def METHOD_NAME(g, ops):
    pattern = \
        OpTypePattern('Add', name='output', inputs=[
            OpTypePattern('Mul', name='mul', inputs=[
                OpTypePattern('RandomUniform', name='input1', inputs=["*"]),
                "Const|ConstV2",
            ]),
            "Const|ConstV2",
        ])
    matcher = GraphMatcher(pattern)
    match_results = list(matcher.match_ops(ops))
    for match in match_results:
        output = match.get_op('output')
        mul = match.get_op('mul')
        ru_op = match.get_op('input1')
        tmax_minus_tmin = mul.inputs[1].get_tensor_value()
        tmin = output.inputs[1].get_tensor_value()
        tmax = tmin + tmax_minus_tmin
        to_delete = list(set(match.get_nodes()))
        new_node = create_onnx_random_uniform_op(g, tmax, tmin, ru_op, output, to_delete)
        g.replace_all_inputs(output.output[0], new_node.output[0], ops=ops)
        g.safe_remove_nodes(to_delete)
    return ops