantizer.get_config()['num_bits'] == self.activation_n_bits)

tests/keras_tests/function_tests/test_activation_weights_composition_substitution.py

@@ -214,7 +214,7 @@ def test_two_conv_net_compose_after_split_activation_only(self):
 
         graph.skip_validation_check = False
 
-        self._verify_two_conv_with_split_test(graph, v_graph, 9, 3)
+        self._verify_two_conv_with_split_test(graph, v_graph, 3, 3)
 
     def test_all_weights_layers_composition(self):
         in_model = multiple_weights_nodes_model()