Add getter methods in QuantDtypeBwInfo (#2595)

Signed-off-by: yathindra kota <quic_ykota@quicinc.com>

TrainingExtensions/common/src/python/aimet_common/defs.py

@@ -346,6 +346,7 @@ class AdaroundConstants:
 
 class QuantizationDataType(Enum):
     """ Enumeration of tensor quantizer data types supported """
+    undefined = 0
     int = 1
     float = 2
 
@@ -361,7 +362,9 @@ class QuantDtypeBwInfo:
     QuantDtypeBwInfo holds activation dtype/bw and param dtype/bw
     """
 
-    def __init__(self, act_dtype: QuantizationDataType, act_bw: int, param_dtype: QuantizationDataType = None, param_bw: int = None):
+
+    def __init__(self, act_dtype: QuantizationDataType, act_bw: int,
+                 param_dtype: QuantizationDataType = QuantizationDataType.undefined, param_bw: int = 0):
         """
         Data class to hold dtype and bw info
         :param act_dtype: Activation datatype of type QuantizationDataType
@@ -375,9 +378,11 @@ def __init__(self, act_dtype: QuantizationDataType, act_bw: int, param_dtype: Qu
         self.param_bw = param_bw
         self._validate_inputs()
 
+    def __repr__(self):
+        return f'(activation:({self.act_dtype}, {self.act_bw}) param:({self.param_dtype}, {self.param_bw})'
+
     def __str__(self):
-        return (f'(activation_data_type = {self.act_dtype}, act_bw = {self.act_bw} '
-                f'param_data_type = {self.param_dtype} param_bw = {self.param_bw})')
+        return f'activation:({self.act_dtype}, {self.act_bw}) param:({self.param_dtype}, {self.param_bw})'
 
     def __eq__(self, other):
         return self.act_dtype == other.act_dtype and self.act_bw == other.act_bw and \
@@ -396,18 +401,26 @@ def _validate_inputs(self):
             raise ValueError(
                 'float act_dtype can only be used when act_bw is set to 16, not ' + str(self.act_bw))
 
-    def is_same_activation(self, bw: int, dtype: QuantizationDataType):
+    def is_same_activation(self, dtype: QuantizationDataType, bw: int):
         """
         helper function to check if activation of the object is same as input
         :param bw: bitwidth to verify against
         :param dtype: dtype to verify against
         """
         return bw == self.act_bw and dtype == self.act_dtype
 
-    def is_same_param(self, bw: int, dtype: QuantizationDataType):
+    def is_same_param(self, dtype: QuantizationDataType, bw: int):
         """
         helper function to check if param of the object is same as input
         :param bw: bitwidth to verify against
         :param dtype: dtype to verify against
         """
         return bw == self.param_bw and dtype == self.param_dtype
+
+    def get_activation(self) -> tuple:
+        """ getter method for activation candidate"""
+        return self.act_dtype, self.act_bw
+
+    def get_param(self) -> tuple:
+        """ getter method for param candidate"""
+        return self.param_dtype, self.param_bw

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

@@ -1681,7 +1681,7 @@ def apply_act_rules(act: Tuple[int, QuantizationDataType], allowed_supported_ker
             """
             if action != SupportedKernelsAction.allow_error:
                 for k in allowed_supported_kernels:
-                    if k.is_same_activation(act[0], act[1]):
+                    if k.is_same_activation(act[1], act[0]):
                         return
 
                 if action == SupportedKernelsAction.warn_on_error: