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data-collection

data-collection

Use Tianshou data carriers, replay buffers, collectors, return batches, and collection statistics safely.

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Documentation de la Skill

GitHub

name: data-collection description: "Use Tianshou data carriers, replay buffers, collectors, return batches, and collection statistics safely." disable-model-invocation: true metadata: disco-role: operating license: MIT

Data Collection

Use this sub-skill when a task mentions Tianshou Batch slicing/merging, BatchProtocol, ReplayBuffer, VectorReplayBuffer, PrioritizedReplayBuffer, HERReplayBuffer, Collector.collect, AsyncCollector, n-step return inputs, collection hooks, CollectStats, InfoStats, SequenceSummaryStats, or MalformedBufferError.

Route First

  • For trainer loops, epoch orchestration, Experiment.run, or how collectors are scheduled during learning, route to ../procedural-training/SKILL.md.
  • For DummyVectorEnv, SubprocVectorEnv, worker choices, async vectorization, EnvPool, or environment construction details, route to ../envs-and-vectorization/SKILL.md.
  • For offline datasets, offline-only algorithms, imitation-learning workflows, or specialized offline RL choices, route to ../offline-and-specialized-rl/SKILL.md.

Read These

  • references/api-reference.md for object contracts, required keys, buffer variants, stats classes, and key signatures.
  • references/workflows.md for practical recipes: shaping batches, adding/sampling buffers, collecting by step or episode, hooks, and validation.
  • references/troubleshooting.md for common shape, null, NaN, malformed-buffer, and collector reset failures.
  • scripts/check_batch_buffer_collector.py for a safe local smoke check of Batch, ReplayBuffer, and a minimal collector.

Fast Checklist

  1. Confirm installed imports with python skills/tianshou/sub-skills/data-collection/scripts/check_batch_buffer_collector.py --help.
  2. Represent data in Batch with consistent first dimensions; nested dictionaries become nested Batch objects.
  3. Add rollout data to buffers with obs, act, rew, terminated, truncated, obs_next, and info; done is inferred by the buffer.
  4. Use VectorReplayBuffer(total_size, buffer_num) whenever collecting from multiple vectorized environments.
  5. Call collector.reset() or use collector.collect(..., reset_before_collect=True) before the first collection.
  6. Use n_episode rather than n_step when an episode-level hook writes fields for whole episodes.

Smoke Check

Run the bundled script after install/import changes or when debugging a data path:

python skills/tianshou/sub-skills/data-collection/scripts/check_batch_buffer_collector.py

Use --skip-collector if only Batch and ReplayBuffer need validation or optional Gymnasium collection dependencies are unavailable.

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