Invalidate irrelevant configuration in node quantization configs

model_compression_toolkit/core/common/graph/base_graph.py

@@ -874,7 +874,7 @@ def override_fused_node_activation_quantization_candidates(self):
             if fusing_op_quantization_cfg is not None and fusing_op_quantization_cfg.enable_activation_quantization:
                 def update(qc):
                     qc.activation_quantization_cfg = NodeActivationQuantizationConfig(fusing_op_quantization_cfg)
-                    qc.activation_quantization_cfg.quant_mode = ActivationQuantizationMode.FLN_QUANT
+                    qc.activation_quantization_cfg.set_quant_mode(ActivationQuantizationMode.FLN_QUANT)
                 node.quantization_cfg.update_all(update, remove_duplicates=True)
             else:
                 node.quantization_cfg.update_activation_quantization_mode(ActivationQuantizationMode.FLN_NO_QUANT)

model_compression_toolkit/core/common/graph/virtual_activation_weights_node.py

@@ -80,8 +80,7 @@ def __init__(self, origin_node: BaseNode, kernel_attr: str):
             base_quantization_cfg=None, validate=False
         )
         for c in self.quantization_cfg.candidates_quantization_cfg:
-            c.activation_quantization_cfg.quant_mode = ActivationQuantizationMode.NO_QUANT
-            c.activation_quantization_cfg.activation_n_bits = FLOAT_BITWIDTH
+            c.activation_quantization_cfg.set_quant_mode(ActivationQuantizationMode.NO_QUANT)
 
 
 class VirtualSplitActivationNode(VirtualSplitNode):

model_compression_toolkit/core/common/mixed_precision/sensitivity_eval/sensitivity_evaluation.py

@@ -99,11 +99,9 @@ def _build_mp_model(self, graph, outputs, disable_activations: bool) -> Tuple[An
         # be added to the model).
         for n in evaluation_graph.get_topo_sorted_nodes():
             if disable_activations or not n.has_configurable_activation():
-                for c in n.candidates_quantization_cfg:
-                    c.activation_quantization_cfg.quant_mode = ActivationQuantizationMode.NO_QUANT
+                n.quantization_cfg.update_activation_quantization_mode(ActivationQuantizationMode.NO_QUANT)
             if not n.has_any_configurable_weight():
-                for c in n.candidates_quantization_cfg:
-                    c.weights_quantization_cfg.disable_all_weights_quantization()
+                n.quantization_cfg.disable_weights_quantization()
 
         model_mp, _, conf_node2layers = self.fw_impl.model_builder(evaluation_graph,
                                                                    mode=ModelBuilderMode.MIXEDPRECISION,

model_compression_toolkit/core/common/quantization/candidate_node_quantization_config.py

@@ -46,6 +46,20 @@ class NodeQuantizationConfig:
 
     validate: InitVar[bool] = True
 
+    def __post_init__(self, validate=True):
+        if validate:
+            if not any(self.base_quantization_cfg == qc for qc in self.candidates_quantization_cfg):
+                raise ValueError('Candidates should contain the base config.')
+            self._validate_consistent_activation_quant_mode()
+            self._validate_consistent_weights_quant_mode()
+
+        self.remove_duplicates()
+
+        # TODO irena
+        # for now make sure they are separate objects so that one doesnt inadvertently modify the other
+        if any(self.base_quantization_cfg is qc for qc in self.candidates_quantization_cfg):
+            self.base_quantization_cfg = copy.deepcopy(self.base_quantization_cfg)
+
     def update_all(self, update_fn: Callable[[CandidateNodeQuantizationConfig], None], remove_duplicates: bool = True):
         """
         Apply update function on the base config and all candidates configs.
@@ -69,7 +83,7 @@ def update_activation_quantization_mode(self, mode: ActivationQuantizationMode):
             mode: quantization mode.
         """
         def fn(c):
-            c.activation_quantization_cfg.quant_mode = mode
+            c.activation_quantization_cfg.set_quant_mode(mode)
 
         self.update_all(fn)
 
@@ -102,17 +116,6 @@ def remove_duplicates(self):
                 uniq_qcs.append(qc)
         self.candidates_quantization_cfg = uniq_qcs
 
-    def __post_init__(self, validate=True):
-        if validate:
-            if not any(self.base_quantization_cfg == qc for qc in self.candidates_quantization_cfg):
-                raise ValueError('Candidates should contain the base config.')
-            self._validate_consistent_activation_quant_mode()
-            self._validate_consistent_weights_quant_mode()
-        # TODO irena
-        # for now make sure they are separate objects so that one doesnt inadvertently modify the other
-        if any(self.base_quantization_cfg is qc for qc in self.candidates_quantization_cfg):
-            self.base_quantization_cfg = copy.deepcopy(self.base_quantization_cfg)
-
     def _validate_consistent_activation_quant_mode(self):
         """
         Validate that base config and all candidates configs contain identical activation quantization mode.