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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def ppo_original_params():
 """Parameters based on the original PPO paper."""

  hparams = ppo_atari_base()
  hparams.learning_rate_constant = 2.5e-4
  hparams.gae_gamma = 0.99
  hparams.gae_lambda = 0.95
  hparams.clipping_coef = 0.1
  hparams.value_loss_coef = 1
  hparams.entropy_loss_coef = 0.01
  hparams.eval_every_epochs = 200
  hparams.dropout_ppo = 0.1
  # The parameters below are modified to accommodate short epoch_length (which
  # is needed for model based rollouts).
  hparams.epoch_length = 50
  hparams.optimization_batch_size = 20
  return hparams