Add error messages

Signed-off-by: Kyunggeun Lee <quic_kyunggeu@quicinc.com>

TrainingExtensions/torch/src/python/aimet_torch/v2/quantsim/quantsim.py

@@ -95,7 +95,7 @@ class QuantizationSimModel(V1QuantizationSimModel):
     """
     Overriden QuantizationSimModel that does off-target quantization simulation using v2 quantsim blocks.
     """
-    def __init__(self, # pylint: disable=too-many-arguments, too-many-locals
+    def __init__(self, # pylint: disable=too-many-arguments, too-many-locals, too-many-branches
                  model: torch.nn.Module,
                  dummy_input: Union[torch.Tensor, Tuple],
                  quant_scheme: Union[str, QuantScheme] = None, # NOTE: Planned to be deprecated
@@ -123,12 +123,31 @@ def __init__(self, # pylint: disable=too-many-arguments, too-many-locals
             else:
                 raise TypeError("'rounding_mode' parameter is no longer supported.")
 
-        for module in model.modules():
-            if isinstance(module, BaseQuantizationMixin):
-                raise RuntimeError
-
-            if isinstance(module, QuantizerBase):
-                raise RuntimeError
+        qmodules = {
+            name: module for name, module in model.named_modules()
+            if isinstance(module, BaseQuantizationMixin)
+        }
+        quantizers = {
+            name: module for name, module in model.named_modules()
+            if isinstance(module, QuantizerBase)
+        }
+
+        if isinstance(model, BaseQuantizationMixin):
+            problem = f"the model itself is already a quantized module of type {type(model)}."
+        elif isinstance(model, QuantizerBase):
+            problem = f"the model itself is already a quantizer object of type {type(model)}."
+        elif qmodules:
+            problem = f"the model already contains quantized modules: {', '.join(qmodules.keys())}."
+        elif quantizers:
+            problem = f"the model already contains quantizers: {', '.join(quantizers.keys())}."
+        else:
+            problem = None
+
+        if problem:
+            raise RuntimeError(
+                "QuantizationSimModel can only take base models WITHOUT quantized modules or quantizers, "
+                "but " + problem
+            )
 
         if not in_place:
             model = copy.deepcopy(model)