Could not render SAC pendulum example given in Documentation

I have tried Pendulum-v0 animation to run in different codes but the code of stable_baselines docs of SAC only shows me the first frame of pendulum render screen and does not animate throughout.

Here is the code in which I can see the animation:

import gym
env = gym.make('Pendulum-v0')
env.reset()

for i in range(1000):
    env.step(env.action_space.sample())
    env.render()

Here is the docs code of SAC I found and the animation freezes:

import gym
import numpy as np

from stable_baselines.sac.policies import MlpPolicy
from stable_baselines import SAC

env = gym.make('Pendulum-v0')

model = SAC(MlpPolicy, env, verbose=1)
model.learn(total_timesteps=100000, log_interval=10)
model.save("sac_pendulum")

model = SAC.load("sac_pendulum")

obs = env.reset()
while True:
    action, _states = model.predict(obs)
    obs, rewards, dones, info = env.step(action)
    env.render()

This code runs but the render screen freezes in the first frame:

System Info Stable Baselines[mpi] Installed from pip Ubuntu 16.04 Nvidia GeForce 940m Python version - 3.7.6 Tensorflow version - 1.15.0 (GPU version) Using IPython in terminal

[araffin]

What I meant, this should work:

import gym
import numpy as np

from stable_baselines import SAC

env = gym.make('Pendulum-v0')

model = SAC('MlpPolicy', env, verbose=1)

# Render before training for 500 steps
obs = env.reset()
for _ in range(500):
    action, _states = model.predict(obs)
    obs, reward, done, info = env.step(action)
    env.render()
    # reset the env at the end of an episode
    if done:
        obs = env.reset()

# Train
model.learn(total_timesteps=20000, log_interval=10)
model.save("sac_pendulum")

model = SAC.load("sac_pendulum")

# Render after training
obs = env.reset()
while True:
    action, _states = model.predict(obs)
    obs, reward, done, info = env.step(action)
    env.render()
    # reset the env at the end of an episode
    if done:
        obs = env.reset()

[sprakashdash]

Thanks a lot, it worked!