What is the use of the seed function in the gym Environment 'Pendulum-v0'? Why do we use the seed function in the 'Pendulum-v0' environment?

https://github.com/openai/gym/blob/master/gym/envs/classic_control/pendulum.py#L25
Reinforcement Learning experiments are empirical and you want to be able to reproduce your experiments. Random numbers are generated off a seed; with the seed function you are fixing the seed so the RNG function produces the same sequence of random numbers.