diff --git a/baselines/common/tf_util.py b/baselines/common/tf_util.py
index 4599d22..b8b2a87 100644
--- a/baselines/common/tf_util.py
+++ b/baselines/common/tf_util.py
@@ -355,43 +355,6 @@ def dropout(x, pkeep, phase=None, mask=None):
         return switch(phase, mask * x, pkeep * x)
 
 
-def batchnorm(x, name, phase, updates, gamma=0.96):
-    k = x.get_shape()[1]
-    runningmean = tf.get_variable(name + "/mean",
-                                  shape=[1, k],
-                                  initializer=tf.constant_initializer(0.0),
-                                  trainable=False)
-    runningvar = tf.get_variable(name + "/var",
-                                 shape=[1, k],
-                                 initializer=tf.constant_initializer(1e-4),
-                                 trainable=False)
-    testy = (x - runningmean) / tf.sqrt(runningvar)
-
-    mean_ = mean(x, axis=0, keepdims=True)
-    var_ = mean(tf.square(x), axis=0, keepdims=True)
-    std = tf.sqrt(var_)
-    trainy = (x - mean_) / std
-
-    updates.extend([
-        tf.assign(runningmean, runningmean * gamma + mean_ * (1 - gamma)),
-        tf.assign(runningvar, runningvar * gamma + var_ * (1 - gamma))
-    ])
-
-    y = switch(phase, trainy, testy)
-
-    scaling = tf.get_variable(name + "/scaling",
-                              shape=[1, k],
-                              initializer=tf.constant_initializer(1.0),
-                              trainable=True)
-
-    translation = tf.get_variable(name + "/translation",
-                                  shape=[1, k],
-                                  initializer=tf.constant_initializer(0.0),
-                                  trainable=True)
-
-    return y * scaling + translation
-
-
 # ================================================================
 # Theano-like Function
 # ================================================================
diff --git a/baselines/deepq/experiments/atari/enjoy.py b/baselines/deepq/experiments/atari/enjoy.py
index 0589138..fe482ca 100644
--- a/baselines/deepq/experiments/atari/enjoy.py
+++ b/baselines/deepq/experiments/atari/enjoy.py
@@ -29,7 +29,7 @@ def parse_args():
 
 
 def make_env(game_name):
-    env = gym.make(game_name + "NoFrameskip-v3")
+    env = gym.make(game_name + "NoFrameskip-v4")
     env = SimpleMonitor(env)
     env = wrap_dqn(env)
     return env
diff --git a/baselines/deepq/experiments/atari/train.py b/baselines/deepq/experiments/atari/train.py
index 1f59090..59cb548 100644
--- a/baselines/deepq/experiments/atari/train.py
+++ b/baselines/deepq/experiments/atari/train.py
@@ -57,7 +57,7 @@ def parse_args():
 
 
 def make_env(game_name):
-    env = gym.make(game_name + "NoFrameskip-v3")
+    env = gym.make(game_name + "NoFrameskip-v4")
     monitored_env = SimpleMonitor(env)  # puts rewards and number of steps in info, before environment is wrapped
     env = wrap_dqn(monitored_env)  # applies a bunch of modification to simplify the observation space (downsample, make b/w)
     return env, monitored_env
diff --git a/baselines/deepq/experiments/atari/wang2015_eval.py b/baselines/deepq/experiments/atari/wang2015_eval.py
index 177dcdf..b1fdfe4 100644
--- a/baselines/deepq/experiments/atari/wang2015_eval.py
+++ b/baselines/deepq/experiments/atari/wang2015_eval.py
@@ -12,7 +12,7 @@ from baselines.deepq.experiments.atari.model import model, dueling_model
 
 
 def make_env(game_name):
-    env = gym.make(game_name + "NoFrameskip-v3")
+    env = gym.make(game_name + "NoFrameskip-v4")
     env_monitored = SimpleMonitor(env)
     env = wrap_dqn(env_monitored)
     return env_monitored, env
diff --git a/baselines/deepq/experiments/enjoy_pong.py b/baselines/deepq/experiments/enjoy_pong.py
index d27e0d0..d70d6e6 100644
--- a/baselines/deepq/experiments/enjoy_pong.py
+++ b/baselines/deepq/experiments/enjoy_pong.py
@@ -5,7 +5,7 @@ from baselines.common.atari_wrappers_deprecated import wrap_dqn, ScaledFloatFram
 
 
 def main():
-    env = gym.make("PongNoFrameskip-v3")
+    env = gym.make("PongNoFrameskip-v4")
     env = ScaledFloatFrame(wrap_dqn(env))
     act = deepq.load("pong_model.pkl")
 
diff --git a/baselines/deepq/experiments/train_pong.py b/baselines/deepq/experiments/train_pong.py
index 86dcc65..efa78c3 100644
--- a/baselines/deepq/experiments/train_pong.py
+++ b/baselines/deepq/experiments/train_pong.py
@@ -5,7 +5,7 @@ from baselines.common.atari_wrappers_deprecated import wrap_dqn, ScaledFloatFram
 
 
 def main():
-    env = gym.make("PongNoFrameskip-v3")
+    env = gym.make("PongNoFrameskip-v4")
     env = ScaledFloatFrame(wrap_dqn(env))
     model = deepq.models.cnn_to_mlp(
         convs=[(32, 8, 4), (64, 4, 2), (64, 3, 1)],
diff --git a/setup.py b/setup.py
index f67e0b1..ac1addd 100644
--- a/setup.py
+++ b/setup.py
@@ -1,14 +1,15 @@
 from setuptools import setup, find_packages
-import os
-
-
-repo_dir = os.path.dirname(os.path.abspath(__file__))
+import sys
 
+if sys.version_info.major != 3:
+    print("This Python is only compatible with Python 3, but you are running "
+          "Python {}. The installation will likely fail.".format(sys.version_info.major))
 
 setup(name='baselines',
       packages=[package for package in find_packages()
                 if package.startswith('baselines')],
       install_requires=[
+          'gym',
           'scipy',
           'tqdm',
           'joblib',
@@ -22,4 +23,4 @@ setup(name='baselines',
       author="OpenAI",
       url='https://github.com/openai/baselines',
       author_email="gym@openai.com",
-      version="0.1.0")
+      version="0.1.3")