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# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
"""
Atari Environment Server Implementation.
This module wraps ALE's ALEInterface and exposes it
via the OpenEnv Environment interface.
"""
import uuid
from typing import Any, Dict, Literal, Optional
from core.env_server import Action, Environment, Observation
from ..models import AtariAction, AtariObservation, AtariState
# Import ALE
try:
from ale_py import ALEInterface, roms
import numpy as np
except ImportError as e:
raise ImportError(
"ALE (Arcade Learning Environment) is not installed. "
"Please install it with: pip install ale-py"
) from e
class AtariEnvironment(Environment):
"""
Atari Environment wrapper for OpenEnv.
This environment wraps Atari 2600 games via the Arcade Learning Environment (ALE)
and provides a clean interface for RL training.
Supported games include: pong, breakout, space_invaders, and 100+ others.
Args:
game_name: Name of the Atari game (e.g., "pong", "breakout").
obs_type: Observation type - "rgb", "grayscale", or "ram".
full_action_space: Use full action space (18 actions) vs minimal.
mode: Game mode (if applicable).
difficulty: Game difficulty (if applicable).
repeat_action_probability: Sticky action probability (default 0.0).
frameskip: Number of frames to skip per action (default 4).
Example:
>>> env = AtariEnvironment("pong")
>>> obs = env.reset()
>>> print(obs.screen_shape) # [210, 160, 3]
>>> obs = env.step(AtariAction(action_id=2)) # UP
>>> print(obs.reward, obs.done)
"""
def __init__(
self,
game_name: str = "pong",
obs_type: Literal["rgb", "grayscale", "ram"] = "rgb",
full_action_space: bool = False,
mode: Optional[int] = None,
difficulty: Optional[int] = None,
repeat_action_probability: float = 0.0,
frameskip: int = 4,
):
"""Initialize Atari environment."""
super().__init__()
self.game_name = game_name
self.obs_type = obs_type
self.full_action_space = full_action_space
self.mode = mode
self.difficulty = difficulty
self.repeat_action_probability = repeat_action_probability
self.frameskip = frameskip
# Create ALE interface
self.ale = ALEInterface()
# Configure ALE
from ale_py import LoggerMode
self.ale.setLoggerMode(LoggerMode.Error) # Error mode only
self.ale.setFloat("repeat_action_probability", repeat_action_probability)
# Load ROM
try:
rom_path = roms.get_rom_path(game_name)
self.ale.loadROM(rom_path)
except Exception as e:
raise ValueError(
f"Failed to load Atari game '{game_name}': {e}\n"
f"Available games can be found via: ale_py.roms.list_roms()"
) from e
# Set mode and difficulty if specified
if mode is not None:
self.ale.setMode(mode)
if difficulty is not None:
self.ale.setDifficulty(difficulty)
# Get action set
if full_action_space:
self._action_set = self.ale.getLegalActionSet()
else:
self._action_set = self.ale.getMinimalActionSet()
# Get screen dimensions for observation space
self.screen_height, self.screen_width = self.ale.getScreenDims()
if obs_type == "rgb":
self.screen_shape = [self.screen_height, self.screen_width, 3]
elif obs_type == "grayscale":
self.screen_shape = [self.screen_height, self.screen_width]
elif obs_type == "ram":
self.screen_shape = [self.ale.getRAMSize()]
else:
raise ValueError(f"Invalid obs_type: {obs_type}")
# Initialize state
self._state = AtariState(
game_name=game_name,
obs_type=obs_type,
full_action_space=full_action_space,
mode=mode,
difficulty=difficulty,
repeat_action_probability=repeat_action_probability,
frameskip=frameskip,
)
def reset(self) -> Observation:
"""
Reset the environment and return initial observation.
Returns:
Initial observation for the agent.
"""
# Reset ALE
self.ale.reset_game()
# Reset state tracking
self._state.episode_id = str(uuid.uuid4())
self._state.step_count = 0
# Get initial observation
return self._make_observation()
def step(self, action: Action) -> Observation:
"""
Execute agent's action and return resulting observation.
Args:
action: AtariAction containing the action_id to execute.
Returns:
Observation after action execution.
Raises:
ValueError: If action is not an AtariAction.
"""
if not isinstance(action, AtariAction):
raise ValueError(f"Expected AtariAction, got {type(action)}")
# Validate action_id
if action.action_id < 0 or action.action_id >= len(self._action_set):
raise ValueError(
f"Invalid action_id: {action.action_id}. "
f"Valid range: [0, {len(self._action_set) - 1}]"
)
# Get actual ALE action
ale_action = self._action_set[action.action_id]
# Execute action with frameskip
total_reward = 0.0
for _ in range(self.frameskip):
total_reward += self.ale.act(ale_action)
if self.ale.game_over():
break
self._state.step_count += 1
# Get observation
obs = self._make_observation()
obs.reward = total_reward
return obs
@property
def state(self) -> AtariState:
"""Get current environment state."""
return self._state
def _make_observation(self) -> AtariObservation:
"""
Create an AtariObservation from current ALE state.
Returns:
AtariObservation for the agent.
"""
# Get screen observation
if self.obs_type == "rgb":
screen = self.ale.getScreenRGB()
elif self.obs_type == "grayscale":
screen = self.ale.getScreenGrayscale()
elif self.obs_type == "ram":
screen = self.ale.getRAM()
else:
raise ValueError(f"Invalid obs_type: {self.obs_type}")
# Flatten screen for JSON serialization
# Handle both numpy arrays and lists
if hasattr(screen, "flatten"):
screen_flat = screen.flatten().tolist()
elif hasattr(screen, "tolist"):
screen_flat = screen.tolist()
else:
screen_flat = list(screen)
# Get game info
lives = self.ale.lives()
episode_frame_number = self.ale.getEpisodeFrameNumber()
frame_number = self.ale.getFrameNumber()
done = self.ale.game_over()
# Create legal actions list (indices into action_set)
legal_actions = list(range(len(self._action_set)))
# Create observation
obs = AtariObservation(
screen=screen_flat,
screen_shape=self.screen_shape,
legal_actions=legal_actions,
lives=lives,
episode_frame_number=episode_frame_number,
frame_number=frame_number,
done=done,
reward=0.0, # Will be filled in by step()
metadata={
"game_name": self.game_name,
"action_meanings": [str(a) for a in self._action_set],
},
)
return obs
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