Shunsuke
98d0430bee
All six adapters duplicated an identical reflect() that delegates to run_minibatch_reflect. The copies had drifted: OfficeQA/DocVQA silently dropped meta_skill_context and ALFWorld dropped update_mode, so those analysts ran without inputs every other benchmark receives (active under the default use_meta_skill: true). Move the delegation into EnvAdapter.reflect as one default that forwards all kwargs uniformly, and delete the six overrides. reflect is no longer abstract — adapters inherit it and override only for custom logic. Net -225 lines. Behavior change: OfficeQA/DocVQA/ALFWorld reflect now receive the kwargs they previously dropped; the three already-correct benchmarks are unaffected. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
44 lines
1.8 KiB
Markdown
44 lines
1.8 KiB
Markdown
# Benchmark Template
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This directory provides scaffold files for adding a new benchmark to SkillOpt.
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## Files
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- `env_template.py` — Environment adapter template (subclasses
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`EnvAdapter`; implements the 4 abstract methods so the file is
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instantiable out of the box — `reflect` is inherited).
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- `loader_template.py` — Data loader template (subclasses
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`SplitDataLoader`; implements `load_split_items` for `.json`/`.jsonl`).
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- `config_template.yaml` — Config file template.
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## Usage
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1. **Copy the directory:**
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```bash
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cp -r skillopt/envs/_template skillopt/envs/your_benchmark
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```
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2. **Rename the files** (drop the `_template` suffix):
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```bash
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cd skillopt/envs/your_benchmark
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mv env_template.py adapter.py
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mv loader_template.py dataloader.py
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```
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…and inside each file rename the classes
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(`TemplateBenchmarkEnv → YourBenchmarkAdapter`,
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`TemplateBenchmarkLoader → YourBenchmarkLoader`)
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and fix the cross-import in `adapter.py`.
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3. **Implement the TODO blocks** inside `adapter.py:rollout` and the
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`_normalize_item` helper in `dataloader.py`. (`reflect` is inherited from
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`EnvAdapter`; override it only for custom reflection logic.)
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4. **Register** the adapter — add a `try / except ImportError` block in
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`scripts/train.py`'s `_register_builtins()` mapping the registry key
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to your `YourBenchmarkAdapter` class. There is no
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`BENCHMARK_REGISTRY` dict in `skillopt/envs/__init__.py`; the live
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registry is `_ENV_REGISTRY` in `scripts/train.py`.
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5. **Create the config** at `configs/your_benchmark/default.yaml`
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(start from `config_template.yaml`). `_base_` is a **string path**,
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not a list.
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See the [Add a New Benchmark guide](../../../docs/guide/new-benchmark.md)
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for the full step-by-step with a worked `docfaithful` example.
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