optimum/onnxruntime/configuration.py [425:446]:
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        format, mode, operators_to_quantize = default_quantization_parameters(
            is_static, operators_to_quantize=operators_to_quantize
        )

        # u8/s8 is faster (than u8/u8) on lower-end ARM64 and identical on higher-end ARM64,
        # so let's use u8/s8 by default
        return QuantizationConfig(
            is_static=is_static,
            format=format,
            mode=mode,
            activations_dtype=QuantType.QUInt8,
            activations_symmetric=use_symmetric_activations,
            weights_dtype=QuantType.QInt8,
            weights_symmetric=use_symmetric_weights,
            per_channel=per_channel,
            reduce_range=False,
            nodes_to_quantize=nodes_to_quantize or [],
            nodes_to_exclude=nodes_to_exclude or [],
            operators_to_quantize=operators_to_quantize,
        )

    @staticmethod
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optimum/onnxruntime/configuration.py [596:615]:
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        format, mode, operators_to_quantize = default_quantization_parameters(
            is_static, operators_to_quantize=operators_to_quantize
        )

        return QuantizationConfig(
            is_static=is_static,
            format=format,
            mode=mode,
            activations_dtype=QuantType.QUInt8,
            activations_symmetric=use_symmetric_activations,
            weights_dtype=QuantType.QInt8,
            weights_symmetric=use_symmetric_weights,
            per_channel=per_channel,
            reduce_range=False,
            nodes_to_quantize=nodes_to_quantize or [],
            nodes_to_exclude=nodes_to_exclude or [],
            operators_to_quantize=operators_to_quantize,
        )

    @staticmethod
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