diff --git a/model_compression_toolkit/core/common/mixed_precision/bit_width_setter.py b/model_compression_toolkit/core/common/mixed_precision/bit_width_setter.py
index 1aadbf25c..76b3fc8d1 100644
--- a/model_compression_toolkit/core/common/mixed_precision/bit_width_setter.py
+++ b/model_compression_toolkit/core/common/mixed_precision/bit_width_setter.py
@@ -84,7 +84,8 @@ def set_bit_widths(mixed_precision_enable: bool,
 
 def _get_node_qc_by_bit_widths(node: BaseNode,
                                bit_width_cfg: List[int],
-                               node_index_in_graph: int) -> Any:
+                               node_index_in_graph: int,
+                               fw_info) -> Any:
     """
     Get the node's quantization configuration that
     matches to the bit width index as in the MP configuration bit_width_cfg.
diff --git a/model_compression_toolkit/trainable_infrastructure/common/get_quantizer_config.py b/model_compression_toolkit/trainable_infrastructure/common/get_quantizer_config.py
index cd9fde61e..3a96191ef 100644
--- a/model_compression_toolkit/trainable_infrastructure/common/get_quantizer_config.py
+++ b/model_compression_toolkit/trainable_infrastructure/common/get_quantizer_config.py
@@ -95,13 +95,14 @@ def get_trainable_quantizer_quantization_candidates(n: BaseNode, attr: str = Non
     """
 
     if attr is not None:
-    # all candidates must have the same weights quantization method
-    weights_quantization_methods = set([cfg.weights_quantization_cfg.weights_quantization_method for cfg in n.candidates_quantization_cfg])
-    if len(weights_quantization_methods) > 1:
-        Logger.critical(f"Invalid 'candidates_quantization_cfg': Inconsistent weights "
-                        f"quantization methods detected: {weights_quantization_methods}. "
-                        f"Trainable quantizer requires all candidates to have the same weights "
-                        f"quantization method.")  # pragma: no cover
+        # all candidates must have the same weights quantization method
+        weights_quantization_methods = set([cfg.weights_quantization_cfg.get_attr_config(attr).weights_quantization_method
+             for cfg in n.candidates_quantization_cfg])
+        if len(weights_quantization_methods) > 1:
+            Logger.critical(f"Invalid 'candidates_quantization_cfg': Inconsistent weights "
+                            f"quantization methods detected: {weights_quantization_methods}. "
+                            f"Trainable quantizer requires all candidates to have the same weights "
+                            f"quantization method.")  # pragma: no cover
 
     # all candidates must have the same activation quantization method
     activation_quantization_methods = set([cfg.activation_quantization_cfg.activation_quantization_method