TrainingExtensions/tensorflow/src/python/aimet_tensorflow/quantsim_config/quantsim_config.py
def _get_op_to_quantizer_lists_dict(self) -> Dict[Op, QuantizerListType]:
        """
        For every connected graph op that has a corresponding output quantizer, associate it with a tuple containing 2
        lists:
            - List of quantize ops to change if op's input quantizer setting is set
            - List of quantize ops to change if op's output quantizer setting is set
        :return: Dictionary mapping connected graph ops to a tuple of lists of qc_quantize_ops.
        """
        op_to_two_quantizer_lists_dict = {}
        for op in self._op_to_quant_ops_dict.keys():
            input_quant_op_list = self._get_quant_ops_for_input_setting(op)
            output_quant_op_list = self._get_quant_ops_for_output_setting(op)
            op_to_two_quantizer_lists_dict[op] = (input_quant_op_list, output_quant_op_list)
        return op_to_two_quantizer_lists_dict

        For every connected graph op that has a corresponding output quantizer, associate it with a tuple containing 2
        lists:
            - List of quantize ops to change if op's input quantizer setting is set
            - List of quantize ops to change if op's output quantizer setting is set
        :return: Dictionary mapping connected graph ops to a tuple of lists of qc_quantize_ops.
        
For every connected graph op that has a corresponding output quantizer, associate it with a tuple containing 2
lists:
List of quantize ops to change if op's input quantizer setting is set
List of quantize ops to change if op's output quantizer setting is set
For every connected graph op that has a corresponding output quantizer associate it with a tuple containing 2 lists : List of quantize ops to change if op ' s input quantizer setting is set List of quantize ops to change if op ' s output quantizer setting is set
def _get_op_to_quantizer_lists_dict(self) -> Dict[Op, QuantizerListType]:
        op_to_two_quantizer_lists_dict = {}
        for op in self._op_to_quant_ops_dict.keys():
            input_quant_op_list = self._get_quant_ops_for_input_setting(op)
            output_quant_op_list = self._get_quant_ops_for_output_setting(op)
            op_to_two_quantizer_lists_dict[op] = (input_quant_op_list, output_quant_op_list)
        return op_to_two_quantizer_lists_dict
def _get_op_to_quantizer_lists_dict ( self ) -> Dict [ Op , QuantizerListType ] : op_to_two_quantizer_lists_dict = { } for op in self . _op_to_quant_ops_dict . keys ( ) : input_quant_op_list = self . _get_quant_ops_for_input_setting ( op ) output_quant_op_list = self . _get_quant_ops_for_output_setting ( op ) op_to_two_quantizer_lists_dict [ op ] = ( input_quant_op_list , output_quant_op_list ) return op_to_two_quantizer_lists_dict
For every connected graph op that has a corresponding output quantizer, associate it with a tuple containing 2
lists:
 List of quantize ops to change if op's input quantizer setting is set
 List of quantize ops to change if op's output quantizer setting is set
For every connected graph op that has a corresponding output quantizer associate it with a tuple containing 2 lists : List of quantize ops to change if op ' s input quantizer setting is set List of quantize ops to change if op ' s output quantizer setting is set
"""
        For every connected graph op that has a corresponding output quantizer, associate it with a tuple containing 2
        lists:
            - List of quantize ops to change if op's input quantizer setting is set
            - List of quantize ops to change if op's output quantizer setting is set
        :return: Dictionary mapping connected graph ops to a tuple of lists of qc_quantize_ops.
        """
Dictionary mapping connected graph ops to a tuple of lists of qc_quantize_ops.
Dictionary mapping connected graph ops to a tuple of lists of qc_quantize_ops .
self