TypeError: reset() got an unexpected keyword argument 'seed' #2531

deepboltzer · 2021-12-16T15:38:55Z

There is an issue with the seeds after the Seeding update (#2422).

File "/home/joe/reinforce/rlenv/lib/python3.8/site-packages/gym/wrappers/time_limit.py", line 29, in reset
    return self.env.reset(seed=seed, **kwargs)
TypeError: reset() got an unexpected keyword argument 'seed'

Code for Imitation:

import gym
import ale_py
import time

print('gym:', gym.__version__)
print('ale_py:', ale_py.__version__)

env = gym.make("BreakoutNoFrameskip-v4")

print("Observation Space: ", env.observation_space)
print("Action Space       ", env.action_space)

obs = env.reset()

for i in range(1000):
    action = env.action_space.sample()
    obs, reward, done, info = env.step(action)
    env.render()
    time.sleep(0.01)
env.close()

I am using gym: 0.21.0 and ale_py: 0.7.3.

The text was updated successfully, but these errors were encountered:

vwxyzjn · 2021-12-16T20:58:49Z

In pybullet I just hit the same issue. It's likely going to cause most of the third-party envs to fail.

vwxyzjn · 2021-12-16T21:02:58Z

@RedTachyon would you mind looking into this?

RedTachyon · 2021-12-16T21:15:44Z

I'm confused, are you sure it's gym release 0.21? This was released long before any seeding changes made their way into master.

RedTachyon · 2021-12-16T21:37:12Z

Ah shit, I managed to replicate it with pybullet, I think I know what's up. Basically wrappers forward the arguments to the inside environment, and while "new style" environments can accept anything in reset, old environments can't. So even if you don't do anything, it's trying to pass the default None onward to the environment.

Thanks for the catch, I think I have an idea on how to fix it, which will be possible thanks to the other change to the reset signature.

RedTachyon · 2021-12-16T21:59:39Z

The latest commit in #2515 fixes it for me with pybullet, can someone check it with atari? (for some reason a simple install doesn't work when I try to use it, and I never used atari, so probably some of the ROM stuff is lost on me)

deepboltzer · 2022-01-06T13:18:20Z

Thank you so much for fixing this issue @RedTachyon! The latest commit in #2515 also fixes the problem for atari.

vwxyzjn · 2022-02-19T23:18:50Z

Hey, I am still having this issue with the latest gym release gym=0.22.0. @jkterry1 could u re-open the issue? See the following snippet:

import gym
import numpy as np
import pybullet_envs

env = gym.make("HopperBulletEnv-v0")
env.reset()

env = gym.make("HopperBulletEnv-v0")
env = gym.wrappers.ClipAction(env)
env = gym.wrappers.NormalizeObservation(env)
env = gym.wrappers.TransformObservation(env, lambda obs: np.clip(obs, -10, 10))
env = gym.wrappers.NormalizeReward(env)
env = gym.wrappers.TransformReward(env, lambda reward: np.clip(reward, -10, 10))
env.reset()

which yields. So looks like without the wrappers the reset was ok, but with the wrappers, the reset was not ok.

pybullet build time: Sep  3 2021 23:59:09
/home/costa/.cache/pypoetry/virtualenvs/cleanrl-ghSZGHE3-py3.9/lib/python3.9/site-packages/gym/spaces/box.py:78: UserWarning: WARN: Box bound precision lowered by casting to float32
  logger.warn(f"Box bound precision lowered by casting to {self.dtype}")
argv[0]=
argv[0]=
Traceback (most recent call last):
  File "/home/costa/Documents/go/src/github.com/cleanrl/cleanrl/test.py", line 14, in <module>
    env.reset()
  File "/home/costa/.cache/pypoetry/virtualenvs/cleanrl-ghSZGHE3-py3.9/lib/python3.9/site-packages/gym/core.py", line 324, in reset
    return self.env.reset(**kwargs)
  File "/home/costa/.cache/pypoetry/virtualenvs/cleanrl-ghSZGHE3-py3.9/lib/python3.9/site-packages/gym/core.py", line 283, in reset
    return self.env.reset(**kwargs)
  File "/home/costa/.cache/pypoetry/virtualenvs/cleanrl-ghSZGHE3-py3.9/lib/python3.9/site-packages/gym/core.py", line 311, in reset
    return self.observation(self.env.reset(**kwargs))
  File "/home/costa/.cache/pypoetry/virtualenvs/cleanrl-ghSZGHE3-py3.9/lib/python3.9/site-packages/gym/wrappers/normalize.py", line 75, in reset
    obs = self.env.reset(seed=seed, options=options)
  File "/home/costa/.cache/pypoetry/virtualenvs/cleanrl-ghSZGHE3-py3.9/lib/python3.9/site-packages/gym/core.py", line 337, in reset
    return self.env.reset(**kwargs)
  File "/home/costa/.cache/pypoetry/virtualenvs/cleanrl-ghSZGHE3-py3.9/lib/python3.9/site-packages/gym/wrappers/time_limit.py", line 26, in reset
    return self.env.reset(**kwargs)
  File "/home/costa/.cache/pypoetry/virtualenvs/cleanrl-ghSZGHE3-py3.9/lib/python3.9/site-packages/gym/wrappers/order_enforcing.py", line 18, in reset
    return self.env.reset(**kwargs)
TypeError: reset() got an unexpected keyword argument 'seed'

vwxyzjn · 2022-02-19T23:51:24Z

Looks like this is an issue with

gym/gym/wrappers/normalize.py

Line 77 in bdde1ed

obs, info = self.env.reset(seed=seed, return_info=True, options=options)

that forces to use the seed during reset

RedTachyon · 2022-02-22T09:37:40Z

Good catch, this will need a patch, should be fairly simple

karlengblom · 2022-03-10T21:12:21Z

Hello! Thanks to everyone for all the work on this repo.
I get the same error message as above when running the bipedal_walker.py heuristic:

(stable-baselines3) karl@omen:~$ python reps/gym/gym/envs/box2d/bipedal_walker.py
pygame 2.1.0 (SDL 2.0.16, Python 3.8.10)
Hello from the pygame community. https://www.pygame.org/contribute.html
Traceback (most recent call last):
File "reps/gym/gym/envs/box2d/bipedal_walker.py", line 687, in
env.reset()
File "reps/gym/gym/envs/box2d/bipedal_walker.py", line 361, in reset
super().reset(seed=seed)
TypeError: reset() got an unexpected keyword argument 'seed'

vwxyzjn · 2022-03-10T21:21:33Z

@karlengblom What is your gym version? Do you have a demo code to replicate this?

karlengblom · 2022-03-10T21:43:18Z

The version is 0.23.0.
I was trying to look at the bipedal walker heuristic, so the code is just python bipedal_walker.py

RedTachyon · 2022-03-10T21:53:29Z

@karlengblom Can you please double check that you have a fresh installation of gym? I can't replicate the issue, and it seems pretty impossible in terms of the code. If you were updating gym from an older version, perhaps there are some __pycache__ and *.pyc with the old code?

vwxyzjn · 2022-03-10T22:35:48Z

It works on my end.

(cleanrl-ghSZGHE3-py3.9) ➜  cleanrl git:(fix-dqn-seed) ✗ pip install gym==0.23.0 box2d-py
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: gym==0.23.0 in /home/costa/.cache/pypoetry/virtualenvs/cleanrl-ghSZGHE3-py3.9/lib/python3.9/site-packages (0.23.0)
Requirement already satisfied: box2d-py in /home/costa/.cache/pypoetry/virtualenvs/cleanrl-ghSZGHE3-py3.9/lib/python3.9/site-packages (2.3.8)
Requirement already satisfied: cloudpickle>=1.2.0 in /home/costa/.cache/pypoetry/virtualenvs/cleanrl-ghSZGHE3-py3.9/lib/python3.9/site-packages (from gym==0.23.0) (2.0.0)
Requirement already satisfied: numpy>=1.18.0 in /home/costa/.cache/pypoetry/virtualenvs/cleanrl-ghSZGHE3-py3.9/lib/python3.9/site-packages (from gym==0.23.0) (1.21.5)
Requirement already satisfied: importlib-metadata>=4.10.0 in /home/costa/.cache/pypoetry/virtualenvs/cleanrl-ghSZGHE3-py3.9/lib/python3.9/site-packages (from gym==0.23.0) (4.11.2)
Requirement already satisfied: gym-notices>=0.0.4 in /home/costa/.cache/pypoetry/virtualenvs/cleanrl-ghSZGHE3-py3.9/lib/python3.9/site-packages (from gym==0.23.0) (0.0.5)
Requirement already satisfied: zipp>=0.5 in /home/costa/.cache/pypoetry/virtualenvs/cleanrl-ghSZGHE3-py3.9/lib/python3.9/site-packages (from importlib-metadata>=4.10.0->gym==0.23.0) (3.7.0)
WARNING: You are using pip version 22.0.3; however, version 22.0.4 is available.
You should consider upgrading via the '/home/costa/.cache/pypoetry/virtualenvs/cleanrl-ghSZGHE3-py3.9/bin/python -m pip install --upgrade pip' command.
(cleanrl-ghSZGHE3-py3.9) ➜  cleanrl git:(fix-dqn-seed) ✗ python /home/costa/.cache/pypoetry/virtualenvs/cleanrl-ghSZGHE3-py3.9/lib/python3.9/site-packages/gym/envs/box2d/bipedal_walker.py
pygame 2.1.0 (SDL 2.0.16, Python 3.9.5)
Hello from the pygame community. https://www.pygame.org/contribute.html

action ['+0.00', '+0.00', '+0.00', '+0.00']
step 0 total_reward -0.08
hull ['-0.01', '-0.00', '-0.00', '-0.00']
leg0 ['+0.44', '+0.06', '+0.12', '-0.08', '+1.00']
leg1 ['+0.34', '+0.07', '+0.12', '-0.09', '+1.00']

action ['+0.03', '-0.01', '-0.02', '+0.42']
step 20 total_reward -0.73
hull ['-0.06', '+0.01', '+0.01', '-0.01']
leg0 ['+1.01', '-0.13', '-0.57', '-0.02', '+0.00']
leg1 ['+0.51', '-0.06', '-0.08', '-0.03', '+0.00']

action ['+0.03', '-0.01', '-0.01', '+0.43']
step 40 total_reward -0.62
hull ['-0.03', '+0.00', '+0.02', '-0.00']
leg0 ['+1.00', '+0.02', '-0.59', '-0.00', '+0.00']
leg1 ['+0.46', '-0.03', '-0.11', '-0.00', '+0.00']

action ['+0.04', '-0.01', '-0.01', '+0.42']
step 60 total_reward -0.29
hull ['-0.03', '-0.00', '+0.06', '-0.00']
leg0 ['+0.99', '-0.01', '-0.59', '+0.00', '+0.00']
leg1 ['+0.39', '-0.07', '-0.10', '+0.01', '+0.00']
^CTraceback (most recent call last):
  File "/home/costa/.cache/pypoetry/virtualenvs/cleanrl-ghSZGHE3-py3.9/lib/python3.9/site-packages/gym/envs/box2d/bipedal_walker.py", line 764, in <module>
    env.render()
  File "/home/costa/.cache/pypoetry/virtualenvs/cleanrl-ghSZGHE3-py3.9/lib/python3.9/site-packages/gym/envs/box2d/bipedal_walker.py", line 658, in render
    self.clock.tick(self.metadata["render_fps"])
KeyboardInterrupt

karlengblom · 2022-03-12T12:51:54Z

It works. I mixed up the gym version containing the bipedal_walker.py file itself with the gym version imported by it. It was imported from a python env made for SB3, so version 0.19. Thanks for responses, sorry for the inconvenience.

bdytx5 · 2022-10-21T16:24:53Z

For me, the solution is to upgrade gym to the newest version

JonaSi754 · 2023-07-01T12:15:35Z

Hi, stable baseline3 had been working well in my project, but when using gymnasium, I encountered this error. What should I do to fix it?

pseudo-rnd-thoughts · 2023-07-01T12:31:01Z

@JonaSi754 Could you provide some code to replicate this

JonaSi754 · 2023-07-01T14:08:34Z

@JonaSi754 Could you provide some code to replicate this

Sure, I use a custom env. Here is the env I create:

import gymnasium
from gymnasium import spaces

class env(gymnasium.Env):
    def __init__(self) -> str:
        super().__init__()
        self.action_shape = (5,)
        self.action_space = spaces.box.Box(low=-1, high=1, shape=self.action_shape)
        self.observation_shape = (9,)
        self.observation_space = spaces.box.Box(low=0, high=1, shape=self.observation_shape)

And here is the traceback:

Traceback (most recent call last):
  File "/home/sssjh/Workspace/MyRL/code/algo/PPO_task.py", line 72, in <module>
    model.learn(total_timesteps=cfg.n_episodes * cfg.n_steps)
  File "/home/sssjh/miniconda3/envs/SB3/lib/python3.9/site-packages/stable_baselines3/ppo/ppo.py", line 308, in learn
    return super().learn(
  File "/home/sssjh/miniconda3/envs/SB3/lib/python3.9/site-packages/stable_baselines3/common/on_policy_algorithm.py", line 246, in learn
    total_timesteps, callback = self._setup_learn(
  File "/home/sssjh/miniconda3/envs/SB3/lib/python3.9/site-packages/stable_baselines3/common/base_class.py", line 424, in _setup_learn
    self._last_obs = self.env.reset()  # type: ignore[assignment]
  File "/home/sssjh/miniconda3/envs/SB3/lib/python3.9/site-packages/stable_baselines3/common/vec_env/dummy_vec_env.py", line 76, in reset
    obs, self.reset_infos[env_idx] = self.envs[env_idx].reset(seed=self._seeds[env_idx])
  File "/home/sssjh/miniconda3/envs/SB3/lib/python3.9/site-packages/stable_baselines3/common/monitor.py", line 83, in reset
    return self.env.reset(**kwargs)
TypeError: reset() got an unexpected keyword argument 'seed'

pseudo-rnd-thoughts · 2023-07-03T09:48:14Z

@JonaSi754 You need to provide the reset function (and step function), also what gym and sb3 do you use?

JonaSi754 · 2023-07-03T13:58:56Z

@pseudo-rnd-thoughts sry for confusion, but my original code could be a little bit long. I remove some irrelevant functions.
Here is the env.py

class env(gymnasium.Env):
    metadata = {'render.modes': ['human']}

def __init__(self, instance) -> str:
    super().__init__()
    self.instance = instance
    self.Jobs = read_JSP(self.instance)
    self.action_shape = (5,)
    self.action_space = spaces.box.Box(low=-1, high=1, shape=self.action_shape)
    self.observation_shape = (9,)
    self.observation_space = spaces.box.Box(low=0, high=1, shape=self.observation_shape)
    self.baseline = schedule_by_rules(instance, 5) # MOPNR

def reset(self):
    for job in self.Jobs:
        job.reset()
    self.states = states(self.Jobs)
    self.done = False
    self.state = np.zeros(self.observation_shape, dtype=np.float32)
    self.next_machines = []
    self.timer = 0
    self.offload = [False for _ in range(len(self.Jobs))]
    self.fillMachines()
    return self.state

def step(self, action):
    
    # Deal with action
    # Get the job and machine that we choose
    selector = action_v6(self.action_shape)
    buffer = self.next_machines[0].buffer
    _job_state = [bool(job.endTime) and job.endTime[-1] > self.timer for job in buffer]
    mask = [-int(n) + 1.1 for n in _job_state]
    this_job = selector.select_job(buffer, action, mask)
    

    # search forward for a position to insert
    # Or append on the tail
    self.forward_insert(this_job)
        
    
    # Record last makespan
    last_makespan = self.states.makespan
    
    
    # Update state space
    self.states.update_state(this_job, self.next_machines[0].No)
        
    # Give a reward
    reward = last_makespan - self.states.makespan
    
    # Judge if this batch of task has been done
    if sum([job.done for job in self.Jobs]) == len(self.Jobs):
        self.done = True

    # skip to the next schedule point
    self.next_machines.remove(self.next_machines[0])
    if not self.done:
        # Calculate observation for next machine
        self.fillMachines()
        self.state = self.states.observe(self.next_machines[0].No)

    # Record extra information of this step
    info = {}
    
    return self.state, reward, self.done, info

'''
And I use gym0.21.0, gymnasium0.28.1 and stable-baselines3 2.0.0

JonaSi754 · 2023-07-03T14:09:45Z

Oh, I just find the pattern code also meets the same problem, can you check it
https://imitation.readthedocs.io/en/latest/algorithms/bc.html
my versions are: gym-0.21.0, gymnasium-0.28.1, SB3-2.0.0

pseudo-rnd-thoughts · 2023-07-03T14:53:40Z

You either need to downgrade sb3 to 1.X or use the Gym compatibility environment (https://gymnasium.farama.org/content/gym_compatibility/#gym-v0-21-environment-compatibility) as your environment is implemented in gym's v0.21 API not v0.26's api

JonaSi754 · 2023-07-03T15:25:23Z

thank you very much, I have resolved this!

Hugh-Kane · 2023-07-07T20:35:15Z

Hi, I was also having similar issues with gym_super_mario_bros, where I get the following error:
TypeError: reset() got an unexpected keyword argument 'seed'

I am currently using:
Python ==3.8
gym == 0.26.2
gym-super-mario-bros == 7.4.0
stable-baselines3 == 2.0.0

I would appreciate any help!
Code is as follows:


# Import game
import gym_super_mario_bros
# Import joypad

from nes_py.wrappers import JoypadSpace
# Import simplified controls
from gym_super_mario_bros.actions import SIMPLE_MOVEMENT


"""
#Preprocessing step
"""
#grayscale cuts down the processing power by 66% since we don't need to process all RGB channels
from gym.wrappers import GrayScaleObservation
#import vectorization wrappers 
from stable_baselines3.common.vec_env import VecFrameStack, DummyVecEnv
from matplotlib import pyplot as plt
from stable_baselines3.common.env_checker import check_env


# 1.Create the base environment.
env = gym_super_mario_bros.make('SuperMarioBros-v3',apply_api_compatibility=True,render_mode="human" )
# 2.Simplify controls
env = JoypadSpace(env,SIMPLE_MOVEMENT)
# 3.Grayscale
#Without keep_dim, shape corresponds to (240, 256)
#With keep_dim, shape corresponds to (240, 256, 1)
env = GrayScaleObservation(env, keep_dim=True)
# 4.Wrap inside the Dummy Environment
env = DummyVecEnv([lambda: env])


state= env.reset()


#print(gym_super_mario_bros.list_envs())

jcianci12 · 2023-09-07T22:28:03Z

For me, the solution is to upgrade gym to the newest version

Do you mean the latest version of gym or gymnasium. Thanks! 🙏

phuongboi · 2023-10-07T08:43:08Z

Install gym 0.18.0 (pip install gym==0.18.0) instead of gymnasium solved my problem

jeffheaton · 2023-11-09T14:09:14Z

Agree, using gym instead solves the issue. So we have to use the old deprecated library?

RedTachyon · 2023-11-09T14:33:45Z

If you want to use another old deprecated library that's been written for the old deprecated library, then there's a chance you'll have to use an old deprecated library, yes

rohitsaikrishnan · 2023-12-24T03:07:30Z

Hi, I was also having similar issues with gym_super_mario_bros, where I get the following error: TypeError: reset() got an unexpected keyword argument 'seed'

I am currently using: Python ==3.8 gym == 0.26.2 gym-super-mario-bros == 7.4.0 stable-baselines3 == 2.0.0

I would appreciate any help! Code is as follows:


# Import game
import gym_super_mario_bros
# Import joypad

from nes_py.wrappers import JoypadSpace
# Import simplified controls
from gym_super_mario_bros.actions import SIMPLE_MOVEMENT


"""
#Preprocessing step
"""
#grayscale cuts down the processing power by 66% since we don't need to process all RGB channels
from gym.wrappers import GrayScaleObservation
#import vectorization wrappers 
from stable_baselines3.common.vec_env import VecFrameStack, DummyVecEnv
from matplotlib import pyplot as plt
from stable_baselines3.common.env_checker import check_env


# 1.Create the base environment.
env = gym_super_mario_bros.make('SuperMarioBros-v3',apply_api_compatibility=True,render_mode="human" )
# 2.Simplify controls
env = JoypadSpace(env,SIMPLE_MOVEMENT)
# 3.Grayscale
#Without keep_dim, shape corresponds to (240, 256)
#With keep_dim, shape corresponds to (240, 256, 1)
env = GrayScaleObservation(env, keep_dim=True)
# 4.Wrap inside the Dummy Environment
env = DummyVecEnv([lambda: env])


state= env.reset()


#print(gym_super_mario_bros.list_envs())

I have the similar issue. Any help here please.

pseudo-rnd-thoughts · 2023-12-25T20:47:28Z

https://github.com/Kautenja/nes-py/blob/b6f4e26a96cf1dc2329b3b45b9f785dd7dbb30c6/nes_py/wrappers/joypad_space.py#L76

The NES-py wrapper reset function doesn't have a seed parameter therefore it fails

AbhayGoyal · 2024-09-08T17:39:01Z

@JonaSi754
Can you tell me how me how you fixed this issue? What are the exact Stable baselines and Gynasium and Gym package version used?

Thanks

AbhayGoyal · 2024-09-10T00:34:08Z

@pseudo-rnd-thoughts, I am using Gym 0.26.0 and stable 2.3.2 and still get the same issue. I thought with v26 this issue should not be there right?

meghbhalerao · 2024-11-19T19:20:06Z

Hi, I am using the follwowing gym (version = 0.21.0 and commit hash with fixed typo (https://stackoverflow.com/questions/76129688/why-is-pip-install-gym-failing-with-python-setup-py-egg-info-did-not-run-succ) fixed is given below) and stable baselines 3 versions -

stable-baselines3==1.5.0
gym @ git+https://github.com/openai/gym.git@9180d12e1b66e7e2a1a622614f787a6ec147ac40
gym-notices==0.0.8
-e git+ssh://[email protected]/meghbhalerao/human-robot-gym.git@da7823a1731a96cab7c8a1f4f88b374e7acad407#egg=human_robot_gym

I am still facing the above error as mentioned in the original issue ...

Does anyone know a final fix for this? That is, what are the correct versions of gym and stable baselines 3 to use so that this gets fixed? Any other things to keep in mind while making our env?

Thanks!

codenigma1 · 2024-12-07T02:24:49Z

Hello I got the same error able to resolve this problem main problem lies with incompatability issue with latest update with gym, stable-baselines3, and nes-py.

Issue: nes-py Reset Method Incompatibility with Gym API

The reset() method in the nes-py wrapper (JoypadSpace) used in gym-super-mario-bros does not support the seed and options parameters introduced in gym>=0.22. When combined with stable-baselines3 and wrappers like DummyVecEnv, this results in a TypeError.

These are the following latest environment:

stable-baselines3==2.4.0
gym==0.26.2
nes-py==8.2.1

from nes_py.wrappers import JoypadSpace
from gym_super_mario_bros import make
from gym_super_mario_bros.actions import SIMPLE_MOVEMENT
from gym.wrappers import GrayScaleObservation
from stable_baselines3.common.vec_env import DummyVecEnv

# Create the environment
env = make('SuperMarioBros-v0', apply_api_compatibility=True, render_mode='rgb_array')
env = JoypadSpace(env, SIMPLE_MOVEMENT)
env = GrayScaleObservation(env, keep_dim=True)

# Wrap in DummyVecEnv
env = DummyVecEnv([lambda: env])  # ERROR occurs here
state = env.reset()

The above code fails with the following error:
TypeError: reset() got an unexpected keyword argument 'seed'

SOLUTION:

Root Cause
The issue arises because the reset() method in nes-py's JoypadSpace does not accept seed or options parameters. This creates incompatibility when using modern Gym APIs (gym>=0.22), which expect environments to handle these parameters. Additionally, stable-baselines3 passes these arguments through DummyVecEnv, causing the failure.

To resolve this issue, we override the reset() method in the JoypadSpace wrapper to gracefully ignore unsupported arguments (seed and options).

from nes_py.wrappers import JoypadSpace
from gym_super_mario_bros import make
from gym_super_mario_bros.actions import SIMPLE_MOVEMENT
from gym.wrappers import GrayScaleObservation
from stable_baselines3.common.vec_env import DummyVecEnv

# Custom wrapper to handle both `seed` and `options` arguments
class CustomJoypadSpace(JoypadSpace):
    def reset(self, seed=None, options=None, **kwargs):
        """
        Overrides the `reset()` method to ignore `seed` and `options` arguments.
        """
        return super().reset(**kwargs)

# Create the environment
env = gym_super_mario_bros.make('SuperMarioBros-v0', apply_api_compatibility=True, render_mode='rgb_array')
# Simplify the controls
env = CustomJoypadSpace(env, SIMPLE_MOVEMENT)
# Using GrayScaleWrapper to pass image in grayscale
env = GrayScaleObservation(env, keep_dim=True)
# Wrap inside the Dummy Environment 
env = DummyVecEnv([lambda: env])

# Test the environment
state = env.reset()

state.shape         
print(f"State shape: {state.shape}")

State shape: (1, 240, 256, 1)

The custom wrapper ensures compatibility with nes-py without altering its core library.

Additional Suggestions

To avoid such compatibility issues in the future:

Update nes-py to support modern Gym APIs (gym>=0.22).
Add optional arguments like seed and options to the reset() method of JoypadSpace.

Versions Tested

gym==0.26.2
gym-super-mario-bros==7.4.0
stable-baselines3==2.4.0
nes-py==8.2.1

araffin mentioned this issue Dec 28, 2021

Fix not-registered env DLR-RM/stable-baselines3#705

Closed

10 tasks

balisujohn mentioned this issue Dec 30, 2021

Adding return_info argument to reset to allow for optional info dict as a second return value #2546

Merged

7 tasks

deepboltzer closed this as completed Jan 6, 2022

araffin mentioned this issue Jan 13, 2022

Update to newest Gym version DLR-RM/stable-baselines3#572

Closed

13 tasks

vwxyzjn mentioned this issue Feb 22, 2022

Make NormalizeObservation compatible with pybullet #2638

Merged

JonaSi754 mentioned this issue Jul 19, 2023

unexpected keyword argument JonaSi754/JSP-RL-Environment#1

Open

rohitsaikrishnan mentioned this issue Dec 24, 2023

env.reset() returns TypeError: JoypadSpace.reset() got an unexpected keyword argument 'seed' error while using DummyVecEnv wrapper Kautenja/nes-py#96

Open

meghbhalerao mentioned this issue Nov 19, 2024

TypeError: reset() got an unexpected keyword argument 'seed' TUMcps/human-robot-gym#12

Closed

shayan223 mentioned this issue Jan 21, 2025

Installation issues Luca96/carla-driving-rl-agent#33

Open

TypeError: reset() got an unexpected keyword argument 'seed' #2531

TypeError: reset() got an unexpected keyword argument 'seed' #2531

Comments

deepboltzer commented Dec 16, 2021

vwxyzjn commented Dec 16, 2021 • edited Loading

vwxyzjn commented Dec 16, 2021

RedTachyon commented Dec 16, 2021

RedTachyon commented Dec 16, 2021

RedTachyon commented Dec 16, 2021

deepboltzer commented Jan 6, 2022

vwxyzjn commented Feb 19, 2022 • edited Loading

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pseudo-rnd-thoughts commented Dec 25, 2023

AbhayGoyal commented Sep 8, 2024 • edited Loading

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meghbhalerao commented Nov 19, 2024 • edited Loading

codenigma1 commented Dec 7, 2024 • edited Loading

SOLUTION:

Additional Suggestions

Versions Tested

vwxyzjn commented Dec 16, 2021 •

edited

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vwxyzjn commented Feb 19, 2022 •

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karlengblom commented Mar 10, 2022 •

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JonaSi754 commented Jul 1, 2023 •

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