Fix rebase changes

model_compression_toolkit/ptq/pytorch/quantization_facade.py

@@ -125,5 +125,5 @@ def pytorch_post_training_quantization(in_module: Module,
     # If torch is not installed,
     # we raise an exception when trying to use these functions.
     def pytorch_post_training_quantization(*args, **kwargs):
-        Logger.critical('PyTorch must be installed to use pytorch_post_training_quantization_experimental. '
+        Logger.critical('PyTorch must be installed to use pytorch_post_training_quantization. '
                         "The 'torch' package is missing.")  # pragma: no cover

model_compression_toolkit/trainable_infrastructure/common/get_quantizer_config.py

@@ -95,13 +95,13 @@ 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.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