diff --git a/overcooked_simulator/game_content/environment_config_rl.yaml b/overcooked_simulator/game_content/environment_config_rl.yaml
index 45c61914ad254158c06cd37413712f294faa9c5e..0b3b4570f92b3ab8554a6183ae56d87b11889f51 100644
--- a/overcooked_simulator/game_content/environment_config_rl.yaml
+++ b/overcooked_simulator/game_content/environment_config_rl.yaml
@@ -1,12 +1,12 @@
plates:
- clean_plates: 2
+ clean_plates: 1
dirty_plates: 0
- plate_delay: [ 5, 10 ]
+ plate_delay: [ 2, 4 ]
return_dirty: False
# range of seconds until the dirty plate arrives.
game:
- time_limit_seconds: 400
+ time_limit_seconds: 300
meals:
all: true
@@ -93,7 +93,7 @@ extra_setup_functions:
hooks: [ completed_order ]
callback_class: !!python/name:overcooked_simulator.scores.ScoreViaHooks ''
callback_class_kwargs:
- static_score: 100
+ static_score: 1
serve_not_ordered_meals:
func: !!python/name:overcooked_simulator.hooks.hooks_via_callback_class ''
@@ -101,35 +101,35 @@ extra_setup_functions:
hooks: [ serve_not_ordered_meal ]
callback_class: !!python/name:overcooked_simulator.scores.ScoreViaHooks ''
callback_class_kwargs:
- static_score: 100
+ static_score: 1
trashcan_usages:
func: !!python/name:overcooked_simulator.hooks.hooks_via_callback_class ''
kwargs:
hooks: [ trashcan_usage ]
callback_class: !!python/name:overcooked_simulator.scores.ScoreViaHooks ''
callback_class_kwargs:
- static_score: -10
+ static_score: -0.15
item_cut:
func: !!python/name:overcooked_simulator.hooks.hooks_via_callback_class ''
kwargs:
hooks: [ cutting_board_100 ]
callback_class: !!python/name:overcooked_simulator.scores.ScoreViaHooks ''
callback_class_kwargs:
- static_score: 10
+ static_score: 0.10
stepped:
func: !!python/name:overcooked_simulator.hooks.hooks_via_callback_class ''
kwargs:
hooks: [ post_step ]
callback_class: !!python/name:overcooked_simulator.scores.ScoreViaHooks ''
callback_class_kwargs:
- static_score: -1
+ static_score: -0.01
combine:
func: !!python/name:overcooked_simulator.hooks.hooks_via_callback_class ''
kwargs:
hooks: [ drop_off_on_cooking_equipment ]
callback_class: !!python/name:overcooked_simulator.scores.ScoreViaHooks ''
callback_class_kwargs:
- static_score: 1
+ static_score: 0.10
# json_states:
# func: !!python/name:overcooked_simulator.recording.class_recording_with_hooks ''
# kwargs:
diff --git a/overcooked_simulator/game_content/layouts/rl.layout b/overcooked_simulator/game_content/layouts/rl.layout
index fd3cd8db1a4d1bcd62e08bcca3bbb2e79d04c67a..5115af280b02654e287bb9365ec0097a676c1986 100644
--- a/overcooked_simulator/game_content/layouts/rl.layout
+++ b/overcooked_simulator/game_content/layouts/rl.layout
@@ -1,5 +1,4 @@
-#X###
-T___#
-#___#
-U___P
-#C#W#
+#X##
+T__W
+U__P
+#C##
diff --git a/overcooked_simulator/gui_2d_vis/overcooked_gui.py b/overcooked_simulator/gui_2d_vis/overcooked_gui.py
index a4d28c5cb9fe468683db502766b2f2f0c37a7371..8bf25de71e3bcc6b0cb66e125bf5bb588e6cc669 100644
--- a/overcooked_simulator/gui_2d_vis/overcooked_gui.py
+++ b/overcooked_simulator/gui_2d_vis/overcooked_gui.py
@@ -12,6 +12,7 @@ import pygame
import pygame_gui
import requests
import yaml
+from pygame._sdl2 import get_drivers
from websockets.sync.client import connect
from overcooked_simulator import ROOT_DIR
@@ -30,6 +31,9 @@ from overcooked_simulator.utils import (
add_list_of_manager_ids_arguments,
)
+for driver in get_drivers():
+ print(driver)
+
class MenuStates(Enum):
Start = "Start"
@@ -970,8 +974,8 @@ class PyGameGUI:
clock = pygame.time.Clock()
- self.reset_window_size()
self.init_ui_elements()
+ self.reset_window_size()
self.manage_button_visibility()
self.update_selection_elements()
diff --git a/overcooked_simulator/gym_env.py b/overcooked_simulator/gym_env.py
index 41c3474dc6a448adf01828cebac21129f1434129..47dbc108da7edc607936d3cfb175bf97e5a9cb48 100644
--- a/overcooked_simulator/gym_env.py
+++ b/overcooked_simulator/gym_env.py
@@ -1,7 +1,6 @@
import json
import random
import time
-from copy import deepcopy
from datetime import timedelta
from enum import Enum
from pathlib import Path
@@ -17,6 +16,7 @@ from stable_baselines3 import PPO
from stable_baselines3.common.callbacks import CallbackList, CheckpointCallback
from stable_baselines3.common.env_checker import check_env
from stable_baselines3.common.env_util import make_vec_env
+from stable_baselines3.common.vec_env import VecVideoRecorder
from wandb.integration.sb3 import WandbCallback
from overcooked_simulator import ROOT_DIR
@@ -134,12 +134,18 @@ with open(environment_config_path, "r") as file:
with open(ROOT_DIR / "gui_2d_vis" / "visualization_rl.yaml", "r") as file:
visualization_config = yaml.safe_load(file)
-vanilla_env: Environment = Environment(
- env_config=environment_config,
- layout_config=layout,
- item_info=item_info,
- as_files=False,
-)
+
+def shuffle_counters(env):
+ sample_counter = []
+ sample_counter = []
+ for counter in env.counters:
+ if counter.__class__ != Counter:
+ sample_counter.append(counter)
+ new_counter_pos = [c.pos for c in sample_counter]
+ random.shuffle(new_counter_pos)
+ for counter, new_pos in zip(sample_counter, new_counter_pos):
+ counter.pos = new_pos
+ env.vector_state_generation = env.setup_vectorization()
class EnvGymWrapper(Env):
@@ -147,29 +153,33 @@ class EnvGymWrapper(Env):
observation, reward, terminated, truncated, info = env.step(action)
"""
- metadata = {"render_modes": ["human"], "render_fps": 30}
+ metadata = {"render_modes": ["human", "rgb_array"], "render_fps": 30}
def __init__(self):
super().__init__()
self.gridsize = 20
- self.env = deepcopy(vanilla_env)
- # sample_counter = []
- # for counter in self.env.counters:
- # if counter.__class__ != Counter:
- # sample_counter.append(counter)
- # new_counter_pos = [c.pos for c in sample_counter]
- # random.shuffle(new_counter_pos)
- # for counter, new_pos in zip(sample_counter, new_counter_pos):
- # counter.pos = new_pos
- # self.env.vector_state_generation = self.env.setup_vectorization()
+ self.randomize_counter_placement = False
+ self.use_rgb_obs = False
+
+ self.env: Environment = Environment(
+ env_config=environment_config,
+ layout_config=layout,
+ item_info=item_info,
+ as_files=False,
+ )
+
+ if self.randomize_counter_placement:
+ shuffle_counters(self.env)
self.visualizer: Visualizer = Visualizer(config=visualization_config)
self.player_name = str(0)
self.env.add_player(self.player_name)
self.player_id = list(self.env.players.keys())[0]
+ self.env.setup_vectorization()
+
self.visualizer.create_player_colors(1)
# self.action_space = {idx: value for idx, value in enumerate(SimpleActionSpace)}
@@ -184,9 +194,8 @@ class EnvGymWrapper(Env):
# Example for using image as input (channel-first; channel-last also works):
dummy_obs = self.get_observation()
- # dummy_obs = self.get_vector_state()
self.observation_space = spaces.Box(
- low=0, high=1, shape=dummy_obs.shape, dtype=float
+ low=-1, high=8, shape=dummy_obs.shape, dtype=int
)
self.last_obs = dummy_obs
@@ -219,27 +228,22 @@ class EnvGymWrapper(Env):
return observation, reward, terminated, truncated, info
def reset(self, seed=None, options=None):
- # self.env: Environment = Environment(
- # env_config=environment_config,
- # layout_config=layout,
- # item_info=item_info,
- # as_files=False
- # )
+ self.env: Environment = Environment(
+ env_config=environment_config,
+ layout_config=layout,
+ item_info=item_info,
+ as_files=False,
+ )
- self.env = deepcopy(vanilla_env)
- # sample_counter = []
- # for counter in self.env.counters:
- # if counter.__class__ != Counter:
- # sample_counter.append(counter)
- # new_counter_pos = [c.pos for c in sample_counter]
- # random.shuffle(new_counter_pos)
- # for counter, new_pos in zip(sample_counter, new_counter_pos):
- # counter.pos = new_pos
- # self.env.vector_state_generation = self.env.setup_vectorization()
+ if self.randomize_counter_placement:
+ shuffle_counters(self.env)
self.player_name = str(0)
self.env.add_player(self.player_name)
self.player_id = list(self.env.players.keys())[0]
+
+ self.env.setup_vectorization()
+
info = {}
obs = self.get_observation()
@@ -248,16 +252,18 @@ class EnvGymWrapper(Env):
return obs, info
def get_observation(self):
- # obs = self.get_env_img(self.gridsize)
- obs = self.get_vector_state()
+ if self.use_rgb_obs:
+ obs = self.get_env_img(self.gridsize)
+ else:
+ obs = self.get_vector_state()
return obs
+
def render(self):
observation = self.get_env_img(self.gridsize)
- img = observation.transpose((1, 2, 0))[:, :, ::-1]
- # print(img.shape)
- img = cv2.resize(img, (img.shape[1] * 5, img.shape[0] * 5))
- cv2.imshow("Overcooked", img)
- cv2.waitKey(1)
+ img = (observation * 255.0).astype(np.uint8)
+ img = img.transpose((1, 2, 0))
+ img = cv2.resize(img, (img.shape[1], img.shape[0]))
+ return img
def close(self):
pass
@@ -268,20 +274,23 @@ class EnvGymWrapper(Env):
observation = self.visualizer.get_state_image(
grid_size=gridsize, state=json_dict
).transpose((1, 0, 2))
- return observation.transpose((2, 0, 1)) / 255.0
+ return (observation.transpose((2, 0, 1)) / 255.0).astype(np.float32)
def get_vector_state(self):
- grid, player, env_time, orders = self.env.get_vectorized_state("0")
+ # grid, player, env_time, orders = self.env.get_vectorized_state_full("0")
+ #
+ #
+ # obs = np.concatenate(
+ # [grid.flatten(), player.flatten()], axis=0, dtype=np.float32
+ # )
+ # return obs
- obs = np.concatenate([grid.flatten(), player.flatten()], axis=0)
+ obs = self.env.get_vectorized_state_simple("0")
return obs
- # flatten: grid + player
- # concatenate all (env_time to array)
def sample_random_action(self):
act = self.action_space.sample()
return act
- # return np.random.randint(len(self.action_space_map))
def main():
@@ -290,14 +299,15 @@ def main():
config = {
"policy_type": "MlpPolicy",
- "total_timesteps": 100_000, # hendric sagt eher so 300_000_000 schritte
+ "total_timesteps": 30_000_000, # hendric sagt eher so 300_000_000 schritte
"env_id": "overcooked",
+ "number_envs_parallel": 16,
}
- debug = True
+ debug = False
do_training = True
vec_env = True
- number_envs_parallel = 8
+ number_envs_parallel = config["number_envs_parallel"]
model_classes = [A2C, DQN, PPO]
model_class = model_classes[2]
@@ -307,12 +317,34 @@ def main():
else:
env = EnvGymWrapper()
- model_save_path = rl_agent_checkpoints / f"overcooked_{model_class.__name__}"
+ env.render_mode = "rgb_array"
+ if not debug:
+ run = wandb.init(
+ project="overcooked",
+ config=config,
+ sync_tensorboard=True, # auto-upload sb3's tensorboard metrics
+ monitor_gym=True
+ # save_code=True, # optional
+ )
+
+ env = VecVideoRecorder(
+ env,
+ f"videos/{run.id}",
+ record_video_trigger=lambda x: x % 100_000 == 0,
+ video_length=300,
+ )
+
+ model_save_path = rl_agent_checkpoints / f"overcooked_{model_class.__name__}"
if do_training:
model = model_class(
- config["policy_type"], env, verbose=1, tensorboard_log=f"runs/{0}"
+ config["policy_type"],
+ env,
+ verbose=1,
+ tensorboard_log=f"runs/{0}",
+ # n_steps=2048,
+ # n_epochs=10,
)
if debug:
model.learn(
@@ -321,16 +353,8 @@ def main():
progress_bar=True,
)
else:
- run = wandb.init(
- project="overcooked",
- config=config,
- sync_tensorboard=True, # auto-upload sb3's tensorboard metrics
- monitor_gym=True
- # save_code=True, # optional
- )
-
checkpoint_callback = CheckpointCallback(
- save_freq=1000,
+ save_freq=50_000,
save_path="./logs/",
name_prefix="rl_model",
save_replay_buffer=True,
@@ -356,14 +380,17 @@ def main():
model = model_class.load(model_save_path)
env = EnvGymWrapper()
+
check_env(env)
obs, info = env.reset()
while True:
- time.sleep(1 / 10)
+ time.sleep(1 / 30)
action, _states = model.predict(obs, deterministic=False)
obs, reward, terminated, truncated, info = env.step(int(action))
print(reward)
- env.render()
+ rgb_img = env.render()
+ cv2.imshow("env", rgb_img)
+ cv2.waitKey(0)
if terminated or truncated:
obs, info = env.reset()
diff --git a/overcooked_simulator/overcooked_environment.py b/overcooked_simulator/overcooked_environment.py
index 54de3fb157e31f41d397185c379f8b93213f3203..c394624a9a75a9ba1f969de43ffb4ee2ca5de4f3 100644
--- a/overcooked_simulator/overcooked_environment.py
+++ b/overcooked_simulator/overcooked_environment.py
@@ -48,7 +48,8 @@ from overcooked_simulator.hooks import (
ACTION_ON_NOT_REACHABLE_COUNTER,
ACTION_PUT,
ACTION_INTERACT_START,
- ITEM_INFO_CONFIG, POST_STEP,
+ ITEM_INFO_CONFIG,
+ POST_STEP,
)
from overcooked_simulator.order import (
OrderManager,
@@ -906,9 +907,11 @@ class Environment:
if name in self.vector_state_generation.meals:
idx = 3 + self.vector_state_generation.meals.index(name)
elif name in self.vector_state_generation.ingredients:
- idx = 3 + len(
- self.vector_state_generation.meals
- ) + self.vector_state_generation.ingredients.index(name)
+ idx = (
+ 3
+ + len(self.vector_state_generation.meals)
+ + self.vector_state_generation.ingredients.index(name)
+ )
else:
raise ValueError(f"Unknown item {name} - {item}")
array[idx] = 1.0
@@ -952,7 +955,7 @@ class Environment:
return item_array
- def get_vectorized_state(
+ def get_vectorized_state_full(
self, player_id: str
) -> Tuple[
npt.NDArray[npt.NDArray[float]],
@@ -1044,6 +1047,162 @@ class Environment:
order_array,
)
+ # def setup_vectorization_simple(self) -> VectorStateGenerationDataSimple:
+ # num_per_item = 114
+ # num_per_counter = 12
+ # num_players = 4
+ # grid_base_array = np.zeros(
+ # (
+ # int(self.kitchen_width),
+ # int(self.kitchen_height),
+ # num_per_item
+ # + num_per_counter
+ # + num_players, # TODO calc based on item info
+ # ),
+ # dtype=np.float32,
+ # )
+ # counter_list = [
+ # "Counter",
+ # "CuttingBoard",
+ # "ServingWindow",
+ # "Trashcan",
+ # "Sink",
+ # "SinkAddon",
+ # "Stove",
+ # "DeepFryer",
+ # "Oven",
+ # ]
+ # grid_idxs = [
+ # (x, y)
+ # for x in range(int(self.kitchen_width))
+ # for y in range(int(self.kitchen_height))
+ # ]
+ # # counters do not move
+ # for counter in self.counters:
+ # grid_idx = np.floor(counter.pos).astype(int)
+ # counter_name = (
+ # counter.name
+ # if isinstance(counter, CookingCounter)
+ # else (
+ # repr(counter)
+ # if isinstance(Counter, Dispenser)
+ # else counter.__class__.__name__
+ # )
+ # )
+ # assert counter_name in counter_list or counter_name.endswith(
+ # "Dispenser"
+ # ), f"Unknown Counter {counter}"
+ # oh_idx = len(counter_list)
+ # if counter_name in counter_list:
+ # oh_idx = counter_list.index(counter_name)
+ #
+ # one_hot = [0] * (len(counter_list) + 2)
+ # one_hot[oh_idx] = 1
+ # grid_base_array[
+ # grid_idx[0], grid_idx[1], 4 : 4 + (len(counter_list) + 2)
+ # ] = np.array(one_hot, dtype=np.float32)
+ #
+ # grid_idxs.remove((int(grid_idx[0]), int(grid_idx[1])))
+ #
+ # for free_idx in grid_idxs:
+ # one_hot = [0] * (len(counter_list) + 2)
+ # one_hot[len(counter_list) + 1] = 1
+ # grid_base_array[
+ # free_idx[0], free_idx[1], 4 : 4 + (len(counter_list) + 2)
+ # ] = np.array(one_hot, dtype=np.float32)
+ #
+ # player_info_base_array = np.zeros(
+ # (
+ # 4,
+ # 4 + 114,
+ # ),
+ # dtype=np.float32,
+ # )
+ # order_base_array = np.zeros((10 * (8 + 1)), dtype=np.float32)
+ #
+ # return VectorStateGenerationData(
+ # grid_base_array=grid_base_array,
+ # oh_len=12,
+ # )
+
+ def get_vectorized_state_simple(self, player):
+ item_list = ["Pot", "Tomato", "ChoppedTomato", "Plate"]
+ counter_list = [
+ "Counter",
+ "PlateDispenser",
+ "TomatoDispenser",
+ "ServingWindow",
+ "PlateReturn",
+ "Trashcan",
+ "Stove",
+ "CuttingBoard",
+ ]
+ player_pos = self.players[player].pos
+ player_dir = self.players[player].facing_direction
+
+ grid_width, grid_height = int(self.kitchen_width), int(self.kitchen_height)
+
+ counter_one_hot_length = len(counter_list) + 1 # one for empty field
+ grid_base_array = np.zeros(
+ (
+ grid_width,
+ grid_height,
+ ),
+ dtype=int,
+ )
+
+ grid_idxs = [(x, y) for x in range(grid_width) for y in range(grid_height)]
+
+ # counters do not move
+ for counter in self.counters:
+ grid_idx = np.floor(counter.pos).astype(int)
+ counter_name = (
+ counter.name
+ if isinstance(counter, CookingCounter)
+ else (
+ repr(counter)
+ if isinstance(Counter, Dispenser)
+ else counter.__class__.__name__
+ )
+ )
+ if counter_name == "Dispenser":
+ counter_name = f"{counter.occupied_by.name}Dispenser"
+ assert counter_name in counter_list, f"Unknown Counter {counter}"
+
+ counter_oh_idx = counter_one_hot_length
+ if counter_name in counter_list:
+ counter_oh_idx = counter_list.index(counter_name)
+
+ grid_base_array[grid_idx[0], grid_idx[1]] = counter_oh_idx
+ grid_idxs.remove((int(grid_idx[0]), int(grid_idx[1])))
+
+ for free_idx in grid_idxs:
+ grid_base_array[free_idx[0], free_idx[1]] = counter_one_hot_length - 1
+
+ counter_grid_one_hot = np.zeros(
+ (grid_width, grid_height, counter_one_hot_length), dtype=int
+ )
+ for x in range(grid_width):
+ for y in range(grid_height):
+ counter_type_idx = grid_base_array[x, y]
+ counter_grid_one_hot[x, y, counter_type_idx] = 1
+
+ player_data = np.concatenate((player_pos, player_dir), axis=0)
+
+ items_one_hot_length = len(item_list) + 1
+ item_one_hot = np.zeros(items_one_hot_length, dtype=int)
+ player_item = self.players[player].holding
+ player_item_idx = items_one_hot_length - 1
+ if player_item:
+ if player_item.name in item_list:
+ player_item_idx = item_list.index(player_item.name)
+ item_one_hot[player_item_idx] = 1
+
+ final = np.concatenate(
+ (counter_grid_one_hot.flatten(), player_data, item_one_hot), axis=0
+ )
+ return final
+
def reset_env_time(self):
"""Reset the env time to the initial time, defined by `create_init_env_time`."""
self.hook(PRE_RESET_ENV_TIME)
diff --git a/overcooked_simulator/utils.py b/overcooked_simulator/utils.py
index 357d26795a14727eb511468f672e97a072745cd3..4ef8b86858a606eebf4ac40e316387d7aea59c72 100644
--- a/overcooked_simulator/utils.py
+++ b/overcooked_simulator/utils.py
@@ -65,6 +65,27 @@ class VectorStateGenerationData:
]
+@dataclasses.dataclass
+class VectorStateGenerationDataSimple:
+ grid_base_array: npt.NDArray[npt.NDArray[float]]
+ oh_len: int
+
+ number_normal_ingredients = 1
+
+ meals = [
+ "TomatoSoup",
+ ]
+ equipments = [
+ "Pot",
+ "Plate",
+ "DirtyPlate",
+ "Extinguisher",
+ ]
+ ingredients = [
+ "Tomato",
+ ]
+
+
def create_init_env_time():
"""Init time of the environment time, because all environments should have the same internal time."""
return datetime(