L’interface est localisée ; les présentations et documents des Skills sont traduits automatiquement par IA dans votre langue. Le code, les commandes, chemins et termes techniques restent en version originale, et le document de l’auteur fait foi.
Explorer les Skills
Productivité · SKILL.md

environments-and-vectorization

environments-and-vectorization

Create and validate Gymnasium custom environments for Stable-Baselines3, then wrap them safely with Monitor, DummyVecEnv/SubprocVecEnv, VecNormalize, VecCheckNan, and frame/dict/image vector wrappers.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: environments-and-vectorization description: "Create and validate Gymnasium custom environments for Stable-Baselines3, then wrap them safely with Monitor, DummyVecEnv/SubprocVecEnv, VecNormalize, VecCheckNan, and frame/dict/image vector wrappers." disable-model-invocation: true metadata: disco-role: operating license: MIT

Environments And Vectorization

Use this sub-skill when the task is about Stable-Baselines3 environment compatibility rather than algorithm selection: custom Gymnasium env APIs, check_env, vectorized env construction, VecEnv API semantics, Monitor logging, normalization, NaN checks, frame stacking, dict/image observations, and multiprocessing caveats.

Route By Task

  • Custom env contract or check_env failure: use references/custom-envs.md for the required reset()/step() API, spaces, image/dict observations, unsupported spaces, and the validation checklist.
  • Vectorization, wrappers, or VecEnv behavior: use references/vectorized-envs.md for make_vec_env, DummyVecEnv, SubprocVecEnv, automatic resets, terminal_observation, seeding/options, VecNormalize, VecCheckNan, VecFrameStack, and dict/image wrappers.
  • Exact signatures and wrapper matrix: use references/api-reference.md for SB3 environment helper signatures and return-value expectations.
  • Errors, warnings, and edge cases: use references/troubleshooting.md for reset/step shape mismatches, Gymnasium vs VecEnv API confusion, unsupported spaces, image warnings, non-zero-start spaces, NaNs/Infs, and subprocess start-method failures.
  • Quick local validation: run python sub-skills/environments-and-vectorization/scripts/check_custom_env.py --mode valid or --mode invalid from a copied skill tree that has Stable-Baselines3 installed.

Boundaries

  • This sub-skill covers env creation, validation, wrapping, vectorization, and observation/action-space compatibility.
  • For choosing PPO/SAC/DQN/A2C/TD3/DDPG/HerReplayBuffer or setting training hyperparameters, route to training-and-algorithms.
  • For evaluation callbacks, model save/load, VecNormalize persistence during evaluation, or rollout metrics, route to evaluation-and-persistence.
  • For custom policy classes, feature extractors, MultiInputPolicy internals, or normalize_images=False policy details, route to policies-and-customization after confirming the env observation routing here.
Skills enregistrées