text: import gym
  import matplotlib.pyplot as plt
  import os
  from stable_baselines.common.policies import MlpPolicy
  from stable_baselines.common.vec_env import DummyVecEnv
  from stable_baselines import PPO2
  from test_params import *
  
  
  
  cwd = os.getcwd()
  '''
  model name ,target,no of epidodes,
  no of steps are all defined in
  test_params.py file
  '''
  
  env = gym.make('gym_learn_wbc:learn_wbc-v0',
  	           learning_steps=no_of_sim_steps,
  	           target_velocity=target_velocity
  	           )
  '''
  model = PPO2(MlpPolicy,
  			 env,
  			 verbose=1,
  			 tensorboard_log=cwd+'/tf_logs/')
  
  '''
  '''
  model = PPO2(MlpPolicy,
  			 env,
  			 gamma=0.95,
  			 learning_rate = 0.000001,
  			 n_steps=no_of_episodes,
  			 noptepochs=10,
  			 nminibatches=5,
  			 verbose=1,
  			 tensorboard_log=cwd+'/tf_logs/')
  '''
  
  model = PPO2(MlpPolicy,
  			 env,
  			 verbose = 1,
  			 n_steps=12,
  			 tensorboard_log=cwd+'/tf_logs/')
  
  env.reset()
  
  model.learn(total_timesteps=10000,
  				 log_interval=1,
  				 tb_log_name=agent_name)
  model.save(save_path=cwd+'/models/'+agent_name+'.zip')
  
  
  