text: import gym
  import gym_panda
  from gym_panda.wrapper_env.VAE import VAE
  import torch
  import tensorflow as tf
  import numpy as np
  import copy
  import pickle
  import gym_panda
  from gym_panda.wrapper_env.wrapper import *
  import pdb
  
  seed = 6
  env = gym.make("disabledpanda-v0")
  env.seed(seed)
  torch.manual_seed(seed)
  np.random.seed(seed)
  pairs = []
  for i in range(1000):
      done = False
      state = env.reset()['ee_position']
      #print(state)
      while not done:
          prev_state = state
          action = env.action_space.sample()
          state, rewards, done, info = env.step(action)
          state = state['ee_position']
          #print(prevstate,state,action)
          tosave = np.concatenate((prev_state,state,action),axis=0)
          pairs.append(tosave)
          #print(tosave)
          #pdb.set_trace()
  #pickle.dump(pairs, open('..\\logs\\data\\pairs100.pkl'), 'wb')
  pickle.dump(pairs, open('..\\logs\\data\\baseline\\pairs1000_6.pkl', 'wb'))
  