Open AI Gym with Neat Algorithm not working on Jupyter

Question

import multiprocessing
import os
import pickle
import numpy as np
import neat
import gym

runs_per_net = 2

# Use the NN network phenotype and the discrete actuator force function.
def eval_genome(genome, config):
    net = neat.nn.FeedForwardNetwork.create(genome, config)

    fitnesses = []

    for runs in range(runs_per_net):
        env = gym.make("CartPole-v1")
        observation = env.reset()
        # Run the given simulation for up to num_steps time steps.
        fitness = 0.0
        done = False
        while not done:
            
            action = np.argmax(net.activate(observation))
            observation, reward, done, info = env.step(action)    
            fitness += reward

        fitnesses.append(fitness)

    # The genome's fitness is its worst performance across all runs.
    return np.mean(fitnesses)

def eval_genomes(genomes, config):
    for genome_id, genome in genomes:
        genome.fitness = eval_genome(genome, config)


def run():
    # Load the config file, which is assumed to live in
    # the same directory as this script.
    config = neat.Config(neat.DefaultGenome, neat.DefaultReproduction,
                         neat.DefaultSpeciesSet, neat.DefaultStagnation,
                         "config")

    pop = neat.Population(config)
    stats = neat.StatisticsReporter()
    pop.add_reporter(stats)
    pop.add_reporter(neat.StdOutReporter(True))

    pe = neat.ParallelEvaluator(multiprocessing.cpu_count(), eval_genome)
    winner = pop.run(pe.evaluate)

    # Save the winner.
    with open('winner', 'wb') as f:
        pickle.dump(winner, f)

    print(winner)

if __name__ == '__main__':
    run()

Trying to run CartPole v1 with Neat Algorithm on jupyter notebook but the output is stuck on

**** Running generation 0 **** 

With increase in amount of GPU usage instead of the CPU.

But when trying to run it on CMD everything is working fine(GPU usage being normal). Is there any way I can do it on Jupyter Notebook.