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Fast Pytest Tests failed at COLLECTION in the base '--extra test' tier
with 'ModuleNotFoundError: No module named datasets': tests/annotations/
conftest.py imported the fixture dataset builder (-> lerobot.datasets ->
the HF 'datasets' lib + pandas/pyarrow), which only ship under the
'dataset' extra, so the whole annotations package crashed.
Fix uses the repo's proven module-level guard pattern (see
tests/datasets/test_language.py), NOT a conftest-level importorskip —
verified empirically that pytest.importorskip raised during conftest
*import* is treated as a collection ERROR (exit 1), while module-level
importorskip is a clean SKIP.
* conftest.py: import build_annotation_dataset LAZILY inside the
fixtures so the conftest itself imports cleanly in every tier.
* test_modules / test_validator / test_writer / test_pipeline_recipe_
render: add module-level pytest.importorskip('datasets') +
('pandas') before the pyarrow / lerobot.* imports (# noqa: E402 to
match the existing convention). pyarrow-importing modules place the
guard before the pyarrow import.
* tests/scripts/test_lerobot_annotate.py: same guard (its _push_to_hub
path imports lerobot.datasets).
Result:
- base / hardware / viz tiers (no dataset extra): annotation tests
skip cleanly; the rest of the suite runs -> exit 0.
- dataset tier: datasets present -> guards pass through -> annotation
tests run with the stub VLM. The pipeline modules import only
stdlib + relative + lerobot.datasets (no module-level datatrove /
vllm / openai), so they import fine there.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
134 lines
4.6 KiB
Python
134 lines
4.6 KiB
Python
#!/usr/bin/env python
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# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Validator behavior tests."""
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from __future__ import annotations
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import json
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from pathlib import Path
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import pytest
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# ``lerobot.annotations`` imports pull in ``lerobot.datasets`` (-> the HF
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# ``datasets`` library), which only ships under the ``dataset`` extra. Skip
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# this module in tiers without it instead of erroring at import.
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pytest.importorskip("datasets", reason="datasets is required (install lerobot[dataset])")
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pytest.importorskip("pandas", reason="pandas is required (install lerobot[dataset])")
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from lerobot.annotations.steerable_pipeline.reader import iter_episodes # noqa: E402
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from lerobot.annotations.steerable_pipeline.staging import EpisodeStaging # noqa: E402
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from lerobot.annotations.steerable_pipeline.validator import StagingValidator # noqa: E402
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from lerobot.annotations.steerable_pipeline.writer import speech_atom # noqa: E402
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def _validate(root: Path, staging_dir: Path):
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records = list(iter_episodes(root))
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return StagingValidator().validate(records, staging_dir)
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def test_validator_catches_misaligned_timestamps(fixture_dataset_root: Path, tmp_path: Path) -> None:
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staging_dir = tmp_path / "stage"
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EpisodeStaging(staging_dir, 0).write(
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"vqa",
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[
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{
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"role": "assistant",
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"content": json.dumps({"label": "cup", "count": 2}, sort_keys=True),
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"style": "vqa",
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"timestamp": 9.999, # not on any 10 fps frame
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"tool_calls": None,
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}
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],
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)
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report = _validate(fixture_dataset_root, staging_dir)
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assert not report.ok
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assert any("does not match any source frame timestamp" in e for e in report.errors)
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def test_validator_catches_orphan_speech(fixture_dataset_root: Path, tmp_path: Path) -> None:
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staging_dir = tmp_path / "stage"
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EpisodeStaging(staging_dir, 0).write(
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"interjections",
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[
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speech_atom(0.0, "Got it."),
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# interjection at 0.3s with NO paired speech
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{
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"role": "user",
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"content": "skip it",
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"style": "interjection",
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"timestamp": 0.3,
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"tool_calls": None,
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},
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],
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)
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report = _validate(fixture_dataset_root, staging_dir)
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assert not report.ok
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assert any("paired speech" in e for e in report.errors)
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def test_validator_catches_inconsistent_plan_memory(fixture_dataset_root: Path, tmp_path: Path) -> None:
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staging_dir = tmp_path / "stage"
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EpisodeStaging(staging_dir, 0).write(
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"plan",
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[
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{
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"role": "assistant",
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"content": "1. do x",
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"style": "plan",
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"timestamp": 0.0,
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"tool_calls": None,
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},
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{
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"role": "assistant",
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"content": "do x",
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"style": "subtask",
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"timestamp": 0.0,
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"tool_calls": None,
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},
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],
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)
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EpisodeStaging(staging_dir, 0).write(
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"interjections",
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[
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speech_atom(0.0, "Got it."),
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speech_atom(0.4, "Replanning."),
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{
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"role": "user",
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"content": "replan",
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"style": "interjection",
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"timestamp": 0.4,
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"tool_calls": None,
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},
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],
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)
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report = _validate(fixture_dataset_root, staging_dir)
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# missing co-timestamped plan refresh at 0.4s → error
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assert not report.ok
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assert any("co-timestamped plan update" in e for e in report.errors)
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def test_validator_catches_wrong_column(fixture_dataset_root: Path, tmp_path: Path) -> None:
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staging_dir = tmp_path / "stage"
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EpisodeStaging(staging_dir, 0).write(
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"plan",
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[
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{"role": "user", "content": "where?", "style": "vqa", "timestamp": 0.0, "tool_calls": None},
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],
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)
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report = _validate(fixture_dataset_root, staging_dir)
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assert not report.ok
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assert any("plan emitted style 'vqa'" in e or "must be persistent" in e for e in report.errors)
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