async def initialize_first_step() -> Optional[Result]:
nonlocal gs
ai._initialize_variables()
game_data = await client.get_game_data()
game_info = await client.get_game_info()
ping_response = await client.ping()
# This game_data will become self.game_data in botAI
ai._prepare_start(
client, player_id, game_info, game_data, realtime=realtime, base_build=ping_response.ping.base_build
)
state = await client.observation()
# check game result every time we get the observation
if client._game_result:
await ai.on_end(client._game_result[player_id])
return client._game_result[player_id]
gs = GameState(state.observation)
proto_game_info = await client._execute(game_info=sc_pb.RequestGameInfo())
try:
ai._prepare_step(gs, proto_game_info)
await ai.on_before_start()
ai._prepare_first_step()
await ai.on_start()
# TODO Catching too general exception Exception (broad-except)
# pylint: disable=W0703
except Exception:
logger.exception("AI on_start threw an error")
logger.error("Resigning due to previous error")
await ai.on_end(Result.Defeat)
return Result.Defeat
def __init__(
self, raw_game_data: Any, raw_game_info: Any, raw_observation: Any
) -> None:
"""
Set up variables for use within Creeper.
Args:
raw_game_data (Any): self.game_data from main instance
raw_game_info (Any): self.game_info from main instance
raw_observation (Any): self.game_state from main instance
Returns:
None
"""
self.bot = BotAI()
game_data = GameData(raw_game_data.data)
game_info = GameInfo(raw_game_info.game_info)
game_state = GameState(raw_observation)
self.bot._initialize_variables()
self.bot._prepare_start(
client=None, player_id=1, game_info=game_info, game_data=game_data
)
self.bot._prepare_step(state=game_state, proto_game_info=raw_game_info)
self.pathing = PathManager(raw_game_data, raw_game_info, raw_observation)
self.pf = PathFind(self.pathing.map_grid)
def import_bot_instance(
raw_game_data: Response,
raw_game_info: Response,
raw_observation: ResponseObservation,
) -> BotAI:
"""
import_bot_instance DocString
"""
bot = BotAI()
game_data = GameData(raw_game_data.data)
game_info = GameInfo(raw_game_info.game_info)
game_state = GameState(raw_observation)
# noinspection PyProtectedMember
bot._initialize_variables()
# noinspection PyProtectedMember
bot._prepare_start(client=None,
player_id=1,
game_info=game_info,
game_data=game_data)
# noinspection PyProtectedMember
bot._prepare_first_step()
# noinspection PyProtectedMember
bot._prepare_step(state=game_state, proto_game_info=raw_game_info)
# noinspection PyProtectedMember
bot._find_expansion_locations()
return bot
def __init__(
self, raw_game_data: Any, raw_game_info: Any, raw_observation: Any
) -> None:
"""
Set up variables for use within PathMangager.
Args:
raw_game_data (Any): self.game_data from main instance
raw_game_info (Any): self.game_info from main instance
raw_observation (Any): self.game_state from main instance
Returns:
None
"""
self.bot = BotAI()
game_data = GameData(raw_game_data.data)
game_info = GameInfo(raw_game_info.game_info)
game_state = GameState(raw_observation)
self.bot._initialize_variables()
self.bot._prepare_start(
client=None, player_id=1, game_info=game_info, game_data=game_data
)
self.bot._prepare_step(state=game_state, proto_game_info=raw_game_info)
map_name = game_info.map_name
self.pathing_dict: Dict[int, PathDict] = {}
map_width = game_info.map_size.width
map_height = game_info.map_size.height
raw_grid = np.zeros((map_width, map_height))
for x in range(map_width):
for y in range(map_height):
pos = Point2((x, y))
raw_grid[x][y] = game_info.pathing_grid[pos]
self.map_grid = np.rot90(raw_grid.astype(int))
np.save(f"map_grids/{map_name}_grid", self.map_grid)
self.pf = PathFind(self.map_grid)
def _ai_preparation(self, bot_ai, player_id, client):
game_data = self._loop_run(client.get_game_data())
game_info = self._loop_run(client.get_game_info())
state = self._loop_run(client.observation())
game_state = GameState(state.observation, game_data)
bot_ai._prepare_start(client, player_id, game_info, game_data)
bot_ai.on_start()
bot_ai._prepare_step(game_state)
bot_ai._prepare_first_step()
return game_data, game_info, game_state
async def _advance_steps(self, steps: int):
"""Advances the game loop by amount of 'steps'. This function is meant to be used as a debugging and testing tool only.
If you are using this, please be aware of the consequences, e.g. 'self.units' will be filled with completely new data."""
await self._after_step()
# Advance simulation by exactly "steps" frames
await self.client.step(steps)
state = await self.client.observation()
gs = GameState(state.observation)
proto_game_info = await self.client._execute(
game_info=sc_pb.RequestGameInfo())
self._prepare_step(gs, proto_game_info)
await self.issue_events()
def get_map_specific_bot(map_path: Path) -> BotAI:
assert map_path in MAPS
with lzma.open(str(map_path.absolute()), "rb") as f:
raw_game_data, raw_game_info, raw_observation = pickle.load(f)
# Build fresh bot object, and load the pickle'd data into the bot object
bot = BotAI()
game_data = GameData(raw_game_data.data)
game_info = GameInfo(raw_game_info.game_info)
game_state = GameState(raw_observation)
bot._initialize_variables()
bot._prepare_start(client=None, player_id=1, game_info=game_info, game_data=game_data)
bot._prepare_step(state=game_state, proto_game_info=raw_game_info)
return bot
async def store_data_to_file(self, file_path: str):
# Grab all raw data from observation
raw_game_data = await self._client._execute(
data=sc_pb.RequestData(ability_id=True, unit_type_id=True, upgrade_id=True, buff_id=True, effect_id=True)
)
raw_game_info = await self._client._execute(game_info=sc_pb.RequestGameInfo())
raw_observation = self.state.response_observation
# To test if this data is convertable in the first place
game_data = GameData(raw_game_data.data)
game_info = GameInfo(raw_game_info.game_info)
game_state = GameState(raw_observation)
os.makedirs(os.path.dirname(file_path), exist_ok=True)
with lzma.open(file_path, "wb") as f:
pickle.dump([raw_game_data, raw_game_info, raw_observation], f)
def get_map_specific_bots() -> Iterable[BotAI]:
folder = os.path.dirname(__file__)
subfolder_name = "pickle_data"
pickle_folder_path = os.path.join(folder, subfolder_name)
files = os.listdir(pickle_folder_path)
for file in (f for f in files if f.endswith(".xz")):
with lzma.open(os.path.join(folder, subfolder_name, file), "rb") as f:
raw_game_data, raw_game_info, raw_observation = pickle.load(f)
# Build fresh bot object, and load the pickle'd data into the bot object
bot = BotAI()
game_data = GameData(raw_game_data.data)
game_info = GameInfo(raw_game_info.game_info)
game_state = GameState(raw_observation)
bot._initialize_variables()
bot._prepare_start(client=None, player_id=1, game_info=game_info, game_data=game_data)
bot._prepare_step(state=game_state, proto_game_info=raw_game_info)
yield bot
async def on_start_async(self):
raw_game_data = await self._client._execute(
data=sc_pb.RequestData(ability_id=True, unit_type_id=True, upgrade_id=True, buff_id=True, effect_id=True)
)
raw_game_info = await self._client._execute(game_info=sc_pb.RequestGameInfo())
raw_observation = self.state.response_observation
# To test if this data is convertable in the first place
game_data = GameData(raw_game_data.data)
game_info = GameInfo(raw_game_info.game_info)
game_state = GameState(raw_observation)
print(f"Saving file to {self.map_name}.xz")
file_path = self.get_pickle_file_path()
os.makedirs(os.path.dirname(file_path), exist_ok=True)
with lzma.open(file_path, "wb") as f:
pickle.dump([raw_game_data, raw_game_info, raw_observation], f)
await self._client.leave()
def _step(self, action_args):
# if self.env.allies_client._status
self.t += 1
allies_game_state = self.allies_game_state
# current game_state
self._loop_run(self.allies.ai.issue_events())
self._loop_run(self.allies.ai.on_step(action_args))
for _ in range(self.frame_skip_rate):
self._loop_run(self.allies_client.step())
allies_state = self._loop_run(self.allies_client.observation())
next_game_state = GameState(allies_state.observation,
self.allies_game_data)
self.allies_game_state = next_game_state
self.allies.ai._prepare_step(allies_game_state)
game_result = self.allies_client._game_result
done = True if game_result else False
return next_game_state, done
async def _play_game_ai(client,
player_id,
ai,
realtime,
step_time_limit,
game_time_limit,
log_queue=None):
if realtime:
assert step_time_limit is None
# step_time_limit works like this:
# * If None, then step time is not limited
# * If given integer or float, the bot will simpy resign if any step takes longer than that
# * Otherwise step_time_limit must be an object, with following settings:
#
# Key | Value | Description
# ------------|------------|-------------
# penalty | None | No penalty, the bot can continue on next step
# penalty | N: int | Cooldown penalty, BotAI.on_step will not be called for N steps
# penalty | "resign" | Bot resigns when going over time limit
# time_limit | int/float | Time limit for a single step
# window_size | N: int | The time limit will be used for last N steps, instad of 1
#
# Cooldown is a harsh penalty. The both loses the ability to act, but even worse,
# the observation data from skipped steps is also lost. It's like falling asleep in
# a middle of the game.
time_penalty_cooldown = 0
if step_time_limit is None:
time_limit = None
time_window = None
time_penalty = None
elif isinstance(step_time_limit, (int, float)):
time_limit = float(step_time_limit)
time_window = SlidingTimeWindow(1)
time_penalty = "resign"
else:
assert isinstance(step_time_limit, dict)
time_penalty = step_time_limit.get("penalty", None)
time_window = SlidingTimeWindow(
int(step_time_limit.get("window_size", 1)))
time_limit = float(step_time_limit.get("time_limit", None))
game_data = await client.get_game_data()
game_info = await client.get_game_info()
ai._prepare_start(client, player_id, game_info, game_data)
try:
ai.on_start()
except Exception as e:
logger.exception(f"AI on_start threw an error")
logger.error(f"resigning due to previous error")
ai.on_end(Result.Defeat)
return Result.Defeat
iteration = 0
while True:
state = await client.observation()
logger.debug(f"Score: {state.observation.observation.score.score}")
if client._game_result:
ai.on_end(client._game_result[player_id])
return client._game_result[player_id]
gs = GameState(state.observation, game_data)
if game_time_limit and (gs.game_loop * 0.725 *
(1 / 16)) > game_time_limit:
ai.on_end(Result.Tie)
return Result.Tie
ai._prepare_step(gs)
if iteration == 0:
ai._prepare_first_step()
logger.debug(
f"Running AI step, it={iteration} {gs.game_loop * 0.725 * (1 / 16):.2f}s"
)
try:
await ai.issue_events()
if realtime:
await ai.on_step(iteration)
else:
if time_penalty_cooldown > 0:
time_penalty_cooldown -= 1
logger.warning(
f"Running AI step: penalty cooldown: {time_penalty_cooldown}"
)
iteration -= 1 # Do not increment the iteration on this round
elif time_limit is None:
await ai.on_step(iteration)
else:
out_of_budget = False
budget = time_limit - time_window.available
# Tell the bot how much time it has left attribute
ai.time_budget_available = budget
if budget < 0:
logger.warning(
f"Running AI step: out of budget before step")
step_time = 0.0
out_of_budget = True
else:
step_start = time.monotonic()
try:
async with async_timeout.timeout(budget):
await ai.on_step(iteration)
except asyncio.TimeoutError:
step_time = time.monotonic() - step_start
logger.warning(
f"Running AI step: out of budget; " +
f"budget={budget:.2f}, steptime={step_time:.2f}, "
+ f"window={time_window.available_fmt}")
out_of_budget = True
step_time = time.monotonic() - step_start
time_window.push(step_time)
if out_of_budget and time_penalty != None:
if time_penalty == "resign":
raise RuntimeError("Out of time")
else:
time_penalty_cooldown = int(time_penalty)
time_window.clear()
except Exception as e:
if isinstance(e, ProtocolError) and e.is_game_over_error:
if realtime:
return None
result = client._game_result[player_id]
if result is None:
log.error("Game over, but no results gathered")
raise
return result
# NOTE: this message is caught by pytest suite
logger.exception(f"AI step threw an error") # DO NOT EDIT!
logger.error(f"resigning due to previous error")
# hspark8312: begin
if log_queue is not None:
from time import gmtime, strftime
import traceback
tb = traceback.format_exc()
log_queue.put(f"AI step threw an error")
log_queue.put(f'{e} -> {tb}')
# hspark8312: end
ai.on_end(Result.Defeat)
return Result.Defeat
logger.debug(f"Running AI step: done")
if not realtime:
if not client.in_game: # Client left (resigned) the game
ai.on_end(client._game_result[player_id])
return client._game_result[player_id]
await client.step()
iteration += 1
async def _play_replay(client, ai, realtime=False, player_id=0):
ai._initialize_variables()
game_data = await client.get_game_data()
game_info = await client.get_game_info()
ping_response = await client.ping()
client.game_step = 1
# This game_data will become self._game_data in botAI
ai._prepare_start(
client, player_id, game_info, game_data, realtime=realtime, base_build=ping_response.ping.base_build
)
state = await client.observation()
# Check game result every time we get the observation
if client._game_result:
await ai.on_end(client._game_result[player_id])
return client._game_result[player_id]
gs = GameState(state.observation)
proto_game_info = await client._execute(game_info=sc_pb.RequestGameInfo())
ai._prepare_step(gs, proto_game_info)
ai._prepare_first_step()
try:
await ai.on_start()
# TODO Catching too general exception Exception (broad-except)
# pylint: disable=W0703
except Exception:
logger.exception("AI on_start threw an error")
logger.error("resigning due to previous error")
await ai.on_end(Result.Defeat)
return Result.Defeat
iteration = 0
while True:
if iteration != 0:
if realtime:
# TODO: check what happens if a bot takes too long to respond, so that the requested
# game_loop might already be in the past
state = await client.observation(gs.game_loop + client.game_step)
else:
state = await client.observation()
# check game result every time we get the observation
if client._game_result:
try:
await ai.on_end(client._game_result[player_id])
except TypeError:
return client._game_result[player_id]
return client._game_result[player_id]
gs = GameState(state.observation)
logger.debug(f"Score: {gs.score.score}")
proto_game_info = await client._execute(game_info=sc_pb.RequestGameInfo())
ai._prepare_step(gs, proto_game_info)
logger.debug(f"Running AI step, it={iteration} {gs.game_loop * 0.725 * (1 / 16):.2f}s")
try:
# Issue event like unit created or unit destroyed
await ai.issue_events()
await ai.on_step(iteration)
await ai._after_step()
# pylint: disable=W0703
# TODO Catching too general exception Exception (broad-except)
except Exception as e:
if isinstance(e, ProtocolError) and e.is_game_over_error:
if realtime:
return None
await ai.on_end(Result.Victory)
return None
# NOTE: this message is caught by pytest suite
logger.exception("AI step threw an error") # DO NOT EDIT!
logger.error(f"Error: {e}")
logger.error("Resigning due to previous error")
try:
await ai.on_end(Result.Defeat)
except TypeError:
return Result.Defeat
return Result.Defeat
logger.debug("Running AI step: done")
if not realtime:
if not client.in_game: # Client left (resigned) the game
await ai.on_end(Result.Victory)
return Result.Victory
await client.step() # unindent one line to work in realtime
iteration += 1
async def _play_game_ai(
client: Client, player_id: int, ai: BotAI, realtime: bool, game_time_limit: Optional[int]
) -> Result:
gs: GameState = None
async def initialize_first_step() -> Optional[Result]:
nonlocal gs
ai._initialize_variables()
game_data = await client.get_game_data()
game_info = await client.get_game_info()
ping_response = await client.ping()
# This game_data will become self.game_data in botAI
ai._prepare_start(
client, player_id, game_info, game_data, realtime=realtime, base_build=ping_response.ping.base_build
)
state = await client.observation()
# check game result every time we get the observation
if client._game_result:
await ai.on_end(client._game_result[player_id])
return client._game_result[player_id]
gs = GameState(state.observation)
proto_game_info = await client._execute(game_info=sc_pb.RequestGameInfo())
try:
ai._prepare_step(gs, proto_game_info)
await ai.on_before_start()
ai._prepare_first_step()
await ai.on_start()
# TODO Catching too general exception Exception (broad-except)
# pylint: disable=W0703
except Exception:
logger.exception("AI on_start threw an error")
logger.error("Resigning due to previous error")
await ai.on_end(Result.Defeat)
return Result.Defeat
result = await initialize_first_step()
if result is not None:
return result
async def run_bot_iteration(iteration: int):
nonlocal gs
logger.debug(f"Running AI step, it={iteration} {gs.game_loop / 22.4:.2f}s")
# Issue event like unit created or unit destroyed
await ai.issue_events()
await ai.on_step(iteration)
await ai._after_step()
logger.debug("Running AI step: done")
# Only used in realtime=True
previous_state_observation = None
for iteration in range(10**10):
if realtime and gs:
# On realtime=True, might get an error here: sc2.protocol.ProtocolError: ['Not in a game']
with suppress(ProtocolError):
requested_step = gs.game_loop + client.game_step
state = await client.observation(requested_step)
# If the bot took too long in the previous observation, request another observation one frame after
if state.observation.observation.game_loop > requested_step:
logger.debug("Skipped a step in realtime=True")
previous_state_observation = state.observation
state = await client.observation(state.observation.observation.game_loop + 1)
else:
state = await client.observation()
# check game result every time we get the observation
if client._game_result:
await ai.on_end(client._game_result[player_id])
return client._game_result[player_id]
gs = GameState(state.observation, previous_state_observation)
previous_state_observation = None
logger.debug(f"Score: {gs.score.score}")
if game_time_limit and gs.game_loop / 22.4 > game_time_limit:
await ai.on_end(Result.Tie)
return Result.Tie
proto_game_info = await client._execute(game_info=sc_pb.RequestGameInfo())
ai._prepare_step(gs, proto_game_info)
await run_bot_iteration(iteration) # Main bot loop
if not realtime:
if not client.in_game: # Client left (resigned) the game
await ai.on_end(client._game_result[player_id])
return client._game_result[player_id]
# TODO: In bot vs bot, if the other bot ends the game, this bot gets stuck in requesting an observation when using main.py:run_multiple_games
await client.step()
return Result.Undecided