How severe does this issue affect your experience of using Ray?
- High: It blocks me to complete my task.
I am learning how to use Ray and the book I am using was written using an older version or Ray. I am currently running into an issue with RLlib where the problem seems to be stemming from using a Custom Environment. The code errors out with a AttributeError: 'NoneType' object has no attribute 'build_encoder'. It seems this is an issue with building a catalog but at this stage of my learning of ray I don’t really know what that is. Any help would be appreciated. Here is the code I am using:
import gymnasium as gym
from gymnasium.spaces import Discrete
import os
from ray.tune.logger import pretty_print
from ray.rllib.algorithms.dqn import DQNConfig
from ray.tune.registry import register_env
class MyEnvironment(gym.Env):
seeker, goal = (0, 0), (4, 4)
info = {'seeker': seeker, 'goal': goal}
def __init__(self, config=None):
self.action_space = Discrete(4)
self.observation_space = Discrete(5*5)
def reset(self, seed=None, options=None):
"""Reset seeker and goal positions, return observations."""
self.seeker = (0, 0)
self.goal = (4, 4)
return self.get_observation(), {}
def get_observation(self):
"""Encode the seeker position as integer"""
return 5 * self.seeker[0] + self.seeker[1]
def get_reward(self):
"""Reward finding the goal"""
return 1 if self.seeker == self.goal else 0
def is_done(self):
"""We're done if we found the goal"""
return self.seeker == self.goal
def step(self, action):
"""Take a step in a direction and return all available information."""
if action == 0: # move down
self.seeker = (min(self.seeker[0] + 1, 4), self.seeker[1])
elif action == 1: # move left
self.seeker = (self.seeker[0], max(self.seeker[1] - 1, 0))
elif action == 2: # move up
self.seeker = (max(self.seeker[0] - 1, 0), self.seeker[1])
elif action == 3: # move right
self.seeker = (self.seeker[0], min(self.seeker[1] + 1, 4))
else:
raise ValueError("Invalid action")
return self.get_observation()[0], self.get_reward(), self.is_done(), False, self.info
def render(self, *args, **kwargs):
"""Render the environment, e.g. by printing its representation."""
os.system('cls' if os.name == 'nt' else 'clear')
try:
from IPython.display import clear_output
clear_output(wait=True)
except Exception:
pass
grid = [['| ' for _ in range(5)] + ["|\n"] for _ in range(5)]
grid[self.goal[0]][self.goal[1]] = '|G'
grid[self.seeker[0]][self.seeker[1]] = '|S'
print(''.join([''.join(grid_row) for grid_row in grid]))
config = (
DQNConfig()
.environment(MyEnvironment, env_config={})
.env_runners(
num_env_runners = 2,
create_env_on_local_worker = True,
)
.api_stack(
enable_rl_module_and_learner=True,
enable_env_runner_and_connector_v2=True
)
)
algo = config.build_algo()