Reverted backend aware quantization API (#2501)

Signed-off-by: Chetan Gulecha <[email protected]>

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

@@ -143,8 +143,7 @@ def __init__(self, model: torch.nn.Module, dummy_input: Union[torch.Tensor, Tupl
                  quant_scheme: Union[str, QuantScheme] = QuantScheme.post_training_tf_enhanced,
                  rounding_mode: str = 'nearest', default_output_bw: int = 8, default_param_bw: int = 8,
                  in_place: bool = False, config_file: str = None,
-                 default_data_type: QuantizationDataType = QuantizationDataType.int,
-                 master_opdef_file: str = None, backend_opdef_files: List[str] = None):
+                 default_data_type: QuantizationDataType = QuantizationDataType.int):
         """
         Constructor for QuantizationSimModel.
 
@@ -163,10 +162,6 @@ def __init__(self, model: torch.nn.Module, dummy_input: Union[torch.Tensor, Tupl
                                  Possible options are QuantizationDataType.int and QuantizationDataType.float.
                                  Note that the mode default_data_type=QuantizationDataType.float is only supported with
                                  default_output_bw=16 and default_param_bw=16
-        :param master_opdef_file: Path to xml file for master ops definition
-        :param backend_opdef_files: List of paths to xml file for backend ops definition
-                                    The bitwidth, datatype applied in case of no matching found
-                                    will be taken according to the order of xml provided
         """
         # Perform sanity checks on inputs
         validate_quantsim_inputs(quant_scheme, rounding_mode, default_output_bw, default_param_bw,
@@ -217,18 +212,8 @@ def __init__(self, model: torch.nn.Module, dummy_input: Union[torch.Tensor, Tupl
 
         # pylint: disable=protected-access
         self._hw_version = quantsim_configurator._get_hw_version()
-
-        if master_opdef_file is not None and backend_opdef_files is not None:
-            try:
-                from aimet_common.backend_aware_quantsim_utility import populate_backend_info, QuantsimInfo
-                quantsim_info = QuantsimInfo(self._default_output_bw, self._default_param_bw, default_data_type)
-                self._supported_kernels = populate_backend_info(self.model, quantsim_configurator.get_module_names(),
-                                                                master_opdef_file, backend_opdef_files, quantsim_info)
-            except ImportError:
-                raise ImportError('Modules for backend aware quantization not found.')
-        else:
-            self._supported_kernels = quantsim_configurator.get_supported_kernels()
-            self._validate_supported_kernels_for_quantizers(SUPPORTED_KERNELS_ACTION)
+        self._supported_kernels = quantsim_configurator.get_supported_kernels()
+        self._validate_supported_kernels_for_quantizers(SUPPORTED_KERNELS_ACTION)
 
     def get_supported_kernels(self) -> Dict:
         """