def main(env_id, policy_file, record, stochastic, extra_kwargs):
import gym
from gym import wrappers
import tensorflow as tf
from es_distributed.policies import ESAtariPolicy
from es_distributed.atari_wrappers import ScaledFloatFrame, wrap_deepmind
from es_distributed.es import get_ref_batch
import numpy as np
is_atari_policy = "NoFrameskip" in env_id
env = gym.make(env_id)
if is_atari_policy:
env = wrap_deepmind(env)
if record:
import uuid
env = wrappers.Monitor(env, '/tmp/' + str(uuid.uuid4()), force=True)
if extra_kwargs:
import json
extra_kwargs = json.loads(extra_kwargs)
with tf.Session():
pi = ESAtariPolicy.Load(policy_file, extra_kwargs=extra_kwargs)
pi.set_ref_batch(get_ref_batch(env, batch_size=128))
while True:
if is_atari_policy:
rews, t, novelty_vector = pi.rollout(env, render=True, random_stream=np.random if stochastic else None)
print('return={:.4f} len={}'.format(rews, t))
if record:
env.close()
return
def build_env(env_id):
gym.undo_logger_setup()
env = gym.make(env_id)
if env_id.endswith('NoFrameskip-v4'):
env = wrap_deepmind(env)
return env
def main(env_ids, policy_directory, record, stochastic, extra_kwargs):
import gym
from gym import wrappers
import tensorflow as tf
from es_distributed.policies import MujocoPolicy, ESAtariPolicy, GAAtariPolicy
from es_distributed.atari_wrappers import ScaledFloatFrame, wrap_deepmind
from es_distributed.es import get_ref_batch
import es_distributed.ns as ns
import numpy as np
import os
env_ids = env_ids.split(' ')
is_atari_policy = "NoFrameskip" in env_ids[0]
files = 0
for policy_name in os.listdir(policy_directory):
files += 1
policy_file = "%s/%s" % (policy_directory, policy_name)
pid = os.fork()
if (pid == 0):
env = []
for i in range(0, len(env_ids)):
env.append(gym.make(env_ids[i]))
if env_ids[i].endswith('NoFrameskip-v4'):
env[i] = wrap_deepmind(env[i])
if extra_kwargs:
import json
extra_kwargs = json.loads(extra_kwargs)
with tf.Session():
if is_atari_policy:
pi = GAAtariPolicy.Load(policy_file, extra_kwargs=extra_kwargs)
if pi.needs_ref_batch:
pi.set_ref_batch(get_ref_batch(env[0], batch_size=128))
else:
pi = MujocoPolicy.Load(policy_file, extra_kwargs=extra_kwargs)
while True:
if is_atari_policy:
rews, t, novelty_vector = pi.rollout(env, render=True, random_stream=np.random if stochastic else None)
for i in range(0, files):
os.wait()
def make_env(self):
from es_distributed.atari_wrappers import wrap_deepmind
env_id = "FrostbiteNoFrameskip-v4"
env = gym.make(env_id)
env = wrap_deepmind(env)
return env