def make_atari_env(name, seed):
from gym.envs.atari.atari_env import AtariEnv
env = AtariEnv(game=name, frameskip=4, obs_type='image')
env = monitor(env, name)
env = wrap_deepmind(env)
env.seed(seed)
return env
def make_atari_env(name, seed):
from gym.wrappers.monitor import Monitor
from gym.envs.atari.atari_env import AtariEnv
env = AtariEnv(game=name, frameskip=4, obs_type='image')
env = Monitor(env, 'videos/', force=True, video_callable=lambda e: False)
env = wrappers.wrap_deepmind(env)
env.seed(seed)
return env
def make_atari_env(name, history_len):
from gym.envs.atari.atari_env import AtariEnv
from gym.wrappers.monitor import Monitor
env = AtariEnv(game=name, frameskip=4, obs_type='image')
env = Monitor(env, 'videos/', force=True, video_callable=lambda e: False)
env = wrappers.wrap_deepmind(env)
env = wrappers.HistoryWrapper(env, history_len)
env.seed(utils.random_seed())
return env
def make(game, size=84, grayscale=True, history_len=4):
env = AtariEnv(game, frameskip=4, obs_type='image')
env = envs.make.monitor(env, game)
if 'FIRE' in env.unwrapped.get_action_meanings():
env = FireResetWrapper(env)
env = NoopResetWrapper(env)
env = EpisodicLifeWrapper(env)
env = ClippedRewardWrapper(env)
env = PreprocessedImageWrapper(env, size, grayscale)
if history_len > 1:
env = HistoryWrapper(env, history_len)
return env
import tensorflow as tf
import numpy as np
import gym
from gym.envs.atari.atari_env import AtariEnv
env_name = 'pong'
# env_name = 'HalfCheetah-v1'
# env_name = 'Swimmer-v1'
# env_name = 'Hopper-v1'
# env_name = 'Humanoid-v1'
# env_name = 'HumanoidStandup-v1'
# env_name = 'BipedalWalker-v2'
# env = gym.make(env_name)
env = AtariEnv(game='breakout', obs_type="ram", frameskip=10)
env.reset()
while (1):
env.render()
def create_env(cls, config):
return AtariEnv(
game=config.game,
obs_type='image',
frameskip=config.frameskip,
repeat_action_probability=config.repeat_action_probability)