Gymnasium Custom Env Step() Returns Invalid Shape: 5 Fixes

The Error That Breaks Every Custom Gymnasium Environment

Your step() function returns a perfectly valid numpy array. Stable Baselines3 throws AssertionError: The observation returned by thestep()method does not match the given observation space. You stare at your code for 20 minutes, print the shape, it looks correct, and yet the environment refuses to work.

This specific error has cost me more debugging hours than any algorithm hyperparameter ever did. The shape mismatch between observation_space and actual returned observations is the single most common bug when building custom Gymnasium environments, and it fails silently in ways that will make you question your sanity.

Here's the working pattern I now use for every custom environment:

python
import gymnasium as gym
import numpy as np
from gymnasium import spaces

class RobustCustomEnv(gym.Env):
    def __init__(self):
        super().__init__()
        self.state_dim = 4

        # Bug fix #1: Always use explicit dtype
        self.observation_space = spaces.Box(
            low=-np.inf,
            high=np.inf,
            shape=(self.state_dim,),
            dtype=np.float32  # CRITICAL: explicit dtype
        )
        self.action_space = spaces.Discrete(2)
        self._state = None

    def reset(self, seed=None, options=None):
        super().reset(seed=seed)
        # Bug fix #2: Cast to correct dtype immediately
        self._state = np.zeros(self.state_dim, dtype=np.float32)

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*Continue reading the full article on [TildAlice](https://tildalice.io/gymnasium-custom-env-observation-space-bugs/)*