def METHOD_NAME(
    self,
    graph: ONNXGraph,
    model: ModelProto,
    match: MatchResult,
):
    (input_dequant,) = match.parents[0]
    weight_init, weight_quantize_node, weight_dequantize_node = match.parents[1]
    if len(match.parents) == 3:
        (bias_init,) = match.parents[2]
    else:
        bias_init = None
    model = add_quantized_conv_matmul_add_ops(
        model=model,
        node=match.node,
        input_quantize_node=input_dequant,
        weight_quantize_node=weight_quantize_node,
        input_quantize_params=get_quantization_params(
            model, input_dequant, include_target=True
        ),
        weight_quantize_params=get_quantization_params(
            model, weight_quantize_node, include_target=True
        ),
        bias_initializer=bias_init,
        bias_add_name="{}_bias_add".format(match.node.name),
        target_output=match.node.output[0],
        transpose_weight=False,
    )
    # Clean up
    self.delete_node_deferred(weight_dequantize_node)
    self.delete_node_deferred(weight_quantize_node)
    if len(graph.get_node_children(input_dequant)) == 1:
        self.delete_node_deferred(input_dequant)
    self.delete_node_deferred(match.node)