--- a
+++ b/baselines/ppo2/run_atari.py
@@ -0,0 +1,40 @@
+#!/usr/bin/env python3
+import sys
+from baselines import logger
+from baselines.common.cmd_util import make_atari_env, atari_arg_parser
+from baselines.common.vec_env.vec_frame_stack import VecFrameStack
+from baselines.ppo2 import ppo2
+from baselines.ppo2.policies import CnnPolicy, LstmPolicy, LnLstmPolicy, MlpPolicy
+import multiprocessing
+import tensorflow as tf
+
+
+def train(env_id, num_timesteps, seed, policy):
+
+    ncpu = multiprocessing.cpu_count()
+    if sys.platform == 'darwin': ncpu //= 2
+    config = tf.ConfigProto(allow_soft_placement=True,
+                            intra_op_parallelism_threads=ncpu,
+                            inter_op_parallelism_threads=ncpu)
+    config.gpu_options.allow_growth = True #pylint: disable=E1101
+    tf.Session(config=config).__enter__()
+
+    env = VecFrameStack(make_atari_env(env_id, 8, seed), 4)
+    policy = {'cnn' : CnnPolicy, 'lstm' : LstmPolicy, 'lnlstm' : LnLstmPolicy, 'mlp': MlpPolicy}[policy]
+    ppo2.learn(policy=policy, env=env, nsteps=128, nminibatches=4,
+        lam=0.95, gamma=0.99, noptepochs=4, log_interval=1,
+        ent_coef=.01,
+        lr=lambda f : f * 2.5e-4,
+        cliprange=lambda f : f * 0.1,
+        total_timesteps=int(num_timesteps * 1.1))
+
+def main():
+    parser = atari_arg_parser()
+    parser.add_argument('--policy', help='Policy architecture', choices=['cnn', 'lstm', 'lnlstm', 'mlp'], default='cnn')
+    args = parser.parse_args()
+    logger.configure()
+    train(args.env, num_timesteps=args.num_timesteps, seed=args.seed,
+        policy=args.policy)
+
+if __name__ == '__main__':
+    main()