mmdnn/conversion/mxnet/mxnet_emitter.py [515:544]:
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            axis = 1
            eps = IR_node.IR_layer.attr["epsilon"].f
            momentum = IR_node.IR_layer.attr["momentum"].f

            fix_gamma = not IR_node.IR_layer.attr["scale"].b

            if self.weight_loaded:
                if not fix_gamma:
                #     self.output_weights[IR_node.name + "_gamma"] = np.multiply(weight_dict['scale'], weight_dict_scale['scale'])
                # self.output_weights[IR_node.name + "_beta"] = np.multiply(weight_dict['bias'], weight_dict_scale['scale']) + weight_dict_scale['bias']
                    self.output_weights[IR_node.name + "_gamma"] = weight_dict['scale']
                self.output_weights[IR_node.name + "_beta"] = weight_dict['bias']

            # not supported yet
            use_global_stats = "False"
            if self.weight_loaded:
                self.output_weights[IR_node.name + "_moving_var"] = weight_dict['var']
                self.output_weights[IR_node.name + "_moving_mean"] = weight_dict['mean']

            code = "{:<15} = mx.sym.BatchNorm(data = {}, axis = {}, eps = {}, momentum = {}, fix_gamma = {}, use_global_stats = {}, name = '{}')".format(
                    IR_node.variable_name,
                    self.parent_variable_name(IR_node),
                    axis,
                    eps,
                    momentum,
                    fix_gamma,
                    use_global_stats,
                    IR_node.name)

            return code
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mmdnn/conversion/mxnet/mxnet_emitter.py [551:578]:
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            axis = 1
            eps = IR_node.IR_layer.attr["epsilon"].f
            momentum = IR_node.IR_layer.attr["momentum"].f

            fix_gamma = not IR_node.IR_layer.attr["scale"].b

            if self.weight_loaded:
                if not fix_gamma:
                    self.output_weights[IR_node.name + "_gamma"] = weight_dict['scale']
                self.output_weights[IR_node.name + "_beta"] = weight_dict['bias']

            # not supported yet
            use_global_stats = "False"
            if self.weight_loaded:
                self.output_weights[IR_node.name + "_moving_var"] = weight_dict['var']
                self.output_weights[IR_node.name + "_moving_mean"] = weight_dict['mean']

            code = "{:<15} = mx.sym.BatchNorm(data = {}, axis = {}, eps = {}, momentum = {}, fix_gamma = {}, use_global_stats = {}, name = '{}')".format(
                    IR_node.variable_name,
                    self.parent_variable_name(IR_node),
                    axis,
                    eps,
                    momentum,
                    fix_gamma,
                    use_global_stats,
                    IR_node.name)

            return code
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